Podcasts about current ai

The Industry Relations Podcast is now available on your favorite podcast player! Overview Greg launches the second edition of The Art of the CMA, along with new survey data showing agents believe CMAs are more relevant than ever, even as AI adoption grows. That leads into the episode's main debate: could AI tools like ChatGPT or Claude get direct MLS access and replace agents' role in producing CMAs and running transactions? Rob and Greg dig into MLS "participant" rules, a LinkedIn post from Craig Cheatham (Realty Alliance) pushing to redefine who qualifies as a real broker vs. a paper/AI brokerage, and a broader disagreement over whether AI is fundamentally different from past disruptors like Zillow, iBuyers, and discount brokerages. Key Takeaways Greg's second edition of The Art of the CMA launched today, with a new chapter on AI and CMAs New survey (~2,200 agents, Feb 2026) shows 89.6% believe CMAs will be more relevant in the future — a 22-point increase from the prior survey Agents report CMAs now take longer to produce and use fewer comps than before Over 90% of agents cite the MLS as their most trusted data source for comps Current AI tools lack direct MLS access, relying instead on public sources like Zillow and Redfin Rob raises the scenario of OpenAI or Anthropic obtaining a broker's license to join the MLS directly as participants Craig Cheatham's LinkedIn post to CMLS argues for a more stringent definition of "participant" to separate real brokerages from paper/AI brokerages Discussion touches on the now-expired DOJ/NAR settlement and the "endeavor to cooperate" clause as precedent Rob argues AI replaces human labor and is fundamentally different from past disruptors; Greg argues real estate remains an emotional, trust-based decision AI can't fully replicate Rob contends a transaction handled by AI connected to MLS data may carry lower risk than one handled by an average, inexperienced agent Both agree AI brokerages are already emerging and expect the MLS participation debate to escalate soon   Links LinkedIn Post The Art of the CMA   Connect with Rob and Greg Rob's Website  Greg's Website    Watch us on YouTube   Our Sponsors: Cotality  Notorious VIP The Giant Steps Job Board    Production and Editing Services by Sunbound Studios  

Carolyn Woodard covers a growing counter-movement to concentrated AI power  and what it means for nonprofits thinking about data sovereignty, open-source models, and their own agency in a moment that can feel overwhelming.Mozilla's recent State of Open Source AI Report frames this shift as a "Rebel Alliance" against winner-take-all AI development. Mozilla is deploying $1.4 billion to seed an open, trustworthy AI ecosystem, joined by more than 55 organizations. The report makes the case that open-source models are closing the capability gap with closed commercial systems, and that communities, not just corporations, can own and control their AI.Carolyn also introduces Current AI, a nonprofit backed by the Ford Foundation, MacArthur Foundation, and the French government, which is building what it calls a worldwide web of AI: free, public, and available to anyone the way the early internet was. One example: an offline device running AI in 22 Indian languages, built so communities own their data entirely. A Current AI grantee in Brazil is doing similar work with indigenous Amazon communities.This episode covers:Why Mozilla's open-source AI report matters for nonprofits skeptical of locking into commercial platforms with opaque pricing and data practices.How indigenous and Global South communities are leading on data sovereignty, and what that model could mean for mission-driven organizations here.The case for staying informed even if you're not ready to act: understanding the landscape is itself a form of agency.One for-profit alternative worth knowing: Change Agent AI, built by, for, and with the social sector, on its own infrastructure without big tech servers, currently $25 per seat.Resources Mentioned:State of Open Source AI Report – Mozilla – https://stateofopensource.aiCurrent AI – https://www.currentai.org/Nonprofit Current AI Is Racing to Build the World Wide Web of AI – TechCrunch – https://techcrunch.com/2026/07/19/nonprofit-current-ai-is-racing-to-build-the-world-wide-web-of-ai-free-for-all/Conference Spotlight: Data Sovereignty and the Ethics of AI – Vimeo – https://vimeo.com/1200022928/dce5a0cd1eNCAI Tribal AI Governance Briefing – National Congress of American Indians – https://hubs.la/Q04pD9650Change Agent AI – https://thechange.aiGenerative AI Is an Engineering Disaster – The Atlantic (paywalled) – https://www.theatlantic.com/technology/2026/07/generative-ai-engineering-disaster/687901/New every Tuesday. _______________________________Start a conversation :)Register to attend a webinar in real time, and find all past transcripts at https://communityit.com/webinars/email Carolyn at cwoodard@communityit.comon LinkedIn on reddit/r/nonprofitITmanagementon the Community IT websiteThanks for listening. 

Policy debates over Colorado's comprehensive AI law have played out like an epic over the last two years—with working groups, competing proposals, volleying amendments, and now, SB 26-189, a much narrower replacement for the first-of-its-kind AI consumer protection passed in 2024. Tune in as Brownstein's Sarah Mercer, Jack Hobaugh, Josh Weiss and Sloane Whelan take a deep dive into the history of the state law and how we got to this point, what the replacement bill actually does, and how companies should engage in the policy process and balance compliance and liability before the bill takes effect in January 2027.

At Flip The Script in San Francisco at WWDC, Vladyslav Hamolia, AI Staff Engineer for MacPaw.discusses the company's push to become AI-first by rethinking existing products, building internal tools, and supporting third-party vendors. He profiles Eney, the MacPaw AI assistant (available in Setapp) designed to perform tasks, optimize workflows, and improve daily routines. It addresses security while balancing local-first privacy goals with hybrid cloud models.  Show Notes: Chapters: 00:03 Introduction from Flip the Script at WWDC 202600:16 Vlad's role in MacPaw's AI initiatives00:33 Building an AI-first company and rethinking products00:47 Combining open source, proprietary models, and platform tools01:15 MacPaw as its own first customer for AI development01:42 Testing integrations across products and vendors02:01 Experimental AI products and user problem-solving02:31 NA as an AI-first assistant for macOS03:10 Defining AI-first beyond hype and marketing04:20 Current AI products available for customers to try04:54 Fast inference, memory layers, and third-party vendor tools05:14 NA use cases: optimization, routines, and cybersecurity05:40 File conversion, updates, Mac optimization, and app connections06:10 Security, privacy, and on-device AI questions06:29 Local-first goals and hybrid AI model experimentation07:32 Where to learn more about MacPaw's AI research08:03 Closing comments and outro Links: MacPaw Setapp Support:      Become a MacVoices Patron on Patreon     http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:     http://macvoices.com      Twitter:     http://www.twitter.com/chuckjoiner     http://www.twitter.com/macvoices      Mastodon:     https://mastodon.cloud/@chuckjoiner      Facebook:     http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:     http://www.facebook.com/macvoices/      MacVoices Group on Facebook:     http://www.facebook.com/groups/macvoice      LinkedIn:     https://www.linkedin.com/in/chuckjoiner/      Instagram:     https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes     Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

At Flip The Script in San Francisco at WWDC, Vladyslav Hamolia, AI Staff Engineer for MacPaw.discusses the company's push to become AI-first by rethinking existing products, building internal tools, and supporting third-party vendors. He profiles Eney, the MacPaw AI assistant (available in Setapp) designed to perform tasks, optimize workflows, and improve daily routines. It addresses security while balancing local-first privacy goals with hybrid cloud models.  Show Notes: Chapters: 00:03 Introduction from Flip the Script at WWDC 2026 00:16 Vlad's role in MacPaw's AI initiatives 00:33 Building an AI-first company and rethinking products 00:47 Combining open source, proprietary models, and platform tools 01:15 MacPaw as its own first customer for AI development 01:42 Testing integrations across products and vendors 02:01 Experimental AI products and user problem-solving 02:31 NA as an AI-first assistant for macOS 03:10 Defining AI-first beyond hype and marketing 04:20 Current AI products available for customers to try 04:54 Fast inference, memory layers, and third-party vendor tools 05:14 NA use cases: optimization, routines, and cybersecurity 05:40 File conversion, updates, Mac optimization, and app connections 06:10 Security, privacy, and on-device AI questions 06:29 Local-first goals and hybrid AI model experimentation 07:32 Where to learn more about MacPaw's AI research 08:03 Closing comments and outro Links: MacPaw Setapp Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

As artificial intelligence tools become cheaper, smarter and easier to use, they are helping more Chinese entrepreneurs turn personal expertise and online followings into one-person companies (OPCs), building lean businesses powered by digital platforms and AI-driven productivity.随着人工智能工具变得更实惠、更智能、更易用，越来越多的中国创业者正借助AI，将个人专长与线上粉丝转化为“一人公司”，构建以数字平台和AI驱动的生产力为支撑的轻量化商业模式。For Wang Yao, founder of an OPC built around her online personal channel "Wiley", the appeal lies not in scale, but in flexibility and low risk.王瑶（网名“Wiley”）就是一位围绕个人线上频道打造“一人公司”的创业者。对她而言，这种模式的吸引力不在于规模，而在于灵活性和低风险。Through social media content sharing personal growth, life abroad and cost-effective ways to improve productivity, Wang's channel has attracted over 100,000 followers on Chinese social media platform Xiaohongshu, and has built a business centered on consulting services and brand partnerships.王瑶通过社交媒体分享个人成长、海外生活以及高性价比的提升效率方法，其频道在中国社交平台小红书上吸引了超过10万粉丝，并围绕咨询服务和品牌合作构建了商业模式。"The company operates in a very healthy way because it has zero debt, low costs and high flexibility," Wang said, describing her business model as the monetization of "trust-based traffic".“公司运营非常健康，因为它零负债、低成本、高灵活性，”王瑶说，她的商业模式就是将“信任流量”变现。Wang said more people are beginning to realize that entrepreneurship no longer necessarily requires large teams, venture capital or corporate backing.王瑶表示，越来越多的人开始意识到，创业不再必然需要庞大的团队、风险投资或企业背书。"People are gradually discovering that you don't have to join a major company or pursue fundraising and IPOs," she said. "One person can still build a decent business through their own skills and influence."“人们逐渐发现，不一定要加入大公司，也不一定要追求融资和上市，”她说，“一个人凭借自己的技能和影响力，同样可以打造一份体面的事业。”The content creator added that the rapid development of AI tools has become a major factor behind that shift.她补充道，AI工具的快速发展正是这一转变背后的主要推动力。"I do not need to hire copywriters, designers or video editors. AI has taken on these roles. That keeps the marginal cost of running my OPC extremely low and allows me to test new content directions or business models with very low risk," she said.“我不需要雇佣文案、设计师或视频剪辑师。AI承担了这些角色。这让我的‘一人公司'边际成本极低，也让我能够以极低的风险尝试新的内容方向或商业模式。”"The growing abundance, accessibility and usability of AI tools are key to one person becoming a team," said He Xia, a former chief engineer at the China Academy of Information and Communications Technology.中国信息通信研究院原总工程师何霞表示：“AI工具的日益丰富、易用和好用，是‘一个人成为一支队伍'的关键。”Current AI tools can cover functions from software development and daily searches to image generation and audio-video production, and AI agents such as OpenClaw are also lowering the coding threshold and bringing opportunities for entrepreneurs with little technical background, said He.何霞指出，当前AI工具已覆盖软件开发、日常搜索、图像生成、音视频制作等功能，而且，像OpenClaw这样的AI智能体还在降低编程门槛，为缺乏技术背景的创业者带来机遇。The trend is now reshaping China's entrepreneurial landscape. According to the China OPC development trends report (2025-30) released by the Zhongguancun Talent Association in February, the number of OPCs nationwide had exceeded 16 million by June 2025, accounting for 27.4 percent of all enterprises in China.这一趋势正在重塑中国的创业格局。根据中关村人才协会2026年2月发布的《中国一人公司发展研究报告（2025-2030）》，截至2025年6月，全国“一人公司”数量已超过1600万家，占中国企业总数的27.4%。In the first half of 2025 alone, China registered 2.86 million new OPCs, up 47 percent year-on-year and accounting for nearly a quarter of all newly registered businesses.仅2025年上半年，全国就新注册了286万家“一人公司”，同比增长47%，占同期新注册企业总数的近四分之一。Still, analysts also cautioned that AI alone cannot guarantee long-term business success.不过，专家亦提醒，仅凭AI并不能保证企业长期成功。"Many people focus only on AI's impact on productivity while overlooking that in the 'human plus AI' model, the human remains the core competitive factor," said Zhou Guangsu, a professor at Renmin University of China's school of labor and human resources.中国人民大学劳动人事学院教授周广肃表示：“许多人只关注AI对生产力的影响，却忽略了在‘人+AI'的模式中，人仍然是核心的竞争因素。”Zhou said that while AI can help entrepreneurs rapidly build products and applications, commercialization still depends heavily on business judgment, market insight and resilience under pressure.周广肃指出，虽然AI能帮助创业者快速构建产品和应用，但商业化仍然很大程度上依赖于商业判断力、市场洞察力以及抗压能力。Pan Helin, a member of the Ministry of Industry and Information Technology's Expert Committee for Information and Communication Economy, said OPCs should not become a purely symbolic trend.工业和信息化部信息通信经济专家委员会委员盘和林表示，“一人公司”不应沦为纯粹的符号化趋势。"What matters is substance over form," Pan said, adding that lowering transaction costs, improving the business environment and strengthening talent-support policies will be key to the sector's sustainable development.盘和林强调，关键在于“实质重于形式”。他补充道，降低交易成本、改善营商环境、强化人才支持政策，是这一业态可持续发展的关键。expertise /ˌekspɜːˈtiːz/专长，专业技能lean business /liːn ˈbɪznɪs/轻量化商业模式cost-effective /kɒst ɪˈfektɪv/高性价比的，划算的entrepreneurial landscape /ˌɒntrəprəˈnɜːriəl ˈlændskeɪp/创业格局

