Podcasts about Snappy

https://web.archive.org/web/19980206194618/http://www.hokuspick.com/bio.html https://www.youtube.com/watch?v=p_z-9zlmuhE&ab_channel=RagamuffinArchive https://www.bezartshub.com/events-calendar/2024/9/27/hokus-pick?fbclid=IwY2xjawJWZllleHRuA2FlbQIxMQABHaOsUJORDm7EhfFvCTFrZp4T2FEQs1t7D86wEPgH-sDn2PutEQG25TXeEA_aem_VPMIVEQI47cx2S5okeC8Cw https://www.facebook.com/groups/2483596859/ https://www.linkedin.com/in/david-strilchuk-b145538/?originalSubdomain=ca https://www.themeetingplace.org/staff-amp-lead-teams https://www.ensembletheatrecompany.ca/rick-colhoun-designer-bio https://www.getbold.com/history/

Don't forget; all liquids have to be three ounces or less, take off your shoes and please don't pack any pets in your pants. And if you spot a thing that shouldn't be, send it in to janesays@civicmedia.us and we might use it on the show! So join us Monday through Friday at 11:51 a.m. for “This Shouldn't Be A Thing!” or search for it on Spotify, Apple or wherever you get your podcasts. And thanks for listening!!

Coming up in this episode * Syncing the Notes * The History of Snaps * And How Much We Absolutely Adore Them 0:00 Cold Open 1:34 Seeking Syncthing 16:42 The History of Snaps 33:52 How'd 9 Years of Snaps Go? 1:01:54 Next Time 1:04:49 Stinger The Video Version https://youtu.be/izDzKkuEyRw It is all about the notes Leo goes back to basics and uses SyncThing (https://syncthing.net/) to move his markdown files around that he edits using a standard text editor (https://code.visualstudio.com/).

Gary Boxall is retiring after 35 years. He formally leaves on 31 March and Snappy Snaps are taking the business over, and after refurbishment will reopen the shop two weeks later; which is good news for the High Street too. Gary talks to Mike Waddington about his love of photography (from age 7) and how he came to open the shop - first on Chapel Street and then into larger premises on Lavant Street. He intends to concentrate on genealogy and write about it. He also says his farewells to Petersfield.See omnystudio.com/listener for privacy information.

Dive into the liminal space between waking and dreaming with “Dream Yoga.” Snappy snares, electric piano, and organ grooves transport you to the “dreaming sea,” a space for reflection and release. From Nothing Will Keep Us Apart, this track invites listeners to journey into the subconscious. Perfect for Chill Vibes or Dreamy Indie Pop playlists. Dream Yoga Written by Clementine Moss/Robert Preston/William Cameron Clementine: Vocals, Drums, Synths Robert Preston: Bass William Cameron: Keys Clementine Moss Nothing Will Keep Us Apart Producers: Clementine Moss and Robert Preston Engineer: Robert Preston, GetReel Productions Mastering: JJ Golden, Golden Mastering Publishing: C. Kingdom Publishing 2024

This episode of CORNDOWN kicks off with some loose parts—literally—before wastedmemory and I try to make sense of questionable food practices, including the unexpected use of glue. There's a lot of discussion about chicken, from giving it away to keeping track of it in a highly unnecessary log. wastedmemory takes a moment to address the chat, and ButtEye stirs things up with a hidden motorcycle situation. Snappy bakes gets involved in a parking lot spectacle, while Hootis deals with a guy who seems a little too invested in parking. Things wrap up with an attempt to balance the new and the old, though not everyone agrees on what that means. This show is made possible by donations from listeners like you. If you enjoy what you hear, please consider donating via patreon or paypal! powered by rogueserver.com

Don't miss our newsletter! That's where we drop weekly knowledge bombs to help you make sense of defense!In this episode, Mike sits down with Brett “Snappy”Abbamonte, a former Marine Corps F-35 pilot now at Advanced Strategic Insight (ASI) Inc. Snappy is the program manager for ELITE (ExpendableLower-cost Integrated Training Emitter), a compact, cost-effective system designed to mimic high-end surface-to-air missile (SAM) threats.Dive into how this innovative tech is reshaping training,enhancing readiness, and solving a critical warfighter problem—offering a firsthand look at how operators are using ELITE in the field to sharpen their edge.If you're into military training, cutting-edge technology,and boosting warfighter readiness—this episode is a must-listen. Links• Sign up for the newsletter⁠! • Support us on ⁠Patreon⁠!• Mike Benitez on LinkedIn• Brett “Snappy” Abbamonte on LinkedIn• ASI company• ELITE product ----Follow us on... • LinkedIn• Instagram⁠• ⁠X⁠• ⁠Facebook⁠• ⁠Website⁠----00:00 start01:11 intro03:08 Snappy 04:49 F-35 magnifies a growing problem07:21 the 3-solution problem10:31 good-enough solution space12:12 ELITE13:51 size and power15:35 as a target17:45 customers20:27 remote controlled22:00 how to keep it low cost23:34 creative training25:09 how the training looks26:47 RAF Lakenheath31:19 SBIR experience38:02 valley of death38:34 end of year money40:27 squadron innovation funds42:14 expendable concept validated42:50 Marine Corps weapons school example44:40 expendable allocation46:14 tools for innovative training49:30 memory lane49:45 callsign story51:40 outro#military #nationaldefense #warfare #nationalsecurity#defense #nationaldefense #tech #technology #defensetech #army #navy #airforce #usmc#innovation #war #strategy #aerospace #china #airpower #f35 #training #readiness #electronicwarfare

Overstimulation in motherhood is a real thing. The more kids you have the more noise there is in the home. Sometimes you might feel at your wits end and the explosion is about to come. How can you remain calm even when all the noise feels like too much?In this episode you will learn:Proactive tips to increase your tolerance to all the noise Tips to calm down when you can walk awayTips to stay calm when you cannot walk away from the kidsHow to communicate your feelings and needs with your familyIf you struggle with overstimulation, you are not alone. This is very common for mom especially with multiple kids. There is nothing wrong with you. Want further help in becoming a calm and patient mom? BOOK FREE CONSULTATION CALL today and let's work together to help you become the mama your desire to be. Text the show. ~~~~~~~~~~~~~~~~~~~~~~~~BOOTCAMP SIGN UP ~~~~~~~~~~~~~~~~~~~~~~Next Steps: 1. Watch FREE TRAINING: 5 Steps to Break free from Mom Rage Shame ⬇️2. Learn about Calm Christian Mom Coaching Program ⬇️3. BOOK A FREE CALL if you are want support in overcoming damaging anger patterns. ~~~~~~~~~~~~~~~~~~~~~~~MINI-COURSE BONUSHow to 10x your Emotional Capacity Levels as a MomLeave a 5 star rating and review on the Podcast and email me (hello@emotionallyhealthylegacy.com) a screenshot of the REVIEW for free access to my Mini-Course or buy it HERE for $27. Website: emotionallyhealthylegacy.comContact: hello@emotionallyhealthylegacy.comQuestions? Form / Voice memo **Shop my favorite Amazon Products**

Want to know what's at the heart of every successful organization? Connection, gifting, recognition, and appreciation! All four of these are so core to making somebody feel seen and heard at work. So in today's episode, we're discussing connection-building because let's face it, loneliness is hitting hard and it's an epidemic that is creeping into our workplaces.  Join me and Ross Langley from Snappy as we unpack innovative and personalized ways to foster connections with anybody in the office.  We're diving deep into creating meaningful experiences, leveraging personalization in gifts, and ensuring everyone in your organization feels truly seen and appreciated. Are you ready to unlock the full potential of your workforce? PI empowers organizations to align talent with business strategy, helping you drive results and build a culture where your people truly thrive. Transform how you hire, engage, and lead—visit predictiveindex.com to learn how you can create meaningful change in your organization today! 00:01:35 - What Topic Has Been Interesting to Ross Lately? 00:05:07 - How We Define Meaningful Connections at Work and Why It Matters 00:08:17 - The Biggest Challenges Orgs Face Trying to Build Authentic Connections 00:13:41 - How Unique Gifts Build Genuine Relationships at Work 00:21:59 - Leveraging Personalization to Create Emotional Impacts 00:25:35 - The Impact of Experiential Vs Physical Gifts 00:30:37 - Creative Ways for HR to Integrate Gifting Into Engagement Programs 00:37:07 - Potential Pitfalls With Using Gifts to Build Connections 00:41:14 - Advice for HR Leaders Incorporating Gifting Into Their Connection-building Efforts And if you love I Hate It Here, sign up to Hebba's newsletter! It's for jaded, overworked, and emotionally burnt-out HR/People Operations professionals needing a little inspiration. https://workweek.com/discover-newsletters/i-hate-it-here-newsletter/   And if you love the podcast, be sure to check out https://www.youtube.com/@ihateit-here for even more exclusive insider content! Follow Ross: LinkedIn: https://www.linkedin.com/in/thomas-ross-langley/ Follow Hebba:  YouTube: https://www.youtube.com/@ihateit-here/videos LinkedIn: https://linkedin.com/in/hebba-youssef Twitter: https://twitter.com/hebbamyoussef

We are going back in time to revisit some of our classic radio bits. Today we set the time machine to return to 2022 when Ben tricked Liam into eating a cat food-flavoured hot cross bun. Enjoy! The Ben, Liam & Belle show is on a break right now! We are back live on the radio on Jan 27th. Don't worry, we're still releasing original(ish) content nearly EVERY weekday until then. Enjoy your Holiday season!!!! Follow us on Instagram - TikTok - Facebook Listen Live on the Nova Player AppSee omnystudio.com/listener for privacy information.

You want rollerskating telephone operators? We got ‘em. You want arguments about how many gears a decent bike should have? It's all here in this episode of Five Brilliant Things with Suzi Ruffell. From the rough-arse pubs of Portsmouth to the fashionable theatres of London's West End, this lovely show touches on all corners of Suzi's past.  Suzi's on tour in 2025 with her brand-new show ‘The Juggle'. It's going all over the UK to a town or city near you in the second half of the year. Tickets and dates can all be found and acquired at suziruffell.com Aaaaand Suzi's latest recorded special ‘Snappy' is out now, available to rent HERE. Today's Patreon episode of Five Brilliant Questions sees both Suzi and Russell get very serious about the question 'Is it ever acceptable to eat a baguette sideways?' If you think you know the answer then please join us and get involved and settle the debate. You can join our Patreon for free if you like, and we'd be delighted to have you on the team. Check it all out at patreon.com/RussellHoward  And who even are you, reading this far down some show notes. But thanks for sticking with me. I hope you have a wonderful 2025. Just think, you're probably the only person in the world who's read this. And that means that it's only you who's received this well-wish. It's just for you. Because you're special. Until next time! Producer: Dan Atkinson Line Producer: Daisy Knight Exec Producer: James Taylor Composer: Fat Lady Music Learn more about your ad choices. Visit podcastchoices.com/adchoices

As the days get colder and darker, are you searching for a nourishing dinner that will warm you up from the inside out? In this bite-sized episode, we share delicious moments about the best things we ate this week to inspire each other – and you! This week we're talking about two must-try winter weeknight meals. You'll discover the secrets to a craveable Minestrone, chock-full of veggies and topped with a vibrant basil sauce. You'll also learn about a unique Midwestern twist on Sloppy Joe's – it will make for a nostalgic weeknight meal that's kid-friendly and parent-approved. Tune in for a quick dose of home cooking inspiration! ***LINKSSign up for our Substack, and you'll receive the Winter minestrone recipe (free) this Sunday (12/22)! You'll also find more soup recipes in the Substack archives.Sloppy Joe recipe with bonus veggies via Celebrating Sweets***Got a cooking question? Call in and leave us a voicemail on our kitchen phone! 323-452-9084Sign up for our newsletter here for special offers and opportunitiesOrder Sonya's debut cookbook Braids for more Food Friends recipes!We love hearing from you — follow us on Instagram @foodfriendspod, or drop us a line at foodfriendspod@gmail.com!

