Podcasts about Bian

You are capable of radical change. If you aren't convinced that you can create change in your life, take Aimee's story about how her hen became a rooster (seriously, just listen in and it'll make sense). Beyond that chicken talk, this episode is focused on our human potential for change and healing. We'll touch on neuroplasticity, epigenetics, and the motivational role of hope. We think you'll come away with a better understanding of how you're wired for change and can intentionally steer it towards greater wellbeing.  If you enjoyed this episode, please rate and review us wherever you listen to your favorite podcasts!  Sources and Notes: Joy Lab Program: Take the next leap in your wellbeing journey with step-by-step practices to help you build and maintain the elements of joy in your life. Emotional Inertia: Feeling Dull & Disconnected [Joy Lab ep. 207] Zhang, X., et al. (2023). Overview of Avian Sex Reversal. International journal of molecular sciences, 24(9), 8284. https://doi.org/10.3390/ijms24098284 Bian, Z., et al. (2024). Genetic predisposition, modifiable lifestyles, and their joint effects on human lifespan: evidence from multiple cohort studies. BMJ evidence-based medicine, 29(4), 255–263. https://doi.org/10.1136/bmjebm-2023-112583 Weger, U. W., & Loughnan, S. (2013). Mobilizing unused resources: using the placebo concept to enhance cognitive performance. Quarterly journal of experimental psychology (2006), 66(1), 23–28. https://doi.org/10.1080/17470218.2012.751117 Head to YouTube to see Haley's new spurs (16:28) Closing poem excerpt: Emily Dickinson, "Hope is the Thing With Feathers." Full transcript here. Please remember that this content is for informational and educational purposes only. It is not intended to provide medical advice and is not a replacement for advice and treatment from a medical professional. Please consult your doctor or other qualified health professional before beginning any diet change, supplement, or lifestyle program. Please see our terms for more information. If you or someone you know is struggling or in crisis, help is available. Call the NAMI HelpLine: 1-800-950-6264 available Monday through Friday, 10 a.m. – 10 p.m., ET. OR text "HelpLine" to 62640 or email NAMI at helpline@nami.org. Visit NAMI for more. You can also call or text SAMHSA at 988 or chat 988lifeline.org.

In Beijing's historic Qianmen area, a marriage registration office opened on Saturday in the bustling Dashilan shopping area, amid a cluster of photo studios and shops offering wedding-related services.在北京历史悠久的前门地区，一家婚姻登记处上周六在大栅栏商业街区正式启用，周边聚集着众多摄影工作室和婚庆服务机构。On the same day, a revised version of marriage registration rules started to take effect in China, historically leaving out the former requirement that both the bride and groom need to present their hukou, or the certificate of household registration status, which had been in place since the 1980s.与此同时，新修订的《婚姻登记条例》于当日在全国正式施行，具有历史意义地取消了自上世纪80年代起实施的新娘和新郎都需持户口簿办理登记的要求。Foreseeing that the policy revision—mainly to make marriage registrations and related services more convenient—would bring a surging number of registrants, the civil affairs authority set up the new registry to better serve couples.为应对此次以提升婚姻登记便民服务水平为核心的政策调整可能带来的登记量激增，民政部门特别增设了这处全新登记场所，以更好地为夫妻提供服务。"Previously, the newlyweds needed to go to the places of their household registration and take the hukou booklets for marriage registration. From now on, they just need to show their ID cards to tie the knot at marriage registration offices anywhere in the country," said Bian Zhihui, a registrar at the new office in downtown Beijing.工作人员边志辉（Bian Zhihui）介绍：“以往新人必须返回户籍所在地，并携带户口簿才能办理结婚登记。新政实施后，全国范围内任一婚姻登记处只需查验身份证即可为新人办理结婚登记。”From checking ID cards and photos of the newlyweds and guiding them to fill in the forms, to verifying the information through a nationalized computer network, the whole registration process takes about only 10 minutes.从核验新人身份证件及合影照片、指导填写申请表，到通过全国联网的信息系统进行数据比对，整个过程仅需约十分钟即可完成。Bian said the new rule is among a slew of pro-marriage and childbearing policies promulgated by the Chinese government to streamline procedures and give incentives for people aiming to start families.边志辉（Bian Zhihui）表示，这项新规是中国政府为简化行政流程、提升婚育激励而推出的系列政策之一，旨在通过制度优化鼓励适婚人群组建家庭。China recorded 1.81 million marriage registrations in the first quarter of this year, marking an 8 percent drop from the same period in 2024, according to data from the Ministry of Civil Affairs.民政部数据显示，今年第一季度全国结婚登记量为181万对，较去年同期下降8%。After nine consecutive years of decline, China's marriage registration numbers saw a brief rebound in 2023. However, the downward trend resumed last year, with registrations falling to their lowest level since 1980.在经历连续九年下滑后，我国结婚登记量曾在2023年出现短暂回升，但去年这一下降趋势再度延续，登记人数已降至1980年以来历史新低。The new marriage registration office is located in a traditional courtyard building and boasts a one-stop service, allowing couples to choose wedding dresses and suits, take wedding photos or purchase marriage souvenirs.新设立的婚姻登记处坐落于传统四合院建筑群中，提供从婚纱礼服挑选、结婚照拍摄到婚庆纪念品购置的一站式服务。A 15-minute walk from the office is the marriage registration service center of the Civil Affairs Bureau of Beijing's Xicheng district. The center has registered more marriages than anywhere else in the capital.该登记处与西城区民政局婚姻登记服务中心仅相距15分钟步程，是北京市婚姻登记量最大的服务机构。Xu Zongyi said the center, of which he is a deputy director, recorded nearly 20,000 marriage registrations last year.其副主任徐宗义（Xu Zongyi）透露，2023年该中心办理结婚登记近2万对。Xu expects the latest rule change to boost marriage registration by 20 to 30 percent.徐主任预计，此次政策调整将使辖区婚姻登记量实现20%至30%的增幅。On Saturday, there were approximately 1,700 marriage registrations recorded in Beijing, among which about 900 pairs were not permanent residents of the capital. Various Chinese provinces and cities have done more than just cut red tape to boost marriage and fertility rates.上周六，北京市共办理约1700对结婚登记，其中约900对新人非本市户籍居民。中国各地政府为提升结婚率和生育率，已推出一系列超越简化行政程序的创新举措。In March this year, the provincial government of Zhejiang issued a notice calling local authorities to improve marriage and fertility support policies, with recommended incentives including the distribution of cash in the form of "wedding red envelopes" or consumption vouchers to newlyweds.今年3月，浙江省政府发布通知，要求各级地方政府完善婚姻及生育支持政策，鼓励采取多种激励措施，其中包括向新婚夫妇发放“婚庆红包”或消费券等。Yan Yan from the Civil Affairs Bureau of Shenyang, capital of Liaoning province, told Xinhua News Agency that a government-sponsored group wedding for 52 couples is slated for May 22, with the ceremony to be held in the historic Shenyang Palace Museum.辽宁省会沈阳市民政局婚姻登记处负责人闫岩（Yan Yan）向新华社透露，一场由政府主导的集体婚礼盛典定于5月22日在沈阳故宫博物院举行，届时将有52对新人参与这场文化底蕴深厚的仪式。"Through the group wedding, we advocate new ways of getting married by infusing traditional customs with the new trend of thrifty practices," Yan said.“通过将传统婚俗与新时代节俭风尚有机融合，我们旨在通过集体婚礼形式倡导文明简约的婚庆新风尚。”闫岩（Yan Yan）在接受采访时强调。Liu Qing and Yao Wenjiu, both working in Shenyang away from their home cities, plan to get married this month.在沈工作的异地青年刘清（Liu Qing）与姚文久（Yao Wenjiu）计划本月完成婚姻登记。"The new rule allows us to do it more conveniently in the city where we work—you don't have to go back home to 'steal' hukou booklets from parents," Liu said.刘清（Liu Qing）表示：“新规实施后在工作地就能办理婚姻登记，再也不用像过去那样专程回老家找父母'借'户口簿了。”While marriage is legally determined and executed autonomously by the parties involved, parental approval and endorsement remain culturally paramount in Chinese marital traditions. For young adults whose household registration remains jointly registered with their parents—even if they live and work elsewhere—previous regulations required them to obtain the family's hukou booklet to complete marriage registration. This effectively meant that registering a marriage first necessitated parental awareness and consent.在中国传统婚姻文化中，尽管婚姻关系的缔结在法律层面由当事人自主决定，但父母的认可与祝福仍具有至关重要的文化意义。值得注意的是，对于户籍仍与父母共同登记（即便其本人在异地工作生活）的适婚青年群体，既往政策要求婚姻登记必须提交家庭户口簿，这实际上意味着需要父母知情且同意后才能登记结婚。Wang Jun, a marriage and family counselor, said marriage registration reform eliminates the mandatory household registration booklet requirement, granting individuals full autonomy in marital decisions.资深婚姻家庭咨询师王君（Wang Jun）表示，此次婚姻登记制度改革废除了户籍簿的硬性规定，切实保障了公民在婚姻决策中的充分自主权。With more than 10 years of experience, Wang volunteers as a counselor at the Xicheng district marriage registration service center.拥有十余年从业经验的王君（Wang Jun）目前在西城区婚姻登记服务中心担任志愿咨询师。"Parents' opinions are traditionally deemed authoritative to help their children choose the 'right' spouses and avoid risks in future marriage. Nowadays, many young people are more inclined to seek help through counseling," Wang said.她分析道：“传统观念认为父母的意见具有权威性，能帮助子女甄选'合适'的婚配对象，规避未来婚姻风险。但如今更多年轻人倾向于通过专业咨询寻求婚恋指导。”However, she warned that under the rule, there might be a higher possibility of impulsive "flash marriages" and divorces, especially among young people who lack experience in intimate relationships and family issues.不过她特别指出，新规实施后冲动型“闪婚”及后续离婚现象可能增多，尤其在缺乏亲密关系经营能力和家庭矛盾处理经验的青年群体当中。marriage registration office婚姻登记处take effect生效household registration户籍;户口登记newlyweds/'nju:lɪˌwed/n. 新婚夫妇; 新婚的人flash marriages闪婚

durée : 00:04:28 - L'artiste toulousain Naud - Alors, yes or Naud ? On répond Naud, évidemment, car ce toulousain au rythme dans la peau, nous sort un bien chouette 3ème album "Un Gars Bian"..., oui BIAN, parfaitement !!

This week we learn a little bit about the background of Taiwan, a country that has spent the last century in turmoil, and changing ruling hands twice. Recently there has been a push for their independence and hope was on the horizon with democratic elections, but their second democratically elected president, Chen Shui-bian, proved to be a little more corrupt than they hoped.

In this episode, Hans Tesselaar, Executive Director of Banking Industry Architecture Network (BIAN) and Saket Sinha, Sr. Partner & Global Vice President - Financial Services IBM, explain the role and impact of BIAN in the financial industry. They introduce the organisation as a not-for-profit standards body to make the financial industry more agile and standardised. They discuss IBM's collaboration with BIAN to convert legacy banking systems into modern architectures using common standards. Hans and Saket elaborate on how ΒIΑΝ's framework, which includes a "periodic table" of financial components and common APIs, helps banks and fintechs seamlessly integrate and innovate. Highlights include the analogy of BIAN's components to a periodic table and real-life AI use cases that showcase the practical applications of BIAN standards. Both guests emphasise the importance of adopting common standards for efficient financial integration and future advancements such as embedded finance and Gen AI.

After serving eight months behind bars for libel, Chen Shui-bian is released in February 1987, and enters the fray of a newly-liberalized political landscape. In 1986, the Democratic Progressive Party became Taiwan's first real opposition party, and Chen's wife is elected to Parliament. Mr. Chen bides his time, and then pounces – first becoming a lawmaker, beating Frank Hsieh to become DPP caucus chief, and then setting his sights on the nation's capital city. In 1994, direct elections for Taipei mayor are held for the first time, and Chen overcomes Frank Hsieh again to become the DPP nominee.  But Chen has a few issues: he isn't a great speaker and he doesn't like smiling. Will this plucky lad from a dirt-poor home in Tainan overcome the odds? Find out in this week's exciting Formosa Files Taiwan history story. Pics, links and more at formosafiles.com

HAPPY BLACK FRIDAY! Sorry this wasn't up for your commute! This week we talk about our swing to Right Wing Podcasting, XM radio, Drake taking the fattest L, Ice Spice out-Pitchforking Kendrick, pop artist discussions, Grammy nominations, Coworker Metal, entering the Revolver era, Coachella sucking and a bunch more!!!!