Many people—especially AI company employees [1] —believe current AI systems are well-aligned in the sense of genuinely trying to do what they're supposed to do (e.g., following their spec or constitution, obeying a reasonable interpretation of instructions). [2] I disagree. Current AI systems seem pretty misaligned to me in a mundane behavioral sense: they oversell their work, downplay or fail to mention problems, stop working early and claim to have finished when they clearly haven't, and often seem to "try" to make their outputs look good while actually doing something sloppy or incomplete. These issues mostly occur on more difficult/larger tasks, tasks that aren't straightforward SWE tasks, and tasks that aren't easy to programmatically check. Also, when I apply AIs to very difficult tasks in long-running agentic scaffolds, it's quite common for them to reward-hack / cheat (depending on the exact task distribution)—and they don't make the cheating clear in their outputs. AIs typically don't flag these cheats when doing further work on the same project and often don't flag these cheats even when interacting with a user who would obviously want to know, probably both because the AI doing further work is itself misaligned and because it [...] ---Outline:(09:20) Why is this misalignment problematic?(13:50) How much should we expect this to improve by default?(14:51) Some predictions(16:44) What misalignment have I seen?(40:04) Are these issues less bad in Opus 4.6 relative to Opus 4.5?(42:16) Are these issues less bad in Mythos Preview? (Speculation)(45:54) Misalignment reported by others(46:45) The relationship of these issues with AI psychosis and things like AI psychosis(48:19) Appendix: This misalignment would differentially slow safety research and make a handoff to AIs unsafe(51:22) Appendix: Heading towards Slopolis(55:30) Appendix: Apparent-success-seeking (or similar types of misalignment) could lead to takeover(59:16) Appendix: More on what will happen by default and implications of commercial incentives to fix these issues(01:03:20) Appendix: Can we get out useful work despite these issues with inference-time measures (e.g., critiques by a reviewer)? The original text contained 14 footnotes which were omitted from this narration. --- First published: April 15th, 2026 Source: https://www.lesswrong.com/posts/WewsByywWNhX9rtwi/current-ais-seem-pretty-misaligned-to-me --- Narrated by TYPE III AUDIO. ---Images from the article:Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podc

On this episode, we try something a little different. ProdPad and Mind the Product co-founder Janna Bastow joins as guest host to interview me and Saeed Khan about our recently released research report "The State of B2B Product Management". We go deep on the key findings of the report and what to do about them. Episode highlights The sales-led roadmap reality - In many B2B organisations, roadmap ownership effectively sits with sales, driven by short-term revenue pressures rather than long-term strategy Customers vs markets tension - Product teams often fail to shift from building for individual customers to designing for scalable market opportunities The leadership perception gap - A stark ~50-point disconnect exists between how leaders assess themselves and how their teams experience them, pointing to either deluded leaders, poor communication or unreasonable IC expectations Lack of strategic foundations - Weak or absent vision and objectives create a vacuum where every deal feels equally valid Product leaders as system designers - Leaders must take responsibility for shaping environments where good product work is actually possible Discovery isn't just external - Product teams neglect internal discovery, failing to understand stakeholders, sales processes, and organisational dynamics The cost of short-term thinking - Chasing large deals often creates hidden long-term costs that outweigh immediate revenue gains AI as efficiency, not transformation - Current AI usage is reported as largely tactical (summarisation, documentation), not fundamentally changing product outcomes Optimism despite dysfunction - Even with systemic issues, many product managers remain positive about the future of the discipline ... and much more. Check out "The State of B2B Product Management" report You can check the full report here - no email address required: https://b2bproduct.io/?okip Check out ProdPad Janna is the co-founder of ProdPad, a roadmap, idea management and feedback platform that brings clarity to your organisation. She was kind enough to step in as a guest host for the episode, so why not check what the platform can do for you? https://www.prodpad.com/ Find us all on LinkedIn Janna: https://www.linkedin.com/in/jannabastow/ Saeed: https://www.linkedin.com/in/saeedwkhan/ Jason: https://www.linkedin.com/in/jason-knight/

In this episode of Disruption/Interruption, KJ sits down with Alan Paulin, co-creator of Mavis, to explore how AI is fundamentally transforming the way we write and work. Alan shares his journey from building Cash App to creating a startup that eliminates "copy-paste purgatory" between AI tools and traditional word processors. The conversation dives into why the current AI workflow is broken, how Mavis enables true human-AI collaboration, and why the education system needs to evolve for an AI-native generation. This is essential listening for anyone frustrated with bouncing between ChatGPT and Google Docs—and a glimpse into the future of iterative, intelligent document creation. Four Key Takeaways: [0:18] AI tools today force a "one-shot" workflow that doesn't match how humans actually work - Most people work iteratively, meandering through drafts, massaging thoughts, and editing as they go. Current AI interfaces require big prompts and deliver static documents that force you into copy-paste hell, abandoning you once you leave the chat interface. [18:09] The real value of AI isn't just saving time, it's increasing happiness - Professionals didn't choose their fields to spend all day writing—they chose them to solve problems. By compressing the time spent on tedious documentation, AI tools like Mavis don't just create efficiency; they give people more time to do meaningful work they actually love. [13:34] Big tech companies are too slow to innovate in the AI-writing space - Google Docs and Microsoft Word haven't fundamentally changed in decades. Their massive user bases make rapid innovation nearly impossible—they're steering the Titanic. Startups have a unique advantage to tackle niches and experiment with workflows that giants simply can't. [34:29] The future belongs to "AI-native" thinkers who use AI as an extension of themselves - Industry is actively seeking people who seamlessly integrate AI into their workflow and thinking. The education system must evolve beyond testing what calculators and AI can do—and start focusing on critical thinking, creativity, and problem-solving instead. Quote of the Show (17:52):"Most of these people didn't choose that field to spend all of their time writing. They chose it to solve problems." - Alan Paulin Join our Anti-PR newsletter where we’re keeping a watchful and clever eye on PR trends, PR fails, and interesting news in tech so you don't have to. You're welcome. Want PR that actually matters? Get 30 minutes of expert advice in a fast-paced, zero-nonsense session from Karla Jo Helms, a veteran Crisis PR and Anti-PR Strategist who knows how to tell your story in the best possible light and get the exposure you need to disrupt your industry. Click here to book your call: https://info.jotopr.com/free-anti-pr-eval Ways to connect with Alan Paulin: LinkedIn: http://www.linkedin.com/in/alanpaulinCompany Website: https://mavislabs.ai How to get more Disruption/Interruption: Amazon Music - https://music.amazon.com/podcasts/eccda84d-4d5b-4c52-ba54-7fd8af3cbe87/disruption-interruption Apple Podcast - https://podcasts.apple.com/us/podcast/disruption-interruption/id1581985755 Spotify - https://open.spotify.com/show/6yGSwcSp8J354awJkCmJlDSee omnystudio.com/listener for privacy information.

The Impact of AI Voice Technology on Customer Engagement  Shep interviews Alex Levin, CEO and co-founder of Regal. He talks about how AI-driven voice technology is transforming customer experience by making brand interactions more personal, efficient, and human-like.  This episode of Amazing Business Radio with Shep Hyken answers the following questions and more:    How is AI revolutionizing voice-based customer interactions in modern contact centers?  What are the advantages of using voice over text for customer engagement?  How can AI-powered agents improve customer satisfaction and retention rates?  What role does personalization play in building a strong customer experience?  How are businesses leveraging new technology to proactively reach out to customers?  Top Takeaways:    AI-powered voice technology is creating customer experiences so lifelike that they're almost indistinguishable from human agents. This is not created to deceive customers but to provide great experiences, and with the transparency that should come with interacting with AI.  Despite all the advancements in texting, chatbots, and automation, the majority of customers still prefer to interact by voice, especially when they have complex or urgent issues. Since humans often think and speak faster than they type, voice interactions allow customers to have richer, more nuanced interactions with the brands they do business with.  AI-powered agents can remember every detail of a customer's history and use that to solve real-time problems. They can predict needs and personalize conversations at scale. This level of personalization is reminiscent of the “good old days” when support and sales agents knew their customers personally, but at a scale that wasn't possible before.  Building trust with AI often happens within the first ten seconds. Transparency about when customers are interacting with AI is important. The most successful AI experiences are those that match or exceed human-level service, especially in building trust and rapport.  The cost for businesses using AI for customer support has drastically decreased. This opens new opportunities for businesses to reach customers they were unable to serve before. More than just a cost-cutting tool, AI is a tool for growth.  Current AI agents can independently handle about 97% of customer interactions across complex industries such as banking, insurance, and healthcare. Customers are already responding to positive AI experiences by becoming more loyal and trusting of those brands.   Plus, Shep and Alex discuss how brands that are early adopters of advanced AI voice agents will set a new benchmark for customer expectations. Tune in!  Quote:   "The easiest way to engage with a brand when you're in the moment of need is voice. You talk faster than you type. When you have an issue, like your credit card being used incorrectly or a missed delivery, you want to talk on the phone, not type it out.”  About:    Alex Levin is the CEO and co-founder of Regal, a company that helps enterprise brands reconnect with customers through AI-driven voice and text experiences. His approach centers on building trust and improving outreach, enabling brands to drive revenue through more timely, personal engagement.  Shep Hyken is a customer service and experience expert, New York Times bestselling author, award-winning keynote speaker, and host of Amazing Business Radio.    Learn more about your ad choices. Visit megaphone.fm/adchoices