Mo is joined by 5kinny000 and Snappy to talk about… Politics Trump Bibles Biden's Pardon Weather UnitedHealth CEO Assassinated Home Owner Life Singing in Theatre  Ozympic Elf on the Shelf Car Entertainment Snappy Talk Sports Talk Music Stuff Faucet Replacement Biological Father Car Decals Road Rage Tipping Culture Sports in School Handshakes Kendrick vs Shultz Baldur's Gate 3 RFK Jr. Step Family Porn Future Endeavours  Outro - Show Links: https://www.patreon.com/apodcastwithmo https://apodcastwithmo.myspreadshop.com/ https://www.youtube.com/@apodcastwithmo Co-Producer Links: https://www.sirnasty74.com/ https://www.flatlinermusic.net/ - Featuring the songs: Don't Matter ft Southern Com4rt and Sir Nasty - A2thaMo Brad Pitt Remix ft Bradster X - A2thaMo Classy Flow - A2thaMo I'm Sorry - A2thaMo Gas Flow - A2thaMo Keep Trying - A2thaMo Losin Faith - A2thaMo 2 DIfferent People - A2thaMo *Bonus* --- Support this podcast: https://podcasters.spotify.com/pod/show/apodcastwithmo/support

The Daily Quiz - Entertainment, Society and Culture Today's Questions: Question 1: What is the name for the quotable, snappy snippets that politicians often use in news broadcasts and speeches? Question 2: Which film contains the character 'Harry Lime'? Question 3: What is the term for when a civilian government is replaced by military rule? Question 4: What religion was founded by Guru Nanak ? Question 5: Which influential historical person was leader of the Parliamentarians in the English civil war? Question 6: Blade Runner was released in which year? Question 7: In Egyptian mythology, who is known as the god of the desert and oases? Question 8: Which film contains the character 'Oda Mae Brown'? Question 9: In which country do they eat 12 grapes as the clock strikes midnight (one each time the clock chimes) on New Year's Eve? This podcast is produced by Klassic Studios Learn more about your ad choices. Visit megaphone.fm/adchoices

Bex Scott is back for a new season of Pyrex with Bex and in this first episode of the season, she's diving into the rabbit hole of collectible salt and pepper shakers. Her own collection started when she found lots of them in an online estate sale and discovered that her favorites are the kitschy anthropomorphic shakers. Why were so many made? When were they popular and why? Which ones are most valuable now? Bex reveals what she learned in this episode. Salt and pepper shakers were easy to collect because of their size, small, and they were also very affordable. They date back to around 1858 though there is some dispute over the exact person who created them. Strangely, the kitschy eye-catching salt and pepper shakers were one of the few things whose sales didn't dip during the Great Depression. Because they were small and cheap, they were easy to continue producing and still affordable to collect or gift. Bex explores how salt and pepper shaker designs reflected the time periods they were created in, the themes that became most popular, the rarest and most valuable salt and pepper shakers to look for now, and a family who collected 80,000 sets and started a museum just to house them. You don't want to miss this episode. It will make you look twice at salt and pepper shakers when you come across them.Resources discussed in this episode:Lefton Bluebirds salt and pepper shakersExtra long dachshund salt and pepper shakersPink poodle chef salt and pepper shakersHolt Howard pixieware salt and pepper shakers“Would You Like Some Salt and Pepper? How About 80,000 Shakers' Worth?” by Derek Workman, Smithsonian Magazine, January 23, 2012—Contact Rebecca Scott | Pyrex With Bex: Website: PyrexWithBex.comInstagram: @pyrexwithbex—TranscriptBex Scott: [00:00:02] Hey everybody, it's Bex Scott and welcome to the Pyrex with Bex podcast, where, you guessed it, I talk about vintage Pyrex, but also all things vintage housewares. I'll take you on my latest thrifting adventures, talk about reselling, chat with other enthusiasts about their collections, and learn about a bunch of really awesome items from the past. Subscribe now on Apple, Spotify, or wherever you love listening to podcasts so you don't miss a beat. Hey, everybody, this is Bex Scott and you are listening to the Pyrex with Bex podcast. And on today's episode it's salt and pepper time. We are talking all about salt and pepper shakers. And for me, this is a super fun topic because I have been collecting salt and pepper shakers on and off for the last couple of years. I don't have a huge collection, but they are one of the easiest things I've found to collect and to unfortunately amass in large quantities. Bex Scott: [00:01:04] So my salt and pepper shaker collection started back when I found a bunch of huge lots of them in an online estate sale, and I didn't actually know how many I was buying until I picked them up. And I probably had three moving boxes full of them, and unpacking them and cataloging them and photographing them was a massive endeavor. But one of the most fun things you can do as a collector, as you guys probably know, is unboxing and seeing what's inside, what you've bought from a sale or an online auction, and finding the little nuggets of maybe a really collectible item or something that you really love. Bex Scott: [00:01:53] So most of these salt and pepper shakers that I did buy, I ended up selling online on Facebook Marketplace or on Poshmark and some of them even on Whatnot now. And I've had a few friends on Whatnot who have had full on salt and pepper shaker sales, and it's so fun to watch them go through each of the shakers and to see just how fun they were. My favorite ones, hands down, are the kitschy salt and pepper shakers, and my great grandma had an absolute love of Lefton Bluebird, so I've been lucky enough to inherit some of her bluebirds. I have the salt and pepper shakers. I also have some of the more kitschy anthropomorphic ones. I have little kittens that are sitting on balls of yarn. I have some skunks that are sitting on logs and they're just very fun, cute, and you can store a lot of them in a small place. So this led me down a hole of looking into salt and pepper shakers, their appeal, their history. And I actually learned quite a bit about them. Bex Scott: [00:03:07] So. Salt and pepper shakers were easy for people to collect because of their size, and they were so affordable and they were just really easy to come across as well. They held on to them or passed them down. And you could, before, get a figural set of a dog, a cat, a bird for 5 to $7. Now the prices have gone up a little bit because they are in higher demand. People are reselling them and there are more that are collectible, some more than others. Salt and pepper shakers, they go back to about 1858 and they were created, some believe, by a man named John Mason who also created the Mason jar. So some people kind of refute this and are questioning whether that's actually true. But this is what I've found so far in my research. And before the salt and pepper shaker came to be, people used a bowl of salt called a salt cellar. And I've come across a lot of salt cellars in my collecting days, and a lot of the really cute ones are the little hens on the nest. I didn't actually know the purpose of a salt cellar. I knew that it was called that and you scooped the salt up with a spoon. People often added rice to it to keep the moisture at bay. And then it wasn't until 1911, when the brand Morton Salt Company introduced magnesium carbonate into salt that helped it to not clump, which is why people don't often put rice into their salt shakers now. Bex Scott: [00:05:02] So with these cute little kitschy and fun sets on home and restaurant tables, there was a high demand for the aesthetically appealing styles, and it was important for homemakers to have these on their table to show them off and to just have fun collecting them. So many people purchased them on road trips back in the day. One of the most popular types of salt and pepper shakers was the souvenir shaker that you got on your road trip that may have said the location it was from and where you got it. Now the Great Depression came along and there was no dip in salt shaker sales because it was one of the cheapest items in the kitchen. And during the 1930s and into the 1940s, the salt shakers went from glass and tin containers to the ceramic or plastic figurines. Most were from occupied Japan after a halt in production during the war. And the kitschier the better. So salt and pepper shakers became more cute, more eye-catching, and the number of salt and pepper shakers sold at local five and dimes and the fancier stores was just increasing. So some of the fun ones that you could find were the anthropomorphic fruit, fish, dogs. There's a set called the Extra Long Daschund that is really cute if you want to look up these funny little skinny wiener dog salt and pepper shakers. Bex Scott: [00:06:45] So by the 1970s, these cute figural shakers had completely gone out of style, out of production, and they were replaced by what we now have, which is a more standard boring cylindrical-style salt and pepper shaker. Don't get me wrong, there's some beautiful salt and pepper shakers out there now still, but it's just not the same anymore. And some of the ones that they were replaced by that people still collect are the Tupperware salt and pepper shakers, which were really popular during that time and not so much the conversation starters of all the cute, anthropomorphic, kitschy ones that you used to be able to find. So by the 1990s, people started to realize that the salt and pepper shakers were worth something because of the demand that collectors had made for them. And some of the most popular ones are cute little ones hanging from trees that have little baskets. I just sold a set. It was an adorable little dog that had two hanging baskets on the left and the right that you could remove, and those were the salt and pepper shakers. And the baskets were filled with flowers. Lots of kissing and hugging shakers. I have two little bears that when you put them together, their arms wrap around each other. Lots of Christmas ones. And some of the most sought after are from Lefton, Napco, Holt Howard. Bex Scott: [00:08:18] So a lot of this information that I found from my friend Worthpoint, and in this article that I was reading they went through the most collectible shakers from Lefton, Napco and Holt Howard, which I thought was super interesting because as a collector, I'm always wondering which ones I should be on the lookout for. So if you want to start the hunt, Lefton's most collectible are Bluebirds, Christmas angels, Miss Dainty, which is the girl with the red and white hat, Mr.Tootles the Maltese dog, Miss Priss the Blue Kitten, Thumbelina, The Green Fairy, Kissing Santa and Mrs. Claus, Christmas birds which are green, the Puppy Pal dogs wearing blue hats, and pink poodle chef, which in brackets they say is beyond expensive. I've actually never seen the pink poodle chef. Bex Scott: [00:09:21] Napco, you have number one, Miss Cutie Pie, two anthropomorphic fruit people, so that would be the artists, musicians, kissing Valentine birds, the bowler and hard hats, devils, flower girls, and long neck animals. And then Holt Howard, you have the Nodder Rock and Roll on springs, merry mice,they are pink and mischievous, Holly Poinsettia girls, winking Santa, Daisydorables, rooster, and pixieware are the most desirable of all the Holt Howard shakers I've seen. Not in person, but on a lot of my favorite collectors Instagrams and some on Facebook Marketplace. The pixieware salt and pepper shakers. They are so cute! Next up we have Enesco. Number one is the Sweet Shop. It says very pricey and rare. Anything anthropomorphic, fruits, vegetables, forks and spoons. I have had some forks and spoons. They're very cute. You can't really hold a lot of salt and pepper in them though, so definitely more for display. Golden Girls, Country Kids, Snappy the Snails, Missy Mouse, Doctor WO Owl, and Jonah and the whale. Bex Scott: [00:10:37] So going into more of the research, I discovered as well that people have local chapters of salt and Pepper shaker clubs. I didn't know that, but it makes sense. There are clubs for Pyrex collectors, Facebook groups and pages, many of which I'm a part of. So it would make sense that these salt and pepper shaker lovers would come together and sell and swap stories about their salt and pepper shakers. So after digging into some of this research about salt and pepper shakers and finding out that there was a salt and pepper shaker museum, I looked into this article by the Smithsonian magazine by Derek Workman, and it goes over this family's 80,000 shakers worth of salt and pepper shakers. So they have 40,000 pairs of shakers. They are called the Ludden family. And they have enough shakers to fill two museums. So it's Andrea, her son Alex, and her daughter, and they are in Gatlinburg, Tennessee, with all of their salt and pepper shakers. So andrea said she started completely by chance when she bought a pepper mill at a garage sale in the mid 1980s. I'm sure that most of the collectors out there listening can totally relate to this. You find one item at a garage sale and it takes you down a spiral of collecting. I know that that's how things usually start for me with my addictive collecting personality. That's how my Pyrex started with finding it in my grandparents garage. So Andrea says that she had this pepper mill. It didn't work, so she bought a couple more, and she used to stand them on the window ledge of her kitchen, and her neighbors thought she was building a collection. Bex Scott: [00:12:32] She said nothing could have been further from her mind, but her neighbors started to bring new ones over, and eventually she had 14,000 on shelves all over her house, even in her bedrooms. And her husband Rolf told her that she needed somewhere else to put these or they're going to get divorced. So that's when they decided to create this museum. So you can wander around the museum. It says there's fat chefs, ruby red tomatoes, guardsmen in bearskins, Santas, feet sticking from a chimney, pistols and potatoes, a copy of the salt and pepper shaker cufflinks worn by Lady Diana. That is very cool. And Andrea, she was or is an archeologist by training, and when she moved to the States, she couldn't find work in her field. So she turned her attention to social anthropology, and she studied everyday life since the early years through her growing collection of salt and pepper shakers. And she says here in the article, "there's almost nothing you can imagine that hasn't been copied as a salt and pepper shaker. And many of them reflect the designs, the colors and the preoccupations of the period", which is very true. And when you think about it, when you look at a salt and pepper shaker you don't really think that deeply about it, but a lot of these designs were reflections of what was going on in the time. Bex Scott: [00:13:58] So they go into how, in the article, it was because people could travel more freely, either for work or on vacation, that the souvenir industry came about. And salt and pepper shakers were cheap, easy to carry, and colorful, and they made ideal gifts. So among the earliest producers of salt and pepper shakers were the German fine pottery maker Goebel. They introduced its first three sets in 1925, and today its Hummel shakers, introduced in 1935, are highly collectible. And ironically, it was the Great Depression of the 1930s that gave a major boost to the popularity of salt and pepper shakers as a household item and a collectible item, and ceramic producers worldwide were forced to restrict production and concentrate on lower priced items, and this helped because salt and pepper shakers were small, easy to produce, bright and cheery, and really could be bought for a few cents at most local hardware stores. Soon other ceramic companies got into the act, and Japanese firms had a large share of the market from the late 1920s through the 1930s. As well, from the late 1940s through the 50s, and production halted during World War Two. So the shakers they produced in postwar years labeled 'made in occupied Japan' or simply 'occupied Japan' are extremely rare and highly sought after. In the 1950s and 60s, they began producing shakers made from plastic. Plastic was very fragile, so fewer of these examples exist, making them extremely valuable. Which is another good thing to know because I have seen a lot of the plastic shakers around. Bex Scott: [00:15:49] Sometimes they're not in the greatest shape, but knowing this, that they are more rare and collectible, definitely makes that a bit exciting for me to try and find the plastic ones over some of the other ceramic ones that you can find. So they go into how, at first glance, the museum seems bright and happy, if a bit haphazard. The displays are well thought out and organized, especially considered the many models on display. I can't even begin to imagine how hard it would be to categorize and organize that many salt and pepper shakers. And because you can work by style, age, subject matter, color, Andrea says they try to do it in a way that combines all of the elements at the same time. There are hundreds of themes, and in those themes there will be many colors. But her mom has a way of laying out displays that are highly planned so that the colors within a theme are displayed together. For example, she continues, all the greens, yellows and reds of the vegetables are arranged in vertical rows. You get bright color bands, but all the shakers are on the same theme. It's a lot more complicated than it sounds because there are so many. A large number of the shaker sets are humorous. There's an aspirin salt shaker, a martini glass pepper shaker, and when they're all set up, there's sometimes an opportunity to create a visual joke. Andrea says that you see what looks like models of the southwest US Adobe houses of the style found in New Mexico with cactus and cowboys and Indians but behind them are two UFOs that have crashed and two aliens that glow in the dark. Bex Scott: [00:17:33] It's amazing how many of these shakers tell a tale that isn't obvious to everyone. One of her favorites is a chef holding a cat in one hand and a cleaver in the other. I always thought it was just a fun item, says Andrea, but her mom explained that it was very significant to older people who had been through the Depression and major wars. Food was short, but you still had to eat, so if a cat strayed by, it went into the pot and came out as chicken surprise! Oh my. As they continue the tour, they're absorbed by all the weird and wonderful shakers. Coca Cola cans, Dolly Parton's photo on a souvenir from Dollywood, the Smokies most fun place, Mickey and Minnie in chef tucks and aprons, the Beatles with the cropped hair and collarless jacket of the early days, a turquoise TV with Lucie Arnaz and her neighbor Ethel Mertz on the screen, and a sofa with an I Love Lucy heart shaped cushion, alligators with sunshades from Florida, bullfighters and bulls from Spain, kangaroos from Australia, a bobby and double decker bus from London, before and after versions of Mount Saint Helens made from the actual volcanic ash. Very cool. There are also familiar ones, shakers your grandmother used to have, or you saw when you went on vacation somewhere, or you gave as a gift once. Bex Scott: [00:18:48] "People come back over and over again and think that we are adding to the displays," says Andrea, "but we aren't. It's just that they didn't see them the first time around." The museum doesn't display all the shakers it owns, but it does exhibit a few Aunt Jemima and Uncle Tom shakers, the cook and butler stereotypical characters from the 1950s, knowing some people might be offended by the negative portrayal of African Americans. They are part of the history of salt and pepper shakers. We display them, but we do it discreetly, she says. You can't change history by simply pretending it didn't happen or ignore it. So that article, if you want to read more in-depth, Smithsonian Magazine, 'Would You Like Some Salt and Pepper? How About 80,000 Shakers Worth?' by Derek Workman. And diving into the world of salt and pepper shakers has definitely been a fun one. I would love to know your favorite salt and pepper shakers, how many you might have in your collection, where you find most of them. It is a super fun topic, and if you do want to find salt and pepper shakers out there, I would highly suggest looking at Facebook Marketplace. A lot of the Canadian sellers that I know, including myself, we sell them on Whatnot, so find us there and also on eBay. Bex Scott: [00:20:11] They can get a little bit pricey, but I really find that the thrill is in the hunt. So check out garage sales. Even ask your family members. I'm sure your grandparents, your parents might even have some stuffed in their china cabinets that they're not using. It's just fun to see how many were produced, how many different kinds are out there, and just to see the evolution of them over time. And if you are buying them to resell them, it is really important to look for damage on them. They, I've found, are one of the easiest things to chip and to break, even the smallest little bump. They chip quite easily, especially if you have, like the little Lefton bird shakers, looking on the ears of animals and the beaks. And just anywhere where there's a corner that they may have been hit against something, just keep an eye out. But if it's for your own personal collection, then it's a lot easier just to pick them up in any condition that they are. So I'd love to connect. You can find me on Instagram @PyrexWithBex. You can find me on Whatnot. Selling weekly on Fridays at usually around 2 p.m. Mountain Standard, and my username on Whatnot is Pyrex with Bex. I sell a variety of vintage items, including Pyrex, of course, but a lot of smaller items and jewelry as well. So I hope you enjoyed this episode of salt and pepper shakers. And when you're sitting down at dinner tonight, you might think of the shakers on your table in a different light. 