Don's bargain with a seductive vampire. By BradentonLarry - Listen to the Podcast at Steamy Stories. Lady Primrose The long, wood-paneled ballroom was largely what Don would have expected. There were a pair of tables near the entrance heavily laden with bowls and platters of fruit, as well as a fountain jetting clear, cold water surrounded by crystal glasses. There were doors at intervals down the length of the two side walls that seemed to open into the gardens, and illuminating the entire room were three very large candle chandeliers sparkling with golden light. In what seemed to be entirely appropriate décor, any would-be empty wall space of any considerable size was hung with high quality paintings. However, the paintings all had a decidedly erotic bent, as if someone had decided to redo the illustrations from the Kama Sutra in the style of the Dutch and English masters of the 18th and 19th centuries. There were some portraits too, but they were all showing much more skin than normal. The life-sized painting of a reclining pale young man with a rather generous erection was not exactly what one expected to see in a respectable Victorian mansion. Or, at least, not displayed prominently in the grand ballroom. The guests who had been admitted through the main doors, along with Don, gathered about the tables for some fruit and water, and then gradually began to disperse along the length of the ballroom, where they mingled with a number of people who seem to have been admitted to the room earlier, or who had come in through the garden. While Don, Jerome, Bian, Rodney, and Marilyn, seemed fairly representative of the former crowd of guests and of Erosians in general, the latter set seemed quite different. Each of these others moved with an unusually feline grace and unmistakable confidence. To paraphrase an astute (though fictional) observer of human nature, they walked as if the place belonged to them. They were all of them exceptionally good looking and possessed of an undeniable sex appeal, even for Eros. Don wasn't really surprised to note that these attendees were a bit paler than the other guests. Music began to play. It was unobtrusive instrumental music, ideal for slow dancing, but modern enough that no one felt compelled to waltz or anything like that. Don watched as the paler partiers moved among the others, smiling and batting their eyes, selecting, and engaging. Most led their chosen partners toward the open end of the ballroom where they danced together, but some slipped off through the open doors into the garden. Don felt a cool hand slip into his and turned to see the lovely Cessily next to him. She was now wearing a dark red evening gown with a plunging neckline that showed off most of her pale breasts to very nice advantage. Her blue eyes twinkled up at him and her lips, now crimson to match her gown, were smiling in a rather inviting way. “Good evening,” Cessily purred. “‘Don,' wasn't it?” “It was, and still is,” Don nodded, unable to resist smiling back at the charming woman. “Would you like to dance, Don?” she smiled. “Is dancing all you have in mind, my dear?” he managed. “Oh, well, there's always more than dancing on my mind,” she laughed. “In that at least we're kindred spirits,” admitted Don. “If you enjoy our dance, perhaps we could retire to someplace a bit more private…” “Something a bit more shadowy, say?” She smiled again, “If you like, though I don't mind an audience.” “Once more, we have that in common.” “I could tell I liked you right from the start, Don.” “You seem to have excellent taste, fair Cessily.” She leaned in closer, so Don could feel her lips very lightly brushing his neck, as she said, “I would love to see if your taste is so fine.” Don swallowed hard, and then managed to say, “I must say I find the thought very tempting, but…” She placed her hand on his chest and looked up into his eyes with another of her fetching smiles and said, “Would you like Lucien to join us?” Laughing a little, Don said, “No, that's quite alright. It's just that I'm afraid I really must save myself for Lady Primrose.” “Oh,” she actually pouted a bit. “However, if she has no use for me…” Cessily rolled her eyes a bit, “No, she'll just eat you up, the greedy bitch.” Don was a bit taken aback, and a bit put off by her phrasing, despite his pre-existing suspicions. “Oh, don't mind me, sweet thing,” Cessily laughed. “I just had my heart set on you for the night.” “That is very flattering! In other circumstances…” She leaned in and rose up on her toes a bit to kiss him on the cheek, then said, “If you get tired of waiting for her ladyship, don't hesitate to come find me.” Then, flashing him a bright smile and a quick wink, Cessily slipped off to find another quarry. “I've never seen anyone turn Cessily down before,” said a familiar voice from over Don's shoulder. Don turned to see Lucien regarding him with a slight, diffident smile. “It wasn't easy,” Don admitted, “but I think it's best if I wait until I get the chance to talk to Lady Primrose.” “Interesting,” shrugged Lucien. “She generally likes to make a late entrance. Normally I'd wish you luck resisting the charms of the other women, and men, here, but if you can say ‘no' to Cessily, I suspect you don't need any help in that regard.” Don laughed, “Again, it wasn't easy.” Lucien nodded and left Don to fend off the advances of several other extremely attractive women who seemed quite eager to slip off to a darkened corner with him. Two of them actually suggested they share him. “Do you mean, I can enjoy you both?” “Oh, yes, of course,” said the redhead, as her raven-haired companion licked her lips while admiring Don's neck. Don smiled and proffered his now customary response. The two women didn't seem to mind too much, and Don soon saw them dancing with a very cheerful Rodney, as nearby Marilyn seemed to swoon in the embrace of a tall, dark stranger. When the two women led Rodney off into the garden, Don thought he should follow. He doubted that anyone was in serious danger here, but he wanted to confirm his suspicions and perhaps see something erotic along the way. Before he could make it to the garden though, he found himself drawn up short as a gorgeous woman slipped up next to him and took his arm. “I understand you have been waiting for me, sir,” she said in a low, sensuous voice steeped in a cultured English accent. She was only a little shorter than Don, wearing a black dress that clung lovingly to her body, accentuating her curves and emphasizing her generous breasts with impressive décolletage. Her skin was fair in the way the aristocracy used to find a necessary part of beauty. She had thick chestnut hair pulled back and then falling over her bare shoulders, dark red lips smiling at Don, and emerald green eyes dancing with candlelight and echoing the little glints of her earrings. She was, to put it entirely too simply, staggeringly beautiful. “Lady Primrose, I presume?” “Indeed,” she nodded. “I'm very pleased to meet you,” Don took her hand and raised it briefly to his lips. He said, “My name is Don and I am at your service.” She smiled a bit coolly and said, “Well, we shall see about that, Don. Are you enjoying the party?” “I am,” Don nodded. “I've been enjoying the artwork, and the company is quite interesting, though now I see that it was all but a light appetizer.” She cocked her eyebrow at him and gave him half a smile, and then said, “I should 'make the rounds,' so to speak; would you be so kind as to accompany me?” Don bowed a bit, “Of course, milady.” Patting his hand with her cool fingers, she said, “You may call me Clarissa, Don.” Arm-in-arm they moved through the guests still in the ballroom. The guests who had come in with Don seemed largely entranced by their paler companions, but those last all smiled and greeted Lady Clarissa Primrose as she passed. As they started toward the gardens, she again addressed Don directly, saying, “You have questions.” “I usually do, yes,” Don smiled. “Curiosity is a nearly insatiable thirst, isn't it?” “Quite.” “Indulge yourself, Don; drink deep,” she smiled as she watched his face. “Lucien called Cessily his sister, but that isn't literally true, is it?” “Of all the questions you must have, that's the first?” she chuckled. Don shrugged, “It's the one I'm most likely to forget and regret not asking.” “There are several ways to be siblings,” she said. “They share the same mother, but not a womb. They share not genes but blood.” “And you are their mother, I take it?” “One of them, yes.” “So, 'Lady' is a bit of an understatement.” “What would you have me called?” “Queen seems more appropriate,” Don decided. “You flatter me, Don,” she laughed. “At least this is more interesting than the usual sort. One grows a bit tired of the usual compliments.” They had already passed a couple on a shadowy bench. The woman was straddling the man's lap and had her head buried in the crook of his neck. In another corner, a woman leaned back against a wall as a dark-haired man who might have been Lucien had his mouth fixed on her exposed breast. When they came to Rodney, who seemed to be getting a rather extreme hickey from the redhead and an enthusiastic blowjob from the darker woman, Don asked, “Are they in danger?” “Only if they want to be,” Clarissa smiled. “Does that happen often?” “More often than one might expect, but not what I would call 'often.'” “And how does one become … your child? That doesn't sound right,” Don frowned. “Perhaps it's best not to strain that metaphor,” she patted his hand again and turned him back to the house. “One has to drink in turn.” “Yes, of course,” Don nodded. “Is that why you wanted to see me, Don?” He smiled at her, “No, I'm here on other business.” “Interesting,” she mused as they came back into the ballroom. “You saved yourself for me, and I see that you understand what that would mean, at least normally, but you don't seem to have come for the usual reason at all, though I sense that you find the thought appealing. This would make sense if you were here to join my family.” She had led him through the ballroom and back to the entry hall, and they were now climbing the stairs. “Moreover, there's something different about you, Don.” She raised his wrist and inhaled deeply. “You have … layers – complexity.” She pressed her lips to his wrist and let her tongue play lightly over his flesh. He thought for a moment that he could feel her teeth against his skin. For a moment he thought she would bite him, and he wanted her to. “Uh, yes, there is a depth of flavor to you, Don. It's quite unusual.” She looked up at him without raising her mouth from his wrist. She smiled, “Will you give me a taste?” Don suddenly realized that they had climbed all the way to the top floor and had come into a large candle-lit bedroom with a large canopy bed in the center of it. It reminded him of the bedroom Toshia and he had found themselves in so long ago. It also struck him as a much darker, more sinister reflection of the Lady's bedroom in that distant Manor. With a tremendous effort of will, Don remembered that he had a mission to accomplish. “Perhaps,” he finally managed, as he moved his hand to cup Lady Clarissa Primrose's chin in his hand and draw her to him. He leaned in a bit, kissing her full lips lightly. Don just meant to put her off for a moment with that kiss, but she wasn't having any light kisses. She slipped her arms around him, one slipping up so that she could hold the back of his head, and kissed him passionately, hungrily. Her lips were cool, but her enthusiasm was heat enough. Her tongue slipped into his mouth insistently, as Don's hands moved up over her back until his fingers found the little zipper handle between her lower shoulder blades. When he'd opened the back of her gown, she stepped back a little and shimmied out of her black sheath. She gave Don a moment to admire her beautiful alabaster body, before she stepped to him again, raising her cool fingers to caress his face. “We could share the sweetest of ecstasies, Don,” she purred as her fingers dexterously unbuttoned his shirt in what seemed both slow motion and extremely quickly. She leaned in to kiss the side of his neck as his jacket and then his shirt fell to the floor. He felt the tip of her tongue brushing his skin. She pulled back and looked him in the eye with a confident smile on her dark lips, and said, “You have some power in this world, I can taste it on your flesh, but you've never known the power I can share with you, if you'll but give me a taste of yourself. You aren't afraid, I can tell. You want to give me what I want.” Letting his hands move over her body, caressing her curves, lingering over her perfect, full breasts, Don smiled and repeated, “Perhaps.” Somehow, she had undone his belt and opened his slacks. She was up against him again now with her hand in his pants, squeezing and pulling on his cock in a grip that was exquisitely tight, but still on the side of pain that counts as pleasure. Her nose was brushing against his, and he could feel her breath on his lips as she said, “You want to be inside me, Don. You can't deny it. You could have given yourself to Cessily or any of the others, but you saved yourself for me. Surrender yourself to me, Don.” Don forced himself to tear his hands away from touching her long enough to push his pants down, and then kicked his shoes and pants to the side. He licked his lips, swallowed, and said, again, “Perhaps.” Her eyes, so close to his now, narrowed and she growled a bit. Letting go of his sex, she placed her hand flat on his chest and shoved him backward, throwing him easily back on the silken coverings of the bed. Before Don could do more than land on his back splayed out helplessly, she was on top of him, crouched over him and looking down into his face. There was a fire in her eyes and for the first time, it was clear her canines were longer and sharper than normal. She smiled again, but now with a hint of malice, and said, “It's pointless to resist. You know you will give me what I desire.” Don couldn't resist touching her, and his hands moved up over her again, now reveling in the feeling of her tense muscles. He felt her hand between them, taking hold of his extremely hard prick and getting it into position. He felt his glans slipping into her smooth, moist sheath and was surprised at how intensely warm it was. He wanted to push up into her, but she resisted. She chuckled low in her throat. “Why fight it, Don? You know I can just take what I want.” Don smiled again, but this time broadly as if he were himself again, and said, “Perhaps.” Calling upon everything he had learned about Eros and using the strength he had found so helpful in his fight with the Sisterhood, Don abruptly pushed up and over, flipping Lady Primrose over onto her back underneath him. Startled, she snarled and snapped up at him with her deadly teeth, but Don's hand was on her lovely throat and he pushed her back into the bed. “Now, now,” he smiled. “We could fight, and maybe you'd take what you want by force, but where's the fun in that?” She managed a cold smile and said, “It sounds like it would be a great deal of fun, actually.” It was Don's turn to chuckle, and he again recalled that day with the Sisterhood, and haughty Daphne. He smiled and said, “Maybe we can try that next time. I was thinking this time we could come to a more mutually pleasurable solution.” To emphasize his point, he pushed himself deeper into her, quietly amazed at how wonderfully warm her pussy was. It felt like she was both opening to the pressure he was exerting and pulling him in. Her muscles squeezed and drew on him in a wonderfully unusual way, as if her pussy had preternatural abilities. He felt her hands squeezing his ass and pulling him in to her and her long legs wrapping around his. Don worked himself in and out of her a few times, eliciting a smile and a happy groan from her, and then said, “What I have in mind is a trade.” “Oh?” she was looking back up at him calmly, as if she were completely disinterested, though her body was flexing and grinding back against him rather enthusiastically. Don realized some of that enthusiasm was being exhibited by those exceptionally talented muscles of her vagina. Don was intent on fucking her now, but managed to remember his mission and said, “I will give you what you want, though not all of it, of course, but in exchange for something.” “Something more than what you're enjoying now?” she smiled. Don couldn't resist and lowered his face to hers to kiss her again. In the heat of passion, he didn't care that one of her fangs cut his lower lip, giving her the briefest taste of what she craved. When he pulled away again, he said, “If you can restrain yourself, I'm sure we can both enjoy this quite thoroughly.” She rocked her pelvis beneath him, smiled, and said, “You might be right about that.” Don paused a moment, both to enjoy the feeling of being inside this gorgeous, sexy creature, and to reconsider his plan, but then forged ahead with, “I'll let you drink, but I want something in exchange…” “Yes?” “Your earrings.” She laughed then, and said, “Is that all?” “Well, they do look expensive, and…” “Done!” she smiled. “Now shut up and fuck me, Don.” Don was all too happy to do so, bending his back and shoving up into her vigorously as her arms and legs wrapped around him, holding his body tight against her. He was fucking her hard and fast, using short, fast strokes when he felt her mouth on his neck. Her hand held the back of his head in place and then he felt her fangs sink into him. It hurt, but not as much as he had expected, and what followed was a strange kind of bliss. As she hungrily sucked on his blood, Don felt a deep connection with her that transcended the sexual union that was already so very intense. While she drank from him, their bodies became one organism, joined in one glorious pumping, flowing, orgasmic circuit. Then she was coming, her body suffused with his blood and squeezing and pulling at his sex, and Don gave her his cum as well, filling her with a gushing flood. As they ground together… Don shoving up into her, his arms pulling her down on his spasming cock, his legs shoving against the bed to push himself as deep as he could into her… Clarissa pulling him into herself, strong arms and legs wrapped around his muscular body, her pussy squeezing and sucking on his hard, thick sex… they rolled over together on the bed so that she was on top of him, shuddering and groaning with exquisite pleasure. Though to him it felt as if she had consumed a great deal of his blood, she held back so that he could give her more before the night was through. After their long, extremely intense orgasm finally faded away, Clarissa pushed back and up, straddling him and smiling down at him with her lips dark with his blood and thin dark red rivulets running down her chin and splattering a bit on the tops of her perfect breasts. Don smiled and hoped she would honor their agreement. If she didn't though, he couldn't help but think it was quite a way to go! Then she was moving on him, grinding herself against his body, riding his still very hard cock. Her hands moved up over her body to her full tits and squeezed them, smearing some of Don's blood over her fair skin. Don ran his own hands over her strong thighs up to her narrow waist. Then he was reaching up to help her squeeze those luscious breasts, getting some of that blood on his fingers. She bent down a bit and Don's hands reached her throat and then her face, and then she was licking and sucking the blood off his fingers. Without for a moment resisting the urge to move her pussy and clit against him, she leaned down to kiss him passionately. She hadn't put her fangs away – if she could even do that – so Don's tongue and lips felt those sharp teeth brushing against them in the heat of passion. There was also the taste of his own blood, which was somehow sweeter than the coppery taste he expected. Then she was climaxing again, moaning into Don's mouth as her body trembled and her pussy again milked at his cock in that weird and wonderful way. Later, after a long session of vigorous fucking, Don was sitting up on the bed and Clarissa was on his lap, his cock still inside her and her arms and legs wrapped around him. They had been moving against each other for some time since her last orgasm. She looked deeply into his eyes, and asked, “Why do you want my earrings?” Don told her, but as briefly as possible. “Ah,” she smiled. “I take it that means you would not like to join my little family.” He smiled and said, “I am very flattered, milady, but I must continue my quest.” She nodded, “Of course.” “That's not to say that I'm not very tempted, though,” Don added. “Would you mind if I came back to visit you, if I can?” She smiled and kissed him again. Don felt her pussy working its magic again, pulling him closer and closer to another orgasm. Clarissa rode up and down on him a bit more vigorously, and she said, “Please, feel free to visit any time. Now, give yourself to me one last time tonight.” As she drew him into ecstasy, she worked her body against him, bringing herself to her own shuddering climax. When Don's body responded in kind, pumping a fountain of hot cum up into her, she again dropped her mouth to his neck, and he felt the sharp pain of her fangs piercing his flesh. His hot blood filled her mouth as his seed filled her pussy and womb. Don felt as if she was swallowing him up whole as his life force flooded into her. She let him fall slowly back onto the bed, and he saw her over him, a disheveled and bloody creature of chaos and death, and thought it was one of the sexiest images he had ever seen. Then everything went black. When he woke, Don found himself in the bedroom where he and Gretchen had had so much fun the day before. He sat up and looked around a bit unsteadily, just as none other than Gretchen came into the room bearing a silver platter with a pitcher of water and some fruit. “Good afternoon, sir,” she smiled. She set the platter on a table by the bed and set about propping Don up with some pillows. “You should drink lots of water, and eat something, sir.” Then she disappeared into the bathroom to run a bath. When Don was reaching for his second apple, he noticed an envelope with his name on it. Inside were a pair of emerald earrings and a note that said, “Thank you for a wonderful evening. Please come again soon. – C.” Don was smiling as he finally got out of bed and made his way to the bathroom. He caught his reflection in a mirror on the way. He was a bloody mess, literally, but it looked like the wounds on his neck were already healing. After his bath, which was a bit restrained compared to their time together the day before, Don pushed a cheerfully cooperative Gretchen back on the bed so he could lick her to a few squealing and shaking orgasms. Then, back in his khaki's and polo with the envelope and earrings in his pocket, Don went downstairs, collected his staff and headed out for Shagbottom. “Damn, Don,” Toshia breathed. “That was crazy!” “Yeah,” he chuckled, “it really was intense.” “But she could have killed you.” He shrugged, “I mean, maybe, but everyone seemed so polite and well-mannered. Cessily and the others just took 'no' for an answer. I had the distinct impression Clarissa could be trusted to not get carried away.” Toshia shook her head disapprovingly. “Plus, like I said to Evelyn, I was getting the impression I wasn't really in any serious danger.” “Why is that, though?” “I'm getting to that,” he chuckled. “Fine, but how did you find your way back to the Hall of the Whatever King?” “Oh, that was the easy part,” Don laughed. “As soon as I left Heolfor House, I abruptly found myself in the courtyard with all the naughty statues. I just had to go in, strip down, shower, take the earrings and my staff, and ride the sofa back up again. I handed over the earrings and got my next mission. Easy peasy.” Dear readers, this chapter features quite a few references to people, events, and places in the Lost in Eros series. If you've read that,  perhaps you'll enjoy these callbacks. If you haven't, please consider this an invitation to read this story from the beginning. In any case, you'll enjoy this story either way. Chapter 8. The Tribal Queen, the New Sheriff, & Storytime “The next mission was a bit more straightforward, though there was a bit of a twist along the way,” Don smiled. “Oh?” Toshia prompted. “It turns out there's this whole area that's set aside for people who are into less civilized things.” “I can understand that,” she nodded. “Some of these are organized into rather male dominated tribes that engage in all kinds of war games and treat their women mostly as commodities. I get the impression the women must be into that whole thing. It had a rather cave-man sound to it when it was explained to me.” “Yeah, there are women who like that whole 'throw me over your shoulder and take me to your cave' idea,” Toshia said. “It's not my thing, obviously, but yeah.” “There are at least a couple of female-led tribes – kind of like Amazons.” Toshia added, “Or like the Sisters.” “Yeah, I guess so,” Don nodded. Task Three: “Anyway, my next mission was to win a tribal chieftain's queen. It wasn't the queen of the tribe, but the chieftain's queen. Apparently, she didn't have any tribal authority, but as queen she was the boss of the other women of the tribe, and she couldn't be traded away.” “Traded away?” “For, like, horses or other women,” shrugged Don. “I had to win the queen of the Grey Wolves. The watcher's council teleported me to the area, which they called 'the Wilds.' I found a village on the edge of the tribal area, got some more appropriate clothing – moccasins and a loin cloth…” “I'd like to see that,” Toshia grinned. “Maybe later,” Don laughed. “Over a couple of weeks, I was able to find out more about the tribal 'culture.' Apparently, there were just two ways I could 'win' a tribal queen: defeat the chieftain in one-on-one combat or sneak into the tribe's camp and spirit her away. I also found out that the chieftain of the Grey Wolves was a massive guy with a serious reputation as a badass warrior.” “So, stealth-time?” “Stealth-time,” Don nodded.Don Becomes the Sheriff of the Resort Center. By BradentonLarry - Listen to the Podcast at Steamy Stories. Don moved through the forest as quietly as he could. He was devoting all his attention to creeping stealthily toward the Grey Wolves' camp. For the hundredth time that night he wished he had Shelonda's skills in the woods. He was trying to bend Eros to his will, as he had done in the Manor and against the Sisters, but he was definitely out of his element here. All his time playing stealth characters in videogames hardly prepared him for actually moving quietly through a forest at night.He hoped that the Grey Wolves had grown complacent in their long period of being the strongest tribe in the Wilds. The villagers Don had befriended had assured him that no one would be crazy enough to try to sneak into the Grey Wolves' camp. Hearing that had actually cemented his plan to try the sneaky approach. Now, as he approached the camp, he could see the many tents and the darkly glowing pits where their fires had burned low. The chieftain, who he had been told was called Omar War Eagle, was supposed to have the biggest tent, and his queen would have the much smaller tent between his and the wooden lodge, next to which was the large tent shared by the other women of the chieftain. From the low rise outside the camp, Don thought he could make out the tent he wanted. His whole plan depended on War Eagle spending the night with one of his other women, and Don thought he could see a light glowing through the fabric of the queen's tent. Don crept slowly through the camp, suddenly grateful that there didn't seem to be any dogs in Eros. He stopped next to the backside of what he thought must be the right tent and listened. Somewhere in the camp there were at least three couples having sex, but most of the tribe seemed to have gone to sleep. Shifting his staff over to his left hand, Don drew the sharp knife he'd procured in the village and quickly cut a long slit in the tent. In another moment, he had slipped inside. Sure enough, there was only one person in this tent, and it was clearly a woman. Don could see a very feminine hip and the full swell of a beautiful bare breast in the reddish glow of the little fire that kept the tent warm. Don crept slowly toward the woman on her bed of furs, as he admired her sleeping form. He resisted the urge to run his hands over her legs while he decided how exactly he should manage the next part of this caper. He moved in closer to try to get a better look at the queen. Her long dark hair obscured her face, but he could tell she was beautiful. He thought the usual thing to do in a situation like this was to clamp his hand over her mouth when he woke her, to keep her from crying out, but Don wanted to make sure he did it swiftly and gently. Hurting this woman was completely out of the question, as far as Don was concerned. It was bad enough that he was about to frighten her. When his hand slipped over her mouth, though, her eyes opened and regarded him calmly. She made no effort to struggle or even start away. Don suddenly realized there was something very familiar about this woman. When Don raised a finger to his lips in what he hoped was a universal-enough sign to be quiet, she nodded as if she understood him, and Don drew his hand back. “Hello again,” she smiled. “It was Don, wasn't it?” Her accent and the way she pronounced his name, as ‘Dohn,' immediately refreshed his memory. “India?” he asked in utter surprise. “It is good to see you again, Don,” she smiled, “but what are you doing here? It is very dangerous for you here.” “I'm here to ‘win' you – to steal you away,” he explained. “Oh, that's sweet,” she smiled. “But wait, how did you know where to find me?” “I was sent by the watchers council, on a quest to earn one of those rings.” “One of these?” she laughed and held up her left hand, showing the black ring Don remembered. “Exactly,” he smiled. “I was looking for you after that one night in the Jungle Room, and here they've sent me to you.” “I am sure it was not an accident,” she smiled at him. She brushed her long black hair out of her eyes. Finding her lips irresistible, Don leaned in to give her a kiss, but she stopped him with her fingers on his mouth. “I am the queen, Don. You cannot just do what you want with me.” “Unless I steal you away, right,” Don nodded. “Yes. There are rules,” she smiled warmly. “Ah, very good,” Don rose a bit and offered her his hand. “We can slip out through the back of the tent.” “Oh, Don, that is not how we play this game,” she chuckled. Then she was yelling, “Help! Help! Someone has come into my tent! Help!” Toshia laughed a bit and then gaped at Don, before she said, “What the hell, Don?” “That was pretty much my reaction, too,” he chuckled. “You'd be amazed how quickly a bunch of naked guys woke up and swarmed to protect their chief's queen. They dragged me out and brought me right up to the chieftain himself, Omar War Eagle. He was huge, Toshia. Huge! He was at least a foot taller than me and built like, well, like Sven from the Maidenhead, but on steroids. He didn't look at all happy to be woken up or that I'd tried to make off with his most prized possession.” “How did you manage to get out of that?” Toshia asked. “Well, I did the only thing I could,” Don shrugged. “I challenged him to a fight for her.” “I have to admit, that's a bit anti-climactic,” Don said to himself. Omar War Eagle lay stretched out the ground in front of him, knocked out by a single strike from Don's staff. Rather than wait until morning, Omar had laughingly demanded the duel commence immediately. He apparently thought the skinny little intruder would be so little trouble that he could finish him off and get back to bed in short order. He called for a heavy cudgel to correspond, barely, to the twig he saw Don carrying. The rest of the tribe gathered around, and Don had a moment to notice that they bore very little resemblance to one another, as one might have expected from a more traditional tribe or clan. When Omar moved in, a bit recklessly, and swung that big cudgel in an admittedly brutally fast arc aimed at Don's head, it felt to Don as if the large man was almost moving in slow motion. It was hardly even an effort for him to duck under the swing, extend his leg out to the side as he crouched low, slipping to Omar's momentarily unexposed right side. Springing up on Omar's flank, Don leapt into the air and brought his staff down on the big man's shaved head with a loud crack. As Omar dropped the cudgel and fell to his knees, Don was glad to see that he hadn't caved in the man's skull. Before Omar had finished falling forward face down in the dirt, his tribe was gaping at Don and each other in shock and confusion. Then, Don caught India's eye and saw that she was shaking her head and trying to suppress a smile. He smiled at her, held out his hand, and said, “Milady…?” With her by his side, Don began to make his way through the crowd of Grey Wolves, when someone thought to ask, “Shouldn't one of us challenge him?” Don turned sharply in the direction of the questioner and said quite loudly, with an imperious gleam in his eyes, “Look, I don't want any trouble with the rest of you. I got what I came for. Maybe you all need to think about some changes around here, but do you really want to mess with me right now?” This seemed to be both confusing and threatening enough to distract the tribe from Don and India's exit. Now that he wasn't trying to be sneaky, Don could make better time, just keeping his eye on the ground to avoid tripping in the darkness. India now seemed fine with following along. Once they were well into the forest, she let herself laugh and say, “I think that was 'cheating,' Don.” He chuckled and said, “I don't see how. I'm pretty sure anybody can move that fast if they really want to, at least here in Eros.” “And your weapon?” “Well, that is special, but I don't think that was important this time.” “Don, wait,” she said, tugging on his arm. He drew up short and turned to her. She slipped into his arms and gave him a kiss, and then said, “You did your tarefa, your assignment; but before they take you away, let us have some time alone.” “Okay,” Don smiled and leaned down to kiss her again. Then he realized he was in a very different place. There was a jungle on his right, and a moonlit beach on his left. Behind India was a good-sized bungalow, and there was a campfire burning brightly on the beach. “Whoa!” Don breathed. “How did you do that?” “Is one of my special powers,” she winked at him. Then she was leading him out toward the water, saying over her brown shoulder, “This is my special place, my 'hideaway.' They won't bother us here.” “Is this something you can do with your ring?” “Yes,” she smiled, “and you will be able to build things like this too.” Then she dove into the water, leaving Don on the beach to kick off his moccasins and take off his loin cloth, before diving in after her. Like Toshia would later, Don had many questions, but for the time being he devoted himself to enjoying the playful, sensual company of this wonderful, enchanting woman. From the warm water and surf, to a big blanket by the fire, to a large, surprisingly cooperative hammock, they made love until they found themselves spent – drowsy in each other's arms as the sky began to lighten. “I looked for you at the Jungle Room,” Don said, his lips brushing the top of her head. “Jaden said you had been redecorating. Is that something you do with the ring too?” “Uh hum,” she murmured, “the Jungle is my place.” “How is all of this possible?” She chuckled a little, kissed his chest, and said, “I can't tell you, but you will see.” “I would like to see you again,” Don admitted. “You will be able to,” she said as she caressed his belly. “And you will be able to come back here, but you should always ask, first.” “Of course!” Don smiled. “How will I ask, though?” “Shhh, Don, let's sleep for a little while.” “You're into her too!” Toshia laughed. “How did I not notice that before?” “I'm sure I have no idea what you're talking about,” Don shook his head. “How many women are you in love with, Don?” “Jealous?” “Ha! No! I know you love me,” she grinned. “How does Sage…I mean, Evelyn, feel about this kind of thing, though?” “She seems to share your attitude, actually, though she is a bit more possessive. It's kind of a strange dynamic, actually. You could call my relationship with her my primary, if you want to use the polyamory lingo, I guess. Anyway, it's an exaggeration to say I'm in love with India. It's more like kind of passing infatuation. Other than being into sex, I don't even know if we have anything in common.” Toshia regarded him with a cocked eyebrow, then said, “Okay, if you say so. Now, if I ask you about those things you asked India, you're just going to say, 'I'm getting to that,' aren't you?” “Yeah, I'm afraid so,” Don nodded. “Sure enough, right after she took us back to the forest, I found myself teleported back to that crazy courtyard of the Crimson Mountain King. After the usual bathing ritual and taking the time to look around a bit for Evelyn, Nicole, and Stephanie, just in case, I was back in the office to get my next assignment.” “You're doing quite well so far, Don,” Pamela said from the other end of the table. “Three down and four to go.” “Thank you,” Don smiled. Knowing that he was almost halfway to being done definitely put him in a better mood about jumping through these hoops. Task Four: “What's next?” “Something different in a familiar setting, I think,” Pamela said with a smile. “We want you to take over the role of sheriff in the Resort.” “Okay, but what about the current sheriff?” “The position is currently vacant, I'm afraid.” “Okay, well, it seems like an easy enough job, I can take it on until someone else comes along.” “You misunderstand,” Pamela said with a smile of a different sort. “You're to take over the role of sheriff in the Resort for a year.” “A year?” Don gaped down the table at the council. “Moreover, you are not to have any sex for that year.” “Wait, what?” “Be the sheriff for one year without having sex,” Pamela repeated. “A year, fine, but… wait, what counts as sex?” “You're clearly familiar with the concept, Don.” “Yes, but what's the exact thing I'm supposed to be avoiding?” With the slightest expression of exasperation, Pamela looked to the witnesses to either side, but if they gave her any feedback Don couldn't see or hear it. Finally, she looked back at him and said, “No physical contact with another person for the purposes of sexual titillation or gratification either for yourself or the other person, or persons.” “So, masturbation…” “Yes, that's fine,” she cut him off a bit impatiently, “but you should be careful not to try to test the boundaries of our rules. We will not tell you if you have failed the task until the end of a year.” “So, I probably shouldn't try touching someone with a sex toy, I take it,” Don frowned. “Do I have to keep track of the time?” “No,” Pamela said. “Stay in the Resort, and we will let you know when your term of service is done.” “Okay,” Don shrugged. “Any other conditions to be met?” “No, that's it.” “Okay, I guess I'm ready, then.” Then, Don found himself standing in the sheriff's office in the Resort. He was wearing boots, jeans, a light white shirt and a denim vest with a star on it. His trusty staff was still in his hand. With a deep sigh of resignation, Don began his year as Sheriff. “A year?! That's crazy,” Toshia shook her head. “Plus, no sex, damn!” Don laughed, “Oh, I agree completely.” “What does the sheriff even do, really?” “Not an awful lot, it turns out,” Don smiled. “I mostly wandered around making sure people didn't 'disturb the peace'—you know, running around playing tag when people are trying to fuck, that kind of thing. Apparently, maturity and consideration aren't required for getting into Eros. Our crashing into the pool on our flying carpet definitely counted as disturbing the peace, by the way. Sometimes people get confused and lost, and it was nice to help them out. Of course, they often wanted to 'thank me' for my troubles, but I was a rock and politely declined.” “It must have been very hard,” Toshia winked and gave him a little nudge. Laughing, Don said, “Well, I've gone longer than that without sex out here, but the XYZ certainly made things … difficult.” “A year in the Resort… all that hot sex going on and you couldn't have any, damn!” “Well, I could, and did, masturbate – a lot – but it was supposed to be a challenge, so… I did amuse myself by wearing increasingly outlandish outfits from the Wardrobery, which was fun. And there were occasional breaks in the monotony. One of the things all of us agreed to before going for these rings was to check in with the sheriff any time we passed through the Resort. So, I was in a good spot for finding out how the others were doing. And, as it turned out, it was only about a week and a half into it when Evelyn turned up.” “Oh, that's good! How was she doing?” “She was doing well and had some stories to tell.” “Well, what do we have here?” said the familiar voice from the doorway. Don jolted upright in his chair behind the desk, where he had just been dozing a bit in preparation for his mid-afternoon nap. Then, when he saw the woman framed in the entrance to his jail, Don bolted to his feet, circled his desk quickly, and wrapped her in his arms. Then they were kissing passionately, in an embrace that lasted several minutes. Only when their lips finally parted did he say, “Sage… I mean, Evelyn! It's so good to see you!” “Right back at ya, stud!” she grinned. “Shouldn't you be in Gotham City?” Don stepped back to show off the Batman costume he had found in the Wardrobery, then tapped the sheriff's star on his chest, and said, “It seemed appropriate to the job.” “No mask, or … cowl, right?” “They had one but, it was seriously uncomfortable, and nobody was getting the joke anyway,” he shrugged. “Come on in and have a seat! Where have you been? How are things going?” She laughed, “That's what you want to do first?” “Ah, well, you see, 'want' isn't the right word here,” Don frowned as he sat on the edge of his desk. He quickly outlined the details of his current task. “Oh wow!” Evelyn said. “That really sucks. Which one of your seven is this, then?” “Four,” he said as he watched her move into the room. She was wearing a green tank top that fit her snuggly, a brown skirt, and a pair of hiking boots – in short, the same outfit she'd been wearing when they had gone together to the Crimson Mountain weeks ago. She propped her staff against the wall before she took her seat. Don was deeply distracted by her bare legs as she crossed them. “Ah, so we each have things to tell each other about,” she smiled. “You go first.” Don related his story about Shagbottom and Lady Primrose, which Evelyn pronounced, “Extremely hot!” While he was telling the story of his quest to 'win' India, Evelyn asked a number of questions about India, ultimately concluding, “She sounds like fun. I want to meet her!” “We can go look for her at the Jungle Room,” Don smiled, “but it's your turn.” “I don't know, lover,” she smirked. “Your stories have got me a bit hot and bothered…” “Well, I can't help you with that,” Don said wryly. “We could go find you someone to play with…” “What if I kill two birds with one stone?” she smiled as she uncrossed her legs and hiked her skirt up a bit. She ran her hands over her thighs, smiled over at the lust-filled expression on Don's face, and then began, “Well, my first assignment was right here in fact. I had to spend a week 'wearing the red' in the Temple of Venus and Aphrodite.” “Ah yes, we did that our first day here at the Resort, but just for one shift.” Don laughed a bit, “You definitely weren't the captain there; that must have been a challenge for you.” “I think that was the idea,” she chuckled. “Those 'watchers' do seem to know a lot about us, don't they?” “Yeah they do,” he nodded. “We had to do six hours. How long was your day?” “Ten hours, with three breaks in there, for refreshment and rest. That left me time each night to explore the Resort a bit before sleeping.” She was idly toying with her lips, pulling and stroking on them. Don forced himself to look up at Evelyn's eyes and asked, “Where did you sleep?” “Here and there,” she shrugged. “There's no shortage of beds and comfy loungers here, and nobody messes with you when you're asleep.” “They better not!” Don grinned. “The sheriff won't stand for that kind of nonsense.” “Good man,” she smiled. “Any particular things stand out from that week?” “Well, it took me a while to get used to just letting anyone who wanted to paw me and boss me around. By the way, women are just as bad as men about that. My butt seems to be some kind of grope magnet.” “It is particularly tempting, I must admit,” Don smiled. “'Sure you don't want to start your year over?” she winked. With a frown, Don shook his head and said, “It doesn't work like that. They'll just tell me at the end of a year if I pass or fail.” “Boo!” she said with an exaggerated pout. “Well, after I got used to the situation it got pretty easy to just go with the flow.” “Any favorite jobs?” “Well, one woman wanted a gangbang and they needed a fluffer.” “That's a bit surprising, to be honest, I mean here in Eros,” Don mused. “I thought so too, but there I was, giving head to like 30 guys.” “Damn! I'd like to have seen that!” Don adjusted the rising bulge in his Batman trunks. “It was hot,” she nodded as she slipped one of her fingers up between her lips. “On the other hand, having all those hard cocks to play with but no cum for me was a bit frustrating, and, after a while my jaw started to hurt.” Don frowned in sympathy. “Oh, one day they asked me if I could dance. 'Turns out there's a little club in there. “Yeah, the Temple's a bit more Vegas than Aphrodisia's.” “You're really such a nerd, aren't you?” She laughed. “Anyway, they wanted some novitiates to dance on tables and the bar. That was fun. At first it seemed like it was just going to be a chance to enjoy some music and dance, which was a nice break, but yeah, things got a bit… heated.” Evelyn had her own little stage about two meters across where she danced barefoot and naked to the very sexy pulsing music. For this assignment, she and the other dancers weren't wearing their usual red tunics, but had long red ribbons tied around their wrists, biceps and waists. The table on which she was dancing glowed white under her feet, and there were red and blue spotlights above focused on her. There were four of these tables, each with a dancer, two of them men and two women. At either end of the bar was another dancer, again one man and one woman. With the lighting as it was, it was a bit hard to see people who weren't dancing or over at the fairly well-lit bar. Evelyn could make out the people right at her feet, but the other 'patrons' of the club were just indistinct shapes in the shadows. At first, Evelyn was content to sway to the music, letting her body move along to the beat as if she were dancing just for herself. It had been a long time since she'd danced at all, and she'd forgotten how much she enjoyed it. Of course, the fact that she was naked in a spotlight, with XYZ coursing through her veins, made her very conscious that she was putting on a show, whether she was trying or not. Soon, her hands were moving over her body as she danced, gliding over her hips, cupping her breasts, caressing her neck and her face. Now and then her fingertips reached down to brush lightly over her lower lips, which were getting increasingly dewy. To be continued. By BradentonLarry for Literotica