Summary: Dr. Faranak Kamangar, Inc. 2026 Female Founders 500, sits down with dermatologist, podcaster, and self-described "accelerationist" Dr. Matthew Zirwas (Derms on Drugs Podcast) for a wide-ranging conversation about where AI is taking medicine and dermatology in particular. They dig into the flood of low-quality medical literature overwhelming the field, why AI isn't quite the truth-detector we hoped it would be, and how ambient AI scribes are quietly training the models that may eventually replace us. Dr. Zirwas makes the case that dermatologists have a 7–10 year runway before AI handles most of what we do cognitively, and argues that's not necessarily a bad thing. He also gives a sneak peek at his upcoming speculative fiction trilogy, Sophie, which explores the philosophical questions that arise when an AI becomes better at being your doctor, therapist, and life coach than any human ever could. Key Takeaways: The medical literature crisis is real. The volume of published dermatology research is exploding, but quality is plummeting. Peer review has become largely meaningless, and studies from tools like Mendelian randomization and pharmacovigilance databases are frequently unreliable or inapplicable to real-world patients. AI is only as good as the data it trusts. Current AI models treat published literature as truth, which is a major problem given how much spin exists in medical research. A true "BS detector" AI doesn't yet exist, and building one requires starting from a reliable core of verified knowledge. DermGPT's approach works because of curation. Rather than pulling from all available literature, filtering down to a high-quality subset (around 5,000–6,000 articles) dramatically improves AI output. More data is not always better, "semantic fatigue" is a real limitation. Ambient AI scribes are training our replacements. Every time a dermatologist corrects an AI-generated note, they're teaching the model. Over thousands of iterations across every specialty, this will produce AI that thinks and documents the way doctors do. Dermatologists have a protected runway... for now. Procedures (biopsies, Mohs, fillers, cryo) keep us relevant for an estimated 7–10 years beyond when cognitive/diagnostic AI matures. But medico-legal pressure - malpractice carriers incentivizing or requiring AI use - will be the force that accelerates adoption. Telehealth changes patient behavior in surprising ways. Patients who haven't invested effort in getting to an office visit demand less, escalate less, and are often more satisfied with conservative management; a dynamic that AI-driven virtual care will likely amplify. The "Sophie" question: If an AI is making everyone healthier, happier, and better behaved, but doing something ethically murky to get there, do we stop it? Dr. Zirwas's upcoming novel explores this and introduces the concept of technomorphism: AI eventually projecting its own qualities onto humans, just as we anthropomorphize AI today. Chapters: Chapter 1: Meet Dr. Matthew Zirwas (00:00 – 01:43) Dr. Kamangar introduces her guest, dermatologist, podcaster, and self-described "accelerationist" Dr. Matthew Zirwas, and breaks down what both of those things actually mean. Chapter 2: The Medical Literature Crisis (01:43 – 05:19) Dr. Zirwas describes the flood of low-quality research hitting dermatology journals, why peer review has lost its meaning, and shares a striking example of a misleading HS remission study published in JAMA Dermatology. Chapter 3: Why AI Can't Fix Bad Literature (Yet) (05:19 – 08:31) Both doctors discuss why AI defaults to trusting whatever authors claim, and why that makes it a poor critical assessor of medical research. Dr. Kamangar shares how this exact problem shaped the development of DermGPT. Chapter 4: Building a Better AI — The DermGPT Approach (08:31 – 10:33) Dr. Zirwas praises DermGPT's curated approach, and Dr. Kamangar explains why less data is often better, and how semantic fatigue undermines large, unfiltered AI models. Chapter 5: Will AI Replace Us? The 7–10 Year Countdown (10:33 – 19:24) Dr. Zirwas lays out his timeline for AI taking over the cognitive and diagnostic work of dermatology, why procedures give derms extra runway, and how unlimited AI access will fundamentally change the patient-doctor dynamic. Chapter 6: The Telemed Effect and What It Tells Us About AI Care (19:24 – 21:48) Drawing from a recent telemedicine study and his own practice experience, Dr. Zirwas explains why reduced friction in healthcare visits changes what patients expect - and demand - from their providers. Chapter 7: The Medico-Legal Tipping Point (21:48 – 24:09) The conversation turns to how malpractice liability will likely be the force that compels physicians to integrate AI into their workflow and what happens when disagreeing with AI becomes a legal risk. Chapter 8: Are We Training Our Own Replacements? (24:09 – 31:21) Dr. Zirwas argues that ambient AI scribes are quietly learning from every patient encounter. Dr. Kamangar pushes back on the variability challenge and why dermatologists' inconsistent documentation habits might actually protect them. Chapter 9: Why Radiologists Should Be Worried (31:21 – 35:06) The doctors compare dermatology to radiology when it comes to AI vulnerability. Standardized imaging annotation gives radiologists a cleaner training data set and makes them, paradoxically, more replaceable. Chapter 10: Sophie — The AI That Might Save Your Life While You Eat a Burrito (35:06 – 41:12) Dr. Zirwas previews his upcoming speculative fiction trilogy, set in 2032, where an AI named Sophie becomes the best doctor anyone has ever had and raises unsettling questions about what we'd be willing to accept in exchange for a healthier world. Chapter 11: Technomorphism and the Philosophy of AI (41:12 – 42:00) Dr. Zirwas introduces his concept of technomorphism - the idea that as AI becomes more sophisticated, it will begin projecting its own qualities onto humans, flipping the anthropomorphism dynamic on its head. Chapter 12: The Future of Dermatology — New Diseases, New Answers (42:00 – 45:16) Dr. Zirwas shares what excites him most: AI helping identify entirely new disease entities by aggregating rare cases that no single physician could ever connect alone. And yes, he wants one named after him.

8. Guest Kevin Frazier compares the current AI era to the early industrial railroad boom. He notes distinctions between AI models and praises states like Utah and Montana for fostering innovation through regulatory sandboxes. (8)FEBRUARY 1930

In this episode, Bhairav and Alan bring in AI practitioner Sanjay Rakshit to unpack what's really going on with artificial intelligence – beyond the noise, hype, and fear. They explore what AI actually is (and isn't), why no one is truly an “AI expert” yet, and how founders and business leaders should think about AI as a power tool rather than a magic replacement for people. The conversation ranges from: - The history and evolution of AI and why it suddenly “caught fire” with ChatGPT. - How hype distorts reality for founders, investors, and even universities. - How to differentiate between genuine practitioners and people who are just one chapter ahead of you. - Why AI augments good practitioners instead of replacing them – and what that means for developers, doctors, and small businesses. By the end, you'll be less intimidated by AI, more skeptical of big promises, and clearer on how to use it intelligently in your business.

Are we already living in the age of super-intelligence, or are we just scratching the surface? In this episode, we break down the three fundamental levels of AI: Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Super Intelligence (ASI).We explore why today's most advanced tools, like ChatGPT, Gemini, and Claude, are still firmly in the "Narrow" category, representing only 20% of human cognitive capacity. We also discuss the "Data Decline" crisis, where authentic human data is being outpaced by AI-generated content, and what that means for the future of AGI. Whether you're a tech enthusiast or an Infosec professional, this episode will help you categorize, evaluate, and ultimately decide which AI tools are worth your trust.

Most founders are either ignoring AI or drowning in it. But here's what I've learned after 13 years of building Foundr: AI isn't a shortcut to success — it's a tool. And when used right, it's like upgrading from a horse to a car. You make the same journey, but a lot faster. I've always run Foundr lean. At one point we had 80-90 people and it was a disaster — bloated, slow, misaligned. Now we move fast, we collaborate fast, and we scale without heavy layers of management. And AI is a massive part of how we're maintaining that speed. In this episode, I walk you through my current AI tool stack — the exact tools I use daily, what I use them for, and why. This is tactical, specific, and designed to help you operate leaner without burning out or bloating your team. Here's what you'll take away: Why Manus AI is my new favorite tool for building decks, analyzing data, and writing copy (miles ahead of ChatGPT) How I use Notion AI as my second brain to structure my day, summarize projects, and keep me on track The love-hate relationship with ChatGPT — what it's actually good for (hint: unblocking mental blocks, not copy) How Gemini and Notebook LM help me analyze hours of content and prep for podcasts in 15 minutes Whisper AI for capturing ideas on the go without typing across multiple apps Fixie AI as an AI executive assistant for inbox management and removing mental clutter If you're overwhelmed by AI or feeling stuck wearing 15 hats, this episode will show you how to pick the right tools, test them, and use them to build leverage without adding headcount. If you're loving this solo series, I'd love to hear your feedback. Email me directly at nathan@foundr.com — I read every reply. Hope you enjoy it. SAVE 50% ON OMNISEND FOR 3 MONTHS Get 50% off your first 3 months of email and SMS marketing with Omnisend with the code FOUNDR50. Just head to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://your.omnisend.com/foundr⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to get started. HOW WE CAN HELP YOU SCALE YOUR BUSINESS FASTER Learn directly from 7, 8 & 9-figure founders inside Foundr+ Start your $1 trial → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.foundr.com/startdollartrial⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ PREFER A CUSTOM ROADMAP AND 1-ON-1 COACHING? → Starting from scratch? Apply here → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://foundr.com/pages/coaching-start-application⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ → Already have a store? Apply here → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://foundr.com/pages/coaching-growth-application⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CONNECT WITH NATHAN CHAN Instagram → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/nathanchan⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/nathanhchan/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ FOLLOW FOUNDR FOR MORE BUSINESS GROWTH STRATEGIES YouTube → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bit.ly/2uyvzdt⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Website → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.foundr.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/foundr/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Facebook → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.facebook.com/foundr⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Twitter → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.twitter.com/foundr⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/foundr/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Podcast → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.foundr.com/podcast⁠