In this hilarious and practical episode of Elevate Your Event, Jeff Porter, CEO of Handbid, is joined by Elise Druckenmiller and the newest Handbid team member, Mikaela Roth, who brings her GenZ flair to the mix. Together, they dive into the power of AI (specifically ChatGPT) and explore how it can take the busywork out of planning auctions. From generating auction item descriptions dripping in GenZ slang to streamlining event spreadsheets, this episode will have you laughing and learning in equal measure.Along the way, the crew discusses auction themes, item bundling, and pro tips for placing the paddle raise at just the right moment to maximize donations. Whether you're an event planner looking to spice things up or just here to learn what “Riz” and “big mood” mean, this episode has something for everyone!TakeawaysAI for Auctions: How ChatGPT can clean up your item spreadsheets, generate starting bids, and even suggest categories.GenZ Slang for Auctions: Transforming item descriptions to be lit with terms like “big mood,” “no cap,” and “flex.”Themes Galore: Brainstorming creative ideas like “Tropical Ties and Tacos” and “Gatsby on the Green” to keep events fresh.Pro Fundraising Tips: Why moving the paddle raise before the live auction could boost engagement and donations.AI Image Creation: Learn how ChatGPT can help generate item images.Listen, rate, and subscribe!Apple PodcastsSpotifyGoogle Podcasts

Join BOP Business Coach Patrice Miles and Heather Hawkins from Van Brunt and Company, as they discuss "Snappy Gifts" on the latest Tuesday Tools On Purpose podcast! Learn how to make a lasting impression with personalized gifts that people actually want! Contact information: Patrice Miles Business Coach, Business On Purpose patrice@mybusinessonpurpose.com Discovery Call: https://bit.ly/patricediscovery Heather Hawkins Van Brunt and Company Are you working IN your business or ON your business? Do you have all of the foundational elements that will liberate you from the business chaos? Take the assessment to find out which areas you can grow and improve on. Take our Healthy Owner Business Assessment HERE➡️ http://bit.ly/healthybusiness1 SIGN UP for our Newsletter HERE ➡️ https://www.boproadmap.com/newsletter For blogs and updates, visit our site HERE ➡️ https://www.mybusinessonpurpose.com/blog/ LISTEN to the Business On Purpose Podcast HERE ➡️ https://podcasts.apple.com/us/podcast/my-business-on-purpose/id969222210 SUBSCRIBE to our YouTube channel HERE ➡️ https://www.youtube.com/channel/UCbPR8lTHY0ay4c0iqncOztg?sub_confirmation=1

Als Desktop-Linux für alle war Ubuntu im Oktober 2004 mit Ubuntu 4.10 mit dem Spitznamen Warty Warthog gestartet. Ubuntu trat als einsteigerfreundliche Linux-Distribution an, als die es sich schnell einen Namen machte. Dafür gab es mehrere Gründe, beispielsweise den Installationsassistenten, der nicht allzu viele Fragen stellt und ein alltagstaugliches Linux-System auf der Festplatte installiert. Ubuntu 4.10 passte zudem auf eine einzige CD und ließ sich so auch leichter verteilen. Von da an erschien zwanzig Jahre lang zweimal im Jahr eine neue Ausgabe und das bis auf eine einzige Ausnahme auch immer recht pünktlich. Und es gibt keinen Grund anzunehmen, dass sich das in nächster Zeit ändern könnte. Im Laufe seiner Entwicklung ging Canonicals Distribution so manches Mal eigene Wege, die sich nicht immer durchsetzen konnten. Die aktuellste Ubuntu-Version ist die im Oktober erschienene Jubiläumsausgabe 24.10 „Oracular Oriole“. In diesem c't uplink skizzieren wir die Entwicklung von Ubuntu mit wichtigen Meilensteinen und ergründen, wo Ubuntu heutzutage erfolgreich ist und wo nicht. Anlässlich des Jubiläums führte c't-Redakteure ein Interview mit Ubuntu-Gründer und -Geldgeber Mark Shuttleworth und befragten diesen zu vergangenen Entwicklungen und Plänen für die Zukunft. Ihre Eindrücke schildern sie ebenfalls in dieser Podcastausgabe. In unserem [WhatsApp-Kanal](https://whatsapp.com/channel/0029VaCUFFEInlqYnQg2lb0h) sortieren Torsten und Jan aus der Chefredaktion das Geschehen in der IT-Welt, fassen das Wichtigste zusammen und werfen einen Blick auf das, was unsere Kollegen gerade so vorbereiten.

In this episode of CORNDOWN, we dive into the curious case of the “normal looking one” and its various twists, while wastedmemory adds humor with making fun and dehydration. Tripping on burgers and Stouffers leads to some unexpected fun, and there's a series of lost and found keys causing confusion. We also explore irrational fears, invalid entries, and acorns without oaks. Snappy bakes gets involved with identity theft and a trick call, while Dwight joins in with a “big number one” and I try a pee-clogged situation. From rewriting SSDs to Monopoly money, this episode covers plenty of odd ground! This show is made possible by donations from listeners like you. If you enjoy what you hear, please consider donating via patreon or paypal! powered by rogueserver.com

Mo is joined by 5kinny000 and Snappy to talk about… Snappy New Job Pot Talk Movie Quotes Pitbulls Stuck in Space Calves Video Games Sports Talk Best TE Ever NFL WNBA Politics First Ladies Student Loans Alcohol Talk Beat Maker Talk Freud  Religion Hell's Angels Colorado Mornings Oral Fixation Top 5 Favorite Docuseries Music Talk and The Future Groceries - Show Links: https://www.patreon.com/apodcastwithmo https://apodcastwithmo.myspreadshop.com/ https://www.youtube.com/@apodcastwithmo Co-Producer Links: https://www.sirnasty74.com/ https://www.flatlinermusic.net/ - Featuring the songs: Its About - Southern Com4rt Pray About It - Sir Nasty Where U At - Sillvz Plotholes - It'sYaBoiH2 My Everything - Nathan Etes Warm - Not Equal To I Get It - A2thaMo --- Support this podcast: https://podcasters.spotify.com/pod/show/apodcastwithmo/support

 “Get on the couch” “Spill the beans… let it all out…tell me about your supply chain problems"*weep *weep“Look, I JUST want to go to SOHO House and drink Negronis and talk about marketing and On Brand and  branding, creative ideas”“I know…I know.“…Go on have a tissue, look, I know, it's tough being knee deep in excel”Dee-lighted to announce a Supply Chain Therapy Sesh with our wonderful sponsor Unleashed. Most founders hate supply chain.Giles Brook says “If you can't hit 45% True Gross Margin… you don't have a challenger brand” Getting all over your supply chain like hot rash claws back margin.Margin C-A-T-A-P-U-L-T-S your brand to INFINITY and BEYOND Josh and Bryony are amazing human beings. They make supply chain fun. It's Short. Snappy. You're going to LOVE this one. Full episode in the comments below 

Mo is joined by 5kinny000, Snappy, Colten with a call-in from It'sYaBoiH2 to talk about… Trump Assassination Skinny's New Truck Snappy Update Colten's New Job College Football 25 Video Games Eminem Talk Food Talk Family Memories Clothes Cost Car Music NBA Talk Cash App Music Talk AI Art The OC Bob Newhart Crowdstrike Issues Tenacious D Canceled Eminem Deep Dive More Music Talk - Show Links: https://www.patreon.com/apodcastwithmo https://apodcastwithmo.myspreadshop.com/ https://www.youtube.com/@apodcastwithmo Co-Producer Links: https://www.sirnasty74.com/ https://www.flatlinermusic.net/ - Featuring the songs: Open Book - Sir Nasty  The Hound - DJ Kawon and Maddog Mcgraw Better Off Without - Blockade Heart of Gold - FPN Norway Bleed in Agony ft Bradster X - Rockey616 Fameless ft MrGoat731, JSYF - ItsYaBoiH2 Truth Flow - A2thaMo --- Support this podcast: https://podcasters.spotify.com/pod/show/apodcastwithmo/support

Welcome to the Retail Media Moguls podcast, hosted by Stuart Adamson and brought to you by Platform 195. Our host Stuart Adamson sits down with Greg Deacon, Vice President of Retail Media, Groups & Business Development at Snappy Shopper, to explore the intersection of quick commerce and retail media in the convenience sector.

In this episode of CORNDOWN, wastedmemory and I tackle a range of bizarre and intense calls. We navigate confrontations, from getting trespassed from McDonald’s to dealing with unexpected orders at a restaurant. There’s a bit of chaos with multiple stolen cars and a hotel makeovers gone awry. Snappy bakes joins us for a naked drawing session and SPLink helps with a neighbor trash issue. We also dive into some peculiar situations like soup sandwiches and the missing dollar riddle, all while handling fights and gluing doors shut. Get ready for a mix of high tension and oddball moments. This show is made possible by donations from listeners like you. If you enjoy what you hear, please consider donating at https://www.patreon.com/dragonmere ! powered by rogueserver.com

Mo is joined by 5kinny000 with a pop in from Snappy and a Call-in from Bradster X to talk about… Intro Snappy Update NCAA Football WNBA & NBA Heat Waves Global Warming Opium Wars Crying AI Translated Speeches WWII Bird Flu Catholics Church Camp Kanye's New Lady Video Games Dave the Diver It Takes Two Elden Ring Beats and Recording Dancing Fast Food - Show Links: https://www.patreon.com/apodcastwithmo https://apodcastwithmo.myspreadshop.com/ https://www.youtube.com/@apodcastwithmo Co-Producer Links: https://www.sirnasty74.com/ https://www.flatlinermusic.net/ - Featuring the songs: Just Hit Play - Sir Nasty Cold Heir - ItsYaBoiH2 Off My Mind - Dom & Jesse Simulations - ThruItAll You, Not Me - Ivy Ash Spaz Out - Bradster X Got Damn - Southern Com4rt & A2thaMo --- Support this podcast: https://podcasters.spotify.com/pod/show/apodcastwithmo/support