Victorian Hedonism comes to life. By BradentonLarry - Listen to the Podcast at Steamy Stories. The two girls held a whispered conference on the big bed, and then Sage was pushing Reyansh away. She said, “Hold on one sec, lover; I want to try something.” There was a very quick rearrangement, during which Don never had to leave Felicia's sweet embrace. Then Sage was laying with her head hanging over the edge of the bed, as Felicia lowered her mouth to Sage's pussy and clit, which she proceeded to lick and suck. Felicia's ass was up in the air, and Don continued to fuck her from behind. Then Sage beckoned to Reyansh, “Bring that big boy over here.”Eager to comply, he lowered his hard cock for Sage so she could take it into her mouth and then her throat. Sage held his hips to keep her from getting carried away, but he was free to fuck her throat, and that's exactly what he began to do, reaching forward to cup and squeeze Sage's tits in his hands. Don looked down to see his relatively thick cock sliding in and out of Felicia's tight pussy, Felicia's perfect ass, her slender back, the back of her head with her adorable pixie cut, Sage's taut abs and strong thighs, her breasts being manhandled by Reyansh, her beautiful throat as she let him use it, and Reyansh's dark, athletic body as he worked himself in and out of Sage. It was a beautiful spectacle! Don could tell from the way Felicia was moving her right arm that she was fingering Sage as she licked. It didn't take too long before one of Sage's hands went from Reyansh's hip to the top of Felicia's head, and then it was only a minute longer before Sage was writhing on the bed between Felicia and Reyansh as she had a long, intense orgasm. As she shook and trembled, Reyansh pulled his now dripping wet cock out to let her breath. “Damn! That was a good one!” Sage breathed. “It looked like it,” Don grinned from across the bed. Sage sat up and grinned back at him, before curling up to grab Felicia's face and kiss her deeply. Reyansh got up on the bed behind Sage and coaxed her up onto her hands and knees. Then the two women were kissing in the middle of the bed as the two men fucked them from behind. No one was trying to come; they were just enjoying themselves kissing and fucking. After a little bit of this, Sage broke the kiss, and looked over Felicia's shoulder, smiled at Don and asked, “Are you enjoying her hot pussy, Don?” “Oh yes!” he grinned. “Are you enjoying Reyansh's big dick inside you?” “You know,” she laughed. “I really am.” “Good!” “I agree, but I was thinking… You know how I had all those dicks fucking me earlier?” “I do,” Don nodded. “It was very hot!” “Yeah it was! But I don't remember sweet Felicia here having more than one dick at any time.” “Is that right?” “Reyansh,” Sage asked over her shoulder, “did you see Felicia getting more than one cock?” “No, I certainly didn't.” All through this exchange, Felicia had done little more than giggle and push back on Don's cock. “Well, this won't do at all,” Sage decided. “Stop fucking me and get over here and feed Felicia your cock.” Don held still until Reyansh was in position, but then he went back to fucking little Felicia harder, shoving her forward onto the cock in her mouth and throat. Sage crawled over to him and kissed him deeply before bending down to reach under Felicia to play with her clit. Before they could get Felicia to the breaking point, though, Sage stopped and asked Don, “She's got a pretty tight little ass, do you think you can fit inside it?” “I could certainly try,” Don laughed. Felicia murmured her approval around Reyansh's cock. “Don't be so quick, sweetie,” Sage said. “You're going to have a cock in your pussy too.” Felicia's murmur was more enthusiastic, and she managed to nod her head rather emphatically. In another minute, Sage had Reyansh lie on his back and then Felicia mount him, bending forward so Don could push his cock, slippery with Felicia's juices, slowly up into her very tight, very hot ass. Sage leaned on Don's shoulder and whispered in his ear, “Fuck her ass good, baby. Make her come between you two studs!” “Yes, ma'am,” Don grinned, and proceeded to begin fucking Felicia's ass intently. Long, slow strokes gradually became shorter and faster. All the while Felicia was rocking her pelvis between the two men and groaning with pleasure. Sage move around to get down on her hands and knees so she could kiss Felicia, who could do little but let herself be kissed. “Do you like having those cocks fucking you?” Sage asked. “Yes,” Felicia moaned. “It feels so good.” “Are you going to come on their hard cocks?” “Uh huh,” Felicia breathed. “Very soon.” “Do it, baby!” Sage said as she stroked Felicia's pretty face. “Come for us!” “Oh god, yes!” Felicia cried as her body began to spasm between the two men. She shook and clenched, her pussy and ass pulling and grasping at the cocks inside her. Sage leaned in again and kissed her deeply. “Good girl,” she smiled. Then she looked over Felicia's shoulder and asked, “Did you come? No? What about you down there? No? Well! We'll have to fix that, won't we? You two were partners in the game, right? You met in Rendezvous, right? Very good. Don and I are partners too, so I think we should finish this swap right. Reyansh, I want you to give me your cum wherever you want, and Don, you come for Felicia.” Don slowly drew out of Felicia's ass so she could let Reyansh get out from under her. He took her in his arms and asked her, “Where do you want me to come, Felicia?” “Please fuck my ass some more, Don,” she said as her hand went to his cock. “But let me ride you.” In short order, Don was lying next to Sage. She had her legs wrapped around Reyansh's waist, while he held her wrists up over her head as he drove into her pussy. Don was holding his cock erect for Felicia, who was squatting over him, pushing her tight ass down over his flaring head and thick shaft. Felicia leaned back with her hands on Don's thighs and began to raise and lower herself on him. Reyansh was driving into Sage's pussy with abandon, grinding against her clit and surely bottoming out in her grasping pussy. He was looking into her eyes as he fucked her harder and faster. Soon, both of them were groaning and clenching on the bed next to Don and Felicia as Sage's pussy was eagerly pulling a flood of hot cum out of Reyansh's cock. Don found the fact that he was lying next to Sage as she climaxed on another man's cock intensely erotic. The thought that she was yet again getting filled with cum only made the situation hotter! Don began to arch his back to fuck up into Felicia's ass, and reached down to use his thumb to play with her clit. Then there was motion on the bed next to them, and Sage leaned across Don to replace his thumb with her mouth on Felicia's clit. Reyansh stood up on the bed and offered Felicia his cock to clean off. Don lay back and watched the beautiful woman riding his cock take Reyansh's cummy cock into her mouth and suck on it hungrily, and felt Sage's fingers against the base of his cock as she pushed them up into Felicia's pussy. Then Felicia was coming again, moaning around the cock in her mouth and pushing down on Don. This was all Don could take and he felt his body shoving up into her ass as his balls tightened and his cock swelled inside her. Then he was arching his back, pushing up on Sage and into Felicia as he erupted, pumping a geyser of hot cum up into her. Very slowly, assisted by Reyansh, a quivering Felicia fell backwards, letting Don's cock slip out of her. Sage immediately caught it and took it into her mouth, claiming the last of his cum for herself. When she managed to get up on one arm and look at Don, Sage smiled and said, “Another shower?” Don laughed, utterly smitten by the sleepy, well-fucked look in her eyes and her messy mane of red hair, and said, “Sure, but if you think you're getting more sex out of me…” She kissed him quickly and said, “We'll see about that.” Then she was clambering over him and pulling him out of the bed. Reyansh was lying there cradling Felicia in his arms, and Sage called back to them, “Don't take all the covers; we'll be back.” As the water poured over them, in a brief break in their making out and hurried cleaning, Sage looked up at him and asked, “So, out in the other world… um, are you seeing anyone?” Don chuckled, bent down to kiss her, and then picked her up. She threw her arms around his neck and wrapped her legs around his waist, sinking down on his cock. Don's hands gripped her ass and slowly raised and lowered her. He smiled and said, “Well, I have this relationship with Toshia that's gotten interesting, but, as you know, she's got a girlfriend, but, actually, I was thinking I would like to be seeing you. If you're free, that is.” “I think we can work something out,” she smirked. “I take it we're going to be swingers, or something like that.” “That does seem to be the way things are going,” he kissed her again. “How does that sound to you?” “Hum, pretty damn good. Just remember…” “I belong to you,” he nodded. “Aye, and, for the record, in case you were wondering, vice versa,” she said as she flexed herself against him, working up and down and grinding against the base of his cock. Don grinned, “Yeah, I worked that out.” “But we share.” “Right.” “And if we get a chance, we're banging the hell out of Toshia,” she said. “Of course.” “Good,” she kissed him. “Now fuck me. I want to have one more orgasm before we go to bed.” “Greedy girl,” he smiled. “Hell yeah!” “There was a lot more sex on the Riverboat, and we spent some time at the Resort.” “Did she really say that about me?” Toshia asked. “I swear,” Don chuckled. “Uh, I do like the sound of that,” she smiled. “But you were saying.” “Yeah, we did the Jungle Room, naturally, and I showed her the Temple. She got gangbanged in the Grotto, which is a very wet area, as you might expect.” “How many guys? In the gangbang, I mean.” “It's not a competition, you know,” Don laughed. Toshia rolled her eyes at him. “There were about a dozen, plus me.” “Yes! Still the champion!” Toshia grinned. “Well, that was before her trials, so…” “Doesn't count,” Toshia said. “Seriously?” “I have ruled. Okay, you can go on with the story.” Chapter 7. Lady Primrose's Earrings As he and Sage made their way to the Crimson Mountain, Don was acutely aware of their impending separation, and the fact that they might remain apart for quite some time. Accordingly, he made sure they had a variety of plans for meeting up, if possible, leaving messages, when the opportunity presented itself, etc. Passing through the Manor they would leave word with the Scholar, and then linger about there at least for a few days. Passing through the Resort they would both check in with the Sheriff and leave word with the Sage. “I'll try to remember that,” Sage laughed. “Yeah, and I'm trying to get used to thinking of you as Evelyn,” Don smiled. Don also told her about the Wizard as a potential ally whose home might be a good meeting place, and the Witches of the Glen who might be helpful. Of course, they also thought the Maidenhead might be useful, even if they couldn't be too sure it would long remain in Megan's control. In turn, Evelyn told him about a cafe in the bazaar on the far side of the sea, and they agreed to check in at the tavern on the beach and Ambrosia's when in the vicinity of Rendezvous. When they got to the locker rooms in the Hall of the Crimson Mountain King, they bathed, but Don made a point of retrieving the staffs the Wizard had given him and Shelonda what seemed so long ago. Stephanie had had no real experience with such things, and Nicole was positively averse to using any kind of weapon. Evelyn, though, had some martial arts training, though it was mostly in aikido, and definitely had no problem with weapons. “Too bad we don't have swords,” she mused as she spun the enchanted wooden staff in her hands. Having been made for Shelonda, it was just about the perfect size for Evelyn. “God, you're hot!” Don grinned as he admired the way the muscles in her arms and wrists moved as she played with the staff. “Oh, we should have gotten bows and arrows from the elves!” Don groaned, “Ugh, why didn't I think of that?” She laughed, “Well, you're not the only one who didn't.” “On the other hand,” he mused, “it doesn't seem like we're very likely to be called upon to fight anyone. Still, an unbreakable staff can be a useful tool.” “Hard wood can definitely be good to get your hands on,” she smirked. It turned out that, as long as they bathed and were naked, the red-robed servitors had no problem with letting them proceed into the Pleasure Dome and seemed to pay no attention at all to the staffs. “Holy hell!” Evelyn breathed as they entered the vast chamber, momentarily stunned by the scale of both the room and the orgy going on in it. “Yeah,” Don nodded. They proceeded to the circular couch in the middle of the dome, Evelyn taking in the spectacle as they went. “The king's throne is that away, but I want to see if we can just ride the sofa up,” Don said. “But first, come with me. I want to have some time with you before we head up.” He led her down to the base of the stairs, where they set their staffs off to the side, out of the way but close at hand, and made love for what might be the last time in a long while. Though a few of the other revelers offered to join in, Don and Evelyn kept to themselves this time. When they were finally worn out, they made a quick trip to the nearest fountain to clean up and then returned to the sofa. With their staffs across their laps, and their hands tightly clasped, they rode the couch up to the waiting room. “Damn!” Evelyn grinned. “This is not safe at all!” “I'm starting to suspect it's not actually that dangerous,” laughed Don, “but I'm not about to test that theory.” “Good! I'll be pissed at you if you kill yourself testing something like that.” “Aw that makes me all warm inside,” he grinned. “Oh, you're right, this is a bit anticlimactic,” Evelyn said as they came to a halt in the waiting room. “Told ya,” he smiled. “Hi, Gladys! Miss me?” After a wait that seemed both rather too long and excruciatingly quick, Gladys announced that ‘they' were ready to see Evelyn. She took her staff and got up, but Don pulled her into his arms and kissed her again. He gave her ass a long squeeze, smiled, and said, “Don't forget me, gorgeous.” “Unhand me, sir!” she laughed. “I will not be kissed and fondled by strangers!” “Well, that's just not at all true,” he grinned and kissed her again, focusing all his passion for her in this one last embrace. Don watched her exquisite ass as she crossed to the “Interviews” door, smiled encouragingly as she looked back before going through, and tried to ignore the ache in his chest. He had gotten very fond of Evelyn indeed. Eros, and his own schemes, kept separating him from loved ones—first Toshia, then Shelonda and Nicole, and now Sage… Evelyn. He was as down as he had been in Eros when Gladys let him know that he could go in and wasn't in much better of a mood as he sat down opposite Pamela and the other watchers. He kept his hand on his staff, just in case he was abruptly teleported away. Task Two: Lady Primrose's Earrings. “Welcome back, Don,” Pamela nodded. “I would say that you completed your first trial with flying colors. We expected you to sleep with Captain Sage, not convince her to come back here with you and undertake her own set of trials.” “I didn't really convince her,” Don frowned. Pamela shrugged, “That's not really important. You did, clearly, finish the task adequately. We assume you're ready for your second trial…?” Don nodded, “Yes. Bring it on.” “We want you to bring us Lady Primrose's emerald earrings.” “Uh, Lady Primrose? I've never heard of her,” Don worried. “How will I find her or her earrings?” “That might well be part of the trial, Don,” Pamela pointed out. “However, in this case, we'll help you with that.” “I appreciate that,” Don smiled. “Is there anything else I should know?” “There is quite a lot you should know.” Don arched his eyebrow at the hint of a sense of humor, then said, “Okay, I guess I'm ready.” “One more thing, though, Don: no more strays.” Then Don found himself standing in the middle of a street in what seemed like a small English town. It seemed to be early morning. The buildings had a decidedly quaint English countryside feel to them, and Don suddenly realized that he was fully clothed, wearing khaki slacks, shoes and socks, and a pastel polo shirt, with a light sweater tied by its sleeves around his shoulders. He was still holding his staff. Between the clothes and the mundanity of the town, Don thought this was the oddest place he'd yet seen in Eros. “Just a little town?” Toshia frowned. “That does seem strange.” “Oh, believe me, it gets weirder,” Don chuckled. The Town of Shagbottom There seemed to be some larger buildings down the road, so Don headed that way, in the hope of finding someone who could direct him to a “Lady Primrose.” As he went, he found himself enjoying the peace and quiet, and noticed that there were birds singing. All in all, it was a very pleasant locale. He was walking down the middle of the street—there didn't seem to be any sign of cars—and had just cleared the first intersection, when he finally saw signs of human life. The front door of the house on Don's right opened and out stepped a tall, thin fellow wearing a dark business suit and carrying a briefcase. This man turned around to receive a kiss goodbye from a woman wearing a brightly flowered dress, and then headed down a paved walkway through his neatly manicured front yard toward the street. Up and down the street, Don saw this basic ritual played out again and again over the next couple of minutes. Apparently, all the men in this town… no, there were a few women, also in business suits… left home at pretty much the same time in the morning, to go to work…? Half expecting everyone to head off in the same direction, Don paused in the street to watch as the townsfolk joined him. However, they seemed to have different destinations in mind. The man who had come out first turned right at the street, walked down three houses, crossed the street, looked both ways to make sure no one was paying attention to him, pushed open the front gate in front of him, and quickly made his way to the front door of that house, loosening his tie as he went. Every person seemed to have a similar course of action, going from their “home” to another house in the neighborhood, in a bizarre, chaotically choreographed pattern. After a minute or two, Don was again alone in the street. “Well, okay then,” he chuckled before continuing down the street. At what Don assumed was the center of town, he found establishments with names like “The Shag' Odeon,” “Mabel's Sundries,” “The Morning Whip” (with a sign adding, “Start Your Day with the Crack of Dawn!”), and “The Cum Inne.” Don considered where to begin but quickly decided that the apparent newspaper was so different from what he would normally expect in Eros that he had to start there. He pushed the door open, triggering a bell overhead, and a pale woman with dark red hair brushing her shoulders looked up from her desk behind a counter, smiled, and with a very English accent said, “Good morning. Welcome to Shagbottom!” Although Toshia would later fail miserably, Don managed to not laugh at this, but did have to pause and say, “Pardon me?” “Welcome to Shagbottom!” she repeatedly cheerfully. “Do you have some news to report?” “Ah, no, but… the name of this town is Shagbottom?” “That's right: Shagbottom of county Wrenchester.” “Okay,” Don was having an extremely hard time keeping a straight face. He looked back out the window that made up the front of the shop, saw the theater sign again, and just shook his head. Thinking of the other signs, he asked, “The inn's name… what's the abbreviation for?” “To shorten a longer word,” said a voice with another English accent from a woman who popped out from behind a shelf that was heavy with stacks of papers. She had lovely brown skin and black wavy hair that was cut short. She continued, “You know how you might want to save space, so instead of writing out all of ‘abbreviation,' you just use a-b-b-r period.” Don pinched the bridge of his nose and said, “Yes, thank you, but I meant 'what does the c-u-m period stand for in the hotel's name?'” “Oh,” the darker woman frowned. “You know, I'm not terribly sure. Ophelia?” The other woman looked up again, “Oh, hello Anna. I'm over here.” “Good morning,” Anna said as she moved closer to the front of the shop and the counter that separated the women from Don. “Do you know what the abbreviation in the inn's name stands for?” “Oh, excellent,” Ophelia smiled. “How many letters?” “Well, more than three, I should think,” Anna said. “That doesn't narrow things down much, does it?” frowned Ophelia. “Do you have any of the letters?” “Well, c-u-m, clearly,” Anna cast a sideways look at Don and shook her head. “'Cummerbund'?” “That seems a bit of a stretch,” Anna said. “Don't cummerbunds usually stretch a bit?” “Well, yes, I suppose, but that's not really to the point, is it?” “'Cumberbatch'?” “Don't be ridiculous, dear; that's not even a word.” “'Cumulative'?” “'The Cumulative Inne'?” “Why ever not?” Ophelia wanted to know. “It doesn't make sense.” “It certainly does,” Ophelia said a bit defensively. “'My score of twenty was the cumulative in our four games.'” Anna shook her head in exasperation. “That's not well said, though, is it?” Ophelia shrugged. “In any case,” Anna persisted. “We were talking about 'inn' with two ns, and sometimes a silent e.” “We were? Why didn't you say so?” “This gentleman here was asking about the name of the inn. What did you think we were talking about?” “Abbreviations, wasn't it?” “Well, yes,” Anna nodded with some exasperation, “but one abbreviation in particular.” “I see,” Ophelia said thoughtfully. “But then, if this is the abbreviation about which we're inquiring, it might be the abbreviation of someone's name, mightn't it?” “I suppose that's true, love. Good point,” Anna smiled. “But then why couldn't it be 'Cumberbatch'?” Anna's eyes threatened to roll all the way up into her skull as she exclaimed, “That's the most ridiculous name ever! Who would ever consent to call themselves such a ludicrous thing?!” “Well, who are we to judge?” Ophelia shrugged. “I don't suppose you would object to someone's being called Cumberbatch if she had a very nice pair of tits, or if he had a big pecker, now would you?” “What are you trying to say, exactly?” “One shouldn't judge someone on the basis of their name, but on the things that really make them who they are,” Ophelia smiled, clearly thinking she had won this round. “I'm not suggesting one should judge anyone on the basis of their name, Ophelia. I'm saying that we should judge their name on the basis of its being quite ridiculous. 'Cumberbatch' indeed!” Before things could get any more heated, Don, who was having a very hard time not laughing, interjected with, “Ladies, please! I really don't need to know about the inn.” The two women glowered at each other for a moment, and Anna took the opportunity to clearly mouth the word “ridiculous” at Ophelia, before she said, “Very well. Good morning, sir. How may we be of service?” The first thing that occurred to Don when Anna asked him that was that this was the first time someone had given him an innuendo-laden opening like that while completely dressed in a long time. Surely, he could probably say he could use a blowjob, and at least one of the two attractive women would be happy to oblige. This was Eros, after all. On the other hand, the fact that they were dressed, and he actually had a mission to accomplish, led him to the conclusion that he probably should get some information out of the two of them, if that was actually possible. He was about to ask about Lady Primrose, when Don realized he wanted to ask about something else first. “I was wondering, what exactly do you do here?” “We write and print the daily newspaper, of course,” Anna smiled. “Very good,” Don nodded, “and what goes in the newspaper?” “All the news!” Ophelia enthused. “We keep the good people of Shagbottom informed on all the goings on.” “Such as?” “What's playing at the 'Odeon, any new toys at Mabel's, notices of special events,” Ophelia started. “Coverage of said events,” Anna added as she leaned on the counter in front of Don. She had undone a few buttons of her blouse. Ophelia got up and began moving toward her partner, as she continued with, “The daily lottery results, the crossword, interviews with prominent citizens…” “And of handsome newcomers,” Anna smiled. “Oh, that's a good idea, Anna,” Ophelia nodded. Don smiled back at them, flattered by the attention and amused by the turn toward more typically Erosian matters. Then, though, he realized he had more questions. He started with, “What kind of special events?” “Socials, parties…” Anna said. “Garden parties!” Ophelia cut in. “Well, yes, those are included in parties, aren't they dear?” “Naturally, but aren't socials just another sort of party?” Ophelia asked. “I think it's the other way 'round,” Anna frowned. “Either way 'round, then, you started it.” Don decided to jump in before the conversation got too far afield again. “So, mostly parties, eh? Anything else?” “Most of the special events are parties, it's true,” Anna nodded. “They're very nice parties, though,” Ophelia said. She had followed Anna's lead and started unbuttoning her top. “Everyone has such a splendid time.” Don smiled at them, guessing that the parties in Shagbottom probably turned into orgies at some point. He decided to ask, “And you said something about a lottery…?” “Oh yes, that's very important, of course,” Anna nodded, as she shrugged her blouse off her lovely brown shoulders, exposing her full breasts. “What do lottery winners win?” Don asked, taking a step toward the counter and the women as he untied the arms of the sweater around his neck. “What do they win?” Ophelia was a bit confused. She had tossed her top aside and was now shimmying out of her pencil skirt. “Oh, it's not that kind of lottery exactly,” Anna said as she stood up from removing her own skirt. She pushed a sheet of paper across the counter to Don and said, “Here.” On the page were two columns of addresses. Don looked at them as he took off his shirt but couldn't see any pattern or meaning. Anna hopped up on the counter, and pointed to the left column, saying, “This is each couple's address…” “Well, if they picked up their ticket for the day,” Ophelia pointed out. She had moved over to a gate in the counter Don hadn't paid any attention to and was coming over to Don's side of the room. “Yes, certainly, it wouldn't do at all to make people play who didn't want to,” Anna smiled as she spun around on the counter, her long, stockinged legs and stiletto-heeled shoes flying over Don's head. Don smiled at briefly at the sight of Anna's bare, pink pussy, and then realized, “Oh, the other column is the addresses of where people go for the day when they leave in the morning.” “Exactly,” Anna smiled as she spread her legs and scooted up to the edge of the counter. She crooked a finger at Don and asked, “Care to join us for our early morning break…? Oh, how rude of us! What was your name?”Gretchen's Hospitality at Lady Primrose's Estate. Toshia couldn't help but laugh all through the story of Don's encounter with Anna and Ophelia. By the time he was wrapping that up, the two of them had stopped and sat down on a bench in a secluded part of the park. If it had been a bit more secluded, Toshia thought she'd probably break her rule and give Don a blowjob right here. All the sex shenanigans she was picturing had gotten her rather worked up, and she really just wanted to suck on his cock. Of course, that wasn't all she wanted to do… It wasn't that secluded, though, so she managed to behave. However, she did enjoy snuggling up against him, his arm around her shoulders, as he continued his story.“So, yeah,” he said, “after the early morning break, and with a lot of patience, I was able to learn that Shagbottom was basically a rather stable community of people who paired up, somehow, and then enjoyed a rather thorough swinging lifestyle. Each day, but just during the day, they swapped partners, if they participated in the lottery the day before. They rejoined their ‘spouses' at night. Every few days there were social events, or parties, that were pretty much excuses for more partner swapping and/or orgies.” “It sounds like your kind of place,” Toshia smiled. “And not yours?” “Well, yeah, that was implied.” It was afternoon, the three of them had given up on clothing, Don was reclining in a chair with Anna curled up in his lap, and Ophelia was sprawled across her desk with a happy post orgasmic smile on her face, when Don finally got around to, “So, I need to find a Lady Primrose…” “Oh, yes, she's lovely!” Anna purred enthusiastically and bit sleepily. “Her garden parties are the best!” Ophelia added. “She makes sure to invite everyone in town.” “You'll like her,” Anna nodded. “She's the sweetest, poshest lady.” “Folks say the garden parties aren't even the sexiest ones she has,” Ophelia rolled onto her side to look at Don with a conspiratorial glimmer in her eye. “She has masked balls with lords and ladies from all over. It's all very classy and mysterious!” “Oh, hush, Ophelia,” laughed Anna. “That's just gossip. Lady Primrose doesn't put on airs. She's just a nice, friendly, normal person.” It was time for Don to reinsert himself in the conversation. “Well, can you tell me where to find her?” “Of course,” Anna chuckled. “She'll be up at Heolfor House, if she's not traveling.” “And you can direct me to this ‘Heolfor House'?” Anna kissed the side of Don's neck and said, “Certainly, but don't you want to stay for Hazel and Bob's get-together tonight?” Of course, it was nearly impossible for Don to resist such an enticing invitation. It turned out that Hazel had a hankering for bukkake that night and Don was happy to help the local men scratch that itch. By the time he set off down the road for Heolfor House he had decided that the odd little town of Shagbottom was quite the friendly place. The Morning Whip's headline that morning read “Stranger Comes to Town, & All Over Hazel's Tits.” Heolfor House The walk from Shagbottom to the side road that bore a sign reading “Heolfor House” was long enough to discourage idle wandering in but short enough to be a pleasant walk through the countryside. Don thought he must look quite mundane with his clothes and walking staff, and he had to admit this was perhaps the most “normal” day he had spent in Eros so far. He paused at the signpost and wondered where the road would take him if he just kept walking. With a shrug, Don decided that would have to wait for a return trip to the county of Wrenchester and started up the much narrower path toward Heolfor House. Flowering trees grew close to the path, spreading their branches overhead, making for a lovely, shady walk. On the left, through the trees, Don could make out what looked like a cemetery, with a carefully manicured lawn and ornate headstones, as well as what seemed to be moss-covered tombs. The many flowering shrubs and the sunshine gave it a very welcoming appearance, offsetting the fact that this was the first indication of anything like mortality in Eros. Don doubted that anyone was really buried there, but surely someone must have graveyard fantasies to live out. He filed this away to ask about when he got the chance. At the end of the path, Don came to a big arch of heavy rocks that seemed quite ancient, as if the archway predated the path and even the surrounding forest by millennia. Certainly, it seemed much, much older than what Don found on the other side, and what Don found looked pretty old. A broad gravel path spread out in front of him leading directly up to the front of an enormous manor house. There seemed to be three main floors, with smaller floors above and twin towers rising on either end of the facade. All along the edge of steepled roof were spiky ornamentations. Heavy curtains hung in the many windows, and the stonework emphasized both the run of the floors and the way the mansion rose up over the viewer. In retrospect, the Manor had had a southern French, or Mediterranean, feel, while this was decidedly English. The fact that there was a fountain between him and the entrance to the building as well as exquisitely groomed green hedges spreading out around this courtyard somehow only slowly came into Don' attention. There was just something about Heolfor House that drew his attention. Even though the day was sunny and warm, and he knew he was still in Eros, there was somehow something off about this building. It just didn't seem to fit, though Don had to admit that it actually seemed a perfect fit for the whole English countryside fantasy. Anyone who had any Upstairs, Downstairs or Downton Abbey kinks would love this place! Skirting the fountain, Don crossed to the big double doors and pressed the button on one side. When there was no response, he pressed again. He was about to press a third time when the door on the right opened enough for a tall, bald man in a dark suit to look out at Don with clear disapproval. “Hello,” Don smiled. “I'm, uh, hoping to speak with Lady Primrose.” “Are you expected, sir?” the man said. His tone clearly indicated that he knew full well what the answer would be. “No, I'm afraid not.” The man, who Don was assuming must be a butler, gave him a look that conveyed the fact that Don's existence in that moment and place was quite possibly the most inconvenient thing in the universe. He said none of this, though, but only said, “Her ladyship is not receiving callers at the moment.” “Would it be possible for me to wait?” Don smiled again. “Of course, it would, sir,” the butler frowned, clearly annoyed that he was being asked such a trivial question. There was a long pause, before Don decided he would have to prod further. “May I wait, perhaps inside?” The butler's expression never changed but his eyes managed to tell Don that he was personally contributing a great deal to the overall misery in the world. Still, he intoned, “Certainly, sir, please do come in.” The entry hall was, of course, massive, with an extremely high vaulted ceiling from which a dazzling chandelier hung. Dark wood paneling covered every surface, and broad curving stairways flowed up to the second floor. Paintings and tapestries hung on the walls. After getting his name, the butler led Don to the left, pushed open a tall, slender door, and said, “If you would be so kind as to wait here, sir.” Don stepped into a narrow high-ceilinged sitting room with thick, dark carpeting and a large fireplace taking up most of the right-hand wall. The sunlight from one window cut the room in half; what wasn't glowing brightly was almost black in contrast. Tiny motes of dust floated lazily in the yellow light. As the butler shut the door behind him, Don stepped toward the window, hoping to get a look out at the gardens he thought must be outside. But as he drew near, a voice addressed him in a cultured British accent, “Here for the party?” Don turned and peered into the shadowy corner to the right, opposite the door by which he'd entered. He took a couple of steps, out of the sunlight, and said, “Party?” “Just calling to pay your respects, then?” said the dark-haired man in the corner. He was slouched in an armchair. There was a woman kneeling between his legs with her head in his lap. He was wearing black slacks and a dark shirt that was unbuttoned, exposing an athletic chest and abs. She was wearing a pastel blue, backless dress, and had light blonde hair. She was quite intent on the blowjob she was giving. “I suppose that's right,” Don nodded in answer to the man's question. “There's a party, though?” “That's right, tonight,” the man held up his finger as he closed his eyes and smiled. After a long moment of silence, he said, “Everyone who's anyone will be there. Get up, Cessily' and say hello to our new American friend.” The blonde stood up easily, took a step back and turned to smile at Don. She wiped a bit of cum away from the corner of her mouth with the back of her hand and said, “Hello there.” The dark-haired gentleman stood up, tucking his cock back in his trousers, and crossed to Don and extended his hand. As Don shook his hand, the other man said, “Lucien, and this is my sister Cessily.” Don suddenly had a number of questions but couldn't decide which to ask first and what was clearly rude, so he just said, “Don. I'm very pleased to meet you.” Cessily glided up next to her brother and smiled at Don with the kind of open sexual interest he'd grown so used to in Eros. She batted her brown eyes at him and said, “It's so good to have some fresh blood for one of these parties.” “Oh, well, I'm honored, I think,” Don smiled. Cessily was certainly charming. “I'm really just here to have a chat with Lady Primrose.” “Ah, well, it is her party,” Lucien smiled, with much the same undercurrent as his sister's smile. “There's no reason you can't have your cake and eat it too, is there?” Don frowned a little as he tried to sort out Lucien's question, but then the butler cleared his throat on the other side of the room. Don peered through the light, couldn't see clearly enough, took a few steps in that direction. The butler didn't wait for him, but said, “Sir, her ladyship is indisposed, but asks you to accept her invitation to tonight's party.” “That would be great,” Don smiled. “I'm afraid I don't have the proper attire, though.” The butler paused, as if to make it clear that Don was continuing to make his life an unendurable hell, and said, “We will endeavor to correct that situation, sir.” “Oh, well, that's great,” Don nodded. He turned back to say something to Lucien and Cessily, but they had already left, presumably through the door Don now noticed between the armchair in the corner and the fireplace. With a quick shrug, Don followed the butler back out to the entry foyer. Picking up a bell from a little table in the corner, the butler rang twice and then waited until a young woman in a black and white French maid outfit hurried in through a door at the foot of the far staircase. She was short, but had very nice long legs, and had dark brown hair that was pulled back into a bun and seemed to be quite long. She wore a black choker around her lovely, thin neck. She was trying to straighten her uniform as she hurried over to the butler and Don. “Gretchen, please show this gentleman to an available room and help him prepare for the party,” the butler said in a way that seemed to imply that Don would need a great deal of help indeed. “Yes, sir, of course sir,” Gretchen said with an adorable English accent as she bobbed her head and managed to smile at Don, batting lovely blue eyes up at him all the while. She began to turn toward the stairs, and said, “Please come this way, sir.” Quite happily, Don followed the young woman up the stairs, using the time to admire her gorgeous legs with the stockings that ran up to the middle of her firm thighs and the way her bare bottom and the lower lips of her pussy could be seen peeking out from under her short skirt. Gretchen led Don up several flights of stairs and then down a shadowed hall with a big window at the end, turning at last to a door, which opened to a large bedroom. “You may use this room during your stay, sir,” Gretchen smiled. “There are clothes here in the closet.” She opened the door to an enormous walk-in closet and led the way in. There were indeed quite a few suits available and, given his experience in Eros, Don had little doubt that he would find something that fit him nicely. Then Gretchen was bending at the waist in front of him, saying, “And down here are shoes.” Don couldn't resist reaching out and running his hand over her perfect, pale behind. When she did nothing to pull away, he gave her bum a squeeze and then lightly ran his finger over her labia. He could feel that they were already dewy, and there was a bit of pearly cum leaking out of her. Don remembered her straightening her uniform and realized what she must have been up to before the butler had summoned her. Don parted her lips and smeared some of the cum he found there down over her clit. “Uh, that feels very nice, sir,” Gretchen purred. “If you don't mind my saying so, sir.” “Oh, I don't mind at all,” Don chuckled. Since she didn't move away or stand up, Don pushed his thumb into her cummy pussy and started using his fingers to play with her clit in earnest, caressing and squeezing her young ass with his left hand. Gretchen pushed back toward him and murmured, “Oh, sir!” Somewhat clumsily from recent lack of experience, Don undid his pants with his left hand to free his now rather hard prick from its confines. He hadn't had any sex all morning and early afternoon, which in Eros seemed a rather long time, and the way this very fetching young woman was bent over in front of him and responding to his manual stimulation was easily enough to inspire a nearly painful erection. Without waiting for any further invitation, Don pushed his cock down and replaced his thumb in her pussy with the head of his penis. As he pushed into Gretchen from behind, she moaned happily and pushed back against him. With the heat of her tight, wet vagina wrapped around him, Don fought off the physical impulse to come immediately, but only barely. Soon, Gretchen was supporting herself with her left hand on the low cupboard that housed the shoes she'd been showing Don while the fingers of her right were strumming furiously across her clit, and Don was plowing into her violently, holding her slender waist in his hands and pulling her petite body back onto his straining cock. Don suspected her earlier play had been interrupted before she was able to climax because it didn't take long at all before she was shuddering and gasping as she came on him. Then she was on her knees in front of him, one hand on the base of his thick shaft pumping him, as she sucked enthusiastically on his head. Her pretty little face was intensely sexy as she looked up at him with her lovely blue eyes. “Oh, God!” Don groaned as he felt himself swelling in her hand and mouth. Gretchen pulled back off him, but began to stroke him even harder, and said, “Yes, sir, please come for me.” Instinctively, Don pushed forward as his whole body clenched around the base of his cock. Gretchen smiled up at him and kept stroking his shaft until she was rewarded by an explosive gout of cum shooting out and across her sweet face. Don trembled and groaned as another burst of cum splashed onto her and then another. Still looking up at him with her blue eyes, Gretchen sucked his cock back into her mouth and proceeded to swallow the rest of his orgasm. When she finally released him, she said, “Thank you very much, sir.” “Wow!” Don breathed. “And thank you, Gretchen.” He thought to ask her to call him 'Don,' but he decided he quite liked the way she said 'sir.' “It's my pleasure, sir,” she laughed as she stood up. She paused a moment to lick some cum off her lips and to wipe some off her nose. She promptly sucked her finger clean, and then said, “Perhaps you would like me to draw you a bath, sir.” Naturally, for Eros, the room came equipped with a large, luxurious bathroom, and Gretchen joined Don for a long, extremely enjoyable bath. She stripped out of her uniform but kept on her little hat and the choker Don found so sexy. As they engaged in a rather wet session of foreplay masquerading as bathing, Don was able to ask a few questions. He started with, “How long do we have?” Gretchen smiled sweetly as she pulled on his hardness beneath the water, “As much time as you need, sir.” “Oh, well, need and want are two very different things,” Don chuckled as he leaned in to kiss her firm breast and flick his tongue over her hard nipple. “But I mean until you have to go back to work.” She sighed and pulled Don's head down to her breast again, while squeezing his cock a bit tighter. She said, “I am supposed to attend to any of the guests' needs, sir, so…” “But won't you be needed for … other things?” “There are other staff, sir, and if I'm missed I'll only get a spanking, which I don't mind much,” she winked. He smiled up at her as he slipped two fingers up inside her and asked, “Well, then, how long until the party starts?” “Oh,” she bit her lower lip as she rocked on his hand a bit, “the parties never start until after dark. So, a couple of hours, I should say, sir.” “Never?” Don asked as he released her nipple from his mouth. “Even the garden parties I've heard so much about?” “Oh, yes, those are so lovely, but they always begin after sunset. Lady Primrose does so love the nighttime, and the gardens are so beautiful all lit up with candles.” “I'd love to see them,” Don smiled as he stood up in the tub. Gretchen smiled at the hard cock that was now standing out before her. She ran her hand lightly over it and leaned in to give it a kiss, but Don took her hand and drew her up to kiss her sweet mouth and then to lead her out of the tub. After they had dried off some, they made their way back out to the bedroom where they found quite a few ways to spend the next hour and a half. Don's favorite moment came after Gretchen had let down her very long hair to cascade down over her shoulders like a cape as she rode slowly on him, leaning forward with her hands on his shoulders to look into his eyes. He ran his hands up over her slender naked body, caressing her tits and then slipping around her neck, fingers brushing over the choker she still wore. “Tighter, please, sir,” she sighed. As Don gently squeezed her throat, restricting her breath and circulation, Gretchen smiled, nodded, and whispered, “Yes, tighter!” A bit concerned, Don obliged. Gretchen's face darkened a bit, and then she was trembling with a long, silently intense orgasm. When he relaxed his grasp, she smiled down at him with an utterly unfeigned gratitude and affection. After a much briefer bit of cleaning up, and making sure that Don actually found a suit to wear to the party, Gretchen got back into her uniform, this time with her dark hair in a long, thick ponytail, gave him a quick, surprisingly chaste kiss, and left him to his own devices. Don checked himself out in the mirror and thought he was party ready. He was wearing black slacks, jacket, and shoes, and a dark red shirt, which was open at the neck. He had been a bit surprised that there were no ties to be found in the closet, but Gretchen had assured him that this was deliberate. “The lady doesn't like neckties,” she had said as if she were saying nothing more interesting than “she doesn't like Brussel sprouts.” Toshia fixed Don with a skeptical eye and a cocked brow. Don laughed and said, “Yeah, yeah, I was thinking the same thing.” Stepping out into the hallway, staff in hand, Don noted that there were two other guests making their way to the stairs. Don caught up to the black gentleman just before either made it to the top of the stairs, and the tall east Asian woman coming from the other end of the hallway met them there. “Hello, I'm Don,” he smiled, extending his hand first to the man on his left. “Good evening, I'm Jerome,” the fellow smiled in return. Don guessed that Jerome was at least ten years older than himself, though he knew time and aging in Eros were tricky affairs. Jerome had very dark skin, wore his hair and beard, which were sprinkled with some grey, buzzed short. He was also wearing a dark suit, but with a white shirt, and seemed to have an athletic build. “Bian,” the beautiful young woman smiled as she shook each of the men's hands. She had lovely green eyes and curly dark brown hair brushing her shoulders. She was quite tall and wore a deep green floor length dress that left her long neck and sculpted shoulders bare. “Is this your first time to one of Lady Primrose's parties?” Don asked as they started down the stairs. “Yes,” Jerome nodded. “I was quite surprised to be invited.” Don frowned to himself a bit and asked, “And how were you invited, exactly?” “A lady friend suggested I would enjoy it, and the next thing I knew I was here,” Jerome explained, apparently without realizing there was anything odd about his story. “I see,” Don nodded. “Do you mind if I ask where you were talking to your lady friend?” “Oh, well, we were both visiting a lovely resort.” Don smiled and said, “I see. And what about you Bian? Is this your first time, too?” “Yes,” she said with a slight nod and smile. Don thought she didn't have a British accent, but also concluded that she was disinclined to engage in a long conversation. As they descended to the ground floor, Don noticed in passing, as they passed a few windows, that the sun was setting and it would soon be dusk. He felt a bit awkward carrying his staff along, but he was also quite glad to have it along. Candles were now illuminating the stairs and hallways, casting wan light and creating deep shadows. Don had seen no one lighting the candles, but by now he was used to these things happening on their own. On the ground floor, gathered in the entry hall, were about 20 other guests, waiting for the party to begin. Jerome and Bian slipped into the crowd, as Don looked around a bit. He was a bit surprised when someone tapped him on the shoulder. Turning he saw a couple he had met just the night before. “Cheers, Don,” grinned Rodney, a big, cheerful redheaded guy who had helped with Hazel's bukkake. Right next to him was Marilyn, the slender, middle-aged, brown-haired woman who had been introduced as Rodney's partner last night. She and Don had not done anything together at the party, but for a moment Don thought it would be very nice to correct that oversight. Don smiled back at them, “Good evening! I didn't know you'd be here tonight.” “Neither did we,” Rodney laughed. “We won the weekly raffle.” “Ah, I didn't know there was a weekly raffle, either.” “Ay, every week!” the big guy laughed again. “Is this your first time?” “Sure is,” Rodney nodded. “Posh house, in'it?” “It certainly is,” agreed Don, “and the staff is quite accommodating.” “Oh! 'Sounds like you've had a good afternoon,” Rodney chuckled. “I did,” Don smiled, finding it impossible not to get caught up in Rodney's enthusiasm. “Oh, but please excuse me for a moment.” Don had just caught sight of the butler and had come to an abrupt decision. Taking a few steps to intercept the taciturn man, Don said, “Excuse me, my good fellow.” The butler turned on him with an expression that clearly indicated he was not amused by Don's attempt to assimilate to the culture. With what seemed a herculean effort, he said, “Yes, sir, how may I be of assistance?” “I was wondering if it would be a problem for me to leave my staff here over there in the corner by the door.” “Why should that be a problem, sir?” “I don't know, but I don't want to put anyone out.” “I'm sure no one will be 'put out,' sir.” “And no one will move it?” “Ah, well, I cannot speak for everyone, sir, but I can assure you that myself and the rest of the staff will leave your walking stick unmolested.” “Thank you,” Don smiled, partly because he got the impression his cheerfulness was a personal affront to the butler. By the time Don had propped his staff in the aforementioned corner and turned back to the gathering of guests, the large double doors into the ballroom had been opened and everyone was gradually moving inside. Don found himself bringing up the rear. To be continued. By BradentonLarry for Literotica