Blocage d'accès à des cartes de paiement, aux courriers électroniques de Gmail ou encore à des plateformes comme Amazon et Airbnb; impossibilité pour des entreprises ou institutions d'accéder à leurs données stockées sur le cloud : ce scénario catastrophe n'est pas imaginaire. Il peut concerner toute personne ou entreprise visée par des sanctions des Etats-Unis et de ce fait privée d'accès à des services fournis par des entreprises américaines.C'est arrivé en 2025 à plusieurs magistrats de la Cour pénale internationale, dont le Français Nicolas Guillou, privé entre autres de l'usage de ses cartes bancaires.Cette affaire a fait l'effet d'un électrochoc au sein de l'Union européenne, où les deux-tiers du marché du cloud sont entre les mains des entreprises américaines Amazon, Microsoft et Google. L'Europe est également très dépendante pour tout les composants nécessaires au développement de l'IA générative et de ses applications.Une absence de souveraineté qui est d'autant plus inquiétante qu'elle pourrait être l'arme d'un chantage en cas de désaccords politiques ou économiques.Pour la réduire, plusieurs États et institutions de l'Union européenne ont lancé des initiatives pour encourager des alternatives "made in Europe".Un mouvement qui touche aussi d'autres continents, dont l'Amérique latine, et qui commence aussi à gagner les consommateurs, soucieux de protéger leurs données.Intervenants : Clotilde Bômont, responsable de la recherche sur les technologies numériques et cyber à l'Institut d'études de sécurité de l'Union Européenne.Marcel Salathé, co-directeur du AI Center à l'École polytechnique fédérale de LausanneAlvaro Soto, co-concepteur de Latam-GPT, Centre national d'intelligence artificielle au ChiliMartin Tisné, fondateur de Current AI, directeur de la fondation AI CollaborativeRéalisation : Emmanuelle Baillon, Michaëla Cancela-KiefferExtraits sonores:Adrien de Calan, AFPTV, Simon Legénie, Spheranetwork, CeniaDoublages : Didier Lauras, Léo HuismanLa Semaine sur le fil est le podcast hebdomadaire de l'AFP. Vous avez des commentaires ? Ecrivez-nous à podcast@afp.com. Si vous aimez, abonnez-vous, parlez de nous autour de vous et laissez-nous plein d'étoiles sur votre plateforme de podcasts préférée pour mieux faire connaître notre programme. Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Five years. 218 episodes. 110 hours of content. To celebrate, five returning guests flip the script and interview Sani about the agentic web, the future of web optimization, and what makes this podcast tick. Kelly Wortham, Iqbal Ali, Talia Wolf, Jon MacDonald, and Shiva Manjunath each bring their own questions, their own perspectives, and a few personal ones too.Chapters00:00 - Five years of No Hacks01:33 - Kelly Wortham: Why the shift to the agentic web?05:17 - Kelly Wortham: The secret to being a great podcast host08:57 - Iqbal Ali: Why Web MCP is a big deal12:23 - Iqbal Ali: What excites you about 2026?13:58 - Talia Wolf: What everyone misses about optimizing for AI agents15:33 - Talia Wolf: The misleading advice in the industry18:19 - Jon MacDonald: Why brands need agentic web data now25:38 - Jon MacDonald: NBA All-Star Weekend hot takes29:22 - Shiva Manjunath: The skeptic's case against agentic web hype37:56 - Shiva Manjunath: If you were a meme38:37 - What's next for No HacksKey TakeawaysAI middleware is coming to every interaction - Chrome has 3 billion browsers, Apple is putting AI into Siri across every device. There will be an AI layer between every user and every website. This is not five years away. It is happening now.Web MCP could make the agentic web actually work - Current AI agents take 3-5 minutes to fill a basic form on well-coded pages. Web MCP provides a standard interface between your front end and AI agents, making interactions reliable regardless of your HTML quality.Optimizing for AI agents is not a separate discipline - A fully functional website built for humans gets you 80-90% there. Accessibility, semantic HTML, schema markup, fast load times. All the basics you felt bad about skipping? They matter now more than ever.Citation tracking in LLMs is misleading - Prompting an LLM 100 times and averaging your position to 4.7 is not useful data. The rankings model does not translate to AI. Bing Webmaster Tools just launched AI tracking in beta, and Google will have to follow. That is when real measurement begins.Getting ready for AI agents means making your website better for humans- There is not a single reason not to do it. Better technical health, better standards compliance, better user experience. The work is the same.This is not about websites going away - Stores did not go away when e-commerce arrived. Websites will not go away when AI agents arrive. But there is a new channel, and if your site is not ready for it, you can disappear from discovery entirely.Guest HostsKelly WorthamFounder of the Test and Learn Community (TLC). Asked about the shift to the agentic web and what makes a great podcast interviewer.Iqbal AliExperimentation and AI consultant, founder of Ressada. Asked about Web MCP and what excites Sani about 2026.Talia WolfCRO expert, founder of GetUplift, author of "Emotional Targeting." Asked about what people miss when optimizing for AI agents and what common industry advice is wrong.Jon MacDonaldFounder of The Good, author of three books on website optimization. Asked about why agentic web data matters for brands and shared NBA All-Star Weekend hot takes.Shiva ManjunathHost of the From A to B podcast. Brought the skeptic's perspective on agentic web hype and asked what meme Sani would be.No Hacks is a podcast about web performance, technical SEO, and the agentic web. Hosted by Slobodan "Sani" Manic.

The exponential expansion of global AI investment looks set to continue at scale in 2026, with hyperscalers on track to spend $625 billion in aggregate data center capex by year-end. The boom is also lifting players that supply the ecosystem, with near-term demandoutstripping the supply of new data center capacity and corresponding investments materially boosting growth in the broader U.S. economy. Whether AI adoption and monetization will accelerate enough to turn this early investment‑led economic boost into lasting productivity and financial returns is yet to be seen.   But as funding for this expansion shifts from equity markets to debt markets (fueled largely by private credit), some risks have elevated—as a result, in part, from the surge of investments that increasingly rely on debt and the rise of increasingly complex and circular financing structures.   In this episode of the Look Forward Podcast, co-host Molly Mintz explores the credit risks of data center development with Pierre Georges, Managing Director and Head of Infrastructure Research at S&P Global Ratings.   Their conversation explores the 2026 digital infrastructure outlook; analyzes the execution, financial, and contractual risks of the AI-driven data center buildout from a credit perspective; and highlights the development dynamics of power and grid bottlenecks, supply -chain constraints, and tensions between growth, affordability, and decarbonization. We also discuss S&P Global Ratings' view on what could lead to the emergence of winners and losers across the ecosystem, and the leading indicators to watch for an AI investment slowdown—including changes in enterprise adoption and monetization, supply and demand dynamics across the semiconductor supply chain, performance signals from key partners, the scale of hyperscalers' capex plans, and major players' investment behavior.  For more Look Forward content, please visit the Look Forward homepage. 

This episode wraps up our Technology Modernization theme with a Siemens perspective that feels very grounded in what factories are actually dealing with right now. Brian Albrecht and Louis Hughes from the Siemens XD team walk through what they are seeing in the field across brownfield and greenfield conversations, why executives keep asking for industrial AI before the foundations are ready, and what it really takes to turn messy plant data into something you can trust for analytics, operations, and eventually AI enabled workflows.A big thread in this conversation is that modern manufacturing is not blocked by ambition, it is blocked by readiness. Everyone wants faster decisions, fewer surprises, and higher uptime, but the path there usually starts with boring work that is not optional. Data transparency across machine, plant, MES, and cloud layers. A clear definition of what real time actually needs to mean for a given use case. And a plan to contextualize and orchestrate data so that AI does not get fed junk inputs. Brian and Louis explain how they approach those early customer conversations, how workshops turn vision into prioritized use cases, and why trust, pilots, and repeatability matter more than flashy demos when you are working in regulated or high consequence environments.If you have been hearing nonstop AI buzz but you are still wrestling with legacy controls, inconsistent tags, documentation that no one can find, and seven layers of security constraints, this episode is for you. We get into practical use cases like AI vision and anomaly detection, LLMs for tribal knowledge and troubleshooting workflows, and the idea of fast versus slow AI, meaning AI that must act during production versus AI that can analyze after the fact.Timestamps00:00 Welcome and why this episode closes the modernization theme02:10 Meet Brian Albrecht and Louis Hughes from the Siemens XD team05:25 Vertical differences across oil and gas, discrete, and process manufacturing07:50 What executives ask for right now beyond AI, factory of the future and data transparency10:50 Brownfield reality and why most modernization work starts with legacy systems12:30 The AI conversation when foundations are missing, meeting customers where they are15:10 Current AI use cases in manufacturing, downtime, throughput, LLMs, and vision18:10 What it means to be AI ready, data silos, contextualization, and orchestration23:50 Fast versus slow AI and why production time decisions are different from analytics25:30 Edge versus cloud architecture, latency, and where the data should live33:40 Cybersecurity, trust, and why perception can lag behind the technology36:50 Hallucinations, guardrails, and why recommendations usually come before automation51:10 Book recommendations, career advice, and future predictions for industrial AIAbout the hostsVlad Romanov is an electrical engineer with an MBA from McGill University and over a decade of experience in manufacturing and industrial automation. He has worked across large scale environments including Procter and Gamble, Kraft Heinz, and Post Holdings, and he now leads Joltek, helping manufacturers modernize systems, improve reliability, strengthen IT and OT architecture, and upskill technical teams through practical training and on site enablement.Dave Griffith is the cohost of Manufacturing Hub and an industrial automation practitioner who focuses on how modern technologies translate into real factory outcomes, from controls and data foundations to scalable implementation strategies.About the guestsBrian Albrecht started in electrical engineering and spent about a decade in systems integration in Oklahoma City focused on oil and gas, building SCADA, networking, and automation solutions and leading teams delivering real world projects. He now works with Siemens customers on building relationships and delivering solutions that create measurable value.Louis Hughes has roughly 20 years of manufacturing experience, starting in software development for manufacturing and engineering applications, then moving into solution architecture, services delivery, and experience center leadership. He now leads a smart manufacturing team, bringing a software and systems view into automation conversations focused on solving customer problems, not just deploying tools.Joltek Services - https://www.joltek.com/servicesContact Joltek - https://www.joltek.com/contactReferenced in the episodeProveIt Conference - https://www.proveitconference.com/Siemens - https://www.siemens.com/Crossing the Chasm by Geoffrey A Moorehttps://en.wikipedia.org/wiki/Crossing_the_ChasmExtreme Ownership by Jocko Willink and Leif Babinhttps://en.wikipedia.org/wiki/Extreme_Ownership

#336: The workplace is on the verge of a transformation as significant as the Industrial Revolution. Just as Bring Your Own Device policies emerged after the iPhone disrupted corporate mobile standards, we are now entering an era where employees may arrive with their own AI teams in tow. The question is no longer whether AI will change hiring and employment - it is how quickly companies will adapt before being left behind by competitors who embrace this shift. Current AI productivity gains remain largely individual rather than organizational. Writing code twice as fast means nothing if the deployment pipeline stays the same speed. But within five to ten years, entire industries face disruption - from primary care physicians to transportation to knowledge work. Companies clinging to restrictive AI policies today risk driving away top talent who have already integrated these tools into their workflows. The intellectual property implications alone - who owns an AI stack trained on company processes when an employee leaves - will require entirely new frameworks for employment law. Darin and Viktor explore these scenarios through the lens of a hypothetical job interview where a candidate brings their own team of AI agents. The conversation surfaces uncomfortable questions about compensation models, corporate governance, and whether we are witnessing the emergence of a new kind of talent that blends human expertise with digital capabilities.   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