Editor's note: One of the top reasons we have hundreds of companies and thousands of AI Engineers joining the World's Fair next week is, apart from discussing technology and being present for the big launches planned, to hire and be hired! Listeners loved our previous Elicit episode and were so glad to welcome 2 more members of Elicit back for a guest post (and bonus podcast) on how they think through hiring. Don't miss their AI engineer job description, and template which you can use to create your own hiring plan! How to Hire AI EngineersJames Brady, Head of Engineering @ Elicit (ex Spring, Square, Trigger.io, IBM)Adam Wiggins, Internal Journalist @ Elicit (Cofounder Ink & Switch and Heroku)If you're leading a team that uses AI in your product in some way, you probably need to hire AI engineers. As defined in this article, that's someone with conventional engineering skills in addition to knowledge of language models and prompt engineering, without being a full-fledged Machine Learning expert.But how do you hire someone with this skillset? At Elicit we've been applying machine learning to reasoning tools since 2018, and our technical team is a mix of ML experts and what we can now call AI engineers. This article will cover our process from job description through interviewing. (You can also flip the perspectives here and use it just as easily for how to get hired as an AI engineer!)My own journeyBefore getting into the brass tacks, I want to share my journey to becoming an AI engineer.Up until a few years ago, I was happily working my job as an engineering manager of a big team at a late-stage startup. Like many, I was tracking the rapid increase in AI capabilities stemming from the deep learning revolution, but it was the release of GPT-3 in 2020 which was the watershed moment. At the time, we were all blown away by how the model could string together coherent sentences on demand. (Oh how far we've come since then!)I'd been a professional software engineer for nearly 15 years—enough to have experienced one or two technology cycles—but I could see this was something categorically new. I found this simultaneously exciting and somewhat disconcerting. I knew I wanted to dive into this world, but it seemed like the only path was going back to school for a master's degree in Machine Learning. I started talking with my boss about options for taking a sabbatical or doing a part-time distance learning degree.In 2021, I instead decided to launch a startup focused on productizing new research ideas on ML interpretability. It was through that process that I reached out to Andreas—a leading ML researcher and founder of Elicit—to see if he would be an advisor. Over the next few months, I learned more about Elicit: that they were trying to apply these fascinating technologies to the real-world problems of science, and with a business model that aligned it with safety goals. I realized that I was way more excited about Elicit than I was about my own startup ideas, and wrote about my motivations at the time.Three years later, it's clear this was a seismic shift in my career on the scale of when I chose to leave my comfy engineering job at IBM to go through the Y Combinator program back in 2008. Working with this new breed of technology has been more intellectually stimulating, challenging, and rewarding than I could have imagined.Deep ML expertise not requiredIt's important to note that AI engineers are not ML experts, nor is that their best contribution to a tech team.In our article Living documents as an AI UX pattern, we wrote:It's easy to think that AI advancements are all about training and applying new models, and certainly this is a huge part of our work in the ML team at Elicit. But those of us working in the UX part of the team believe that we have a big contribution to make in how AI is applied to end-user problems.We think of LLMs as a new medium to work with, one that we've barely begun to grasp the contours of. New computing mediums like GUIs in the 1980s, web/cloud in the 90s and 2000s, and multitouch smartphones in the 2000s/2010s opened a whole new era of engineering and design practices. So too will LLMs open new frontiers for our work in the coming decade.To compare to the early era of mobile development: great iOS developers didn't require a detailed understanding of the physics of capacitive touchscreens. But they did need to know the capabilities and limitations of a multi-touch screen, the constrained CPU and storage available, the context in which the user is using it (very different from a webpage or desktop computer), etc.In the same way, an AI engineer needs to work with LLMs as a medium that is fundamentally different from other compute mediums. That means an interest in the ML side of things, whether through their own self-study, tinkering with prompts and model fine-tuning, or following along in #llm-paper-club. But this understanding is so that they can work with the medium effectively versus, say, spending their days training new models.Language models as a chaotic mediumSo if we're not expecting deep ML expertise from AI engineers, what are we expecting? This brings us to what makes LLMs different.We'll assume already that our ideal candidate is already inspired by, and full of ideas about, all the new capabilities AI can bring to software products. But the flip side is all the things that make this new medium difficult to work with. LLM calls are annoying due to high latency (measured in tens of seconds sometimes, rather than milliseconds), extreme variance on latency, high error rates even under normal operation. Not to mention getting extremely different answers to the same prompt provided to the same model on two subsequent calls!The net effect is that an AI engineer, even working at the application development level, needs to have a skillset comparable to distributed systems engineering. Handling errors, retries, asynchronous calls, streaming responses, parallelizing and recombining model calls, the halting problem, and fallbacks are just some of the day-in-the-life of an AI engineer. Chaos engineering gets new life in the era of AI.Skills and qualities in candidatesLet's put together what we don't need (deep ML expertise) with what we do (work with capabilities and limitations of the medium). Thus we start to see what Elicit looks for in AI engineers:* Conventional software engineering skills. Especially back-end engineering on complex, data-intensive applications.* Professional, real-world experience with applications at scale.* Deep, hands-on experience across a few back-end web frameworks.* Light devops and an understanding of infrastructure best practices.* Queues, message buses, event-driven and serverless architectures, … there's no single “correct” approach, but having a deep toolbox to draw from is very important.* A genuine curiosity and enthusiasm for the capabilities of language models.* One or more serious projects (side projects are fine) of using them in interesting ways on a unique domain.* …ideally with some level of factored cognition, e.g. breaking the problem down into chunks, making thoughtful decisions about which things to push to the language model and which stay within the realm of conventional heuristics and compute capabilities.* Personal studying with resources like Elicit's ML reading list. Part of the role is collaborating with the ML engineers and researchers on our team. To do so, the candidate needs to “speak their language” somewhat, just as a mobile engineer needs some familiarity with backends in order to collaborate effectively on API creation with backend engineers.* An understanding of the challenges that come along with working with large models (high latency, variance, etc.) leading to a defensive, fault-first mindset.* Careful and principled handling of error cases, asynchronous code (and ability to reason about and debug it), streaming data, caching, logging and analytics for understanding behavior in production.* This is a similar mindset that one can develop working on conventional apps which are complex, data-intensive, or large-scale apps. The difference is that an AI engineer will need this mindset even when working on relatively small scales!On net, a great AI engineer will combine two seemingly contrasting perspectives: knowledge of, and a sense of wonder for, the capabilities of modern ML models; but also the understanding that this is a difficult and imperfect foundation, and the willingness to build resilient and performant systems on top of it.Here's the resulting AI engineer job description for Elicit. And here's a template that you can borrow from for writing your own JD.Hiring processOnce you know what you're looking for in an AI engineer, the process is not too different from other technical roles. Here's how we do it, broken down into two stages: sourcing and interviewing.SourcingWe're primarily looking for people with (1) a familiarity with and interest in ML, and (2) proven experience building complex systems using web technologies. The former is important for culture fit and as an indication that the candidate will be able to do some light prompt engineering as part of their role. The latter is important because language model APIs are built on top of web standards and—as noted above—aren't always the easiest tools to work with.Only a handful of people have built complex ML-first apps, but fortunately the two qualities listed above are relatively independent. Perhaps they've proven (2) through their professional experience and have some side projects which demonstrate (1).Talking of side projects, evidence of creative and original prototypes is a huge plus as we're evaluating candidates. We've barely scratched the surface of what's possible to build with LLMs—even the current generation of models—so candidates who have been willing to dive into crazy “I wonder if it's possible to…” ideas have a huge advantage.InterviewingThe hard skills we spend most of our time evaluating during our interview process are in the “building complex systems using web technologies” side of things. We will be checking that the candidate is familiar with asynchronous programming, defensive coding, distributed systems concepts and tools, and display an ability to think about scaling and performance. They needn't have 10+ years of experience doing this stuff: even junior candidates can display an aptitude and thirst for learning which gives us confidence they'll be successful tackling the difficult technical challenges we'll put in front of them.One anti-pattern—something which makes my heart sink when I hear it from candidates—is that they have no familiarity with ML, but claim that they're excited to learn about it. The amount of free and easily-accessible resources available is incredible, so a motivated candidate should have already dived into self-study.Putting all that together, here's the interview process that we follow for AI engineer candidates:* 30-minute introductory conversation. Non-technical, explaining the interview process, answering questions, understanding the candidate's career path and goals.* 60-minute technical interview. This is a coding exercise, where we play product manager and the candidate is making changes to a little web app. Here are some examples of topics we might hit upon through that exercise:* Update API endpoints to include extra metadata. Think about appropriate data types. Stub out frontend code to accept the new data.* Convert a synchronous REST API to an asynchronous streaming endpoint.* Cancellation of asynchronous work when a user closes their tab.* Choose an appropriate data structure to represent the pending, active, and completed ML work which is required to service a user request.* 60–90 minute non-technical interview. Walk through the candidate's professional experience, identifying high and low points, getting a grasp of what kinds of challenges and environments they thrive in.* On-site interviews. Half a day in our office in Oakland, meeting as much of the team as possible: more technical and non-technical conversations.The frontier is wide openAlthough Elicit is perhaps further along than other companies on AI engineering, we also acknowledge that this is a brand-new field whose shape and qualities are only just now starting to form. We're looking forward to hearing how other companies do this and being part of the conversation as the role evolves.We're excited for the AI Engineer World's Fair as another next step for this emerging subfield. And of course, check out the Elicit careers page if you're interested in joining our team.Podcast versionTimestamps* [00:00:24] Intros* [00:05:25] Defining the Hiring Process* [00:08:42] Defensive AI Engineering as a chaotic medium* [00:10:26] Tech Choices for Defensive AI Engineering* [00:14:04] How do you Interview for Defensive AI Engineering* [00:19:25] Does Model Shadowing Work?* [00:22:29] Is it too early to standardize Tech stacks?* [00:32:02] Capabilities: Offensive AI Engineering* [00:37:24] AI Engineering Required Knowledge* [00:40:13] ML First Mindset* [00:45:13] AI Engineers and Creativity* [00:47:51] Inside of Me There Are Two Wolves* [00:49:58] Sourcing AI Engineers* [00:58:45] Parting ThoughtsTranscript[00:00:00] swyx: Okay, so welcome to the Latent Space Podcast. This is another remote episode that we're recording. This is the first one that we're doing around a guest post. And I'm very honored to have two of the authors of the post with me, James and Adam from Elicit. Welcome, James. Welcome, Adam.[00:00:22] James Brady: Thank you. Great to be here.[00:00:23] Hey there.[00:00:24] Intros[00:00:24] swyx: Okay, so I think I will do this kind of in order. I think James, you're, you're sort of the primary author. So James, you are head of engineering at Elicit. You also, We're VP Eng at Teespring and Spring as well. And you also , you have a long history in sort of engineering. How did you, , find your way into something like Elicit where, , it's, you, you are basically traditional sort of VP Eng, VP technology type person moving into a more of an AI role.[00:00:53] James Brady: Yeah, that's right. It definitely was something of a Sideways move if not a left turn. So the story there was I'd been doing, as you said, VP technology, CTO type stuff for around about 15 years or so, and Notice that there was this crazy explosion of capability and interesting stuff happening within AI and ML and language models, that kind of thing.[00:01:16] I guess this was in 2019 or so, and decided that I needed to get involved. , this is a kind of generational shift. And Spent maybe a year or so trying to get up to speed on the state of the art, reading papers, reading books, practicing things, that kind of stuff. Was going to found a startup actually in in the space of interpretability and transparency, and through that met Andreas, who has obviously been on the, on the podcast before asked him to be an advisor for my startup, and he countered with, maybe you'd like to come and run the engineering team at Elicit, which it turns out was a much better idea.[00:01:48] And yeah, I kind of quickly changed in that direction. So I think some of the stuff that we're going to be talking about today is how actually a lot of the work when you're building applications with AI and ML looks and smells and feels much more like conventional software engineering with a few key differences rather than really deep ML stuff.[00:02:07] And I think that's one of the reasons why I was able to transfer skills over from one place to the other.[00:02:12] swyx: Yeah, I[00:02:12] James Brady: definitely[00:02:12] swyx: agree with that. I, I do often say that I think AI engineering is about 90 percent software engineering with like the, the 10 percent of like really strong really differentiated AI engineering.[00:02:22] And that might, that obviously that number might change over time. I want to also welcome Adam onto my podcast because you welcomed me onto your podcast two years ago.[00:02:31] Adam Wiggins: Yeah, that was a wonderful episode.[00:02:32] swyx: That was, that was a fun episode. You famously founded Heroku. You just wrapped up a few years working on Muse.[00:02:38] And now you've described yourself as a journalist, internal journalist working on Elicit.[00:02:43] Adam Wiggins: Yeah, well I'm kind of a little bit in a wandering phase here and trying to take this time in between ventures to see what's out there in the world and some of my wandering took me to the Elicit team. And found that they were some of the folks who were doing the most interesting, really deep work in terms of taking the capabilities of language models and applying them to what I feel like are really important problems.[00:03:08] So in this case, science and literature search and, and, and that sort of thing. It fits into my general interest in tools and productivity software. I, I think of it as a tool for thought in many ways, but a tool for science, obviously, if we can accelerate that discovery of new medicines and things like that, that's, that's just so powerful.[00:03:24] But to me, it's a. It's kind of also an opportunity to learn at the feet of some real masters in this space, people who have been working on it since it was, before it was cool, if you want to put it that way. So for me, the last couple of months have been this crash course, and why I sometimes describe myself as an internal journalist is I'm helping to write some, some posts, including Supporting James in this article here we're doing for latent space where I'm just bringing my writing skill and that sort of thing to bear on their very deep domain expertise around language models and applying them to the real world and kind of surface that in a way that's I don't know, accessible, legible, that, that sort of thing.[00:04:03] And so, and the great benefit to me is I get to learn this stuff in a way that I don't think I would, or I haven't, just kind of tinkering with my own side projects.[00:04:12] swyx: I forgot to mention that you also run Ink and Switch, which is one of the leading research labs, in my mind, of the tools for thought productivity space, , whatever people mentioned there, or maybe future of programming even, a little bit of that.[00:04:24] As well. I think you guys definitely started the local first wave. I think there was just the first conference that you guys held. I don't know if you were personally involved.[00:04:31] Adam Wiggins: Yeah, I was one of the co organizers along with a few other folks for, yeah, called Local First Conf here in Berlin.[00:04:36] Huge success from my, my point of view. Local first, obviously, a whole other topic we can talk about on another day. I think there actually is a lot more what would you call it , handshake emoji between kind of language models and the local first data model. And that was part of the topic of the conference here, but yeah, topic for another day.[00:04:55] swyx: Not necessarily. I mean , I, I selected as one of my keynotes, Justine Tunney, working at LlamaFall in Mozilla, because I think there's a lot of people interested in that stuff. But we can, we can focus on the headline topic. And just to not bury the lead, which is we're talking about hire, how to hire AI engineers, this is something that I've been looking for a credible source on for months.[00:05:14] People keep asking me for my opinions. I don't feel qualified to give an opinion and it's not like I have. So that's kind of defined hiring process that I'm super happy with, even though I've worked with a number of AI engineers.[00:05:25] Defining the Hiring Process[00:05:25] swyx: I'll just leave it open to you, James. How was your process of defining your hiring, hiring roles?[00:05:31] James Brady: Yeah. So I think the first thing to say is that we've effectively been hiring for this kind of a role since before you, before you coined the term and tried to kind of build this understanding of what it was.[00:05:42] So, which is not a bad thing. Like it's, it was a, it was a good thing. A concept, a concept that was coming to the fore and effectively needed a name, which is which is what you did. So the reason I mentioned that is I think it was something that we kind of backed into, if you will. We didn't sit down and come up with a brand new role from, from scratch of this is a completely novel set of responsibilities and skills that this person would need.[00:06:06] However, it is a A kind of particular blend of different skills and attitudes and and curiosities interests, which I think makes sense to kind of bundle together. So in the, in the post, the three things that we say are most important for a highly effective AI engineer are first of all, conventional software engineering skills, which is Kind of a given, but definitely worth mentioning.[00:06:30] The second thing is a curiosity and enthusiasm for machine learning and maybe in particular language models. That's certainly true in our case. And then the third thing is to do with basically a fault first mindset, being able to build systems that can handle things going wrong in, in, in some sense.[00:06:49] And yeah, the I think the kind of middle point, the curiosity about ML and language models is probably fairly self evident. They're going to be working with, and prompting, and dealing with the responses from these models, so that's clearly relevant. The last point, though, maybe takes the most explaining.[00:07:07] To do with this fault first mindset and the ability to, to build resilient systems. The reason that is, is so important is because compared to normal APIs, where normal, think of something like a Stripe API or a search API or something like this. The latency when you're working with language models is, is wild, like you can get 10x variation.