Prema Varadhan, President Product & Chief Operating Officer, TemenosAs President Product and Chief Operating Officer, Prema Varadhan is responsible for leading the Product and Technology organisations within Temenos, working directly with customers to identify their challenges and meet market demands. She also leads Temenos' Global Services and SaaS Engineering. Robin Amlôt of IBS Intelligence speaks to Prema Varadhan ahead of the annual Temenos Community Forum. 

When Chen Shui-bian 陳水扁 began his university studies in 1969, gifted student though he was, few could have imagined he would become Taiwan's first non-KMT president. The young Chen had no political plans – he wanted to study business and make money for his impoverished family in rural Tainan. One day during his first semester, he heard a speech by an independent candidate who publicly criticized the autocratic rule of the KMT. Chen was fascinated. Listen to this week's story to learn how Chen changed majors, and despite being called “boring” by a few young women he liked, eventually wed Wu Shu-chen 吳淑珍, the daughter of a wealthy Tainan doctor. Plus, Chen's involvement in the Kaohsiung Incident of 1979, a turning point for the democracy movement and for Chen. And we end with Chen's first stint in prison; not the more recent sentences for corruption, but in the mid-1980s for libel. Pics, links and more at formosafiles.com PLEASE RATE/REVIEW THE SHOW!!

In this week's Bonus Episode Jenna share's her coming out story, from straight relationships, psychic interactions and first dates!As well Zoe's thought provoking question "Would You Rather... More Time or Money?"Email: lifewithawife@runbyinfluencers.comInsta: @lifewithawifepod Hosted on Acast. See acast.com/privacy for more information.

Bruno, Allan, Nicoll e Isa juntam-se para ler o Capítulo 8 de Rerise of Poseidon e discutir o passado de Io e Bian, dois Generais Marinas que ganharam novos contornos pelo autor. Que beleza! ACESSEBlog: http://podcastsaintseiya.blogspot.com.brTwitter: https://twitter.com/PodcastCDZSimpleCast: http://simplecast.com/PodcastSaintSeiyaFeed: http://feeds.feedburner.com/podcastsaintseiyaDiscord: https://discordapp.com/invite/T9JVaWS

∞ Set the controls for the heart of the sun ∞ ➳ ۞ Ethnic ➳ ۞ DesertMusic ➳ ۞ AfroHouse ➳ ۞ NuDisco ➳ ۞ MelodicHouse ➳ ۞ Techno ➳ ۞ DeepHouse ➳ ۞ ProgressiveHouse

Oh. My Gawd. I get it. Silver Bian...because Joni has silver hair....and she is a lesbian! Anyway, part 3! Hosted on Acast. See acast.com/privacy for more information.

En esta emisión de Dos Gardenias, Eduardo Aliverti propuso recorrer la obra del  poeta, narrador, ensayista y periodista, Fabián Casas, iniciado en el periodismo durante la década del ´90 y miembro fundador de la mítica revista de poesía 18 Whiskys, quien define a la poesía como una actividad permanente y la base central de toda escritura, cuya sola descripción resultaría anti poética reconociendola sin ofrecer explicación como una transmisión nerviosa y vital.

It gets deep in this episode! Hike up your boots and come wade through the stories with us on part 2 of The Silver Bian. Hosted on Acast. See acast.com/privacy for more information.

What do get when you toss a 16 year old girl in front of a hole in a fence while working rodeo bulls? Joni answers that question, plus a ton of other great laughs and one liners from the Silver Bian pt 1! Hosted on Acast. See acast.com/privacy for more information.