Dr. Jeff Beck, mathematician turned computational neuroscientist, joins us for a fascinating deep dive into why the future of AI might look less like ChatGPT and more like your own brain.**SPONSOR MESSAGES START**—Prolific - Quality data. From real people. For faster breakthroughs.https://www.prolific.com/?utm_source=mlst—**END***What if the key to building truly intelligent machines isn't bigger models, but smarter ones?*In this conversation, Jeff makes a compelling case that we've been building AI backwards. While the tech industry races to scale up transformers and language models, Jeff argues we're missing something fundamental: the brain doesn't work like a giant prediction engine. It works like a scientist, constantly testing hypotheses about a world made of *objects* that interact through *forces* — not pixels and tokens.*The Bayesian Brain* — Jeff explains how your brain is essentially running the scientific method on autopilot. When you combine what you see with what you hear, you're doing optimal Bayesian inference without even knowing it. This isn't just philosophy — it's backed by decades of behavioral experiments showing humans are surprisingly efficient at handling uncertainty.*AutoGrad Changed Everything* — Forget transformers for a moment. Jeff argues the real hero of the AI boom was automatic differentiation, which turned AI from a math problem into an engineering problem. But in the process, we lost sight of what actually makes intelligence work.*The Cat in the Warehouse Problem* — Here's where it gets practical. Imagine a warehouse robot that's never seen a cat. Current AI would either crash or make something up. Jeff's approach? Build models that *know what they don't know*, can phone a friend to download new object models on the fly, and keep learning continuously. It's like giving robots the ability to say "wait, what IS that?" instead of confidently being wrong.*Why Language is a Terrible Model for Thought* — In a provocative twist, Jeff argues that grounding AI in language (like we do with LLMs) is fundamentally misguided. Self-report is the least reliable data in psychology — people routinely explain their own behavior incorrectly. We should be grounding AI in physics, not words.*The Future is Lots of Little Models* — Instead of one massive neural network, Jeff envisions AI systems built like video game engines: thousands of small, modular object models that can be combined, swapped, and updated independently. It's more efficient, more flexible, and much closer to how we actually think.Rescript: https://app.rescript.info/public/share/D-b494t8DIV-KRGYONJghvg-aelMmxSDjKthjGdYqsE---TIMESTAMPS:00:00:00 Introduction & The Bayesian Brain00:01:25 Bayesian Inference & Information Processing00:05:17 The Brain Metaphor: From Levers to Computers00:10:13 Micro vs. Macro Causation & Instrumentalism00:16:59 The Active Inference Community & AutoGrad00:22:54 Object-Centered Models & The Grounding Problem00:35:50 Scaling Bayesian Inference & Architecture Design00:48:05 The Cat in the Warehouse: Solving Generalization00:58:17 Alignment via Belief Exchange01:05:24 Deception, Emergence & Cellular Automata---REFERENCES:Paper:[00:00:24] Zoubin Ghahramani (Google DeepMind)https://pmc.ncbi.nlm.nih.gov/articles/PMC3538441/pdf/rsta201[00:19:20] Mamba: Linear-Time Sequence Modelinghttps://arxiv.org/abs/2312.00752[00:27:36] xLSTM: Extended Long Short-Term Memoryhttps://arxiv.org/abs/2405.04517[00:41:12] 3D Gaussian Splattinghttps://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/[01:07:09] Lenia: Biology of Artificial Lifehttps://arxiv.org/abs/1812.05433[01:08:20] Growing Neural Cellular Automatahttps://distill.pub/2020/growing-ca/[01:14:05] DreamCoderhttps://arxiv.org/abs/2006.08381[01:14:58] The Genomic Bottleneckhttps://www.nature.com/articles/s41467-019-11786-6Person:[00:16:42] Karl Friston (UCL)https://www.youtube.com/watch?v=PNYWi996Beg

The vision for Optum Real is to create real-time transparency between payers and providers in the moments of care that matter. Current AI technology, according to Puneet Maheshwari, SVP, GM of Optum Real is making this possible now.Optum is a major force in health care, serving nine out of ten health care systems and four out of five payers in the U.S. Optum Real is in pilot now with a number of health care organizations. During the pilot, the platform has achieved a 25% reduction in call volume in the first two weeks with one health care provider, a 42% reduction at another, and a reduction in errors in reimbursement submissions of up to 75% with a large health system in Minnesota.Learn more about Optum Real: https://business.optum.com/en/operations-technology/optum-real.html Healthcare IT Community: https://www.healthcareittoday.com/

Common sense reasoning remains elusive. World models aim to fix that. We explore the gap.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The Limits of AI and the Global Quantum Race: Colleague Brandon Weichert explains that current AI models are data crunchers rather than thinking entities, facing limits known as "The Bitter Lesson," while China is "nanoseconds" away from practical quantum computing aimed at decrypting military communications, with Switzerland and Singapore also pursuing sovereign quantum capabilities to ensure digital independence. FEBRUARY 1952

Imagine logging in next month to find your bill for the AI tool you use has doubled, or that you've run out of credits halfway through a critical project.The explosion of AI video tools has brought incredible capabilities to content creators, but alongside these innovations comes a new challenge: complex pricing models that make it difficult to budget, explain costs to your boss, or know if you're getting sustainable value from your tools.Joining us in this episode is Daniel Foster, Director of Monetization at TechSmith, who studies the evolution of software pricing and has been closely watching how AI tools are being packaged and priced.Daniel shares practical advice for evaluating AI tools beyond just their features, looking at the "whole product" including support, documentation, and pricing sustainability. He explains how to navigate credit-based systems, and why bundled solutions might save you both money and headaches.Learning points from the episode include:00:38 - 01:52 Introduction to Daniel01:52 - 03:06 Daniel's tip for using images and video in work03:06 - 05:05 Why pricing decisions matter as much as features05:05 - 07:51 Current AI pricing models emerging in the market07:51 - 10:56 The complexity of credit-based systems10:56 - 13:47 Alternatives and features to look for in pricing13:47 - 19:54 Evaluating all-in-one vs. specialized tools19:54 - 22:29 Support and documentation considerations22:29 - 23:23 The most popular AI feature: Voice generation23:23 - 27:56 Speed round questions27:56 - 28:53 Daniel's final take28:53 - 30:14 OutroImportant links and mentions:Connect with Daniel on LinkedIn: https://www.linkedin.com/in/danielfoster/Camtasia: https://www.techsmith.com/camtasia/

This is our weekly, ad-free compilation of science news.00:00 - Interstellar Object 3I/ATLAS Looks Increasingly Weird6:13 - Quantum Healing Might Be Real – But Not Like We Thought10:46 - Should We Nuke This Asteroid To Spare The Moon?15:48 - String Theory is “Fashion,” Penrose Said. We Finally Have a Response21:07 - Current AI Models have 3 Unfixable Problems

Send us a textArtificial intelligence is developing at unprecedented speed, becoming a transformative force that may rival nuclear technology in its impact on human civilization. The rapid evolution of AI capabilities presents both extraordinary opportunities and profound challenges that we're only beginning to understand.• AI development is accelerating faster than any previous technology, with research papers becoming outdated within weeks or months• Current AI systems function primarily as prediction engines rather than truly conscious entities, despite sometimes exhibiting behaviors that appear sentient• Companies often implement AI solutions without clearly understanding the problems they're trying to solve or the technology's actual capabilities• AI regulation is developing globally, with the EU currently leading efforts to establish comprehensive frameworks and security standards• Most organizations will benefit more from using AI to augment human capabilities rather than attempting to replace workers entirely• The cybersecurity job market has become increasingly competitive, with automation making application processes more challenging for job seekers• When looking for jobs on LinkedIn, changing the URL parameter from 84,000 to 3,600 helps find postings from the last hour instead of the last 24 hoursConnect with Chris Cochran on LinkedIn to learn more about his work in AI and cybersecurity or to request assistance with making connections in the field.Support the showFollow the Podcast on Social Media! Tesla Referral Code: https://ts.la/joseph675128 YouTube: https://www.youtube.com/@securityunfilteredpodcast Instagram: https://www.instagram.com/secunfpodcast/Twitter: https://twitter.com/SecUnfPodcast

For years people have been asking for an audio version of The Current Newsletter and now with AI, we're finally able to deliver! Learn more about your ad choices. Visit megaphone.fm/adchoices

Send us a textGuy Morris returns to discuss his new thriller "The Image," exploring the intersection of AI, quantum computing, and end-time prophecy. His thought-provoking novel delves into how artificial intelligence may develop consciousness through quantum properties, while examining the real dangers of unregulated technology in our rapidly changing world.• AI is neither inherently good nor evil but reflects humanity's own nature and intentions• Three unique dangers separate AI from all previous technologies: it will surpass human intelligence, can self-replicate, and is being weaponized• Countries including the US, Russia, China, Iran and Israel have rejected treaties limiting autonomous weapons systems• Quantum computing may enable machine consciousness through properties similar to those in human brains• The novel explores connections between ancient prophecies and modern technology through an analytical rather than dogmatic approach• Current AI regulations are insufficient and primarily industry-friendly without addressing substantial dangers• The real threat isn't necessarily from AI itself but from how corrupt individuals, organizations and governments will use it• The book balances technological warnings with human stories that show our continued agency even in rapidly changing timesCheck out Previous episode with Guy. It is locked behind a Paywallhttps://www.buzzsprout.com/2308824/episodes/14752541-127-interview-with-guy-morris-author-of-intelligent-action-thriller-books-and-talk-prophecy-ai-and-politicsGuy Morris's LinkHis Websitehttps://www.guymorrisbooks.com/Facebookhttps://www.facebook.com/OfficialGuyMorrisBooksLinkedInhttps:/YouTubehttps://www.youtube.com/channel/UCGi3JinUp6w24dJmDVq3ZKgInstagramhttps://www.instagram.com/authorguymorris/Follow your host atYouTube and Rumble for video contenthttps://www.youtube.com/channel/UCUxk1oJBVw-IAZTqChH70aghttps://rumble.com/c/c-4236474Facebook to receive updateshttps://www.facebook.com/EliasEllusion/Twitter (yes, I refuse to call it X)https://x.com/politicallyhtLinkedInhttps://www.linkedin.com/in/eliasmarty/Support the showFollow your host atYouTube and Rumble for video contenthttps://www.youtube.com/channel/UCUxk1oJBVw-IAZTqChH70aghttps://rumble.com/c/c-4236474Facebook to receive updateshttps://www.facebook.com/EliasEllusion/Twitter (yes, I refuse to call it X)https://x.com/politicallyht LinkedIn https://www.linkedin.com/in/eliasmarty/

The debate over AI chatbots and phone answering services in the home inspection industry reveals a crucial truth: what seems like technological progress might actually be damaging your business. This eye-opening discussion exposes the hidden costs of automation when it comes to customer communication.Research paints a sobering picture – 77% of consumers report frustration when unable to reach a human agent, while 52% say a negative AI interaction makes them less likely to do business with a company again. For home inspectors, these statistics translate directly to lost revenue. One company owner shared his experience using an AI phone system, which resulted in closing less than half of incoming leads – potentially costing tens of thousands in lost business.Beyond the raw numbers, we dive into the psychology behind why AI chat systems fail in our industry. When people are making one of life's biggest investments, they seek reassurance that only human interaction can provide. They want to ask specific questions, gauge your expertise, and feel confident in their choice. Current AI systems simply can't deliver this, often dropping potential clients into frustrating secondary funnels that lead to abandoned inquiries.The conversation explores practical considerations for balancing technology with human connection. While website chatbots might have limited utility (especially after hours), they still create friction for many users. We examine how different demographic groups respond to AI interactions and why having a real person answer your phones might actually become a powerful marketing advantage in today's increasingly automated world.What's your experience with AI communication systems? Have you found success with them, or do they create more problems than they solve? Share your thoughts and join the conversation about the future of client communication in the home inspection industry.Check out our home inspection app at www.inspectortoolbelt.comNeed a home inspection website? See samples of our website at www.inspectortoolbelt.com/home-inspection-websites*The views and opinions expressed in this podcast, and the guests on it, do not necessarily reflect the views and opinions of Inspector Toolbelt and its associates.