[00:07:32] I mean, I was looking at the stats before, actually, before, before the podcast. We do often, normally, in fact, see a 10x variation in the P90 latency over the course of, Half an hour, an hour when we're prompting these models, which is way higher than if you're working with a, more kind of conventional conventionally backed API.[00:07:49] And the responses that you get, the actual content and the responses are naturally unpredictable as well. They come back with different formats. Maybe you're expecting JSON. It's not quite JSON. You have to handle this stuff. And also the, the semantics of the messages are unpredictable too, which is, which is a good thing.[00:08:08] Like this is one of the things that you're looking for from these language models, but it all adds up to needing to. Build a resilient, reliable, solid feeling system on top of this fundamentally, well, certainly currently fundamentally shaky foundation. The models do not behave in the way that you would like them to.[00:08:28] And yeah, the ability to structure the code around them such that it does give the user this warm, reassuring, Snappy, solid feeling is is really what we're driving for there.[00:08:42] Defensive AI Engineering as a chaotic medium[00:08:42] Adam Wiggins: What really struck me as we, we dug in on the content for this article was that third point there. The, the language models is this kind of chaotic medium, this, this dragon, this wild horse you're, you're, you're riding and trying to guide in the direction that is going to be useful and reliable to users, because I think.[00:08:58] So much of software engineering is about making things not only high performance and snappy, but really just making it stable, reliable, predictable, which is literally the opposite of what you get from from the language models. And yet, yeah, the output is so useful, and indeed, some of their Creativity, if you want to call it that, which is, is precisely their value.[00:09:19] And so you need to work with this medium. And I guess the nuanced or the thing that came out of Elissa's experience that I thought was so interesting is quite a lot of working with that is things that come from distributed systems engineering. But you have really the AI engineers as we're defining them or, or labeling them on the illicit team is people who are really application developers.[00:09:39] You're building things for end users. You're thinking about, okay, I need to populate this interface with some response to user input. That's useful to the tasks they're trying to do, but you have this. This is the thing, this medium that you're working with that in some ways you need to apply some of this chaos engineering, distributed systems engineering, which typically those people with those engineering skills are not kind of the application level developers with the product mindset or whatever, they're more deep in the guts of a, of a system.[00:10:07] And so it's, those, those skills and, and knowledge do exist throughout the engineering discipline, but sort of putting them together into one person that is That feels like sort of a unique thing and working with the folks on the Elicit team who have that skills I'm quite struck by that unique that unique blend.[00:10:23] I haven't really seen that before in my 30 year career in technology.[00:10:26] Tech Choices for Defensive AI Engineering[00:10:26] swyx: Yeah, that's a Fascinating I like the reference to chaos engineering. I have some appreciation, I think when you had me on your podcast, I was still working at Temporal and that was like a nice Framework, if you live within Temporal's boundaries, you can pretend that all those faults don't exist, and you can, you can code in a sort of very fault tolerant way.[00:10:47] What is, what is you guys solutions around this, actually? Like, I think you're, you're emphasizing having the mindset, but maybe naming some technologies would help? Not saying that you have to adopt these technologies, but they're just, they're just quick vectors into what you're talking about when you're, when you're talking about distributed systems.[00:11:03] Like, that's such a big, chunky word, , like are we talking, are Kubernetes or, and I suspect we're not, , like we're, we're talking something else now.[00:11:10] James Brady: Yeah, that's right. It's more at the application level rather than at the infrastructure level, at least, at least the way that it works for us.[00:11:17] So there's nothing kind of radically novel here. It is more a careful application of existing concepts. So the kinds of tools that we reach for to handle these kind of slightly chaotic objects that Adam was just talking about, are retries and fallbacks and timeouts and careful error handling. And, yeah, the standard stuff, really.[00:11:39] There's also a great degree of dependence. We rely heavily on parallelization because, , these language models are not innately very snappy, and , there's just a lot of I. O. going back and forth. So All these things I'm talking about when I was in my earlier stages of a career, these are kind of the things that are the difficult parts that most senior software engineers will be better at.[00:12:01] It is careful error handling, and concurrency, and fallbacks, and distributed systems, and, , eventual consistency, and all this kind of stuff and As Adam was saying, the kind of person that is deep in the guts of some kind of distributed systems, a really high, high scale backend kind of a problem would probably naturally have these kinds of skills.[00:12:21] But you'll find them on, on day one, if you're building a, , an ML powered app, even if it's not got massive scale. I think one one thing that I would mention that we do do yeah, maybe, maybe two related things, actually. The first is we're big fans of strong typing. We share the types all the way from the Backend Python code all the way to the to the front end in TypeScript and find that is I mean We'd probably do this anyway But it really helps one reason around the shapes of the data which can going to be going back and forth and that's really important When you can't rely upon You you're going to have to coerce the data that you get back from the ML if you want if you want for it to be structured basically speaking and The second thing which is related is we use checked exceptions inside our Python code base, which means that we can use the type system to make sure we are handling, properly handling, all of the, the various things that could be going wrong, all the different exceptions that could be getting raised.[00:13:16] So, checked exceptions are not, not really particularly popular. Actually there's not many people that are big fans of them. For our particular use case, to really make sure that we've not just forgotten to handle, , This particular type of error we have found them useful to to, to force us to think about all the different edge cases that can come up.[00:13:32] swyx: Fascinating. How just a quick note of technology. How do you share types from Python to TypeScript? Do you, do you use GraphQL? Do you use something[00:13:39] James Brady: else? We don't, we don't use GraphQL. Yeah. So we've got the We've got the types defined in Python, that's the source of truth. And we go from the OpenAPI spec, and there's a, there's a tool that you work and use to generate types dynamically, like TypeScript types from those OpenAPI definitions.[00:13:57] swyx: Okay, excellent. Okay, cool. Sorry, sorry for diving into that rabbit hole a little bit. I always like to spell out technologies for people to dig their teeth into.[00:14:04] How do you Interview for Defensive AI Engineering[00:14:04] swyx: One thing I'll, one thing I'll mention quickly is that a lot of the stuff that you mentioned is typically not part of the normal interview loop.[00:14:10] It's actually really hard to interview for because this is the stuff that you polish out in, as you go into production, the coding interviews are typically about the happy path. How do we do that? How do we, how do we design, how do you look for a defensive fault first mindset?[00:14:24] Because you can defensive code all day long and not add functionality. to your to your application.[00:14:29] James Brady: Yeah, it's a great question and I think that's exactly true. Normally the interview is about the happy path and then there's maybe a box checking exercise at the end of the candidate says of course in reality I would handle the edge cases or something like this and that unfortunately isn't isn't quite good enough when when the happy path is is very very narrow and yeah there's lots of weirdness on either side so basically speaking, it's just a case of, of foregrounding those kind of concerns through the interview process.[00:14:58] It's, there's, there's no magic to it. We, we talk about this in the, in the po in the post that we're gonna be putting up on, on Laton space. The, there's two main technical exercises that we do through our interview process for this role. The first is more coding focus, and the second is more system designy.[00:15:16] Yeah. White whiteboarding a potential solution. And in, without giving too much away in the coding exercise. You do need to think about edge cases. You do need to think about errors. The exercise consists of adding features and fixing bugs inside the code base. And in both of those two cases, it does demand, because of the way that we set the application up and the interview up, it does demand that you think about something other than the happy path.[00:15:41] But your thinking is the right prompt of how do we get the candidate thinking outside of the, the kind of normal Sweet spot, smooth smooth, smoothly paved path. In terms of the system design interview, that's a little easier to prompt this kind of fault first mindset because it's very easy in that situation just to say, let's imagine that, , this node dies, how does the app still work?[00:16:03] Let's imagine that this network is, is going super slow. Let's imagine that, I don't know, like you, you run out of, you run out of capacity in, in, in this database that you've sketched out here, how do you handle that, that, that sort of stuff. So. It's, in both cases, they're not firmly anchored to and built specifically around language models and ways language models can go wrong, but we do exercise the same muscles of thinking defensively and yeah, foregrounding the edge cases, basically.[00:16:32] Adam Wiggins: James, earlier there you mentioned retries. And this is something that I think I've seen some interesting debates internally about things regarding, first of all, retries are, can be costly, right? In general, this medium, in addition to having this incredibly high variance and response rate, and, , being non deterministic, is actually quite expensive.[00:16:50] And so, in many cases, doing a retry when you get a fail does make sense, but actually that has an impact on cost. And so there is Some sense to which, at least I've seen the AI engineers on our team, worry about that. They worry about, okay, how do we give the best user experience, but balance that against what the infrastructure is going to, , is going to cost our company, which I think is again, an interesting mix of, yeah, again, it's a little bit the distributed system mindset, but it's also a product perspective and you're thinking about the end user experience, but also the.[00:17:22] The bottom line for the business, you're bringing together a lot of a lot of qualities there. And there's also the fallback case, which is kind of, kind of a related or adjacent one. I think there was also a discussion on that internally where, I think it maybe was search, there was something recently where there was one of the frontline search providers was having some, yeah, slowness and outages, and essentially then we had a fallback, but essentially that gave people for a while, especially new users that come in that don't the difference, they're getting a They're getting worse results for their search.[00:17:52] And so then you have this debate about, okay, there's sort of what is correct to do from an engineering perspective, but then there's also what actually is the best result for the user. Is giving them a kind of a worse answer to their search result better, or is it better to kind of give them an error and be like, yeah, sorry, it's not working right at the moment, try again.[00:18:12] Later, both are obviously non optimal, but but this is the kind of thing I think that that you run into or, or the kind of thing we need to grapple with a lot more than you would other kinds of, of mediums.[00:18:24] James Brady: Yeah, that's a really good example. I think it brings to the fore the two different things that you could be optimizing for of uptime and response at all costs on one end of the spectrum and then effectively fragility, but kind of, if you get a response, it's the best response we can come up with at the other end of the spectrum.[00:18:43] And where you want to land there kind of depends on, well, it certainly depends on the app, obviously depends on the user. I think it depends on the, feature within the app as well. So in the search case that you, that you mentioned there, in retrospect, we probably didn't want to have the fallback. And we've actually just recently on Monday, changed that to Show an error message rather than giving people a kind of degraded experience in other situations We could use for example a large language model from a large language model from provider B rather than provider A and Get something which is within the A few percentage points performance, and that's just a really different situation.[00:19:21] So yeah, like any interesting question, the answer is, it depends.[00:19:25] Does Model Shadowing Work?[00:19:25] swyx: I do hear a lot of people suggesting I, let's call this model shadowing as a defensive technique, which is, if OpenAI happens to be down, which, , happens more often than people think then you fall back to anthropic or something.[00:19:38] How realistic is that, right? Like you, don't you have to develop completely different prompts for different models and won't the, won't the performance of your application suffer from whatever reason, right? Like it may be caused differently or it's not maintained in the same way. I, I think that people raise this idea of fallbacks to models, but I don't think it's, I don't, I don't see it practiced very much.[00:20:02] James Brady: Yeah, it is, you, you definitely need to have a different prompt if you want to stay within a few percentage points degradation Like I, like I said before, and that certainly comes at a cost, like fallbacks and backups and things like this It's really easy for them to go stale and kind of flake out on you because they're off the beaten track And In our particular case inside of Elicit, we do have fallbacks for a number of kind of crucial functions where it's going to be very obvious if something has gone wrong, but we don't have fallbacks in all cases.[00:20:40] It really depends on a task to task basis throughout the app. So I can't give you a kind of a, a single kind of simple rule of thumb for, in this case, do this. And in the other, do that. But yeah, we've it's a little bit easier now that the APIs between the anthropic models and opening are more similar than they used to be.[00:20:59] So we don't have two totally separate code paths with different protocols, like wire protocols to, to speak, which makes things easier, but you're right. You do need to have different prompts if you want to, have similar performance across the providers.[00:21:12] Adam Wiggins: I'll also note, just observing again as a relative newcomer here, I was surprised, impressed, not sure what the word is for it, at the blend of different backends that the team is using.[00:21:24] And so there's many The product presents as kind of one single interface, but there's actually several dozen kind of main paths. There's like, for example, the search versus a data extraction of a certain type, versus chat with papers, versus And each one of these, , the team has worked very hard to pick the right Model for the job and craft the prompt there, but also is constantly testing new ones.[00:21:48] So a new one comes out from either, from the big providers or in some cases, Our own models that are , running on, on essentially our own infrastructure. And sometimes that's more about cost or performance, but the point is kind of switching very fluidly between them and, and very quickly because this field is moving so fast and there's new ones to choose from all the time is like part of the day to day, I would say.[00:22:11] So it isn't more of a like, there's a main one, it's been kind of the same for a year, there's a fallback, but it's got cobwebs on it. It's more like which model and which prompt is changing weekly. And so I think it's quite, quite reasonable to to, to, to have a fallback that you can expect might work.[00:22:29] Is it too early to standardize Tech stacks?[00:22:29] swyx: I'm curious because you guys have had experience working at both, , Elicit, which is a smaller operation and, and larger companies. A lot of companies are looking at this with a certain amount of trepidation as, as, , it's very chaotic. When you have, when you have , one engineering team that, that, knows everyone else's names and like, , they, they, they, they meet constantly in Slack and knows what's going on.[00:22:50] It's easier to, to sync on technology choices. When you have a hundred teams, all shipping AI products and all making their own independent tech choices. It can be, it can be very hard to control. One solution I'm hearing from like the sales forces of the worlds and Walmarts of the world is that they are creating their own AI gateway, right?[00:23:05] Internal AI gateway. This is the one model hub that controls all the things and has our standards. Is that a feasible thing? Is that something that you would want? Is that something you have and you're working towards? What are your thoughts on this stuff? Like, Centralization of control or like an AI platform internally.[00:23:22] James Brady: Certainly for larger organizations and organizations that are doing things which maybe are running into HIPAA compliance or other, um, legislative tools like that. It could make a lot of sense. Yeah. I think for the TLDR for something like Elicit is we are small enough, as you indicated, and need to have full control over all the levers available and switch between different models and different prompts and whatnot, as Adam was just saying, that that kind of thing wouldn't work for us.[00:23:52] But yeah, I've spoken with and, um, advised a couple of companies that are trying to sell into that kind of a space or at a larger stage, and it does seem to make a lot of sense for them. So, for example, if you're trying to sell If you're looking to sell to a large enterprise and they cannot have any data leaving the EU, then you need to be really careful about someone just accidentally putting in, , the sort of US East 1 GPT 4 endpoints or something like this.[00:24:22] I'd be interested in understanding better what the specific problem is that they're looking to solve with that, whether it is to do with data security or centralization of billing, or if they have a kind of Suite of prompts or something like this that people can choose from so they don't need to reinvent the wheel again and again I wouldn't be able to say without understanding the problems and their proposed solutions , which kind of situations that be better or worse fit for but yeah for illicit where really the The secret sauce, if there is a secret sauce, is which models we're using, how we're using them, how we're combining them, how we're thinking about the user problem, how we're thinking about all these pieces coming together.[00:25:02] You really need to have all of the affordances available to you to be able to experiment with things and iterate rapidly. And generally speaking, whenever you put these kind of layers of abstraction and control and generalization in there, that, that gets in the way. So, so for us, it would not work.[00:25:19] Adam Wiggins: Do you feel like there's always a tendency to want to reach for standardization and abstractions pretty early in a new technology cycle?[00:25:26] There's something comforting there, or you feel like you can see them, or whatever. I feel like there's some of that discussion around lang chain right now. But yeah, this is not only so early, but also moving so fast. , I think it's . I think it's tough to, to ask for that. That's, that's not the, that's not the space we're in, but the, yeah, the larger an organization, the more that's your, your default is to, to, to want to reach for that.[00:25:48] It, it, it's a sort of comfort.[00:25:51] swyx: Yeah, I find it interesting that you would say that , being a founder of Heroku where , you were one of the first platforms as a service that more or less standardized what, , that sort of early developer experience should have looked like.[00:26:04] And I think basically people are feeling the differences between calling various model lab APIs and having an actual AI platform where. , all, all their development needs are thought of for them. , it's, it's very much, and, and I, I defined this in my AI engineer post as well.[00:26:19] Like the model labs just see their job ending at serving models and that's about it. But actually the responsibility of the AI engineer has to fill in a lot of the gaps beyond that. So.