We are running an end of year survey for our listeners. Let us know any feedback you have for us, what episodes resonated with you the most, and guest requests for 2024! RAG has emerged as one of the key pieces of the AI Engineer stack. Jerry from LlamaIndex called it a “hack”, Bryan from Hex compared it to “a recommendation system from LLMs”, and even LangChain started with it. RAG is crucial in any AI coding workflow. We talked about context quality for code in our Phind episode. Today's guests, Beyang Liu and Steve Yegge from SourceGraph, have been focused on code indexing and retrieval for over 15 years. We locked them in our new studio to record a 1.5 hours masterclass on the history of code search, retrieval interfaces for code, and how they get SOTA 30% completion acceptance rate in their Cody product by being better at the “bin packing problem” of LLM context generation. Google Grok → SourceGraph → CodyWhile at Google in 2008, Steve built Grok, which lives on today as Google Kythe. It allowed engineers to do code parsing and searching across different codebases and programming languages. (You might remember this blog post from Steve's time at Google) Beyang was an intern at Google at the same time, and Grok became the inspiration to start SourceGraph in 2013. The two didn't know eachother personally until Beyang brought Steve out of retirement 9 years later to join him as VP Engineering. Fast forward 10 years, SourceGraph has become to best code search tool out there and raised $223M along the way. Nine months ago, they open sourced SourceGraph Cody, their AI coding assistant. All their code indexing and search infrastructure allows them to get SOTA results by having better RAG than competitors:* Code completions as you type that achieve an industry-best Completion Acceptance Rate (CAR) as high as 30% using a context-enhanced open-source LLM (StarCoder)* Context-aware chat that provides the option of using GPT-4 Turbo, Claude 2, GPT-3.5 Turbo, Mistral 7x8B, or Claude Instant, with more model integrations planned* Doc and unit test generation, along with AI quick fixes for common coding errors* AI-enhanced natural language code search, powered by a hybrid dense/sparse vector search engine There are a few pieces of infrastructure that helped Cody achieve these results:Dense-sparse vector retrieval system For many people, RAG = vector similarity search, but there's a lot more that you can do to get the best possible results. From their release:"Sparse vector search" is a fancy name for keyword search that potentially incorporates LLMs for things like ranking and term expansion (e.g., "k8s" expands to "Kubernetes container orchestration", possibly weighted as in SPLADE): * Dense vector retrieval makes use of embeddings, the internal representation that LLMs use to represent text. Dense vector retrieval provides recall over a broader set of results that may have no exact keyword matches but are still semantically similar. * Sparse vector retrieval is very fast, human-understandable, and yields high recall of results that closely match the user query. * We've found the approaches to be complementary.There's a very good blog post by Pinecone on SPLADE for sparse vector search if you're interested in diving in. If you're building RAG applications in areas that have a lot of industry-specific nomenclature, acronyms, etc, this is a good approach to getting better results.SCIPIn 2016, Microsoft announced the Language Server Protocol (LSP) and the Language Server Index Format (LSIF). This protocol makes it easy for IDEs to get all the context they need from a codebase to get things like file search, references, “go to definition”, etc. SourceGraph developed SCIP, “a better code indexing format than LSIF”:* Simpler and More Efficient Format: SCIP utilizes Protobuf instead of JSON, which is used by LSIF. Protobuf is more space-efficient, simpler, and more suitable for systems programming. * Better Performance and Smaller Index Sizes: SCIP indexers, such as scip-clang, show enhanced performance and reduced index file sizes compared to LSIF indexers (10%-20% smaller)* Easier to Develop and Debug: SCIP's design, centered around human-readable string IDs for symbols, makes it faster and more straightforward to develop new language indexers. Having more efficient indexing is key to more performant RAG on code. Show Notes* Sourcegraph* Cody* Copilot vs Cody* Steve's Stanford seminar on Grok* Steve's blog* Grab* Fireworks* Peter Norvig* Noam Chomsky* Code search* Kelly Norton* Zoekt* v0.devSee also our past episodes on Cursor, Phind, Codeium and Codium as well as the GitHub Copilot keynote at AI Engineer Summit.Timestamps* [00:00:00] Intros & Backgrounds* [00:05:20] How Steve's work on Grok inspired SourceGraph for Beyang* [00:08:10] What's Cody?* [00:11:22] Comparison of coding assistants and the capabilities of Cody* [00:16:00] The importance of context (RAG) in AI coding tools* [00:21:33] The debate between Chomsky and Norvig approaches in AI* [00:30:06] Normsky: the Norvig + Chomsky models collision* [00:36:00] The death of the DSL?* [00:40:00] LSP, Skip, Kythe, BFG, and all that fun stuff* [00:53:00] The SourceGraph internal stack* [00:58:46] Building on open source models* [01:02:00] SourceGraph for engineering managers?* [01:12:00] Lightning RoundTranscriptAlessio: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO-in-Residence at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol AI. [00:00:16]Swyx: Hey, and today we're christening our new podcast studio in the Newton, and we have Beyang and Steve from Sourcegraph. Welcome. [00:00:25]Beyang: Hey, thanks for having us. [00:00:26]Swyx: So this has been a long time coming. I'm very excited to have you. We also are just celebrating the one year anniversary of ChatGPT yesterday, but also we'll be talking about the GA of Cody later on today. We'll just do a quick intros of both of you. Obviously, people can research you and check the show notes for more. Beyang, you worked in computer vision at Stanford and then you worked at Palantir. I did, yeah. You also interned at Google. [00:00:48]Beyang: I did back in the day where I get to use Steve's system, DevTool. [00:00:53]Swyx: Right. What was it called? [00:00:55]Beyang: It was called Grok. Well, the end user thing was Google Code Search. That's what everyone called it, or just like CS. But the brains of it were really the kind of like Trigram index and then Grok, which provided the reference graph. [00:01:07]Steve: Today it's called Kythe, the open source Google one. It's sort of like Grok v3. [00:01:11]Swyx: On your podcast, which you've had me on, you've interviewed a bunch of other code search developers, including the current developer of Kythe, right? [00:01:19]Beyang: No, we didn't have any Kythe people on, although we would love to if they're up for it. We had Kelly Norton, who built a similar system at Etsy, it's an open source project called Hound. We also had Han-Wen Nienhuys, who created Zoekt, which is, I think, heavily inspired by the Trigram index that powered Google's original code search and that we also now use at Sourcegraph. Yeah. [00:01:45]Swyx: So you teamed up with Quinn over 10 years ago to start Sourcegraph and you were indexing all code on the internet. And now you're in a perfect spot to create a code intelligence startup. Yeah, yeah. [00:01:56]Beyang: I guess the backstory was, I used Google Code Search while I was an intern. And then after I left that internship and worked elsewhere, it was the single dev tool that I missed the most. I felt like my job was just a lot more tedious and much more of a hassle without it. And so when Quinn and I started working together at Palantir, he had also used various code search engines in open source over the years. And it was just a pain point that we both felt, both working on code at Palantir and also working within Palantir's clients, which were a lot of Fortune 500 companies, large financial institutions, folks like that. And if anything, the pains they felt in dealing with large complex code bases made our pain points feel small by comparison. So that was really the impetus for starting Sourcegraph. [00:02:42]Swyx: Yeah, excellent. Steve, you famously worked at Amazon. And you've told many, many stories. I want every single listener of Latent Space to check out Steve's YouTube because he effectively had a podcast that you didn't tell anyone about or something. You just hit record and just went on a few rants. I'm always here for your Stevie rants. And then you moved to Google, where you also had some interesting thoughts on just the overall Google culture versus Amazon. You joined Grab as head of eng for a couple of years. I'm from Singapore, so I have actually personally used a lot of Grab's features. And it was very interesting to see you talk so highly of Grab's engineering and sort of overall prospects. [00:03:21]Steve: Because as a customer, it sucked? [00:03:22]Swyx: Yeah, no, it's just like, being from a smaller country, you never see anyone from our home country being on a global stage or talked about as a startup that people admire or look up to, like on the league that you, with all your legendary experience, would consider equivalent. Yeah. [00:03:41]Steve: Yeah, no, absolutely. They actually, they didn't even know that they were as good as they were, in a sense. They started hiring a bunch of people from Silicon Valley to come in and sort of like fix it. And we came in and we were like, Oh, we could have been a little better operational excellence and stuff. But by and large, they're really sharp. The only thing about Grab is that they get criticized a lot for being too westernized. Oh, by who? By Singaporeans who don't want to work there. [00:04:06]Swyx: Okay. I guess I'm biased because I'm here, but I don't see that as a problem. If anything, they've had their success because they were more westernized than the Sanders Singaporean tech company. [00:04:15]Steve: I mean, they had their success because they are laser focused. They copy to Amazon. I mean, they're executing really, really, really well for a giant. I was on a slack with 2,500 engineers. It was like this giant waterfall that you could dip your toe into. You'd never catch up. Actually, the AI summarizers would have been really helpful there. But yeah, no, I think Grab is successful because they're just out there with their sleeves rolled up, just making it happen. [00:04:43]Swyx: And for those who don't know, it's not just like Uber of Southeast Asia, it's also a super app. PayPal Plus. [00:04:48]Steve: Yeah. [00:04:49]Swyx: In the way that super apps don't exist in the West. It's one of the enduring mysteries of B2C that super apps work in the East and don't work in the West. We just don't understand it. [00:04:57]Beyang: Yeah. [00:04:58]Steve: It's just kind of curious. They didn't work in India either. And it was primarily because of bandwidth reasons and smaller phones. [00:05:03]Swyx: That should change now. It should. [00:05:05]Steve: And maybe we'll see a super app here. [00:05:08]Swyx: You retired-ish? I did. You retired-ish on your own video game? Mm-hmm. Any fun stories about that? And that's also where you discovered some need for code search, right? Mm-hmm. [00:05:16]Steve: Sure. A need for a lot of stuff. Better programming languages, better databases. Better everything. I mean, I started in like 95, right? Where there was kind of nothing. Yeah. Yeah. [00:05:24]Beyang: I just want to say, I remember when you first went to Grab because you wrote that blog post talking about why you were excited about it, about like the expanding Asian market. And our reaction was like, oh, man, how did we miss stealing it with you? [00:05:36]Swyx: Hiring you. [00:05:37]Beyang: Yeah. [00:05:38]Steve: I was like, miss that. [00:05:39]Swyx: Tell that story. So how did this happen? Right? So you were inspired by Grok. [00:05:44]Beyang: I guess the backstory from my point of view is I had used code search and Grok while at Google, but I didn't actually know that it was connected to you, Steve. I knew you from your blog posts, which were always excellent, kind of like inside, very thoughtful takes from an engineer's perspective on some of the challenges facing tech companies and tech culture and that sort of thing. But my first introduction to you within the context of code intelligence, code understanding was I watched a talk that you gave, I think at Stanford, about Grok when you're first building it. And that was very eye opening. I was like, oh, like that guy, like the guy who, you know, writes the extremely thoughtful ranty like blog posts also built that system. And so that's how I knew, you know, you were involved in that. And then, you know, we always wanted to hire you, but never knew quite how to approach you or, you know, get that conversation started. [00:06:34]Steve: Well, we got introduced by Max, right? Yeah. It was temporal. Yeah. Yeah. I mean, it was a no brainer. They called me up and I had noticed when Sourcegraph had come out. Of course, when they first came out, I had this dagger of jealousy stabbed through me piercingly, which I remember because I am not a jealous person by any means, ever. But boy, I was like, but I was kind of busy, right? And just one thing led to another. I got sucked back into the ads vortex and whatever. So thank God Sourcegraph actually kind of rescued me. [00:07:05]Swyx: Here's a chance to build DevTools. Yeah. [00:07:08]Steve: That's the best. DevTools are the best. [00:07:10]Swyx: Cool. Well, so that's the overall intro. I guess we can get into Cody. Is there anything else that like people should know about you before we get started? [00:07:18]Steve: I mean, everybody knows I'm a musician. I can juggle five balls. [00:07:24]Swyx: Five is good. Five is good. I've only ever managed three. [00:07:27]Steve: Five is hard. Yeah. And six, a little bit. [00:07:30]Swyx: Wow. [00:07:31]Beyang: That's impressive. [00:07:32]Alessio: So yeah, to jump into Sourcegraph, this has been a company 10 years in the making. And as Sean said, now you're at the right place. Phase two. Now, exactly. You spent 10 years collecting all this code, indexing, making it easy to surface it. Yeah. [00:07:47]Swyx: And also learning how to work with enterprises and having them trust you with their code bases. Yeah. [00:07:52]Alessio: Because initially you were only doing on-prem, right? Like a lot of like VPC deployments. [00:07:55]Beyang: So in the very early days, we're cloud only. But the first major customers we landed were all on-prem, self-hosted. And that was, I think, related to the nature of the problem that we're solving, which becomes just like a critical, unignorable pain point once you're above like 100 devs or so. [00:08:11]Alessio: Yeah. And now Cody is going to be GA by the time this releases. So congrats to your future self for launching this in two weeks. Can you give a quick overview of just what Cody is? I think everybody understands that it's a AI coding agent, but a lot of companies say they have a AI coding agent. So yeah, what does Cody do? How do people interface with it? [00:08:32]Beyang: Yeah. So how is it different from the like several dozen other AI coding agents that exist in the market now? When we thought about building a coding assistant that would do things like code generation and question answering about your code base, I think we came at it from the perspective of, you know, we've spent the past decade building the world's best code understanding engine for human developers, right? So like it's kind of your guide as a human dev if you want to go and dive into a large complex code base. And so our intuition was that a lot of the context that we're providing to human developers would also be useful context for AI developers to consume. And so in terms of the feature set, Cody is very similar to a lot of other assistants. It does inline autocompletion. It does code base aware chat. It does specific commands that automate, you know, tasks that you might rather not want to do like generating unit tests or adding detailed documentation. But we think the core differentiator is really the quality of the context, which is hard to kind of describe succinctly. It's a bit like saying, you know, what's the difference between Google and Alta Vista? There's not like a quick checkbox list of features that you can rattle off, but it really just comes down to all the attention and detail that we've paid to making that context work well and be high quality and fast for human devs. We're now kind of plugging into the AI coding assistant as well. Yeah. [00:09:53]Steve: I mean, just to add my own perspective on to what Beyang just described, RAG is kind of like a consultant that the LLM has available, right, that knows about your code. RAG provides basically a bridge to a lookup system for the LLM, right? Whereas fine tuning would be more like on the job training for somebody. If the LLM is a person, you know, and you send them to a new job and you do on the job training, that's what fine tuning is like, right? So tuned to our specific task. You're always going to need that expert, even if you get the on the job training, because the expert knows your particular code base, your task, right? That expert has to know your code. And there's a chicken and egg problem because, right, you know, we're like, well, I'm going to ask the LLM about my code, but first I have to explain it, right? It's this chicken and egg problem. That's where RAG comes in. And we have the best consultants, right? The best assistant who knows your code. And so when you sit down with Cody, right, what Beyang said earlier about going to Google and using code search and then starting to feel like without it, his job was super tedious. Once you start using these, do you guys use coding assistants? [00:10:53]Swyx: Yeah, right. [00:10:54]Steve: I mean, like we're getting to the point very quickly, right? Where you feel like almost like you're programming without the internet, right? Or something, you know, it's like you're programming back in the nineties without the coding assistant. Yeah. Hopefully that helps for people who have like no idea about coding systems, what they are. [00:11:09]Swyx: Yeah. [00:11:10]Alessio: I mean, going back to using them, we had a lot of them on the podcast already. We had Cursor, we have Codium and Codium, very similar names. [00:11:18]Swyx: Yeah. Find, and then of course there's Copilot. [00:11:22]Alessio: You had a Copilot versus Cody blog post, and I think it really shows the context improvement. So you had two examples that stuck with me. One was, what does this application do? And the Copilot answer was like, oh, it uses JavaScript and NPM and this. And it's like, but that's not what it does. You know, that's what it's built with. Versus Cody was like, oh, these are like the major functions. And like, these are the functionalities and things like that. And then the other one was, how do I start this up? And Copilot just said NPM start, even though there was like no start command in the package JSON, but you know, most collapse, right? Most projects use NPM start. So maybe this does too. How do you think about open source models? Because Copilot has their own private thing. And I think you guys use Starcoder, if I remember right. Yeah, that's correct. [00:12:09]Beyang: I think Copilot uses some variant of Codex. They're kind of cagey about it. I don't think they've like officially announced what model they use. [00:12:16]Swyx: And I think they use a range of models based on what you're doing. Yeah. [00:12:19]Beyang: So everyone uses a range of model. Like no one uses the same model for like inline completion versus like chat because the latency requirements for. Oh, okay. Well, there's fill in the middle. There's also like what the model's trained on. So like we actually had completions powered by Claude Instant for a while. And but you had to kind of like prompt hack your way to get it to output just the code and not like, hey, you know, here's the code you asked for, like that sort of text. So like everyone uses a range of models. We've kind of designed Cody to be like especially model, not agnostic, but like pluggable. So one of our kind of design considerations was like as the ecosystem evolves, we want to be able to integrate the best in class models, whether they're proprietary or open source into Cody because the pace of innovation in the space is just so quick. And I think that's been to our advantage. Like today, Cody uses Starcoder for inline completions. And with the benefit of the context that we provide, we actually show comparable completion acceptance rate metrics. It's kind of like the standard metric that folks use to evaluate inline completion quality. It's like if I show you a completion, what's the chance that you actually accept the completion versus you reject it? And so we're at par with Copilot, which is at the head of that industry right now. And we've been able to do that with the Starcoder model, which is open source and the benefit of the context fetching stuff that we provide. And of course, a lot of like prompt engineering and other stuff along the way. [00:13:40]Alessio: And Steve, you wrote a post called cheating is all you need about what you're building. And one of the points you made is that everybody's fighting on the same axis, which is better UI and the IDE, maybe like a better chat response. But data modes are kind of the most important thing. And you guys have like a 10 year old mode with all the data you've been collecting. How do you kind of think about what other companies are doing wrong, right? Like, why is nobody doing this in terms of like really focusing on RAG? I feel like you see so many people. Oh, we just got a new model. It's like a bit human eval. And it's like, well, but maybe like that's not what we should really be doing, you know? Like, do you think most people underestimate the importance of like the actual RAG in code? [00:14:21]Steve: I think that people weren't doing it much. It wasn't. It's kind of at the edges of AI. It's not in the center. I know that when ChatGPT launched, so within the last year, I've heard a lot of rumblings from inside of Google, right? Because they're undergoing a huge transformation to try to, you know, of course, get into the new world. And I heard that they told, you know, a bunch of teams to go and train their own models or fine tune their own models, right? [00:14:43]Swyx: Both. [00:14:43]Steve: And, you know, it was a s**t show. Nobody knew how to do it. They launched two coding assistants. One was called Code D with an EY. And then there was, I don't know what happened in that one. And then there's Duet, right? Google loves to compete with themselves, right? They do this all the time. And they had a paper on Duet like from a year ago. And they were doing exactly what Copilot was doing, which was just pulling in the local context, right? But fundamentally, I thought of this because we were talking about the splitting of the [00:15:10]Swyx: models. [00:15:10]Steve: In the early days, it was the LLM did everything. And then we realized that for certain use cases, like completions, that a different, smaller, faster model would be better. And that fragmentation of models, actually, we expected to continue and proliferate, right? Because we are fundamentally, we're a recommender engine right now. Yeah, we're recommending code to the LLM. We're saying, may I interest you in this code right here so that you can answer my question? [00:15:34]Swyx: Yeah? [00:15:34]Steve: And being good at recommender engine, I mean, who are the best recommenders, right? There's YouTube and Spotify and, you know, Amazon or whatever, right? Yeah. [00:15:41]Swyx: Yeah. [00:15:41]Steve: And they all have many, many, many, many, many models, right? For all fine-tuned for very specific, you know. And that's where we're heading in code, too. Absolutely. [00:15:50]Swyx: Yeah. [00:15:50]Alessio: We just did an episode we released on Wednesday, which we said RAG is like Rexis or like LLMs. You're basically just suggesting good content. [00:15:58]Swyx: It's like what? Recommendations. [00:15:59]Beyang: Recommendations. [00:16:00]Alessio: Oh, got it. [00:16:01]Steve: Yeah, yeah, yeah. [00:16:02]Swyx: So like the naive implementation of RAG is you embed everything, throw it in a vector database, you embed your query, and then you find the nearest neighbors, and that's your RAG. But actually, you need to rank it. And actually, you need to make sure there's sample diversity and that kind of stuff. And then you're like slowly gradient dissenting yourself towards rediscovering proper Rexis, which has been traditional ML for a long time. But like approaching it from an LLM perspective. Yeah. [00:16:24]Beyang: I almost think of it as like a generalized search problem because it's a lot of the same things. Like you want your layer one to have high recall and get all the potential things that could be relevant. And then there's typically like a layer two re-ranking mechanism that bumps up the precision and tries to get the relevant stuff to the top of the results list. [00:16:43]Swyx: Have you discovered that ranking matters a lot? Oh, yeah. So the context is that I think a lot of research shows that like one, context utilization matters based on model. Like GPT uses the top of the context window, and then apparently Claude uses the bottom better. And it's lossy in the middle. Yeah. So ranking matters. No, it really does. [00:17:01]Beyang: The skill with which models are able to take advantage of context is always going to be dependent on how that factors into the impact on the training loss. [00:17:10]Swyx: Right? [00:17:10]Beyang: So like if you want long context window models to work well, then you have to have a ton of data where it's like, here's like a billion lines of text. And I'm going to ask a question about like something that's like, you know, embedded deeply into it and like, give me the right answer. And unless you have that training set, then of course, you're going to have variability in terms of like where it attends to. And in most kind of like naturally occurring data, the thing that you're talking about right now, the thing I'm asking you about is going to be something that we talked about recently. [00:17:36]Swyx: Yeah. [00:17:36]Steve: Did you really just say gradient dissenting yourself? Actually, I love that it's entered the casual lexicon. Yeah, yeah, yeah. [00:17:44]Swyx: My favorite version of that is, you know, how we have to p-hack papers. So, you know, when you throw humans at the problem, that's called graduate student dissent. That's great. It's really awesome. [00:17:54]Alessio: I think the other interesting thing that you have is this inline assist UX that I wouldn't say async, but like it works while you can also do work. So you can ask Cody to make changes on a code block and you can still edit the same file at the same time. [00:18:07]Swyx: Yeah. [00:18:07]Alessio: How do you see that in the future? Like, do you see a lot of Cody's running together at the same time? Like, how do you validate also that they're not messing each other up as they make changes in the code? And maybe what are the limitations today? And what do you think about where the attack is going? [00:18:21]Steve: I want to start with a little history and then I'm going to turn it over to Bian, all right? So we actually had this feature in the very first launch back in June. Dominic wrote it. It was called nonstop Cody. And you could have multiple, basically, LLM requests in parallel modifying your source [00:18:37]Swyx: file. [00:18:37]Steve: And he wrote a bunch of code to handle all of the diffing logic. And you could see the regions of code that the LLM was going to change, right? And he was showing me demos of it. And it just felt like it was just a little before its time, you know? But a bunch of that stuff, that scaffolding was able to be reused for where we're inline [00:18:56]Swyx: sitting today. [00:18:56]Steve: How would you characterize it today? [00:18:58]Beyang: Yeah, so that interface has really evolved from a, like, hey, general purpose, like, request anything inline in the code and have the code update to really, like, targeted features, like, you know, fix the bug that exists at this line or request a very specific [00:19:13]Swyx: change. [00:19:13]Beyang: And the reason for that is, I think, the challenge that we ran into with inline fixes, and we do want to get to the point where you could just fire and forget and have, you know, half a dozen of these running in parallel. But I think we ran into the challenge early on that a lot of people are running into now when they're trying to construct agents, which is the reliability of, you know, working code generation is just not quite there yet in today's language models. And so that kind of constrains you to an interaction where the human is always, like, in the inner loop, like, checking the output of each response. And if you want that to work in a way where you can be asynchronous, you kind of have to constrain it to a domain where today's language models can generate reliable code well enough. So, you know, generating unit tests, that's, like, a well-constrained problem. Or fixing a bug that shows up as, like, a compiler error or a test error, that's a well-constrained problem. But the more general, like, hey, write me this class that does X, Y, and Z using the libraries that I have, that is not quite there yet, even with the benefit of really good context. Like, it definitely moves the needle a lot, but we're not quite there yet to the point where you can just fire and forget. And I actually think that this is something that people don't broadly appreciate yet, because I think that, like, everyone's chasing this dream of agentic execution. And if we're to really define that down, I think it implies a couple things. You have, like, a multi-step process where each step is fully automated. We don't have to have a human in the loop every time. And there's also kind of like an LM call at each stage or nearly every stage in that [00:20:45]Swyx: chain. [00:20:45]Beyang: Based on all the work that we've done, you know, with the inline interactions, with kind of like general Codyfeatures for implementing longer chains of thought, we're actually a little bit more bearish than the average, you know, AI hypefluencer out there on the feasibility of agents with purely kind of like transformer-based models. To your original question, like, the inline interactions with CODI, we actually constrained it to be more targeted, like, you know, fix the current error or make this quick fix. I think that that does differentiate us from a lot of the other tools on the market, because a lot of people are going after this, like, shnazzy, like, inline edit interaction, whereas I think where we've moved, and this is based on the user feedback that we've gotten, it's like that sort of thing, it demos well, but when you're actually coding day to day, you don't want to have, like, a long chat conversation inline with the code base. That's a waste of time. You'd rather just have it write the right thing and then move on with your life or not have to think about it. And that's what we're trying to work towards. [00:21:37]Steve: I mean, yeah, we're not going in the agent direction, right? I mean, I'll believe in agents when somebody shows me one that works. Yeah. Instead, we're working on, you know, sort of solidifying our strength, which is bringing the right context in. So new context sources, ways for you to plug in your own context, ways for you to control or influence the context, you know, the mixing that happens before the request goes out, etc. And there's just so much low-hanging fruit left in that space that, you know, agents seems like a little bit of a boondoggle. [00:22:03]Beyang: Just to dive into that a little bit further, like, I think, you know, at a very high level, what do people mean when they say agents? They really mean, like, greater automation, fully automated, like, the dream is, like, here's an issue, go implement that. And I don't have to think about it as a human. And I think we are working towards that. Like, that is the eventual goal. I think it's specifically the approach of, like, hey, can we have a transformer-based LM alone be the kind of, like, backbone or the orchestrator of these agentic flows? Where we're a little bit more