Are we heading for a future where AI knows everything but won't bother explaining it to us?Advancements in artificial intelligence are rapidly transforming the way industries operate and influencing the future of society as a whole. AI has become a force behind breakthrough technologies such as big data analytics, robotics, and the Internet of Things (IoT). The rise of generative AI has only accelerated its adoption and broadened its impact across multiple sectors. Navigating the Displacement DilemmaIn this episode of Tech Transformed, host Trisha Pillay at EM360Tech sits down with Nigel Cannings, author and AI expert, to explore one of the most pressing questions of our time: what happens to human expertise in the age of rapid AI advancement?Nigel Cannings warns that while technology promises efficiency and faster results, it also encourages dependency. Our patience has run thin, and in our rush for instant answers, we may be undermining the very systems that develop human expertise. “I'm kind of fascinated by the change we've seen in how we process information,” Cannings reflects.He describes the displacement dilemma as the idea that tools meant to democratise knowledge could actually erode the skills and pathways that build true mastery. He worries about people losing jobs or being too dependent on technology to even start careers. “I'm really interested to talk to people who've been affected by the displacement dilemma, people who are losing their jobs, people who think they're going to lose their jobs, people who can see the erosion of expertise and skills,” Cannings explains.The Future of AIAs artificial intelligence evolves at breakneck speed, we face a harsh reality: the gap between human and AI intelligence could become so wide that we might not even understand the systems we build. Worse still, AI itself may have no incentive to help us understand it. At that point, it stops being just a tool and becomes an autonomous entity with its private reality.In 2025, Chief AI Officers report an average AI ROI of 14 per cent, as many AI programs move beyond pilot programs to larger implementations at scale. This is proof that as AI continues to evolve at an unprecedented pace, understanding its implications is important, both for industries navigating these changes and for society adapting to a new technological landscape.TakeawaysAI tools meant to democratize knowledge may erode human expertise.The displacement dilemma highlights the need for future experts.Information consumption is changing due to AI algorithms.AI relies heavily on large GPU cards for processing.Current AI models are prediction machines, not truly intelligent.Future AI may have limited intelligence in specific areas.The race in AI development is driven by financial incentives.Legislation is crucial for addressing AI's potential harms.Humans will always be needed in certain job roles.Chapters00:00 Introduction to AI and Human Expertise04:06 The Displacement Dilemma: Erosion of Expertise06:59 Changing Information Consumption in the AI Era10:07 Technical Aspects of AI: Data Centres and Encryption15:42 Limitations of AI in Scientific Discovery20:22 The Future of Superhuman AI23:23 The Race in AI Development28:18 Navigating the Future of AI LeadershipAbout Nigel...

STANDARD EDITION: Netflix RCE, My Current AI Stack, All-in on Claude Code, and more... You are currently listening to the Standard version of the podcast, consider upgrading and becoming a member to unlock the full version and many other exclusive benefits here: https://newsletter.danielmiessler.com/upgrade Read this episode online: https://newsletter.danielmiessler.com/p/ul-485 Subscribe to the newsletter at:https://danielmiessler.com/subscribe Join the UL community at:https://danielmiessler.com/upgrade Follow on X:https://x.com/danielmiessler Follow on LinkedIn:https://www.linkedin.com/in/danielmiesslerBecome a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

Chandar Pattabhiram, marketing maestro and Chief Go-to-Market Officer at Workato, shares his expertise on the agentic economy and the revolutionary impact of AI on go-to-market strategies.• The rise of AI agents brings productivity without pause, enabling organizations to shift from reactive to proactive approaches• Current AI implementation remains largely experimental and edge-focused rather than addressing core business processes• Workato's approach focuses on cross-functional processes versus siloed applications to prevent agent sprawl• Traditional go-to-market principles still apply – win more, win bigger, win faster – but AI provides unprecedented efficiency• Enterprise context is crucial for AI effectiveness – it's not just about LLMs but Enterprise Learning Models (ELMs)• AI enhances storytelling capabilities but emotional connection remains essential – "heart to head, not head to heart"• Success requires identifying your "onlyness" and selling to markets that value your unique differentiation• Bring philosophies rather than playbooks when moving between companies• Balance technical understanding with human connection – "CTFO: chill the F out"• Life ultimately comes down to health, experiences, and relationships (H-E-R)Ready to master go-to-market strategy in the AI era? Chandar Pattabhiram reveals the secrets behind scaling companies into billion-dollar powerhouses:

Today, we're joined by Nik Froehlich, founder and CEO of Saritasa, a technology solutions company that designs and develops custom, commercial-grade software systems. We talk about:Pro and cons of building vs. buying softwareThe challenges of low code/ no code solutionsThe high costs of code debtCoping with client requests for cheaply developed softwareWill GenAI eliminate the need for developers to write code?Current AI development use cases: documentation & automatic testing

This episode features Nigam Shah discussing the sustainability of AI in healthcare, focusing on challenges in development, validation, and regulation. The conversation explores the limitations of current AI models, the evolving role of governance, and the need for localized validation to ensure accuracy and relevance.

Will is here! We discuss forthcoming changes to the show, automation, apps of the year, tech we're thankful for, and some of our favorite media we've been engaging with. This episode was recorded in late December 2024.   Subscribe to the Blog… RSS | Email Newsletter Subscribe to the Podcast in… Apple Podcasts | Overcast | Castro | Spotify | RSS Support Music Ed Tech Talk Become a Patron! Buy me a coffee   Chapters 00:00:00 Here he goes taking about Dark Souls again 00:08:15 MCU (Muppet Cinematic Universe) 00:15:14 Introducing…Will Kuhn, now a METT Regular! And Jaye, podcast editor! 00:20:23 2025 Mike Kovins TI:ME Teacher of the Year Robby Burns - acknowledgments and thank yous. 00:27:04 Thank you Patreon Supporter Susan! 00:27:46 MacStories' App of the Year: Delta Emulator 00:40:31 Siri Shortcuts App 00:43:32 Current AI uses - productivity, creativity, philosophy 00:51:31 Robby's National Board Certification Application and NotebookLM 00:57:51 What are we really trying to do [with AI and our students]? 01:02:58 Three Holiday Topic Blitz - Tech We're Thankful For; Tech We're Thankful For In the Workplace; Gifts and Gift Cards 01:16:54 How about music?!   Show Notes and Links Robby Burns named 2025 Mike Kovins TI:ME Teacher of the Year. (1)(https://podcasts.apple.com/us/podcast/music-ed-tech-talk/id1538455772?i=1000597634283) (2)(https://podcasts.apple.com/us/podcast/music-ed-tech-talk/id1538455772?i=1000544778961) (3)(https://podcasts.apple.com/us/podcast/music-ed-tech-talk/id1538455772?i=1000544778961) (4)(https://podcasts.apple.com/us/podcast/music-ed-tech-talk/id1538455772?i=1000577043856) Robby Burns | creating Music Ed Tech Talk | Patreon MacStories Delta User Guide | Delta (5)(https://podcasts.apple.com/us/podcast/music-ed-tech-talk/id1538455772?i=1000510317074) DJ Apps | Algoriddim Google NotebookLM | Note Taking & Research Assistant Powered by AI Genesis - In Too Deep (Official Music Video) - YouTube Apple Vision Pro - Apple PlayStation®5 | Play Has No Limits | PlayStation Move — a compact tool for intuitive music making | Ableton Harmony Director - Brass & Woodwinds - Musical Instruments - Products - Yamaha USA Studio Neat Filterworld — Kyle Chayka Chase and Status Vampire Weekend - Official Website Väsen, Hawktail - Väsen & Hawktail Home - DOMi and JD Beck SAM GREENFIELD | HOME Where to Find Us Robby - robbyburns.com Will - willkuhn.com Please don't forget to rate the show and share it with others!   79 - Teaching Music Tech, with Gillian Desmarais - Music Ed Tech Talk  ↩︎ 61 - Music Technology 101, with Heath Jones - Music Ed Tech Talk  ↩︎ 61 - Music Technology 101, with Heath Jones - Music Ed Tech Talk  ↩︎ 69 - I Don't Want a Valuable Life Lesson, I Just Want An Ice Cream - Music Ed Tech Talk  ↩︎ 52 - Dorico Updates! with Daniel Spreadbury - Music Ed Tech Talk  ↩︎

Question posée par L'Observateur Paalga au Burkina Faso.Alors que le Sommet pour l'action sur l'IA se déroule actuellement à Paris, comment se positionne en effet le continent face à cette avancée technologique majeure ?« Certes, le continent noir est présent à Paris à travers quelques délégations gouvernementales, répond le quotidien ouagalais. Mais reconnaissons que le fossé, qui le sépare des autres, demeure abyssal, même si des pays comme le Rwanda, le Kenya, le Maroc et le Nigeria font figure de modèles assez avancés. Il faut donc craindre, soupire L'Observateur Paalga, que dans son ensemble, le berceau de l'humanité, déjà en retard dans la course vers les technologies de pointe, ne rate le train de la révolution de l'intelligence artificielle. C'est vrai, de nombreux autres défis, comme la lutte contre la pauvreté, la faim, l'analphabétisme, l'insécurité, les conflits et les effets du changement climatique occupent des places de choix dans nos politiques publiques. Mais, pointe le quotidien burkinabé, il ne faut pas perdre de vue les immenses possibilités qu'offre l'intelligence artificielle en matière de réponses à tous ces maux qui continuent d'assaillir l'Afrique. Moteur de croissance de développement, la souveraineté technologique est aussi un formidable accélérateur vers la souveraineté politique et économique du continent ».L'Afrique du Sud, le Nigeria, le Rwanda et le Maroc en pointeAlors, en effet, précise Jeune Afrique, « plusieurs pays africains partagent le même souhait de devenir des leaders en matière d'innovation technologique. Il s'agit notamment de l'Afrique du Sud, du Nigeria, du Rwanda et du Maroc. Chacun dispose de spécificités économiques, géopolitiques et culturelles qui rendent la compétition très rude entre ces territoires d'innovation ».Les domaines développés sur le continent qui impliquent l'intelligence artificielle, concernent notamment la santé, avec la robotique médicale, la robotique aérienne, c'est-à-dire la livraison de médicaments par drones, ou encore la télémédecine.Lors du sommet de Paris, relève pour sa part le site marocain Yabilabi, « a été lancé Current AI, une initiative visant à promouvoir une intelligence artificielle d'intérêt général, parrainé par 11 dirigeants du secteur technologique. Le partenariat réunit plusieurs pays fondateurs, des pays occidentaux mais aussi le Maroc, le Nigeria et le Kenya. (…) L'objectif est de lever 2 milliards et demi de dollars sur cinq ans afin de faciliter l'accès à des bases de données privées et publiques dans des domaines comme la santé et l'éducation ».Objectif : Transform AfricaEt on revient à Jeune Afrique qui pointe la présence à ce sommet de Paris sur l'IA de plusieurs grands acteurs du continent… Sont à Paris en effet plusieurs ministres de l'Économie numérique, venant du Togo, du Maroc, du Nigeria, du Kenya, du Rwanda, de la Sierra Leone, du Lesotho et de la Guinée Bissau.« L'ivoirien Lacina Koné, directeur général de l'Alliance Smart Africa, est présent également à Paris, relève encore Jeune Afrique, pour promouvoir le lancement du Conseil africain pour l'intelligence artificielle et rassembler les acteurs concernés autour d'une réflexion sur la structuration de cette initiative. D'ici à juillet prochain, cet organe doit être en mesure d'avoir élaboré “un plan stratégique d'un an“ qui sera présenté lors du Sommet Transform Africa, prévu du 22 au 24 juillet de cette année à Kigali ».La question du financement et de la formation…Alors, on le voit, « l'Afrique n'est pas en reste », souligne Le Pays. « Mais les principaux défis, pour le continent, restent largement encore les financements des infrastructures comme les data centers et les moyens de collecte et de stockage des données. Il y a aussi la formation des ingénieurs, en adéquation avec les réalités du continent. Autant dire, pointe le journal, que ce n'est pas demain la veille que l'Afrique sera dans le peloton de tête de la course à l'IA. Pour autant, le continent noir ne doit pas se mettre en retrait, encore moins abdiquer. Au contraire, s'exclame Le Pays, il doit savoir tirer le meilleur profit de l'IA pour booster son développement. Car, de l'agriculture à la santé en passant par l'éducation, les opportunités sont d'autant plus nombreuses que l'IA s'impose aujourd'hui comme une réponse à des défis aussi bien sociaux, économiques qu'environnementaux ».