[00:26:31] Adam Wiggins: Yeah, that's true. I think, , a huge part of the exercise with Heroku, which It was largely inspired by Rails, which itself was one of the first frameworks to standardize the SQL database.[00:26:42] And people had been building apps like that for many, many years. I had built many apps. I had made my own templates based on that. I think others had done it. And Rails came along at the right moment. We had been doing it long enough that you see the patterns and then you can say look let's let's extract those into a framework that's going to make it not only easier to build for the experts but for people who are relatively new the best practices are encoded into you.[00:27:07] That framework, , Model View Controller, to take one example. But then, yeah, once you see that, and once you experience the power of a framework, and again, it's so comforting, and you can develop faster, and it's easier to onboard new people to it because you have these standards. And this consistency, then folks want that for something new that's evolving.[00:27:29] Now here I'm thinking maybe if you fast forward a little to, for example, when React came on the on the scene, , a decade ago or whatever. And then, okay, we need to do state management. What's that? And then there's, , there's a new library every six months. Okay, this is the one, this is the gold standard.[00:27:42] And then, , six months later, that's deprecated. Because of course, it's evolving, you need to figure it out, like the tacit knowledge and the experience of putting it in practice and seeing what those real What those real needs are are, are critical, and so it's, it is really about finding the right time to say yes, we can generalize, we can make standards and abstractions, whether it's for a company, whether it's for, , a library, an open source library, for a whole class of apps and it, it's very much a, much more of a A judgment call slash just a sense of taste or , experience to be able to say, Yeah, we're at the right point.[00:28:16] We can standardize this. But it's at least my, my very, again, and I'm so new to that, this world compared to you both, but my, my sense is, yeah, still the wild west. That's what makes it so exciting and feels kind of too early for too much. too much in the way of standardized abstractions. Not that it's not interesting to try, but , you can't necessarily get there in the same way Rails did until you've got that decade of experience of whatever building different classes of apps in that, with that technology.[00:28:45] James Brady: Yeah, it's, it's interesting to think about what is going to stay more static and what is expected to change over the coming five years, let's say. Which seems like when I think about it through an ML lens, it's an incredibly long time. And if you just said five years, it doesn't seem, doesn't seem that long.[00:29:01] I think that, that kind of talks to part of the problem here is that things that are moving are moving incredibly quickly. I would expect, this is my, my hot take rather than some kind of official carefully thought out position, but my hot take would be something like the You can, you'll be able to get to good quality apps without doing really careful prompt engineering.[00:29:21] I don't think that prompt engineering is going to be a kind of durable differential skill that people will, will hold. I do think that, The way that you set up the ML problem to kind of ask the right questions, if you see what I mean, rather than the specific phrasing of exactly how you're doing chain of thought or few shot or something in the prompt I think the way that you set it up is, is probably going to be remain to be trickier for longer.[00:29:47] And I think some of the operational challenges that we've been talking about of wild variations in, in, in latency, And handling the, I mean, one way to think about these models is the first lesson that you learn when, when you're an engineer, software engineer, is that you need to sanitize user input, right?[00:30:05] It was, I think it was the top OWASP security threat for a while. Like you, you have to sanitize and validate user input. And we got used to that. And it kind of feels like this is the, The shell around the app and then everything else inside you're kind of in control of and you can grasp and you can debug, etc.[00:30:22] And what we've effectively done is, through some kind of weird rearguard action, we've now got these slightly chaotic things. I think of them more as complex adaptive systems, which , related but a bit different. Definitely have some of the same dynamics. We've, we've injected these into the foundations of the, of the app and you kind of now need to think with this defined defensive mindset downwards as well as upwards if you, if you see what I mean.[00:30:46] So I think it would gonna, it's, I think it will take a while for us to truly wrap our heads around that. And also these kinds of problems where you have to handle things being unreliable and slow sometimes and whatever else, even if it doesn't happen very often, there isn't some kind of industry wide accepted way of handling that at massive scale.[00:31:10] There are definitely patterns and anti patterns and tools and whatnot, but it's not like this is a solved problem. So I would expect that it's not going to go down easily as a, as a solvable problem at the ML scale either.[00:31:23] swyx: Yeah, excellent. I would describe in, in the terminology of the stuff that I've written in the past, I describe this inversion of architecture as sort of LLM at the core versus LLM or code at the core.[00:31:34] We're very used to code at the core. Actually, we can scale that very well. When we build LLM core apps, we have to realize that the, the central part of our app that's orchestrating things is actually prompt, prone to, , prompt injections and non determinism and all that, all that good stuff.[00:31:48] I, I did want to move the conversation a little bit from the sort of defensive side of things to the more offensive or, , the fun side of things, capabilities side of things, because that is the other part. of the job description that we kind of skimmed over. So I'll, I'll repeat what you said earlier.[00:32:02] Capabilities: Offensive AI Engineering[00:32:02] swyx: It's, you want people to have a genuine curiosity and enthusiasm for the capabilities of language models. We just, we're recording this the day after Anthropic just dropped Cloud 3. 5. And I was wondering, , maybe this is a good, good exercise is how do people have Curiosity and enthusiasm for capabilities language models when for example the research paper for cloud 3.[00:32:22] 5 is four pages[00:32:23] James Brady: Maybe that's not a bad thing actually in this particular case So yeah If you really want to know exactly how the sausage was made That hasn't been possible for a few years now in fact for for these new models but from our perspective as when we're building illicit What we primarily care about is what can these models do?[00:32:41] How do they perform on the tasks that we already have set up and the evaluations we have in mind? And then on a slightly more expansive note, what kinds of new capabilities do they seem to have? Can we elicit, no pun intended, from the models? For example, well, there's, there's very obvious ones like multimodality , there wasn't that and then there was that, or it could be something a bit more subtle, like it seems to be getting better at reasoning, or it seems to be getting better at metacognition, or Or it seems to be getting better at marking its own work and giving calibrated confidence estimates, things like this.[00:33:19] So yeah, there's, there's plenty to be excited about there. It's just that yeah, there's rightly or wrongly been this, this, this shift over the last few years to not give all the details. So no, but from application development perspective we, every time there's a new model release, there's a flow of activity in our Slack, and we try to figure out what's going on.[00:33:38] What it can do, what it can't do, run our evaluation frameworks, and yeah, it's always an exciting, happy day.[00:33:44] Adam Wiggins: Yeah, from my perspective, what I'm seeing from the folks on the team is, first of all, just awareness of the new stuff that's coming out, so that's, , an enthusiasm for the space and following along, and then being able to very quickly, partially that's having Slack to do this, but be able to quickly map that to, okay, What does this do for our specific case?[00:34:07] And that, the simple version of that is, let's run the evaluation framework, which Lissa has quite a comprehensive one. I'm actually working on an article on that right now, which I'm very excited about, because it's a very interesting world of things. But basically, you can just try, not just, but try the new model in the evaluations framework.[00:34:27] Run it. It has a whole slew of benchmarks, which includes not just Accuracy and confidence, but also things like performance, cost, and so on. And all of these things may trade off against each other. Maybe it's actually, it's very slightly worse, but it's way faster and way cheaper, so actually this might be a net win, for example.[00:34:46] Or, it's way more accurate. But that comes at its slower and higher cost, and so now you need to think about those trade offs. And so to me, coming back to the qualities of an AI engineer, especially when you're trying to hire for them, It's this, it's, it is very much an application developer in the sense of a product mindset of What are our users or our customers trying to do?[00:35:08] What problem do they need solved? Or what what does our product solve for them? And how does the capabilities of a particular model potentially solve that better for them than what exists today? And by the way, what exists today is becoming an increasingly gigantic cornucopia of things, right? And so, You say, okay, this new model has these capabilities, therefore, , the simple version of that is plug it into our existing evaluations and just look at that and see if it, it seems like it's better for a straight out swap out, but when you talk about, for example, you have multimodal capabilities, and then you say, okay, wait a minute, actually, maybe there's a new feature or a whole new There's a whole bunch of ways we could be using it, not just a simple model swap out, but actually a different thing we could do that we couldn't do before that would have been too slow, or too inaccurate, or something like that, that now we do have the capability to do.[00:35:58] I think of that as being a great thing. I don't even know if I want to call it a skill, maybe it's even like an attitude or a perspective, which is a desire to both be excited about the new technology, , the new models and things as they come along, but also holding in the mind, what does our product do?[00:36:16] Who is our user? And how can we connect the capabilities of this technology to how we're helping people in whatever it is our product does?[00:36:25] James Brady: Yeah, I'm just looking at one of our internal Slack channels where we talk about things like new new model releases and that kind of thing And it is notable looking through these the kind of things that people are excited about and not It's, I don't know the context, the context window is much larger, or it's, look at how many parameters it has, or something like this.[00:36:44] It's always framed in terms of maybe this could be applied to that kind of part of Elicit, or maybe this would open up this new possibility for Elicit. And, as Adam was saying, yeah, I don't think it's really a I don't think it's a novel or separate skill, it's the kind of attitude I would like to have all engineers to have at a company our stage, actually.[00:37:05] And maybe more generally, even, which is not just kind of getting nerd sniped by some kind of technology number, fancy metric or something, but how is this actually going to be applicable to the thing Which matters in the end. How is this going to help users? How is this going to help move things forward strategically?[00:37:23] That kind of, that kind of thing.[00:37:24] AI Engineering Required Knowledge[00:37:24] swyx: Yeah, applying what , I think, is, is, is the key here. Getting hands on as well. I would, I would recommend a few resources for people listening along. The first is Elicit's ML reading list, which I, I found so delightful after talking with Andreas about it.[00:37:38] It looks like that's part of your onboarding. We've actually set up an asynchronous paper club instead of my discord for people following on that reading list. I love that you separate things out into tier one and two and three, and that gives people a factored cognition way of Looking into the, the, the corpus, right?[00:37:55] Like yes, the, the corpus of things to know is growing and the water is slowly rising as far as what a bar for a competent AI engineer is. But I think, , having some structured thought as to what are the big ones that everyone must know I think is, is, is key. It's something I, I haven't really defined for people and I'm, I'm glad that this is actually has something out there that people can refer to.[00:38:15] Yeah, I wouldn't necessarily like make it required for like the job. Interview maybe, but , it'd be interesting to see like, what would be a red flag. If some AI engineer would not know, I don't know what, , I don't know where we would stoop to, to call something required knowledge, , or you're not part of the cool kids club.[00:38:33] But there increasingly is something like that, right? Like, not knowing what context is, is a black mark, in my opinion, right?[00:38:40] I think it, I think it does connect back to what we were saying before of this genuine Curiosity about and that. Well, maybe it's, maybe it's actually that combined with something else, which is really important, which is a self starting bias towards action, kind of a mindset, which again, everybody needs.[00:38:56] Exactly. Yeah. Everyone needs that. So if you put those two together, or if I'm truly curious about this and I'm going to kind of figure out how to make things happen, then you end up with people. Reading, reading lists, reading papers, doing side projects, this kind of, this kind of thing. So it isn't something that we explicitly included.[00:39:14] We don't have a, we don't have an ML focused interview for the AI engineer role at all, actually. It doesn't really seem helpful. The skills which we are checking for, as I mentioned before, this kind of fault first mindset. And conventional software engineering kind of thing. It's, it's 0. 1 and 0.[00:39:32] 3 on the list that, that we talked about. In terms of checking for ML curiosity and there are, how familiar they are with these concepts. That's more through talking interviews and culture fit types of things. We want for them to have a take on what Elisa is doing. doing, certainly as they progress through the interview process.[00:39:50] They don't need to be completely up to date on everything we've ever done on day zero. Although, , that's always nice when it happens. But for them to really engage with it, ask interesting questions, and be kind of bought into our view on how we want ML to proceed. I think that is really important, and that would reveal that they have this kind of this interest, this ML curiosity.[00:40:13] ML First Mindset[00:40:13] swyx: There's a second aspect to that. I don't know if now's the right time to talk about it, which is, I do think that an ML first approach to building software is something of a different mindset. I could, I could describe that a bit now if that, if that seems good, but yeah, I'm a team. Okay. So yeah, I think when I joined Elicit, this was the biggest adjustment that I had to make personally.[00:40:37] So as I said before, I'd been, Effectively building conventional software stuff for 15 years or so, something like this, well, for longer actually, but professionally for like 15 years. And had a lot of pattern matching built into my brain and kind of muscle memory for if you see this kind of problem, then you do that kind of a thing.[00:40:56] And I had to unlearn quite a lot of that when joining Elicit because we truly are ML first and try to use ML to the fullest. And some of the things that that means is, This relinquishing of control almost, at some point you are calling into this fairly opaque black box thing and hoping it does the right thing and dealing with the stuff that it sends back to you.[00:41:17] And that's very different if you're interacting with, again, APIs and databases, that kind of a, that kind of a thing. You can't just keep on debugging. At some point you hit this, this obscure wall. And I think the second, the second part to this is the pattern I was used to is that. The external parts of the app are where most of the messiness is, not necessarily in terms of code, but in terms of degrees of freedom, almost.[00:41:44] If the user can and will do anything at any point, and they'll put all sorts of wonky stuff inside of text inputs, and they'll click buttons you didn't expect them to click, and all this kind of thing. But then by the time you're down into your SQL queries, for example, as long as you've done your input validation, things are pretty pretty well defined.[00:42:01] And that, as we said before, is not really the case. When you're working with language models, there is this kind of intrinsic uncertainty when you get down to the, to the kernel, down to the core. Even, even beyond that, there's all that stuff is somewhat defensive and these are things to be wary of to some degree.[00:42:18] Though the flip side of that, the really kind of positive part of taking an ML first mindset when you're building applications is that you, If you, once you get comfortable taking your hands off the wheel at a certain point and relinquishing control, letting go then really kind of unexpected powerful things can happen if you lean on the, if you lean on the capabilities of the model without trying to overly constrain and slice and dice problems with to the point where you're not really wringing out the most capability from the model that you, that you might.[00:42:47] So, I was trying to think of examples of this earlier, and one that came to mind was we were working really early when just after I joined Elicit, we were working on something where we wanted to generate text and include citations embedded within it. So it'd have a claim, and then a, , square brackets, one, in superscript, something, something like this.[00:43:07] And. Every fiber in my, in my, in my being was screaming that we should have some way of kind of forcing this to happen or Structured output such that we could guarantee that this citation was always going to be present later on that the kind of the indication of a footnote would actually match up with the footnote itself and Kind of went into this symbolic.[00:43:28] I need full control kind of kind of mindset and it was notable that Andreas Who's our CEO, again, has been on the podcast, was was the opposite. He was just kind of, give it a couple of examples and it'll probably be fine. And then we can kind of figure out with a regular expression at the end. And it really did not sit well with me, to be honest.[00:43:46] I was like, but it could say anything. I could say, it could literally say anything. And I don't know about just using a regex to sort of handle this. This is a potent feature of the app. But , this is that was my first kind of, , The starkest introduction to this ML first mindset, I suppose, which Andreas has been cultivating for much longer than me, much longer than most, of yeah, there might be some surprises of stuff you get back from the model, but you can also It's about finding the sweet spot, I suppose, where you don't want to give a completely open ended prompt to the model and expect it to do exactly the right thing.[00:44:25] You can ask it too much and it gets confused and starts repeating itself or goes around in loops or just goes off in a random direction or something like this. But you can also over constrain the model. And not really make the most of the, of the capabilities. And I think that is a mindset adjustment that most people who are coming into AI engineering afresh would need to make of yeah, giving up control and expecting that there's going to be a little bit of kind of extra pain and defensive stuff on the tail end, but the benefits that you get as a, as a result are really striking.[00:44:58] The ML first mindset, I think, is something that I struggle with as well, because the errors, when they do happen, are bad. , they will hallucinate, and your systems will not catch it sometimes if you don't have large enough of a sample set.[00:45:13] AI Engineers and Creativity[00:45:13] swyx: I'll leave it open to you, Adam. What else do you think about when you think about curiosity and exploring capabilities?[00:45:22] Do people are there reliable ways to get people to push themselves? for joining us on Capabilities, because I think a lot of times we have this implicit overconfidence, maybe, of we think we know what it is, what a thing is, when actually we don't, and we need to keep a more open mind, and I think you do a particularly good job of Always having an open mind, and I want to get that out of more engineers that I talk to, but I, I, I, I struggle sometimes.[00:45:45] Adam Wiggins: I suppose being an engineer is, at its heart, this sort of contradiction of, on one hand, yeah,