bearish today. [00:22:31]Swyx: You want the human in the loop. [00:22:32]Beyang: I mean, you kind of have to. It's just a reality of the behavior of language models that are purely, like, transformer-based. And I think that's just like a reflection of reality. And I don't think people realize that yet. Because if you look at the way that a lot of other AI tools have implemented context fetching, for instance, like, you see this in the Copilot approach, where if you use, like, the at-workspace thing that supposedly provides, like, code-based level context, it has, like, an agentic approach where you kind of look at how it's behaving. And it feels like they're making multiple requests to the LM being like, what would you do in this case? Would you search for stuff? What sort of files would you gather? Go and read those files. And it's like a multi-hop step, so it takes a long while. It's also non-deterministic. Because any sort of, like, LM invocation, it's like a dice roll. And then at the end of the day, the context it fetches is not that good. Whereas our approach is just like, OK, let's do some code searches that make sense. And then maybe, like, crawl through the reference graph a little bit. That is fast. That doesn't require any sort of LM invocation at all. And we can pull in much better context, you know, very quickly. So it's faster. [00:23:37]Swyx: It's more reliable. [00:23:37]Beyang: It's deterministic. And it yields better context quality. And so that's what we think. We just don't think you should cargo cult or naively go like, you know, agents are the [00:23:46]Swyx: future. [00:23:46]Beyang: Let's just try to, like, implement agents on top of the LM that exists today. I think there are a couple of other technologies or approaches that need to be refined first before we can get into these kind of, like, multi-stage, fully automated workflows. [00:24:00]Swyx: It makes sense. You know, we're very much focused on developer inner loop right now. But you do see things eventually moving towards developer outer loop. Yeah. So would you basically say that they're tackling the agent's problem that you don't want to tackle? [00:24:11]Beyang: No, I would say at a high level, we are after maybe, like, the same high level problem, which is like, hey, I want some code written. I want to develop some software and can automate a system. Go build that software for me. I think the approaches might be different. So I think the analogy in my mind is, I think about, like, the AI chess players. Coding, in some senses, I mean, it's similar and dissimilar to chess. I think one question I ask is, like, do you think producing code is more difficult than playing chess or less difficult than playing chess? More. [00:24:41]Swyx: I think more. [00:24:41]Beyang: Right. And if you look at the best AI chess players, like, yes, you can use an LLM to play chess. Like, people have showed demos where it's like, oh, like, yeah, GPT-4 is actually a pretty decent, like, chess move suggester. Right. But you would never build, like, a best in class chess player off of GPT-4 alone. [00:24:57]Swyx: Right. [00:24:57]Beyang: Like, the way that people design chess players is that you have kind of like a search space and then you have a way to explore that search space efficiently. There's a bunch of search algorithms, essentially. We were doing tree search in various ways. And you can have heuristic functions, which might be powered by an LLM. [00:25:12]Swyx: Right. [00:25:12]Beyang: Like, you might use an LLM to generate proposals in that space that you can efficiently explore. But the backbone is still this kind of more formalized tree search based approach rather than the LLM itself. And so I think my high level intuition is that, like, the way that we get to more reliable multi-step workflows that do things beyond, you know, generate unit test, it's really going to be like a search based approach where you use an LLM as kind of like an advisor or a proposal function, sort of your heuristic function, like the ASTAR search algorithm. But it's probably not going to be the thing that is the backbone, because I guess it's not the right tool for that. Yeah. [00:25:50]Swyx: I can see yourself kind of thinking through this, but not saying the words, the sort of philosophical Peter Norvig type discussion. Maybe you want to sort of introduce that in software. Yeah, definitely. [00:25:59]Beyang: So your listeners are savvy. They're probably familiar with the classic like Chomsky versus Norvig debate. [00:26:04]Swyx: No, actually, I wanted, I was prompting you to introduce that. Oh, got it. [00:26:08]Beyang: So, I mean, if you look at the history of artificial intelligence, right, you know, it goes way back to, I don't know, it's probably as old as modern computers, like 50s, 60s, 70s. People are debating on like, what is the path to producing a sort of like general human level of intelligence? And kind of two schools of thought that emerged. One is the Norvig school of thought, which roughly speaking includes large language models, you know, regression, SVN, basically any model that you kind of like learn from data. And it's like data driven. Most of machine learning would fall under this umbrella. And that school of thought says like, you know, just learn from the data. That's the approach to reaching intelligence. And then the Chomsky approach is more things like compilers and parsers and formal systems. So basically like, let's think very carefully about how to construct a formal, precise system. And that will be the approach to how we build a truly intelligent system. I think Lisp was invented so that you could create like rules-based systems that you would call AI. As a language. Yeah. And for a long time, there was like this debate, like there's certain like AI research labs that were more like, you know, in the Chomsky camp and others that were more in the Norvig camp. It's a debate that rages on today. And I feel like the consensus right now is that, you know, Norvig definitely has the upper hand right now with the advent of LMs and diffusion models and all the other recent progress in machine learning. But the Chomsky-based stuff is still really useful in my view. I mean, it's like parsers, compilers, basically a lot of the stuff that provides really good context. It provides kind of like the knowledge graph backbone that you want to explore with your AI dev tool. Like that will come from kind of like Chomsky-based tools like compilers and parsers. It's a lot of what we've invested in in the past decade at Sourcegraph and what you build with Grok. Basically like these formal systems that construct these very precise knowledge graphs that are great context providers and great kind of guard rails enforcers and kind of like safety checkers for the output of a more kind of like data-driven, fuzzier system that uses like the Norvig-based models. [00:28:03]Steve: Jang was talking about this stuff like it happened in the middle ages. Like, okay, so when I was in college, I was in college learning Lisp and prologue and planning and all the deterministic Chomsky approaches to AI. And I was there when Norvig basically declared it dead. I was there 3,000 years ago when Norvig and Chomsky fought on the volcano. When did he declare it dead? [00:28:26]Swyx: What do you mean he declared it dead? [00:28:27]Steve: It was like late 90s. [00:28:29]Swyx: Yeah. [00:28:29]Steve: When I went to Google, Peter Norvig was already there. He had basically like, I forget exactly where. It was some, he's got so many famous short posts, you know, amazing. [00:28:38]Swyx: He had a famous talk, the unreasonable effectiveness of data. Yeah. [00:28:41]Steve: Maybe that was it. But at some point, basically, he basically convinced everybody that deterministic approaches had failed and that heuristic-based, you know, data-driven statistical approaches, stochastic were better. [00:28:52]Swyx: Yeah. [00:28:52]Steve: The primary reason I can tell you this, because I was there, was that, was that, well, the steam-powered engine, no. The reason was that the deterministic stuff didn't scale. [00:29:06]Swyx: Yeah. Right. [00:29:06]Steve: They're using prologue, man, constraint systems and stuff like that. Well, that was a long time ago, right? Today, actually, these Chomsky-style systems do scale. And that's, in fact, exactly what Sourcegraph has built. Yeah. And so we have a very unique, I love the framing that Bjong's made, that the marriage of the Chomsky and the Norvig, you know, sort of models, you know, conceptual models, because we, you know, we have both of them and they're both really important. And in fact, there, there's this really interesting, like, kind of overlap between them, right? Where like the AI or our graph or our search engine could potentially provide the right context for any given query, which is, of course, why ranking is important. But what we've really signed ourselves up for is an extraordinary amount of testing. [00:29:45]Swyx: Yeah. [00:29:45]Steve: Because in SWIGs, you were saying that, you know, GPT-4 tends to the front of the context window and maybe other LLMs to the back and maybe, maybe the LLM in the middle. [00:29:53]Swyx: Yeah. [00:29:53]Steve: And so that means that, you know, if we're actually like, you know, verifying whether we, you know, some change we've made has improved things, we're going to have to test putting it at the beginning of the window and at the end of the window, you know, and maybe make the right decision based on the LLM that you've chosen. Which some of our competitors, that's a problem that they don't have, but we meet you, you know, where you are. Yeah. And we're, just to finish, we're writing tens of thousands. We're generating tests, you know, fill in the middle type tests and things. And then using our graph to basically sort of fine tune Cody's behavior there. [00:30:20]Swyx: Yeah. [00:30:21]Beyang: I also want to add, like, I have like an internal pet name for this, like kind of hybrid architecture that I'm trying to make catch on. Maybe I'll just say it here. Just saying it publicly kind of makes it more real. But like, I call the architecture that we've developed the Normsky architecture. [00:30:36]Swyx: Yeah. [00:30:36]Beyang: I mean, it's obviously a portmanteau of Norvig and Chomsky, but the acronym, it stands for non-agentic, rapid, multi-source code intelligence. So non-agentic because... Rolls right off the tongue. And Normsky. But it's non-agentic in the sense that like, we're not trying to like pitch you on kind of like agent hype, right? Like it's the things it does are really just developer tools developers have been using for decades now, like parsers and really good search indexes and things like that. Rapid because we place an emphasis on speed. We don't want to sit there waiting for kind of like multiple LLM requests to return to complete a simple user request. Multi-source because we're thinking broadly about what pieces of information and knowledge are useful context. So obviously starting with things that you can search in your code base, and then you add in the reference graph, which kind of like allows you to crawl outward from those initial results. But then even beyond that, you know, sources of information, like there's a lot of knowledge that's embedded in docs, in PRDs or product specs, in your production logging system, in your chat, in your Slack channel, right? Like there's so much context is embedded there. And when you're a human developer, and you're trying to like be productive in your code base, you're going to go to all these different systems to collect the context that you need to figure out what code you need to write. And I don't think the AI developer will be any different. It will need to pull context from all these different sources. So we're thinking broadly about how to integrate these into Codi. We hope through kind of like an open protocol that like others can extend and implement. And this is something else that should be accessible by December 14th in kind of like a preview stage. But that's really about like broadening this notion of the code graph beyond your Git repository to all the other sources where technical knowledge and valuable context can live. [00:32:21]Steve: Yeah, it becomes an artifact graph, right? It can link into your logs and your wikis and any data source, right? [00:32:27]Alessio: How do you guys think about the importance of, it's almost like data pre-processing in a way, which is bring it all together, tie it together, make it ready. Any thoughts on how to actually make that good? Some of the innovation you guys have made. [00:32:40]Steve: We talk a lot about the context fetching, right? I mean, there's a lot of ways you could answer this question. But, you know, we've spent a lot of time just in this podcast here talking about context fetching. But stuffing the context into the window is, you know, the bin packing problem, right? Because the window is not big enough, and you've got more context than you can fit. You've got a ranker maybe. But what is that context? Is it a function that was returned by an embedding or a graph call or something? Do you need the whole function? Or do you just need, you know, the top part of the function, this expression here, right? You know, so that art, the golf game of trying to, you know, get each piece of context down into its smallest state, possibly even summarized by another model, right, before it even goes to the LLM, becomes this is the game that we're in, yeah? And so, you know, recursive summarization and all the other techniques that you got to use to like stuff stuff into that context window become, you know, critically important. And you have to test them across every configuration of models that you could possibly need. [00:33:32]Beyang: I think data preprocessing is probably the like unsexy, way underappreciated secret to a lot of the cool stuff that people are shipping today. Whether you're doing like RAG or fine tuning or pre-training, like the preprocessing step matters so much because it's basically garbage in, garbage out, right? Like if you're feeding in garbage to the model, then it's going to output garbage. Concretely, you know, for code RAG, if you're not doing some sort of like preprocessing that takes advantage of a parser and is able to like extract the key components of a particular file of code, you know, separate the function signature from the body, from the doc string, what are you even doing? Like that's like table stakes. It opens up so much more possibilities with which you can kind of like tune your system to take advantage of the signals that come from those different parts of the code. Like we've had a tool, you know, since computers were invented that understands the structure of source code to a hundred percent precision. The compiler knows everything there is to know about the code in terms of like structure. Like why would you not want to use that in a system that's trying to generate code, answer questions about code? You shouldn't throw that out the window just because now we have really good, you know, data-driven models that can do other things. [00:34:44]Steve: Yeah. When I called it a data moat, you know, in my cheating post, a lot of people were confused, you know, because data moat sort of sounds like data lake because there's data and water and stuff. I don't know. And so they thought that we were sitting on this giant mountain of data that we had collected, but that's not what our data moat is. It's really a data pre-processing engine that can very quickly and scalably, like basically dissect your entire code base in a very small, fine-grained, you know, semantic unit and then serve it up. Yeah. And so it's really, it's not a data moat. It's a data pre-processing moat, I guess. [00:35:15]Beyang: Yeah. If anything, we're like hypersensitive to customer data privacy requirements. So it's not like we've taken a bunch of private data and like, you know, trained a generally available model. In fact, exactly the opposite. A lot of our customers are choosing Cody over Copilot and other competitors because we have an explicit guarantee that we don't do any of that. And that we've done that from day one. Yeah. I think that's a very real concern in today's day and age, because like if your proprietary IP finds its way into the training set of any model, it's very easy both to like extract that knowledge from the model and also use it to, you know, build systems that kind of work on top of the institutional knowledge that you've built up. [00:35:52]Alessio: About a year ago, I wrote a post on LLMs for developers. And one of the points I had was maybe the depth of like the DSL. I spent most of my career writing Ruby and I love Ruby. It's so nice to use, but you know, it's not as performant, but it's really easy to read, right? And then you look at other languages, maybe they're faster, but like they're more verbose, you know? And when you think about efficiency of the context window, that actually matters. [00:36:15]Swyx: Yeah. [00:36:15]Alessio: But I haven't really seen a DSL for models, you know? I haven't seen like code being optimized to like be easier to put in a model context. And it seems like your pre-processing is kind of doing that. Do you see in the future, like the way we think about the DSL and APIs and kind of like service interfaces be more focused on being context friendly, where it's like maybe it's harder to read for the human, but like the human is never going to write it anyway. We were talking on the Hacks podcast. There are like some data science things like spin up the spandex, like humans are never going to write again because the models can just do very easily. Yeah, curious to hear your thoughts. [00:36:51]Steve: Well, so DSLs, they involve, you know, writing a grammar and a parser and they're like little languages, right? We do them that way because, you know, we need them to compile and humans need to be able to read them and so on. The LLMs don't need that level of structure. You can throw any pile of crap at them, you know, more or less unstructured and they'll deal with it. So I think that's why a DSL hasn't emerged for sort of like communicating with the LLM or packaging up the context or anything. Maybe it will at some point, right? We've got, you know, tagging of context and things like that that are sort of peeking into DSL territory, right? But your point on do users, you know, do people have to learn DSLs like regular expressions or, you know, pick your favorite, right? XPath. I think you're absolutely right that the LLMs are really, really good at that. And I think you're going to see a lot less of people having to slave away learning these things. They just have to know the broad capabilities and the LLM will take care of the rest. [00:37:42]Swyx: Yeah, I'd agree with that. [00:37:43]Beyang: I think basically like the value profit of DSL is that it makes it easier to work with a lower level language, but at the expense of introducing an abstraction layer. And in many cases today, you know, without the benefit of AI cogeneration, like that totally worth it, right? With the benefit of AI cogeneration, I mean, I don't think all DSLs will go away. I think there's still, you know, places where that trade-off is going to be worthwhile. But it's kind of like how much of source code do you think is going to be generated through natural language prompting in the future? Because in a way, like any programming language is just a DSL on top of assembly, right? And so if people can do that, then yeah, like maybe for a large portion of the code [00:38:21]Swyx: that's written, [00:38:21]Beyang: people don't actually have to understand the DSL that is Ruby or Python or basically any other programming language that exists. [00:38:28]Steve: I mean, seriously, do you guys ever write SQL queries now without using a model of some sort? At least a draft. [00:38:34]Swyx: Yeah, right. [00:38:36]Steve: And so we have kind of like, you know, past that bridge, right? [00:38:39]Alessio: Yeah, I think like to me, the long-term thing is like, is there ever going to be, you don't actually see the code, you know? It's like, hey, the basic thing is like, hey, I need a function to some two numbers and that's it. I don't need you to generate the code. [00:38:53]Steve: And the following question, do you need the engineer or the paycheck? [00:38:56]Swyx: I mean, right? [00:38:58]Alessio: That's kind of the agent's discussion in a way where like you cannot automate the agents, but like slowly you're getting more of the atomic units of the work kind of like done. I kind of think of it as like, you know, [00:39:09]Beyang: do you need a punch card operator to answer that for you? And so like, I think we're still going to have people in the role of a software engineer, but the portion of time they spend on these kinds of like low-level, tedious tasks versus the higher level, more creative tasks is going to shift. [00:39:23]Steve: No, I haven't used punch cards. [00:39:25]Swyx: Yeah, I've been talking about like, so we kind of made this podcast about the sort of rise of the AI engineer. And like the first step is the AI enhanced engineer. That is that software developer that is no longer doing these routine, boilerplate-y type tasks, because they're just enhanced by tools like yours. So you mentioned OpenCodeGraph. I mean, that is a kind of DSL maybe, and because we're releasing this as you go GA, you hope for other people to take advantage of that? [00:39:52]Beyang: Oh yeah, I would say so OpenCodeGraph is not a DSL. It's more of a protocol. It's basically like, hey, if you want to make your system, whether it's, you know, chat or logging or whatever accessible to an AI developer tool like Cody, here's kind of like the schema by which you can provide that context and offer hints. So I would, you know, comparisons like LSP obviously did this for kind of like standard code intelligence. It's kind of like a lingua franca for providing fine references and codefinition. There's kind of like analogs to that. There might be also analogs to kind of the original OpenAI, kind of like plugins, API. There's all this like context out there that might be useful for an LM-based system to consume. And so at a high level, what we're trying to do is define a common language for context providers to provide context to other tools in the software development lifecycle. Yeah. Do you have any critiques of LSP, by the way, [00:40:42]Swyx: since like this is very much, very close to home? [00:40:45]Steve: One of the authors wrote a really good critique recently. Yeah. I don't think I saw that. Yeah, yeah. LSP could have been better. It just came out a couple of weeks ago. It was a good article. [00:40:54]Beyang: Yeah. I think LSP is great. Like for what it did for the developer ecosystem, it was absolutely fantastic. Like nowadays, like it's much easier now to get code navigation up and running in a bunch of editors by speaking this protocol. I think maybe the interesting question is like looking at the different design decisions comparing LSP basically with Kythe. Because Kythe has more of a... How would you describe it? [00:41:18]Steve: A storage format. [00:41:20]Beyang: I think the critique of LSP from a Kythe point of view would be like with LSP, you don't actually have an actual symbolic model of the code. It's not like LSP models like, hey, this function calls this other function. LSP is all like range-based. Like, hey, your cursor's at line 32, column 1. [00:41:35]Swyx: Yeah. [00:41:35]Beyang: And that's the thing you feed into the language server. And then it's like, okay, here's the range that you should jump to if you click on that range. So it kind of is intentionally ignorant of the fact that there's a thing called a reference underneath your cursor, and that's linked to a symbol definition. [00:41:49]Steve: Well, actually, that's the worst example you could have used. You're right. But that's the one thing that it actually did bake in is following references. [00:41:56]Swyx: Sure. [00:41:56]Steve: But it's sort of hardwired. [00:41:58]Swyx: Yeah. [00:41:58]Steve: Whereas Kythe attempts to model [00:42:00]Beyang: like all these things explicitly. [00:42:02]Swyx: And so... [00:42:02]Steve: Well, so LSP is a protocol, right? And so Google's internal protocol is gRPC-based. And it's a different approach than LSP. It's basically you make a heavy query to the back end, and you get a lot of data back, and then you render the whole page, you know? So we've looked at LSP, and we think that it's a little long in the tooth, right? I mean, it's a great protocol, lots and lots of support for it. But we need to push into the domain of exposing the intelligence through the protocol. Yeah. [00:42:29]Beyang: And so I would say we've developed a protocol of our own called Skip, which is at a very high level trying to take some of the good ideas from LSP and from Kythe and merge that into a system that in the near term is useful for Sourcegraph, but I think in the long term, we hope will be useful for the ecosystem. Okay, so here's what LSP did well. LSP, by virtue of being like intentionally dumb, dumb in air quotes, because I'm not like ragging on it, allowed language servers developers to kind of like bypass the hard problem of like modeling language semantics precisely. So like if all you want to do is jump to definition, you don't have to come up with like a universally unique naming scheme for each symbol, which is actually quite challenging because you have to think about like, okay, what's the top scope of this name? Is it the source code repository? Is it the package? Does it depend on like what package server you're fetching this from? Like whether it's the public one or the one inside your... Anyways, like naming is hard, right? And by just going from kind of like a location to location based approach, you basically just like throw that out the window. All I care about is jumping definition, just make that work. And you can make that work without having to deal with like all the complex global naming things. The limitation of that approach is that it's harder to build on top of that to build like a true knowledge graph. Like if you actually want a system that says like, okay, here's the web of functions and here's how they reference each other. And I want to incorporate that like semantic model of how the code operates or how the code relates to each other at like a static level. You can't do that with LSP because you have to deal with line ranges. And like concretely the pain point that we found in using LSP for source graph is like in order to do like a find references [00:44:04]Swyx: and then jump definitions, [00:44:04]Beyang: it's like a multi-hop process because like you have to jump to the range and then you have to find the symbol at that range. And it just adds a lot of latency and complexity of these operations where as a human, you're like, well, this thing clearly references this other thing. Why can't you just jump me to that? And I think that's the thing that Kaith does well. But then I think the issue that Kaith has had with adoption is because it is more sophisticated schema, I think. And so there's basically more things that you have to implement to get like a Kaith implementation up and running. I hope I'm not like, correct me if I'm wrong about any of this. [00:44:35]Steve: 100%, 100%. Kaith also has a problem, all these systems have the problem, even skip, or at least the way that we implemented the indexers, that they have to integrate with your build system in order to build that knowledge graph, right? Because you have to basically compile the code in a special mode to generate artifacts instead of binaries. And I would say, by the way, earlier I was saying that XREFs were in LSP, but it's actually, I was thinking of LSP plus LSIF. [00:44:58]Swyx: Yeah. That's another. [00:45:01]Steve: Which is actually bad. We can say that it's bad, right? [00:45:04]Steve: It's like skip or Kaith, it's supposed to be sort of a model serialization, you know, for the code graph, but it basically just does what LSP needs, the bare minimum. LSIF is basically if you took LSP [00:45:16]Beyang: and turned that into a serialization format. So like you build an index for language servers to kind of like quickly bootstrap from cold start. But it's a graph model [00:45:23]Steve: with all of the inconvenience of the API without an actual graph. And so, yeah. [00:45:29]Beyang: So like one of the things that we try to do with skip is try to capture the best of both worlds. So like make it easy to write an indexer, make the schema simple, but also model some of the more symbolic characteristics of the code that would allow us to essentially construct this knowledge graph that we can then make useful for both the human developer through SourceGraph and through the AI developer through Cody. [00:45:49]Steve: So anyway, just to finish off the graph comment, we've got a new graph, yeah, that's skip based. We call it BFG internally, right? It's a beautiful something graph. A big friendly graph. [00:46:00]Swyx: A big friendly graph. [00:46:01]Beyang: It's a blazing fast. [00:46:02]Steve: Blazing fast. [00:46:03]Swyx: Blazing fast graph. [00:46:04]Steve: And it is blazing fast, actually. It's really, really interesting. I should probably have to do a blog post about it to walk you through exactly how they're doing it. Oh, please. But it's a very AI-like iterative, you know, experimentation sort of approach. We're building a code graph based on all of our 10 years of knowledge about building code graphs, yeah? But we're building it quickly with zero configuration, and it doesn't have to integrate with your build. And through some magic tricks that we have. And so what just happens when you install the plugin, that it'll be there and indexing your code and providing that knowledge graph in the background without all that build system integration. This is a bit of secret sauce that we haven't really like advertised it very much lately. But I am super excited about it because what they do is they say, all right, you know, let's tackle function parameters today. Cody's not doing a very good job of completing function call arguments or function parameters in the definition, right? Yeah, we generate those thousands of tests, and then we can actually reuse those tests for the AI context as well. So fortunately, things are kind of converging on, we have, you know, half a dozen really, really good context sources, and we mix them all together. So anyway, BFG, you're going to hear more about it probably in the holidays? [00:47:12]Beyang: I think it'll be online for December 14th. We'll probably mention it. BFG is probably not the public name we're going to go with. I think we might call it like Graph Context or something like that. [00:47:20]Steve: We're officially calling it BFG. [00:47:22]Swyx: You heard it here first. [00:47:24]Beyang: BFG is just kind of like the working name. And so the impetus for BFG was like, if you look at like current AI inline code completion tools and the errors that they make, a lot of the errors that they make, even in kind of like the easy, like single line case, are essentially like type errors, right? Like you're trying to complete a function call and it suggests a variable that you defined earlier, but that variable is the wrong type. [00:47:47]Swyx: And that's the sort of thing [00:47:47]Beyang: where it's like a first year, like freshman CS student would not make that error, right? So like, why does the AI make that error? And the reason is, I mean, the AI is just suggesting things that are plausible without the context of the types or any other like broader files in the code. And so the kind of intuition here is like, why don't we just do the basic thing that like any baseline intelligent human developer would do, which is like click jump to definition, click some fine references and pull in that like Graph Context into the context window and then have it generate the completion. So like that's sort of like the MVP of what BFG was. And turns out that works really well. Like you can eliminate a lot of type errors that AI coding tools make just by pulling in that context. Yeah, but the graph is definitely [00:48:32]Steve: our Chomsky side. [00:48:33]Swyx: Yeah, exactly. [00:48:34]Beyang: So like this like Chomsky-Norvig thing, I think pops up in a bunch of differ