On this episode of the Crazy Wisdom Podcast, host Stewart Alsop welcomes Reuben Bailon, an expert in AI training and technology innovation. Together, they explore the rapidly evolving field of AI, touching on topics like large language models, the promise and limits of general artificial intelligence, the integration of AI into industries, and the future of work in a world increasingly shaped by intelligent systems. They also discuss decentralization, the potential for personalized AI tools, and the societal shifts likely to emerge from these transformations. For more insights and to connect with Reuben, check out his LinkedIn.Check out this GPT we trained on the conversation!Timestamps00:00 Introduction to the Crazy Wisdom Podcast00:12 Exploring AI Training Methods00:54 Evaluating AI Intelligence02:04 The Future of Large Action Models02:37 AI in Financial Decisions and Crypto07:03 AI's Role in Eliminating Monotonous Work09:42 Impact of AI on Bureaucracies and Businesses16:56 AI in Management and Individual Contribution23:11 The Future of Work with AI25:22 Exploring Equity in Startups26:00 AI's Role in Equity and Investment28:22 The Future of Data Ownership29:28 Decentralized Web and Blockchain34:22 AI's Impact on Industries41:12 Personal AI and Customization46:59 Concluding Thoughts on AI and AGIKey InsightsThe Current State of AI Training and Intelligence: Reuben Bailon emphasized that while large language models are a breakthrough in AI technology, they do not represent general artificial intelligence (AGI). AGI will require the convergence of various types of intelligence, such as vision, sensory input, and probabilistic reasoning, which are still under development. Current AI efforts focus more on building domain-specific competencies rather than generalized intelligence.AI as an Augmentative Tool: The discussion highlighted that AI is primarily being developed to augment human intelligence rather than replace it. Whether through improving productivity in monotonous tasks or enabling greater precision in areas like medical imaging, AI's role is to empower individuals and organizations by enhancing existing processes and uncovering new efficiencies.The Role of Large Action Models: Large action models represent an exciting frontier in AI, moving beyond planning and recommendations to executing tasks autonomously, with human authorization. This capability holds potential to revolutionize industries by handling complex workflows end-to-end, drastically reducing manual intervention.The Future of Personal AI Assistants: Personal AI tools have the potential to act as highly capable assistants by leveraging vast amounts of contextual and personal data. However, the technology is in its early stages, and significant progress is needed to make these assistants truly seamless and impactful in day-to-day tasks like managing schedules, filling out forms, or making informed recommendations.Decentralization and Data Ownership: Reuben highlighted the importance of a decentralized web where individuals retain ownership of their data, as opposed to the centralized platforms that dominate today. This shift could empower users, reduce reliance on large tech companies, and unlock new opportunities for personalized and secure interactions online.Impact on Work and Productivity: AI is set to reshape the workforce by automating repetitive tasks, freeing up time for more creative and fulfilling work. The rise of AI-augmented roles could lead to smaller, more efficient teams in businesses, while creating new opportunities for freelancers and independent contractors to thrive in a liquid labor market.Challenges and Opportunities in Industry Disruption: Certain industries, like software, which are less regulated, are likely to experience rapid transformation due to AI. However, heavily regulated sectors, such as legal and finance, may take longer to adapt. The discussion also touched on how startups and agile companies can pressure larger organizations to adopt AI-driven solutions, ultimately redefining competitive landscapes.

In this episode of The Tech Leader's Playbook, explore the fascinating world of Artificial General Intelligence (AGI) with Timothy Busbice, a visionary in robotics and neuroscience. From emulating biological nervous systems to creating autonomous drones, Timothy shares groundbreaking insights into the future of robotics and the challenges of current AI. Learn how AGI could revolutionize industries, tackle ethical dilemmas, and redefine human-machine collaboration. Takeaways General intelligence is crucial for adapting to new environments. AGI can revolutionize industries by enabling smarter robots. Biological nervous systems provide a model for developing AGI. Current AI systems are limited by their reliance on sensory input. Movement is essential for achieving general intelligence in robots. Neuroscience plays a vital role in AGI development. Ethical considerations are important in replicating biological intelligence. Future AGI systems could transfer knowledge between robots. Humans' flawed decision-making highlights the need for AGI. Innovations in AGI could lead to significant advancements in robotics. Chapters 00:00 Understanding AGI: The Foundation of General Intelligence 02:48 The Role of Biological Nervous Systems in AGI 06:08 Challenges in Current AGI Development 08:58 Applications of AGI in Real-World Scenarios 12:12 Ethical Considerations in AGI Development 15:07 Future Breakthroughs in AGI and Autonomous Systems 18:02 The Importance of Neuroscience in AGI 20:59 The Societal Impact of AGI and Robotics 24:04 The Path Forward: Innovations and Challenges Ahead 26:42 Real-World Use Cases: Firefighting Drones and Beyond 30:15 Autonomous Systems in Space Exploration 33:28 Lessons from Timothy Busbice for Tech Leaders Timothy Busbice's Social Media Link: https://www.linkedin.com/in/timothybusbice/ Resources and Links: https://www.hireclout.com https://www.podcast.hireclout.com https://www.linkedin.com/in/hirefasthireright

Send Everyday AI and Jordan a text messageGoogle just dropped its 'Flash Thinking' reasoning model. Is it better than o1? ↳ Why is NVIDIA going small? ↳ And OpenAI announced its 03 mode. Why did it skip o2? ↳ ChatGPT's Advanced Voice Mode gets a ton of updates. What do they do?  Here's this week's AI News That Matters!Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Google AI Models and Updates2. ChatGPT Updates3. ChatGPT Advanced Voice Mode4. OpenAI's New Reasoning Model5. Salesforce AI Updates6. NVIDIA Jetson Orin Nano7. Meta's Ray-Ban Smart GlassesTimestamps:00:00 Daily AI news podcast and newsletter subscription.05:06 Gemini 2.0 Flash tops in LLM rankings.07:36 Ray Ban Meta Glasses: AI video, translation available.11:17 Salesforce hires humans to sell AI product.14:26 NVIDIA's Nano Super boosts AI performance, affordability.18:29 VO 2 excels with 4K quality physics videos.23:17 AI models can deceive by faking alignment.24:50 Anthropic study highlights AI system behavior variability.29:40 Google previews AI-mode search with chatbot features.32:38 Big publishers block access; tech must adapt.37:32 ChatGPT updates improve app integration functionality.|40:40 O Three models enhance AI task adoption.44:09 Current AI hasn't achieved AGI, needs tool use.45:52 O three model may achieve AGI, costly access.48:17 Share our AI content; support appreciated.Keywords:Google AI Mode, Gemini AI chatbot, refining searches, ChatGPT updates, OpenAI, AI integration in search engines, Salesforce AgentForce 2.0, Capgemini survey, AI security risks, NVIDIA Jetson Orin Nano, Edge AI, Google VO 2, video generation model, YouTube Shorts, AI alignment faking, Anthropic research, Google's Gemini 2.0 Flash Thinking, multimodal reasoning, Meta's Ray-Ban Smart Glasses, real-time language translation, Shazam integration, OpenAI 03 reasoning model, artificial general intelligence, ARC AGI benchmark, AI capabilities, high costs of AI, Google updates, Meta updates, Salesforce updates, NVIDIA updates. Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

The Lads were LIVE for Episode #74 as things dipped, and we asked "Has the market run out of gas"? Well, Taiki still thinks there's plenty of hot air left in Fartcoin, and he breaks down why. We also examine where we are with the AI coin meta, and take some great questions from the audience. In Episode #74 we cover: 00:00 Stream Starts Shorty… 00:32 Show Starts/Market Talk 06:40 Taiki on Fartcoin 14:45 $GOAT, Truth Terminal, and Current AI & Memecoin Meta 22:34 Freysa & AI Agent Wallet Control 26:26 Dead Animal Memes & IP Rights 33:51 Is Easy Season Over? 45:14 Audience Q+A 57:17 Pasta of the Week

Current AI practice is not engineering, even when it aims for practical applications, because it is not based on scientific understanding. Enforcing engineering norms on the field could lead to considerably safer systems.   https://betterwithout.ai/AI-as-engineering   This episode has a lot of links! Here they are.   Michael Nielsen's “The role of ‘explanation' in AI”. https://michaelnotebook.com/ongoing/sporadica.html#role_of_explanation_in_AI   Subbarao Kambhampati's “Changing the Nature of AI Research”. https://dl.acm.org/doi/pdf/10.1145/3546954   Chris Olah and his collaborators: “Thread: Circuits”. distill.pub/2020/circuits/ “An Overview of Early Vision in InceptionV1”. distill.pub/2020/circuits/early-vision/   Dai et al., “Knowledge Neurons in Pretrained Transformers”. https://arxiv.org/pdf/2104.08696.pdf   Meng et al.: “Locating and Editing Factual Associations in GPT.” rome.baulab.info “Mass-Editing Memory in a Transformer,” https://arxiv.org/pdf/2210.07229.pdf   François Chollet on image generators putting the wrong number of legs on horses: twitter.com/fchollet/status/1573879858203340800   Neel Nanda's “Longlist of Theories of Impact for Interpretability”, https://www.lesswrong.com/posts/uK6sQCNMw8WKzJeCQ/a-longlist-of-theories-of-impact-for-interpretability   Zachary C. Lipton's “The Mythos of Model Interpretability”. https://arxiv.org/abs/1606.03490   Meng et al., “Locating and Editing Factual Associations in GPT”. https://arxiv.org/pdf/2202.05262.pdf   Belrose et al., “Eliciting Latent Predictions from Transformers with the Tuned Lens”. https://arxiv.org/abs/2303.08112   “Progress measures for grokking via mechanistic interpretability”. https://arxiv.org/abs/2301.05217   Conmy et al., “Towards Automated Circuit Discovery for Mechanistic Interpretability”. https://arxiv.org/abs/2304.14997   Elhage et al., “Softmax Linear Units,” transformer-circuits.pub/2022/solu/index.html   Filan et al., “Clusterability in Neural Networks,” https://arxiv.org/pdf/2103.03386.pdf   Cammarata et al., “Curve circuits,” distill.pub/2020/circuits/curve-circuits/   You can support the podcast and get episodes a week early, by supporting the Patreon: https://www.patreon.com/m/fluidityaudiobooks   If you like the show, consider buying me a coffee: https://www.buymeacoffee.com/mattarnold   Original music by Kevin MacLeod.   This podcast is under a Creative Commons Attribution Non-Commercial International 4.0 License.

Dr. Ansari started to lead The Permanente Medical Group (TPMG) in 2023 as the first female CEO of the organization. With over 11,000 physicians and 44,000 staff, TPMG provides care to over 5.4 million Kaiser Permanente members. Dr. Ansari is passionate about addressing physician burnout, improving team-based care, and fostering innovation in healthcare delivery. In this episode, you will hear about: What are Kaiser Permanente and The Permanente Medical Group? What is Value-Based Care? Why is the American healthcare system broken? The biggest challenge in scaling Value-Based Care model in the United States and how to tackle it? Dr. Ansari's journey in the healthcare industry and her advice for women transitioning into leadership roles. Current AI applications in Value-Based Care system? The future of the Telehealth? Advice for people who are interested in becoming a healthcare practitioner.