DM ME "ACADEMY" for details on my Ditch Decade Diets Academy where you get PERSONALIZED coaching to step into your BINGE FREE LIFE!CONNECT WITH LORNA:---> Instagram @lorna_bingeeatingcoach---> Tiktok @lorna_bingeeatingcoach---> DOWNLOAD FREE GUIDE: Top 3 Tips To Stop Binge Eating---> Join my private Facebook group Ditch The Diet & End Binge Eating Support Group. 

Sometimes I'm a little too diligent. Learn how to snooze snappy to bring back happy. #ThePitch #INICIVOX #VirtualMentorship

The fellas cover all things NBA playoffs, talk Caitlyn Clark's WBNA debut, the new TV deal, plus is Tiger Woods too old?

Join the sailing club to contribute financially to James Donald Forbes McCann's journey to boat ownership: https://www.patreon.com/jdfmccannBuy the several books written by James Donald Forbes McCann: https://www.jdfmccann.com/booksAmos Gill is on instagram: https://www.instagram.com/abitofamosgill/?hl=en Hosted on Acast. See acast.com/privacy for more information.

Today, we're swinging by Ridgeland to check out the 2024 Snappy Sync Soiree and Firefly Tours, at the Bill Waller Craft Center, May 16th through the 19th, we'll also check in live with Germaine at the MPB Antique Showcase in Natchez, in addition to hearing her convo with Veteran NPR host Rachel Martin, around the launch of her new podcast "Wild Card with Rachel Martin," then we're off to Starkville for the world's largest wiener dog race, The 2024 Starkville Derby, happening May 4th… and of course, we'll check out what's happening around your neck of the woods! Stay tuned, buckle up and hold on tight for your Next Stop MS!Next Stop, Mississippi is your #1 on-air source for information about upcoming events and attractions across the state. Get to know the real Mississippi! Each week the show's hosts, Germaine Flood and Kamel King, Tourism Development Bureau Manger with Visit Mississippi, highlight well-known and unknown places in Mississippi with the best food, parks, music and arts. They'll not only tell you what's going on in your neck of the woods, but also share the history and people behind the markets, sporting events, concerts, fairs and festivals all over Mississippi. Hear the personal stories and traditions behind that favorite event you attend each year on Next Stop, Mississippi. Check out our Sipp Events calendar to help plan your next trip! Hosted on Acast. See acast.com/privacy for more information.

Mo is joined by 5kinny000 and Snappy to talk about… Snappy Update Family Talk Politics Music Industry Garbage Cans OJs Gloves NBA Talk Caitlyn Clark Sketch Dabs Cookin Talk Kanye Presidential Immunity Video Game Talk FF7 Rebirth Balatro Fallout American Flag Civil War Olympics Traffic Home Talk - Show Links: https://www.patreon.com/apodcastwithmo https://apodcastwithmo.myspreadshop.com/ https://www.youtube.com/@apodcastwithmo Co-Producer Links: https://www.sirnasty74.com/ https://www.flatlinermusic.net/ - Featuring the songs: Intro to ZoZo - Bradster X P.A.B. ft Corri, FPN Norway - Karmaa Purinique - Sir Nasty Letter to My Heart (Chrome Hearts 2) - YNG KURT Trouble ft Karmaa - FPN Norway Loud Pipes - ItsThaFame You Know - PearlZ Journey - Southern Com4rt & A2thaMo --- Support this podcast: https://podcasters.spotify.com/pod/show/apodcastwithmo/support

On this jam-packed episode of Highly Cultured, we start off dissecting the ongoing beef between Drake and Kendrick Lamar. Next, we delve into the resurgence of Bush and what it means to "Make Bush Great Again." NBA Young Boy's recent crash out and DaBaby walking away with $20k are also on the agenda. Plus, we're discussing which celebrities have the biggest veneers in the industry, the NBA playoffs are heating up and we break down the latest matchups and predictions. And in a reflective segment, we'll remember the legacy of O.J. Simpson. Tap in! 

GoVols247's Ben McKee, Wes Rucker and Ryan Callahan discuss the final week of spring football, the Lady Vols getting a new basketball coach, Vols hoopers heading into the portal and much more. To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

In this episode: Alan has the most exotic GPU configuration and needs your help now! Martin has improved his desktop Linux chat quality of life with Telegram GTK4 Color palette, Fractal and Halloy. Mark is migrating data to his new home server in a very snappy way. You can send your feedback via show@linuxmatters.sh or the Contact Form. If you’d like to hang out with other listeners and share your feedback with the community you can join: The Linux Matters Chatters on Telegram. The #linux-matters channel on the Late Night Linux Discord server. If you enjoy the show, please consider supporting us using Patreon or PayPal. For $5 a month on Patreon, you can enjoy an ad-free feed of Linux Matters, or for $10, get access to all the Late Night Linux family of podcasts ad-free.

In this episode: Alan has the most exotic GPU configuration and needs your help now! Martin has improved his desktop Linux chat quality of life with Telegram GTK4 Color palette, Fractal and Halloy. Mark is migrating data to his new home server in a very snappy way. You can send your feedback via show@linuxmatters.sh or the Contact Form. If you’d like to hang out with other listeners and share your feedback with the community you can join: The Linux Matters Chatters on Telegram. The #linux-matters channel on the Late Night Linux Discord server. If you enjoy the show, please consider supporting us using Patreon or PayPal. For $5 a month on Patreon, you can enjoy an ad-free feed of Linux Matters, or for $10, get access to all the Late Night Linux family of podcasts ad-free.

In this episode: Alan has the most exotic GPU configuration and needs your help now! Martin has improved his desktop Linux chat quality of life with Telegram GTK4 Color palette, Fractal and Halloy. Mark is migrating data to his new home server in a very snappy way.   You can send your feedback via show@linuxmatters.sh... Read More

In today's episode Stacey and Rhee talk about the importance of making the transition to dance easy for your new customers. Just as we as consumers love it when it's easy to make a purchase or to sign up for an activity, you want to make sure your process for signing up a new student is as user friendly as possible.  Happy customers stay with us for longer, keep them happy by keeping your systems short and snappy!See omnystudio.com/listener for privacy information.