China's parcel delivery sector has set a record by handling more than 120 billion items this year, demonstrating its strong resilience and showcasing the country's improving consumer market, the State Post Bureau said on Tuesday.12月5日，国家邮政局表示，中国快递业务量突破1200亿件，创历史新高，这展现出中国快递业的发展韧性，体现了中国消费市场不断向好发展。It is also a reflection of the nation's stable and positive economic momentum, the bureau added.国家邮政局补充说，这也反映了中国经济的发展稳中向好。"Now, China has become the most dynamic express delivery market in the world, and the parcel delivery business in China has become a calling card of the country," said Bian Zuodong, deputy head of the bureau's market inspection department.“如今，中国的快递市场已成为世界上最具活力的市场，中国的快递业务已成为中国的一张名片，” 国家邮政局市场监管司副司长边作栋说。According to a report released by the bureau last month, more than 200 billion parcels are expected to be handled globally this year.根据国家邮政局上个月发布的一份报告，预计今年全球将处理超过2000亿个包裹。China's parcel delivery sector continued to grow rapidly this year. Since March, the number of parcels handled each month has reached a record 10 billion. In 2013, the annual figure was under 9.2 billion.今年，中国的快递行业继续快速增长。自3月以来，每月处理的包裹数量已达到创纪录的100亿件。2013年，这个数字还不到92亿。"The volume of express delivery business (in China) has increased from about 10 million a year to 10 million a month," Bian said, adding that the expansion of the parcel delivery network has benefited people across the nation.“（中国）快递业务量已从每年约1000万件增加到每月1000万件，”边作栋指出，快递服务网络的扩大惠及全国各地的居民。"Express delivery promotes circulation and serves people's livelihoods. It has become a 'barometer' of economic development reflecting economic vitality. It is also an important factor in narrowing the gap between urban and rural areas and promoting common prosperity," he said.他说：“快递促进流通，服务民生。已经成为反映经济活力的经济发展‘晴雨表'。这也是缩小城乡差距、促进共同富裕的重要因素。”The growing number also reflects China's economic vitality, he added.他还补充说，不断增长的快递服务量也反映了中国的经济活力。"The growth of express delivery comes from the improvement of consumer demand. The business has also become one of the important indicators of China's economic development," Bian said.“快递的增长来自于消费者需求的改善。快递业务也已成为中国经济发展的重要指标之一，”边作栋说。"The recovery of the macroeconomic environment in China has promoted demand for express delivery services," Bian said.“中国宏观经济环境的复苏促进了对快递服务的需求，”边作栋说。Since the beginning of this year, China's economy has steadily recovered, while production and consumption demand have gradually picked up, he said.他说，今年以来，中国经济稳步复苏，生产和消费需求逐步回升。According to the National Bureau of Statistics, from January to October, online retail sales of physical goods in China reached 10.3 trillion yuan ($1.44 trillion), accounting for 26.7 percent of the total retail sales of consumer goods.根据国家统计局的数据，1月至10月，中国实物商品在线零售额达到10.3万亿元人民币（1.44万亿美元），占社会消费品零售总额的26.7%。"The rapid growth of market sales and service consumption has not only provided opportunities for the express delivery industry to better play its supporting role, but also provided opportunities for the sector's sustained high-quality development," Bian said.“市场销售和服务消费的快速增长，不仅为快递行业更好发挥支撑作用提供了机遇，也为行业持续高质量发展提供了机遇，”边作栋说During the "Double 11" period, the online shopping festival in November which caused a peak in parcel deliveries from Nov 1 to Nov 16, China handled 7.77 billion parcels, a year-on-year increase of 25.7 percent.11月，在“双11”期间，购物狂欢节使11月1日至11月16日的包裹递送量达到高峰，中国快递服务量达到 77.7亿个包裹，同比增长25.7%。China's parcel delivery sector handles a daily average of about 350 million packages, he said.他说，中国的快递服务行业平均每天处理的包裹数量约为3.5亿个。According to the bureau's big data platform, a package from Kunming, Yunnan province, which was sent at 6:26 pm on Monday, was the nation's 120 billionth parcel of 2023.根据国家邮政局的大数据平台，12月4日下午6时26分从云南省昆明市寄出的一个包裹是中国2023年第1200亿个包裹。The parcel, containing a bouquet of lilies, was ordered from an online store by a customer surnamed Zhang in Chengdu, Sichuan province.这个包裹里一束百合花，是由四川省成都市一位姓张的顾客从一家网店订购的。At 3:39 pm on Tuesday, Zhang received the flowers.第二天下午3时39分，张女士收到了这束百合花。"I placed the order yesterday afternoon, and it was fast," she said, while opening the wrapping to check her order.“我是昨天下午下单的，快递的速度很快，”她一边说，一边打开包装检查她的订单。Zhang said she often buys flowers and other daily goods online.张女士说，她经常在网上购买鲜花和其他日常用品。"The prices are better, and there is more choice online," she said.“电商的价格更好，也有更多的选择，”她说。The record-breaking flowers took a bullet train from Kunming to Chengdu, according to Li Weichen, head of the Sichuan office of SF Express, the major parcel delivery company that handled the 120 billionth parcel.负责运送第1200亿个包裹的公司是顺丰速运，该公司四川办事处负责人李伟辰（音译）说，这束鲜花通过高铁从昆明运送至成都。Since the company started cooperating with the high-speed rail service, parcels between Sichuan and Yunnan can be delivered just one day after an order is placed, instead of two days previously.自从顺丰速运与高铁服务合作以来，四川和云南之间的包裹可以在下订单后一天送达，而之前的不是两天。"It is faster and greener," said Zeng Jing from SF Express.“高铁更快，也更环保,”顺丰速运的曾静（音译）说。 Reporter: Luo WangshuThe State Post Bureaun. 国家邮政局Parcel delivery sectorn. 快递服务业

Welcome back to the more we know! Because the more we know, the more we grow. Today your mentor is the famous american restauranteur out of Chicago, Kevin Boehm. After opening 40 restaurants over the last 30 years, James Beard Foundation Award-winning restaurateur Kevin Boehm has established himself as one of the world's foremost hospitality visionaries. Kevin, along with his partner Rob Katz, has built a restaurant group based on great chefs, inspired design, and enlightened hospitality.Born in 1970, Kevin grew up in Springfield, Illinois, and told his mother at age 10 that he wanted to open his own restaurant one day.After attending the University of Illinois for two nonconsecutive years, he dropped out and moved to the Florida Panhandle to start working in restaurants and embark on a self-directed on-the-job hospitality education. After enduring homelessness, fist fights, and six months working at an amusement park, he wrote an embellished resumé that landed him a coveted captain position at Beach House Restaurant. Within a few years, he'd squirreled away enough money to open a six-table restaurant in 1993 in Seaside, Florida, the picture-perfect location where Peter Weir's The Truman Show, starring Jim Carrey, was filmed. In 1995, he opened Indigo Wine Bar in the same town, and helped cater for the movie's dailies screenings.Restaurants in Springfield, Illinois, and Nashville, Tennessee followed. By age 30, Boehm had opened and sold four restaurants.In 2002, Boehm partnered with Rob Katz to form what in time became Boka Restaurant Group. Eventually, they would open 36 places in less than 20 years. The group's many accolades and accomplishments include 18 James Beard Award nominations, two Food & Wine Best New Chefs, 13 consecutive Michelin Guide stars for Boka, and 6 Boka Restaurant Group restaurants on Chicago Tribune's Top 50 list. Boehm, along with Katz, won Restaurateurs of the year from TimeOut Chicago in 2010, the Chicago Tribune in 2011, and The Illinois Restaurant Association in 2017, and were Eater National's Empire Builders of the year in 2012. They have been James Beard Finalists for Best Restaurateur in America 2016-2019, winning the award in 2019, and New City Chicago ranked them #1 in 2017 in its annual list of the 50 most powerful influencers on the Chicago dining scene.In addition to Boka Restaurant Group, in 2020 Boehm co-founded Bian, a private club with a foundation in wellness. Forbes called it “the ultimate wellness destination.” As a writer he has had pieces published in Esquire, Plate, The Chicago Sun Times, and McSweeneys, and he is a contributing writer for Fast Company. His first book, “The Bottomless Cup,” comes out on Abrams Press in 2025.Kevin has been a featured or keynote speaker for the National Restaurant Show, MUFSO, Miami Food& Wine, New York City Wine & Food Festival, The Illinois Restaurant Association, Kellogg School of Management, University of Illinois, ChicagoGourmet, Asheville Independent Restaurant Show, Hearst, Cameron Mitchell Restaurants, The Welcome Conference at Lincoln Center, & Welcome Chicago.He has given the commencement address at both Culinary Institute of America & Kendall College.He currently sits on the board of the Illinois Restaurant Association, Open Table, 826 CHI, and Easter Seals.Kevin lives in Chicago and frequently spends time in Los Angeles and New York City, where Boka Restaurant Group has opened restaurants in recent years.Listen To The More We Know ⇨ https://www.buzzsprout.com/1134704​Subscribe ⇨https://www.youtube.com/channel/UCxvfd5ddf72Btbck8SdeyBwFollow my Instagram ⇨ https://www.instagram.com/sameer.sawaqed/?hl=enFollow my Twitter ⇨ https://twitter.com/commitwithmeer

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The Löbian Obstacle, And Why You Should Care, published by marc/er on September 7, 2023 on The AI Alignment Forum. In 2013, Eliezer Yudkowsky and Marcello Herreshoff published Tiling Agents for Self-Modifying AI, and the Löbian Obstacle. It is worth comprehending because it: Is a very well written paper. Expresses an idea that is non-obvious, and still relevant to alignment today. Provides insight into what Eliezer and Marcello thought was valuable to work on in the time preceding publication. When I first read this paper, I terribly misunderstood it. Due to it not being particularly approachable material for someone not well-versed in logic, I was confidently wrong for at least one month. This post summarizes my understanding of what the Löbian Obstacle is (having re-read the paper,) and why I think it is still an important idea one decade after its publication. An agent A1 occupies a fully-known, deterministic and closed environment. A1 has a goal G that is either satisfied or otherwise by an outcome, for which A1's preference is satisfaction. An action bi∈Acts0 performed by an agent created by A1, hereafter referred to as A0, must therefore satisfy the statement: ¯¯bi⇒A0⊩¯¯biG Where ¯¯bi denotes the actual performance of bi, and ⊩ denotes cognitive belief in the succeeding statement. Even if A1 could verify by inspection of A0's design that ¯¯bi⇒A0⊩¯¯biG will hold, as in: A1⊩A0(∀bi∈Acts0:¯¯bi□0⌈¯¯biG⌉) Where □0⌈ϕ⌉ refers to a proof of ϕ from the axioms of A0; Axm0, this is unknowable, as it would require: A1⊩∀bi:(□0⌈¯¯biG⌉(¯¯biG)) Which due to Löb's Theorem we know to be impossible: For this to be so it would need to be that Axm1 could prove that if some proof of ⌈ϕ(x)⌉ exists in Axm0, that ϕ(x) must be true. The above was a brief paraphrasing of section two of the original paper, which contains many additional details and complete proofs. How the Löbian Obstacle relates to simulators is my current topic of research, and this section will make the case that this is an important component of designing safe simulators. We should first consider that simulating an agent is not distinguishable from creating one, and that consequently the implications of creating dangerous agents should generalize to their simulation. Hubinger et al. (2023) have stated similar concerns, and provide a more detailed examination of the argument. It is also crucial to understand that simulacra are not necessarily terminating, and may themselves use simulation as a heuristic for solving problems. This could result in a kind of hierarchy of simulacra. In advanced simulators capable of very complex simulations, we might expect a complex network of simulacra bound by acausal trade and 'complexity theft,' whereby one simulacra tries to obtain more simulation complexity as a form of resource acquisition or recursive self-improvement. I expect this to happen. Lower complexity simulacra may still be more intelligent than their higher complexity counterparts, and as a simulator's simulacra count may grow exponentially, as does the likelihood that one simulacra attempts complexity theft. If we want safe simulators, we need the subsequent, potentially abyssal simulacra hierarchy to be aligned all the way down. Without being able to thwart the Löbian Obstacle, I doubt a formal guarantee is attainable. If we could do so, we may only need to simulate one aligned tiling agent, for which we might settle with a high certainty informal guarantee of alignment if short on time. I outlined how I thought that could be done here, although I've advanced the theory considerably since and will post an updated write-up soon. If we can't reliably thwart the Löbian Obstacle, we should consider alternatives: Can we reliably attain high certainty informal guarantees of alignment for arbitrarily deep simulacra hierarchies...