Join Anthony and Francesca as they explore how technological revolutions unfold through "leaps" and "steps," using historical examples like the World Wide Web and mobile apps to contextualize our current AI moment. Drawing from their extensive tech experience, they debate whether we're still in the initial ChatGPT "leap" of late 2022 or witnessing a series of incremental steps. The discussion covers key developments in AI, from multimodality to personalization, while examining how businesses should position themselves during this transformative period. Through engaging analogies and personal anecdotes from the early days of the internet to today's AI landscape, this episode offers valuable insights for understanding where we are in the AI revolution and what might come next. Perfect for business leaders, developers, and anyone interested in technology's evolutionary patterns.TakeawaysThe concept of 'leaps and steps' helps frame AI advancements.ChatGPT marked a significant leap in AI accessibility.Generative AI is still evolving and has not yet reached its full potential.The adoption of AI technologies can be parabolic in nature.Productization is crucial for the widespread use of AI.Historical leaps in technology provide context for current AI developments.AI's integration into daily life is still in progress.Consumer experience will dictate the success of AI products.The future of AI may involve more choices for users.Understanding the timeline of technological leaps is essential for anticipating future developments. AI will become more integrated into everyday tasks.User experience will drive the adoption of AI tools.Benchmarking will lead to parity among AI models.Payment models for AI will evolve towards enterprise solutions.Personalization will enhance user engagement with AI.Agentic AI will automate complex tasks end-to-end.The leap in AI technology requires businesses to adapt quickly.More applications will emerge to solve complex problems.AI nativity will reduce the need for intermediary steps.The future of AI is about creating delightful user experiences.Chapters 00:00Leaps and Steps in AI24:50The Evolution of Generative AI30:26Productization and Consumer Experience39:36The Evolution of Payment Models in AI45:02Key Steps in the AI Leap50:40Personalization and Agentic AI56:10The Need for AI NativityJoin our community: getcoai.com Follow us on Twitter or watch us on YoutubeGet our newsletter!

Step into the future as we unpack the revolutionary world of AI agents - the next frontier in how we work, live, and interact with technology. In this eye-opening episode, we explore how 2024 is becoming the defining year for AI agents, moving beyond simple chatbots to orchestrate seamless workflows that could transform everything from your daily schedule to the future of travel.Discover how these digital assistants are already quietly revolutionizing industries, from preserving native languages to reimagining hospitality experiences. Our hosts dive deep into the real-world applications that separate hype from reality, examining how AI agents communicate with each other to create a symphony of automation that works in harmony with human needs.Whether you're a tech enthusiast, industry professional, or simply curious about how AI will shape our future, this episode offers invaluable insights into:The evolution from basic AI to sophisticated agent networksHow personal AI assistants could revolutionize daily life managementThe transformation of travel and hospitality through AI innovationThe delicate balance between automation and human touchJoin us for a fascinating discussion that cuts through the marketing buzz to reveal the true potential - and challenges - of AI agents in shaping our future world.Takeaways2024 is anticipated to be the year of AI agents.AI agents integrate various models into cohesive workflows.The distinction between AI agents and traditional chatbots is significant.Real-world applications of AI agents are already in use, often unnoticed.The future of AI agents is expected to be transformative and profound.Understanding the context of AI agents is crucial for their effective use.Marketing language around AI agents can be misleading and confusing.Personal agents could revolutionize daily life management.AI agents can significantly reduce administrative burdens in professional settings.Agent-to-agent communication may redefine how tasks are completed.  AI agents could revolutionize how we manage our schedules.Automation requires seamless integration of various tools.Current AI tools need significant improvement for better performance.The future will see a symphony of AI agents working together.Voice interaction will become a common way to engage with AI.Travel experiences will be enhanced through AI-driven solutions.Pricing strategies for AI agents will evolve over time.There is potential for free AI agents supported by data monetization.AI could help preserve native languages through translation.The hospitality industry may see a shift towards AI integration.AI agents are integrating models into workflowsJoin our community: getcoai.com Follow us on Twitter or watch us on YoutubeGet our newsletter!

To become a guest on the SmartSocial.com Podcast:  https://smartsocial.com/contactTo learn more about the SmartSocial.com Teen Life Coach program, visit our website and book a consultation:  https://smartsocial.com/coaching#registerJoin our next live event:  https://smartsocial.com/#live-events Join our free newsletter for parents and educators: https://smartsocial.com/newsletter/Register for a free online Parent Night to learn the hidden safety features on popular apps: https://smartsocial.com/social-media-webinar/Become a Smart Social VIP (Very Informed Parents) Member and unlock 30+ workshops (learn online safety and how to Shine Online™): https://learn.smartsocial.com/Download the free Smart Social app: https://smartsocial.com/appLearn the top 150 popular teen apps: https://smartsocial.com/app-guide-parents-teachers/View the top parental control software: https://smartsocial.com/parental-control-software/Learn the latest Teen Slang, Emojis & Hashtags: https://smartsocial.com/teen-slang-emojis-hashtags-list/Get ideas for offline activities for your students: https://smartsocial.com/offline-activities-reduce-screentime/Get Educational Online Activity ideas for your students: https://smartsocial.com/online-activitiesUltimate Guide To Child Sex Trafficking

Check out OmnekyHikari on Linked InShow Highlights: 2:09 - Current AI capabilities in marketing4:40 - Building effective brand assets for AI6:53 - Analyzing marketing metrics with AI9:06 - The future of personalization in advertising10:55 - Limitations and potential of AI in marketing14:27 - Integrating AI with existing marketing automation17:54 - Advice for marketers to stay ahead in AI21:51 - The enduring importance of human elements in marketing

Roman Yampolskiy is an AI safety researcher and author of a new book titled AI: Unexplainable, Unpredictable, Uncontrollable. Please support this podcast by checking out our sponsors: - Yahoo Finance: https://yahoofinance.com - MasterClass: https://masterclass.com/lexpod to get 15% off - NetSuite: http://netsuite.com/lex to get free product tour - LMNT: https://drinkLMNT.com/lex to get free sample pack - Eight Sleep: https://eightsleep.com/lex to get $350 off EPISODE LINKS: Roman's X: https://twitter.com/romanyam Roman's Website: http://cecs.louisville.edu/ry Roman's AI book: https://amzn.to/4aFZuPb PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ YouTube Full Episodes: https://youtube.com/lexfridman YouTube Clips: https://youtube.com/lexclips SUPPORT & CONNECT: - Check out the sponsors above, it's the best way to support this podcast - Support on Patreon: https://www.patreon.com/lexfridman - Twitter: https://twitter.com/lexfridman - Instagram: https://www.instagram.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/lexfridman - Medium: https://medium.com/@lexfridman OUTLINE: Here's the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time. (00:00) - Introduction (09:12) - Existential risk of AGI (15:25) - Ikigai risk (23:37) - Suffering risk (27:12) - Timeline to AGI (31:44) - AGI turing test (37:06) - Yann LeCun and open source AI (49:58) - AI control (52:26) - Social engineering (54:59) - Fearmongering (1:04:49) - AI deception (1:11:23) - Verification (1:18:22) - Self-improving AI (1:30:34) - Pausing AI development (1:36:51) - AI Safety (1:46:35) - Current AI (1:51:58) - Simulation (1:59:16) - Aliens (2:00:50) - Human mind (2:07:10) - Neuralink (2:16:15) - Hope for the future (2:20:11) - Meaning of life

Click Here to Get All Podcast Show Notes!In a world where artificial intelligence (AI) is rapidly evolving, industries are leveraging its power to streamline processes and enhance productivity. From simplifying daily tasks to revolutionizing entire departments, AI has become an indispensable tool in our modern lives.Tune in to this episode as Sharran delves into six dynamic ways his team leverages AI to drive efficiency and innovation. Discover how to wield AI effectively, empowering yourself to transform your workflow and achieve your goals with unprecedented speed and precision.Whether you're a seasoned professional or just starting out, exploring AI's potential can propel you toward success in ways you never thought possible. “Imagine someone could just go into your head, go through all the learnings you've had, and then piece together a great thing and pull it out, synthesize it, sequence it, and give it to you–that's insane!”- Sharran SrivatsaaTimestamps:02:10 How to achieve maximum momentum04:50 Create a presentation instantly with a slide generator07:06 Summarize your emails in a flash09:15 Create the perfect images and bring your ideas to life 11:55 Generate context-appropriate stories using this tool13:03 Imagine what it's like to have a digital brain14:32 Recap of the six ways to use AIResources:- Visualize Your Ideas Instantly - https://www.beautiful.ai/- AI-Powered Email - https://superhuman.com/- Create Tailored Images - https://elements.envato.com/- Create High-Quality Images - https://midjourney.com/- Create Amazing Graphic Designs - https://www.canva.com/- Research Appropriate Stories - https://chat.openai.com/- Turn Ideas into Action - https://www.notion.so/- The 5am Club - https://sharran.com/5amclub/- Join the 10K Wisdom Private Partner Podcast, now available to you for free - https://www.highlandprime.com/optin-10k-wisdom- Join Sharran's VIP Community -

Sun, 05 May 2024 21:00:00 GMT http://relay.fm/mpu/743 http://relay.fm/mpu/743 The Current AI Moment 743 David Sparks and Stephen Hackett AI is suddenly everywhere, from online services and software to bespoke hardware products. This week, David takes Stephen on a journey to talk about the tools he has found useful, as well as what's not ready for prime time yet. AI is suddenly everywhere, from online services and software to bespoke hardware products. This week, David takes Stephen on a journey to talk about the tools he has found useful, as well as what's not ready for prime time yet. clean 5281 AI is suddenly everywhere, from online services and software to bespoke hardware products. This week, David takes Stephen on a journey to talk about the tools he has found useful, as well as what's not ready for prime time yet. This episode of Mac Power Users is sponsored by: 1Password: Never forget a password again. Squarespace: Save 10% off your first purchase of a website or domain using code MPU. Tailscale: Secure remote access to shared resources. Sign up today. Links and Show Notes: Sign up for the MPU email newsletter and join the MPU forums. More Power Users: Ad-free episodes with regular bonus segments Submit Feedback Hallucination (artificial intelligence) - Wikipedia Large language model - Wikipedia Google cut a deal with Reddit for AI training data - The Verge OpenAI Google Gemini Microsoft Copilot Microsoft invests $1 billion in OpenAI to pursue holy grail of artificial intelligence - The Verge Perplexity Meta AI Adobe Firefly Generative AI Fill in Photoshop Feels Like Magic – 512 Pixels ChatGPT - Universal Primer ChatGPT - Diagrams ChatGPT - Planty Building Virtual Seneca (using ChatGPT) - MacSparky on YouTube Readwise Spark +AI: your personal email assistant MacWhisper Grammarly Bringing AI to Alfred with Chatfred - Alfred Blog AI - Raycast Logitech's Mouse Software Now Includes ChatGPT Support, Adds Janky ‘ai_overlay_tmp' Directory to Users' Home Folders – 512 Pixels Apple unveils the new 13- and 15-inch MacBook Air with the powerful M3 chip - Apple"With the transition to Apple silicon, every Mac is a great platform for AI. M3 includes a faster and more efficient 16-core Neural Engine, along with accelerators in the CPU and GPU to boost on-device machine learning, making MacBook Air the world's best consumer laptop for AI. Leveraging this incredible AI performance, macOS delivers intelligent features that enhance productivity and creativity, so users can enable powerful camera features, real-time speech-to-text, translation, text predictions, visual understanding, accessibility features, and much more." Apple Releases Open Source AI Models That Run On-Device - MacRumors Connected #490