On Episode 396 we discuss...→ Molly and vehicular manslaughter→ Grunge era, 90s' cool, Bill→ Hermione, torn between amusement and anxiety→ No one cares about Bertha→ The complicated relationship between Molly, George, and Fred→ A plea for Percy→ Ginny is just awesome

Puberty. Periods. Motherhood. Menopause.   Let's be real—women go through a lot of challenging life stages. So why then, do employee benefits often feel like a one-size-fits-all? How can HR find a way to help women throughout all stages of their life, in a way where they feel fully supported? Hebba sits down with Isha Vij, Vice President of Sales at Maven Clinic, a digital health organization focused on women's and family health, to chat about the challenges and solutions surrounding women's health benefits in the workplace. What are the logistical challenges to supporting IVF and fertility treatments? If cost is a major impediment to fertility support, how then, can employers still show support for employees in their family-building journey? Isha and Hebba discuss how current access to reproductive care is often insufficient and explain the massive impact reproductive and family benefits can have on workers' happiness.    And later, Isha explains how Maven Clinic supports women beyond family planning and into menopause. Why is menopause often so poorly understood? With symptoms like insomnia, brain fog, hot flashes, and pain, what can employers do to ensure women receive proper support through this oft-misunderstood life event? She explains why the status quo simply isn't enough and how Maven is seeking to revolutionize things.    The Predictive Index (PI) is an award-winning talent optimization platform that aligns business strategy with people strategy for optimal business results. More than 60 years of proven science, software, and a curriculum of insightful management workshops make PI the solution for any company looking to design great teams and culture, make objective hiring decisions, foster engagement, and inspire greatness in their people anywhere in the world. More than 10,000 clients and 480+ partners use PI—including Nissan, Citizens Bank, Subway, Blue Cross Blue Shield, and Omni Hotels—across 90+ countries. Learn more at https://www.predictiveindex.com/.   Snappy is the award-winning B2B gifting platform that takes all of the guesswork out of gifting and helps companies build cultures of gratitude and appreciation. Send gifts to anyone (employees, customers, co-workers) for any occasion (birthdays, holidays, Employee Appreciation Day - coming up March 1, hint hint!). Choose the perfect gift from Snappy's extensive gifting catalog, create custom swag, or send gift options and let them pick! They put in their own address, and Snappy takes care of the rest. It's fast, easy, and delightful!   Go to https://www.snappy.com/ihateithere to sign up for free and start gifting today.   00:00:25 - Digital Health VP Talks HR Challenges 00:10:13 - Balancing Work and Motherhood Expectations 00:19:03 - Employer Support for Fertility Treatments 00:23:36 - Accessing Fertility Treatments: Major Challenges 00:30:31 - Creating a Consolidated Benefits System 00:34:28 - The Importance of Access to Virtual Healthcare 00:37:59 - Workplace Benefits for Menopausal Women And if you love HR Therapy, sign up to I Hate it Here, the newsletter for jaded, overworked, and emotionally burnt-out HR/People Operations professionals needing a little inspiration. https://workweek.com/discover-newsletters/i-hate-it-here-newsletter/   And if you love the podcast, be sure to check out https://www.youtube.com/@ihateit-here for even more exclusive insider content!   Follow Isha:  LinkedIn: https://www.linkedin.com/in/ishavij/   Follow Hebba:  YouTube: https://www.youtube.com/@ihateit-here/videos LinkedIn: https://linkedin.com/in/hebba-youssef Twitter: https://twitter.com/hebbamyoussef

Mo is joined by 5kinny000 and Snappy to talk about… Parent Visit Check Talk Former Co-Worker: https://www.youtube.com/watch?v=KP0iU4kLvIc Snappy Job Talk Corporations Magnesium Oil Sports Talk Fake NFL NBA Cam Camp Fight Owasso Incident Cooking Talk Pokemon Israel Aaron Bushnell Top 5 Favorite PS2 Games Taylor Swift Door Knobs Possible Future Plans Music Plans Yankee Doodle Lore School Plays Porn - Show Links: https://www.patreon.com/apodcastwithmo https://apodcastwithmo.myspreadshop.com/ https://www.youtube.com/@apodcastwithmo Co-Producer Links: https://www.sirnasty74.com/ https://www.flatlinermusic.net/ - Featuring the songs: I Rap Like Me - Sir Nasty Corgasm ft ItsYaBoiH2, Southern Com4rt - Karmaa Nobody Above Us ft Lowkea - Karmaa Lights Out - Rockey616 Messages - Southern Com4rt Summer Breeze - Ceejay Jonez Be Late ft A2thaMo - Forgotten One ABCS Cypher ft ItsYaBoiH2 - A2thaMo, Bradster X, Southern Com4rt, Ceejay Jonez --- Support this podcast: https://podcasters.spotify.com/pod/show/apodcastwithmo/support

Too often, HR is expected to bet the jack of all trades for a business. But what do you do when it leaves you feeling like a master of none? Hebba sits down with Sarah Rose Hattem, a former HR team of one and currently a Senior HR Consultant for Rippling, to discuss the challenges of being a one-person HR department. How, as a one-person department, can you more effectively communicate your value to leaders who may not view you as a primary function of the business?  Sarah Rose shares why utilizing technology to streamline day-to-day processes is absolutely critical for better time management and reveals the top HR tools she simply couldn't function without. Then, she dives into some of her most time-tested strategies for better task prioritization before unpacking the nuances balancing the needs of the business with the mission-critical tasks that need to be done.     The Predictive Index (PI) is an award-winning talent optimization platform that aligns business strategy with people strategy for optimal business results. More than 60 years of proven science, software, and a curriculum of insightful management workshops make PI the solution for any company looking to design great teams and culture, make objective hiring decisions, foster engagement, and inspire greatness in their people anywhere in the world. More than 10,000 clients and 480+ partners use PI—including Nissan, Citizens Bank, Subway, Blue Cross Blue Shield, and Omni Hotels—across 90+ countries. Learn more at https://www.predictiveindex.com/.   Snappy is the award-winning B2B gifting platform that takes all of the guesswork out of gifting and helps companies build cultures of gratitude and appreciation. Send gifts to anyone (employees, customers, co-workers) for any occasion (birthdays, holidays, Employee Appreciation Day - coming up March 1, hint hint!). Choose the perfect gift from Snappy's extensive gifting catalog, create custom swag, or send gift options and let them pick! They put in their own address, and Snappy takes care of the rest. It's fast, easy, and delightful!   Go to https://www.snappy.com/ihateithere to sign up for free and start gifting today.   00:01:09 - Sarah Rose Hattem's HR Journey 00:03:15 - Balancing HR Responsibilties 00:06:47 - Efficient Time Management Tips for HR Teams 00:14:12 - Balancing HR Functions as a Team of One 00:19:37 - Leveraging Technology for a One-Person HR Team 00:26:25 - Elevating HR's Role in Business 00:36:00 - Balancing Business and People Needs 00:38:47 - Surviving Difficult Days in HR 00:41:01 - How to Connect with Sarah Rose   And if you love HR Therapy, sign up to I Hate it Here, the newsletter for jaded, overworked, and emotionally burnt-out HR/People Operations professionals needing a little inspiration. https://workweek.com/discover-newsletters/i-hate-it-here-newsletter/   And if you love the podcast, be sure to check out https://www.youtube.com/@ihateit-here for even more exclusive insider content!   Follow Sarah Rose:  LinkedIn: https://www.linkedin.com/in/sarah-hattem/   Follow Hebba:  YouTube: https://www.youtube.com/@ihateit-here/videos LinkedIn: https://linkedin.com/in/hebba-youssef Twitter: https://twitter.com/hebbamyoussef

It's not just in your head—we've all felt underappreciated at work at one point or another. So how can managers and HR cultivate an environment where people, not just their accomplishments, are appreciated?  Megan Paige, CMO of Snappy, stops by the pod to chat with Hebba about the art of appreciation and implementing employee appreciation strategies that go beyond simply recognizing workplace accomplishments. Hear why she believes there is no ROI for gratitude and why, sometimes, recognition campaigns backfire, leaving employees feeling like the entire thing was just part of a “to-do” list that needed to be checked off.  And later, Megan shares her top tips for creating authentic shared experiences in a remote work environment and reveals the best ways to show appreciation for your team.   Snappy is the award-winning B2B gifting platform that takes all of the guesswork out of gifting and helps companies build cultures of gratitude and appreciation. Send gifts to anyone (employees, customers, co-workers) for any occasion (birthdays, holidays, Employee Appreciation Day - coming up March 1, hint hint!). Choose the perfect gift from Snappy's extensive gift offerings, create custom swag, or send gift options and let your recipient pick! They put in their own address, and Snappy takes care of the rest. It's fast, easy, and delightful!   Go to https://www.snappy.com/ihateithere to sign up for free and start gifting today.   The Predictive Index (PI) is an award-winning talent optimization platform that aligns business strategy with people strategy for optimal business results. More than 60 years of proven science, software, and a curriculum of insightful management workshops make PI the solution for any company looking to design great teams and culture, make objective hiring decisions, foster engagement, and inspire greatness in their people anywhere in the world. More than 10,000 clients and 480+ partners use PI—including Nissan, Citizens Bank, Subway, Blue Cross Blue Shield, and Omni Hotels—across 90+ countries. Learn more at https://www.predictiveindex.com/.   And if you love HR Therapy, sign up to I Hate it Here, the newsletter for jaded, overworked, and emotionally burnt-out HR/People Operations professionals needing a little inspiration. https://workweek.com/discover-newsletters/i-hate-it-here-newsletter/   And if you love the podcast, be sure to check out https://www.youtube.com/@ihateit-here for even more exclusive insider content!   Follow Megan: Website: https://www.snappy.com/ihateithere LinkedIn: https://www.linkedin.com/in/meganclevelandpaige/   Follow Hebba:  YouTube: https://www.youtube.com/@ihateit-here/videos LinkedIn: https://linkedin.com/in/hebba-youssef Twitter: https://twitter.com/hebbamyoussef

CHEERS Season 7, episode 4: "One Happy Chappy in a Snappy Serape" Hosted by Ryan Daly with special guest Omar Uddin. Let us know what you think! Leave a comment or send an email to: RDalyPodcast@gmail.com. Like the CHEERS CAST Facebook page at: https://www.facebook.com/cheerscast/ This podcast is a proud member of the FIRE AND WATER PODCAST NETWORK. Visit our WEBSITE: http://fireandwaterpodcast.com/ Follow us on TWITTER - https://twitter.com/FWPodcasts Like our FACEBOOK page - https://www.facebook.com/FWPodcastNetwork Use our HASHTAG online: #FWPodcasts Subscribe to CHEERS CAST on iTunes: https://itunes.apple.com/us/podcast/cheers-cast/id1403495561?mt=2 Or subscribe via iTunes as part of the FIRE AND WATER PODCAST: http://itunes.apple.com/podcast/the-fire-and-water-podcast/id463855630 Support CHEERS CAST and the FIRE AND WATER PODCAST NETWORK on Patreon: https://www.patreon.com/fwpodcasts Thanks for listening!

CHEERS Season 7, episode 4: "One Happy Chappy in a Snappy Serape" Hosted by Ryan Daly with special guest Omar Uddin. Let us know what you think! Leave a comment or send an email to: RDalyPodcast@gmail.com. Like the CHEERS CAST Facebook page at: https://www.facebook.com/cheerscast/ This podcast is a proud member of the FIRE AND WATER PODCAST NETWORK. Visit our WEBSITE: http://fireandwaterpodcast.com/ Follow us on TWITTER - https://twitter.com/FWPodcasts Like our FACEBOOK page - https://www.facebook.com/FWPodcastNetwork Use our HASHTAG online: #FWPodcasts Subscribe to CHEERS CAST on iTunes: https://itunes.apple.com/us/podcast/cheers-cast/id1403495561?mt=2 Or subscribe via iTunes as part of the FIRE AND WATER PODCAST: http://itunes.apple.com/podcast/the-fire-and-water-podcast/id463855630 Support CHEERS CAST and the FIRE AND WATER PODCAST NETWORK on Patreon: https://www.patreon.com/fwpodcasts Thanks for listening!

A banking crisis brewing? Say it aint so Fed's trying to talk down rate cuts – Powell on 60 Minutes Looking like a pullback could be in the cards Guest, Frank Curzio – Curzio Research   Frank Curzio can be reached by email at frank@curzioresearch.com Frank Curzio is an equity analyst with close to two decades of experience covering small- and mid-cap stocks. Check out his newsletters. (Free trial subscriptions available) He has been the editor of several well respected newsletters with major companies as well on of the top performers with TheStreet.com where he significantly outperformed the markets during his tenure. He was also a research analyst for Jim Cramer. Frank is the host of Wall Street Unplugged. Frank has been a guest on various media outlets including Fox Business News, CNBC's The Kudlow Report and CNBC's The Call. He has also been mentioned numerous times on Jim Cramer's™s Mad Money, is a featured guest on CNN Radio and has been quoted in financial magazines and websites. Before TheStreet.com, Frank was the editor of The FXC Newsletter and received one of the top rankings by Hulbert's Financial Digest for risk-adjusted performance. Follow @frankcurzio Check this out and find out more at: http://www.interactivebrokers.com/ Follow @andrewhorowitz Looking for style diversification? More information on the TDI Managed Growth Strategy - HERE Stocks mentioned in this episode: (META), (F), (GM), (NVDA), (AMD), (SNAP), (TSLA), (DIS)

Welcome to our first ever publicly broadcast planning meeting. And just to get us started, Nick has a few of what he is calling 'Mid-faith Crisis Moderately Interesting Questions'. Snappy. Before that, we talk about haggis, ghosts, whether it's wrong to get angry and the idea of church as a place to share stories. Support the podcast Contact the podcast through your email machine Mentioned in this episode: Haggis Burns Night Ghosts

QUICK SNAPS - NINERS PLAYOFFS EDITION! It is QUICK! It is SNAPPY! Our Quick Snaps preview pod lives to see another week! Tune in to hear us break down the #GBvsSF game!

Join the crew of Off Topic as they talk about Joe's snappy attitude, doctor visits, South Park as a cultural phenomenon, and more!  This episode is sponsored by BetterHelp, MeUndies, and Rocket Money! - Go to http://betterhelp.com/offtopic to get 10% off your first month - Go to http://meundies.com/offtopic to get 25% off your first order. - Go to http://rocketmoney.com/offtopic to cancel your unwanted subscriptions. Learn more about your ad choices. Visit megaphone.fm/adchoices

In this week's First $1,000 segment, we hear from a financial analyst with a secret side hustle making snappy short videos. Side Hustle School features a new episode EVERY DAY, featuring detailed case studies of people who earn extra money without quitting their job. This year, the show includes free guided lessons and listener Q&A several days each week. Show notes: SideHustleSchool.com Email: team@sidehustleschool.com Be on the show: SideHustleSchool.com/questions Connect on Twitter: @chrisguillebeau Connect on Instagram: @193countries Visit Chris's main site: ChrisGuillebeau.com If you're enjoying the show, please pass it along! It's free and has been published every single day since January 1, 2017. We're also very grateful for your five-star ratings—it shows that people are listening and looking forward to new episodes.