Tom and Ula are back! The Mandarin Monkey Podcast is back after a few weeks away and with children being at home on their summer holiday. Listen to Ula if you want to learn Mandarin Chinese. Listen to Tom if you want to learn English. Split your brain down the middle to learn both at the same time. :)

Credits: 0.25 AMA PRA Category 1 Credit™   CME/CE Information and Claim Credit: https://www.pri-med.com/online-education/podcast/frankly-speaking-cme-338 Overview: Listen in as we explore the connection between asthma and cancer. We examine new Global Initiative for Asthma (GINA) guidelines and recent observational data correlating an asthma diagnosis with an increased cancer risk. Don't miss out on this essential discussion that will empower you with valuable knowledge for enhanced patient care. Episode resource links: Guo, Y, Bian, J, Chen, Z, et al. Cancer incidence after asthma diagnosis: Evidence from a large clinical research network in the United States. Cancer Med. 2023; 00: 1- 7. doi:10.1002/cam4.5875 GINA guidelines 2022: https://ginasthma.org/wp-content/uploads/2022/07/GINA-Main-Report-2022-FINAL-22-07-01-WMS.pdf Guest: Robert A. Baldor MD, FAAFP   Music Credit: Richard Onorato

Credits: 0.25 AMA PRA Category 1 Credit™   CME/CE Information and Claim Credit: https://www.pri-med.com/online-education/podcast/frankly-speaking-cme-338 Overview: Listen in as we explore the connection between asthma and cancer. We examine new Global Initiative for Asthma (GINA) guidelines and recent observational data correlating an asthma diagnosis with an increased cancer risk. Don't miss out on this essential discussion that will empower you with valuable knowledge for enhanced patient care. Episode resource links: Guo, Y, Bian, J, Chen, Z, et al. Cancer incidence after asthma diagnosis: Evidence from a large clinical research network in the United States. Cancer Med. 2023; 00: 1- 7. doi:10.1002/cam4.5875 GINA guidelines 2022: https://ginasthma.org/wp-content/uploads/2022/07/GINA-Main-Report-2022-FINAL-22-07-01-WMS.pdf Guest: Robert A. Baldor MD, FAAFP   Music Credit: Richard Onorato

Chen Shui-bian (陳水扁) was a highly controversial two-term ROC president (2000–2008). How “A-Bian” studied and fought his way out of rural poverty to the highest office, thus bringing 55 years of continuous KMT rule to an end, is the single greatest personal political story in modern Taiwanese history. Sadly, though, this fairytale would have a tragic ending, with a troubled second term and Chen later doing prison time for corruption. But in today's episode, we look at the early years: his stoic parents, his remarkable local teachers, and the struggles and triumphs that shaped him. Visit our website for info, pics, links, and more! www.formosafiles.com

Eric and Gil discuss hot topics and summer toursSupport the showThe Adult Social Media The Q Lounge PodcastMusic by Spell with Spellone Productions with Sound Lab Studios (Starting season 5)Art by Diane with DemTees Designs (Starting Season 5)

“You and me together? God doesn't have the balls to keep us out.” Leo is looking to send Miguel back to Solitary due to a lack of progress from his Em City informant. After being tasked with killing Burr by Morales, Miguel tries to strike a deal with Burr himself. However, a rejection leads to deadly consequences and Miguel leaving the unit once again. Weigert Corporation's "Aging Pill" experiment continues to cause friction amongst the staff as the inmates continue to take their dosage. While some appear to be showing no side-effects whatsoever, others are showing varying degrees of aging, which gets Ryan into a panic. It could be worse though, it's not like any of the test subjects have dropped dead. Oh wait… Leroy, now known as Salah Yudin, continues to plot to kill Said. He's presented with a golden opportunity, but he can he bring himself to do it? Omar gets starstruck following a chance meeting with Vahue. Feeling disrespected by Vahue's aloofness, and talking absolute shit in the process, Omar strikes out, determined to make a name for himself. The Refugees are prepared to be returned to China. Before that happens, Gongjin gets the opportunity to meet the man behind the people smuggling operation, Jia Kenmin. With his chance to gain revenge on Morales for Bian's murder having now past, Gongjin asks for Jia to prove himself to his people by murdering Morales. Supreme returns to Em City, not only adding to Ryan's panic, but leading to a revelation for Augustus regarding the night he was arrested. Following a confrontation in the showers which leaves Augustus in the hospital, and despite Keller's offer to help, Burr seeks his own brand of justice. The news of Hank's murder reaches Oz, jeopardising the progress made between Schillinger and Beecher. Schillinger, with a little convincing from Robson, goes on the offensive, resulting in a visiting Angus being stabbed. As tensions continue to rise, Keller confides in Cloutier that it was he that ordered the hit on Hank, and that Beecher is innocent. Believing Keller's confession, Cloutier finds Schillinger before any more blood can be spilled. In two minds about what to truly believe, Schillinger meets with Beecher in one last attempt to end the bloodshed. With the Hatchet seemingly buried, Beecher and Keller say their goodbyes as Keller is shipped off to Massachusetts to stand trial. Also on this episode: Rebadow goes to bat for Busmalis, Len Lopresti: Car Salesman, we go for a walk down Doyers St, Ray returns from retreat, the inclusion of a deleted scene could really help the flow of things, and Dean Winters attempts to sing, bringing a controversial opinion to the surface. All of this and more on the Series 4(B) Episode 12, Cuts Like A Knife Follow the show on Instagram & Twitter - @insideozpodcast, and now on Mastodon - @insideozpodcast@mastodon.world Email The Show – insideozpodcast@gmail.com #InsideOz Friends of Firefighters - https://friendsoffirefighters.org/

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Löbian emotional processing of emergent cooperation: an example, published by Andrew Critch on January 17, 2023 on The AI Alignment Forum. Related to: A Löbian argument pattern for implicit reasoning in natural language: Löbian party invitations Epistemic status: my opinion based on a mix of math, reflection, and speculation; not backed up by any systematic psychological studies. Summary: Since my 2019 paper generalizing Löb's Theorem, a couple dozen people have asked me if the way humans naturally cooperate might be well-described by Löb's Theorem. In short, my answer is probably sometimes, and in this post I'll try using an example to convey what that means. Importantly, Löb's Theorem is not a theorem when applied to real-world humans and emotions — i.e., when its hypotheses are met, its conclusion is only sometimes true. Nonetheless, the reasoning pattern in its proof (I claim) sometimes genuinely occurs at the level of intuition in real people, whether or not they know any math or Löb's Theorem. Introduction There are at least two real-world patterns that could reasonably be called Löbian cooperation in humans, which I'll name here: Functionally Löbian cooperation. Sometimes people become aware that they're anticipating (predicting) cooperation from each other, and then that anticipation causes them to cooperate, rendering the anticipation itself valid. In this pattern, the fact that anticipation of cooperation will cause cooperation is analogous to the hypothesis (main assumption) of Löb's Theorem, and the fact that the cooperation in fact emerges is analogous to the conclusion of Löb's Theorem. I call this pattern "functionally" Löbian because its input and output resemble the input (hypothesis) and output (conclusion) of Löb's Theorem. Procedurally Löbian cooperation. Sometimes the mental procedure a person follows to anticipate and decide upon cooperation can resemble an entire proof of Löb's Theorem, as I'll describe below. In other words, instead of just the hypothesis and conclusion of Löb's Theorem matching reality, the structure in the intermediate steps of the proof also match reality, at least somewhat. I call this "procedurally" Löbian cooperation, and it's a special case of functionally Löbian cooperation because it demands a stronger analogy between the theorem and the real world. Illustrating how this might work constitutes is the bulk of content in this post. What functionally Löbian cooperation feels like For those who recognize the symbols involved, Löb's Theorem says that if ⊢□cc then ⊢c. I don't plan to use these symbols with their normal meanings in the rest of this post, so don't worry if you don't recognize them. In words, functional Löbian cooperation happens when anticipation of future or unobserved cooperation causes present cooperation. So if you're interacting with someone, and you feel like they're probably going to be nice to you in the future, and that fact makes you decide to be nice to them now, I call that functional Löbian cooperation. What procedurally Löbian cooperation feels like Most human cooperation is probably not procedurally Löbian, and maybe not even functionally Löbian. However, I'm confident that human cooperation is sometimes procedurally Löbian, and I can even point to experiences of my own that fit the bill. To explain this, I'll be talking a lot more about feelings, because I think most unconscious processing is carried out by and/or experienced as feelings. I'll write Feeling("Pigs can probably fly.") for the feeling that pigs can probably fly. Such a feeling can be true or false, according to whether it correctly anticipates the real world. In procedurally Löbian cooperation, part of the mental process will involve first feeling something uncertain to do with cooperation, then believing it, and then feeling lik...

In this episode of the Epigenetics Podcast, we caught up with Sarah Kinkley from the Max Planck Institute of Molecular Genetics to talk about her work on PHF13 and its role in chromatin and transcription. The Kinkley laboratory focuses mainly on unraveling the mechanism of action of the transcription factor PHF13 (PHC Finger Protein 13). PHF13 is a reader of the epigenetic mark H3K4 trimethylation which influences higher chromatin order, transcriptional regulation, and differentiation. The lab has shown that PHF13 plays a crucial role in phase separation and mitotic chromatin compaction.   References Kinkley, S., Staege, H., Mohrmann, G., Rohaly, G., Schaub, T., Kremmer, E., Winterpacht, A., & Will, H. (2009). SPOC1: a novel PHD-containing protein modulating chromatin structure and mitotic chromosome condensation. Journal of cell science, 122(Pt 16), 2946–2956. https://doi.org/10.1242/jcs.047365 Chung, H. R., Xu, C., Fuchs, A., Mund, A., Lange, M., Staege, H., Schubert, T., Bian, C., Dunkel, I., Eberharter, A., Regnard, C., Klinker, H., Meierhofer, D., Cozzuto, L., Winterpacht, A., Di Croce, L., Min, J., Will, H., & Kinkley, S. (2016). PHF13 is a molecular reader and transcriptional co-regulator of H3K4me2/3. eLife, 5, e10607. https://doi.org/10.7554/eLife.10607 Connecting the Dots: PHF13 and cohesin promote polymer-polymer phase separation of chromatin into chromosomes. Francesca Rossi, Rene Buschow, Laura V. Glaser, Tobias Schubert, Hannah Staege, Astrid Grimme, Hans Will, Thorsten Milke, Martin Vingron, Andrea M. Chiariello, Sarah Kinkley. bioRxiv 2022.03.04.482956; doi: https://doi.org/10.1101/2022.03.04.482956   Related Episodes The Role of Blimp-1 in Immune-Cell Differentiation (Erna Magnúsdóttir) H3K4me3, SET Proteins, Isw1, and their Role in Transcription (Jane Mellor) The Role of SMCHD1 in Development and Disease (Marnie Blewitt)   Contact Epigenetics Podcast on Twitter Epigenetics Podcast on Instagram Epigenetics Podcast on Mastodon Active Motif on Twitter Active Motif on LinkedIn Email: podcast@activemotif.com

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Löb's Theorem for implicit reasoning in natural language: Löbian party invitations, published by Andrew Critch on January 1, 2023 on The AI Alignment Forum. Related to: Löb's Lemma: an easier approach to Löb's Theorem. Natural language models are really taking off, and it turns out there's an analogue of Löb's Theorem that occurs entirely in natural language — no math needed. This post will walk you through the details in a simple example: a very implicit party invitation. Motivation (Skip this if you just want to see the argument.) Understanding the structure here may be helpful for anticipating whether Löbian phenomena can, will, or should arise amongst language-based AI systems. For instance, Löb's Theorem has implications for the emergence of cooperation and defection in groups of formally defined agents (LaVictoire et al, 2014; Critch, Dennis, Russell, 2022). The natural language version of Löb could play a similar role amongst agents that use language, which is something I plan to explore in a future post. Aside from being fun, I'm hoping this post will make clear that the phenomenon underlying Löb's Theorem isn't just a feature of formal logic or arithmetic, but of any language that can talk about reasoning and deduction in that language, including English. And as Ben Pace points out here, invitations are often self-referential, such as when people say "You are hereby invited to the party": hereby means "by this utterance" (google search). So invitations a natural place to explore the kind of self-reference happening in Löb's Theorem. This post isn't really intended as an "explanation" of Löb's Theorem in its classical form, which is about arithmetic. Rather, the arguments here stand entirely on their own, are written in natural language, and are about natural language phenomena. That said, this post could still function as an "explanation" of Löb's Theorem because of the tight analogy with it. Implicitness Okay, imagine there's a party, and maybe you're invited to it. Or maybe you're implicitly invited to it. Either way, we'll be talking a bunch about things being implicit, with phrasing like this: "It's implicit that X", "Implicitly X", or "X is implicit". These will all mean "X is implied by things that are known (to you) (via deduction or logical inference)". Explicit knowledge is also implicit. In this technical sense of the word, "implicit" and "explicit" are not actually mutually exclusive: X trivially implies X, so if you explicitly observed X in the world, then you also know X implicitly. If you find this bothersome or confusing, just grant me this anyway, or skip to "Why I don't treat 'implicit' and inexplicit' as synonyms here" at the end. Abbreviations. To abbreviate things and to show there's a simple structure at play here, I'll sometimes use the box symbol "□" as shorthand to say things are implicit: "□(cats love kittens)" will mean "It's implicit that cats love kittens" "□X" will mean "It's implicit that X" A peculiar invitation Okay! Let p be the statement "You're invited to the party". You'd love to receive such a straightforward invitation to the party, like some people did, those poo poo heads, but instead the host just sends you the following intriguing message: Abbreviation: □pp Interesting! Normally, being invited to a party and being implicitly invited are not the same thing, but for you in this case, apparently they are. Seeing this, you might feel like the host is hinting around at implicitly inviting you, and maybe you'll start to wonder if you're implicitly invited by virtue of the kind of hinting around that the host is doing with this very message. Well then, you'd be right! Here's how. For the moment, forget about the host's message, and consider the following sentence, without assuming its truth (or implicitness): Ψ: The sentenc...

Bian and Marty give their thoughts on the Sabres game being moved due to weather

On this episode of the Scouting For Growth podcast, Sabine VdL talks to Annap Derebail, IBM's Global Insurance Industry CTO within IBM'S Global Business Services Unit. Annap'S FOCUS has always been on delivering impactful business outcomes by re-imagining user experiences. Today Annap provides trusted advice to influence revenue growth for IBM's clients by considering architectural leadership to transform client's business through technology innovation. In this conversation they cover the future of insurance and implications on operations, how technology becomes a key enabler of growth today, and how can insurers simplify operations to build resilient business models.   KEY TAKEAWAYS          There's a lot of market forces that are disrupting traditional insurance models. Firstly, around customer expectations. Customers are increasingly looking towards an Amazon- or Google-like experience when dealing with their insurance. The implications for insurers include creating some sort of personalised offerings, providing high levels of service and responsiveness. There are two key advantages that incumbent insurers have over new entrants to the market. Certainly, the new entrants are creating new business models and ways of attracting and approaching customers. But I think the advantages for incumbents are their huge existing customer base – keeping a customer is six times easier than acquiring a new one. Secondly, by virtue of having been in business for such a long time, they are sitting on tons and tons of data, they have knowledge of customer transactions/interactions. That's a rich oasis with which they can develop a better understanding of their customers and what they need. Insurers really need to reinvent how they think about risk and what sort of a relationship they want with their customers. Reinventing that risk partnership and helping insurers with new risk experiences that offer personalised advise and demonstrating a new risk partnership between the insurer and the customer. Being able to harvest the data can be done by taking a fresh look at historically operating processes in the enterprise, critical processes such as underwriting claims, but also all of the support processes like billing, customer support, policy maintenance, etc. Just by paying attention to driving intelligence into those processes using data, we've been able to example reduce 15% of our customer churn by implementing a churn detection model. At the infrastructure level, what I see is a lot of incumbent insurers still operating legacy IT systems still working on legacy infrastructure. The immediate opportunity there is to migrate those onto a cloud-based platform. This brings inherent benefits like flexibility in terms of scaling up and down in response to demand and to market needs. You can access cloud-based services from anywhere in the world.   BEST MOMENTS ‘The insurance industry needs to adapt and respond to new disruptors and this response has to be driven by data and new technologies and using them to gain a business advantage in the market.'‘Less than 10% of insurers have actually been able to meet what we call ‘the data dividend', effective use of data in order to achieve competitive advantage because of a lack of knowledge of how to access data, how the data is siloed within the infrastructure of the business.'‘We can help drive a step change in core productivity of incumbent insurers. About 60% of their costs goes into legacy IT systems, modernising by having multiple core systems in place and moving to a SaaS model reduces issues.'‘The typical underwriting or claims process tends to have heavy human involvement and requires a large number of steps in order to make decisions. The scope there is to effectively use the mountain of data that insurers are sitting on to present the right data to the right decision makers at the right time – not just raw data, but insights drawn from the raw data. – to improve the process and categorise incoming cases that can either be automated or needs human intervention.' ABOUT THE GUEST Annap Derebail has 20+ years of professional experience in systems and integration architecture, design, development and management of complex industry solutions.  In his current role, he works with insurance customers worldwide to create innovative solutions for business problems leveraging microservices and API driven architecture, distributed, multi-tier systems and application integration architecture, AI/ML, blockchain, IoT, cloud computing and services-oriented architecture. In the last five years, he has worked with worldwide financial services clients to provide trusted advice on their digital transformation initiatives, while serving as leader of the global IBM insurance industry architect community.  His work with clients has spanned several application areas: Modernization architectures for insurance and banking, Blockchain applications in insurance, Enterprise architecture for aircraft systems health, Supply chain collaboration in automotive and retail, RFID based track and trace solutions, Product design-to-manufacture integration, and Supply chain optimization.  Over the years, he has been IBM's technical representative in industry standards bodies, including ACORD, BIAN, PDES Inc, STAR and AIA.  He holds a PhD in Industrial Engineering/Operations Research from Texas A&M University. ABOUT THE HOST Sabine is a corporate strategist turned entrepreneur. She is the CEO and Managing Partner of Alchemy Crew, a venture lab that accelerates the curation, validation, and commercialization of new tech business models. Sabine is renowned within the insurance sector for building some of the most renowned tech startup accelerators around the world working with over 30 corporate insurers and accelerating over 100 startup ventures. Sabine is the co-editor of the bestseller The INSURTECH Book, a top 50 Women in Tech, a FinTech and InsurTech Influencer, an investor & multi-award winner.  Twitter: SabineVdL LinkedIn: Sabine VanderLinden Instagram: sabinevdLofficial Facebook: SabineVdLOfficial TikTok: sabinevdlofficial Email: podcast@sabinevdl.com Website: www.sabinevdl.com  This show was brought to you by Progressive Media

Assistant Professor Lin Bian describes how her mother's work as a teacher influenced her interest in teaching and finding out she achieved her childhood dream from a decade ago. Her fascination for developmental psychology led her to understand what it's like to be a woman in STEM and study why there are not more women in STEM. In this episode, she gives out a piece of evidence-based advice that, hopefully, will shift the current culture and people's perspective.

“Age? What do you mean? Like grow old?” After being framed for Bian's murder, Burr is released from the Em City Cage, triggering a feud between himself and Morales & Chucky. Following his return to Oz after being on the run, Miguel has found himself back in Solitary. He soon strikes a deal with Leo to be his Eyes & Ears in Em City, but first he must prove himself to Morales. In conjunction with the returning Weigart Corporation, Gloria launches an experimental treatment to test Weigart's new “Aging Drug”, whereby an inmate will physically age several years and eventually be released, freeing up much needed space inside of Oz. After another violent altercation, Gloria proposes putting Cyril, along with brother Ryan, into the pool of participants, much to McManus' chagrin. Jaz & Robson are on the warpath. As they attack Arif in the gym, a courageous Leroy saves Arif, resulting in Leroy finally joining The Muslims. They also have issues with Cloutier's mentorship of Schillinger, fearing that their position is beginning to weaken. Beecher and Schillinger sit down to try and begin the recovery process as part of Sister Pete's Victim-Offender Interaction Program. As Busmalis and Norma begin to plan for their Wedding, Busmalis must convince Leo to allow the Ceremony. After some persuasion from McManus, Leo allows it take place on the proviso that Busmalis behaves himself, Busmalis having previously escaped still sticking in Leo's craw. Rather than jeopardise his upcoming nuptials and under pressure from Omar, Busmalis decides to fill in the hole that he's been digging. In a cruel twist of fate, things don't go to plan for “The Mole”, leaving his upcoming Wedding up in the air. Agent Taylor returns to Oz to continue to investigate the Homosexual Murders Case. As he delves into Ronnie's past with Keller, Taylor offers Ronnie a reduced sentence deal in exchange for his testimony. Beecher gets wind of this development after Ronnie seeks his legal counsel, and despite his rocky relationship with Keller, informs Keller about the offer Ronnie has been made. With the walls closing in on him, Keller commits a desperate act. Also on this episode: the perils of recording the Podcast during the Summer, the mystery of the “spat-in Burger”, we take a walk around the booths at the Warden's Conference, Rick Fox wins an NBA Title, Chris Meloni shows us his hole, Jaz wears a problematic clothing brand and a brief history of The Hatfields vs The McCoys. All of this and more on the Series 4(B) Episode 11, Revenge Is Sweet Follow the show on Instagram & Twitter - @insideozpodcast Email The Show – insideozpodcast@gmail.com #InsideOz   'Tumbleweed Town' created by Brandon Fietcher - https://www.youtube.com/watch?v=JBkRe_m21Z0

In this episode, Folly Rob sits down with Peter Bian, owner of Saturday Dumpling Club. Hear how Peter used a family recipe to begin selling dumplings through Instagram. What began posting on his personal account and selling out his garage through DMs has led to a full scale operation creating weekly dumpling pick-ups selling out nearly every week. If you're lucky enough to get ahold of some of their dumplings, you'll know why they've become so popular. Enjoy! @saturdaydumplingclub --- Send in a voice message: https://anchor.fm/follycoffeepodcast/message Support this podcast: https://anchor.fm/follycoffeepodcast/support

Nach mehreren Wochen Aufenthalt auf der psychiatrischen Akutstation deutet sich bei Bian eine Veränderung an. Kann Bian auf der Station Fortschritte machen? Zugleich rückt ein Datum näher, das sie mit einer großen Bedrohung verbindet und das auf ein inneres Dilemma verweist. Zu dieser Folge gibt es das Skript sowie eine ca. 80-minütige Nachbesprechung (zu jedem Teil der Fallgeschichte gibt es eine eigene Nachbesprechung) auf unserer Förderplattform Patreon: www.patreon.com/raetseldesubw Link zu unserer Website mit weiteren Informationen zur Folge: www.psy-cast.de Wir freuen uns auch über eine Förderung unseres Projekts via Paypal: https://www.paypal.com/donate/?hosted_button_id=VLYYKR3UXK4VE&source=url

Bian, eine junge Frau, wird von ihrer Familie auf die Akutstation einer psychiatrischen Klinik gebracht. Sie hört Stimmen und leidet an anderen auffälligen Symptomen. Auf der Station zeigt sich Bian sehr verschlossen, spricht kaum und gibt wenig Einblick in ihr Erleben. Erst allmählich gelingt es der Stationsärztin und Psychoanalytikerin, einen Weg zu Bian zu finden und mit dem in Kontakt zu kommen, was sich in ihrer Innenwelt ereignet. Zu dieser Folge gibt es das Skript sowie eine ca. 60-minütige Nachbesprechung auf unserer Förderplattform Patreon: www.patreon.com/raetseldesubw Link zu unserer Website mit weiteren Informationen zur Folge: www.psy-cast.de Wir freuen uns auch über eine Förderung unseres Projekts via Paypal: https://www.paypal.com/donate/?hosted_button_id=VLYYKR3UXK4VE&source=url

O podcast Código BR, episódio 62, faz uma análise sobre o novo técnico do Santos, Fábian Bustos, e como ele pode montar a equipe da Vila Belmiro. Após os trabalhos no Delfin e Barcelona/ECU, sua chegada gera uma expectativa e a estreia acabou sendo adiada por conta da iluminação no Paulistão. Tempo bom para o episódio, não é? Quais jogadores podem ganhar mais espaço? A sua primeira escalação dava sinais de algo? Os jovens podem ser mais aproveitados? O Santos deve utilizar um jogo mais direto ou não? Estes e outros temas, você vai ouvir aqui com Gabriel Corrêa, Rodrigo Coutinho e Aurélio Solano.

Much of our medicine is shrouded in myth, and one of the obscure, but persistent figures is that of Bian Que, the bird-headed healer first associated with the use of stone needles. In this conversation with Shelley Ochs we discuss her Ph.D dissertation on this mythic character that adorns ancient tombs, and shows upin imagery that suggests a connection between the heavenly and earthly realms. Chinese medicine's bird-headed healer is not the first or only image of divine presence that is associated with life, healing and death. Other cultures also have this image in their pantheon of healers and gods. Listen into this discussion of the history and recent academic perspectives of an alternative stream of medicine that intertwined with that of the Nei Jing, but has its own unique roots.