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We just launched our new book! You can grab The Power of Your Personal Brand: A Playbook for Struggling Middle Managers Who Want to Do Big Things on Amazon or at ForthRight-People.com AI is pulling from Large Language Models (LLMs), which means what it generates is really an amalgamation of what already exists. It's hard to own the attribution of this content. And, it often comes off sounding like AI and not you. But, what if you were intentional in the way you train AI to represent you in voice and POV? This could be a game-changer. We wanted you to learn from a couple experts who know how to leverage AI marketing to own your POV, so we welcomed on Patrice Greene & Kathy Macchi, the Co-Founders of Inverta. They're the #1 AI-powered B2B growth marketing agency. For more about ForthRight Business by ForthRight People or for 1:1 consultation, check us out at ForthRight-Business.com And as always, if you need Strategic Counsel, don't hesitate to reach out to us at: ForthRight-People.com FACEBOOK https://www.facebook.com/forthrightpeople.marketingagency INSTAGRAM https://www.instagram.com/forthrightpeople/ LINKEDIN https://www.linkedin.com/company/forthright-people/ RESOURCES https://www.forthright-people.com/resources VIRTUAL CONSULTANCY https://www.forthright-people.com/shop
In this episode of Elixir Wizards, Charles Suggs and Emma Whamond are joined by Zach Daniel, creator of the Ash Framework and Igniter, VP of Engineering at Remedy Meds, and upcoming ElixirConf keynote speaker, to talk about what sits between an LLM and useful engineering work. Zach reflects on how much has changed since his last appearance on the podcast in October 2024, moving from Igniter, code generation, and project patching into AI agents, context layers, and custom engineering workflows. The conversation explores how deterministic tools and probabilistic LLMs can work together, and why the most useful AI systems often depend on the structure built around the model. We also discuss why teams should be careful about outsourcing the systems that hold their organizational knowledge and decision-making. He shares his perspective on owning the AI stack, building internal knowledge systems, training junior developers in an AI-augmented world, avoiding vendor lock-in, and why Elixir may be especially well-suited for safer agentic workflows. Zach will be a keynote speaker at ElixirConf 2026, September 10–11 in Chicago, and the Elixir Wizards will be there too! Join us and the broader Elixir community, and use promo code Elixirwizards for 10% off in-person or virtual tickets at https://elixirconf.com/ Key topics discussed in this episode: Zach Daniel's work with Ash, Igniter, and AI tooling How software development has changed since 2024 Deterministic code generation vs. LLM-generated code Combining structured tools with AI agents What it means to own your AI stack Organizational knowledge as an engineering “spinal column” Context layers, documentation, and internal workflows Building custom agentic systems Security, vendor lock-in, and open source LLMs Junior developers and apprenticeship in the AI era Why Elixir and the BEAM fit agentic workflows Links mentioned: Ash Framework https://ash-hq.org/ Igniter https://igniter.hexdocs.pm/ Phoenix Framework https://www.phoenixframework.org/ Remedy Meds https://remedymeds.com/ Keynote: Code Generators are Dead. Long Live Code Generators - Chris McCord | ElixirConf EU 2025 https://www.youtube.com/watch?v=ojL_VHc4gLk https://phoenix.hexdocs.pm/Mix.Tasks.Phx.Gen.Live.html LSP https://en.wikipedia.org/wiki/Language_Server_Protocol Claude Code https://claude.com/product/claude-code GitHub Actions https://github.com/features/actions Harness Engineering https://en.wikipedia.org/wiki/Agent_harness Claude SDK https://code.claude.com/docs/en/agent-sdk/overview Zach's Twitter https://x.com/ZachSDaniel1 ElixirConf https://elixirconf.com/ AshConf https://luma.com/wz4z0iz6 Goatmire https://goatmire.com/Special Guest: Zach Daniel.
Supply chain benchmarking has been evolving rapidly, but the biggest shifts in driving true organizational value may still be unfolding. In this episode of Supply Chain Now, Scott W. Luton and Lora Cecere (Founder of Supply Chain Insights), are joined by Dave Winstone (Global Director, Supply Chain Excellence at Dow) and Wael Abdelmalek (CEO of Uthereal). Together, they explore what it truly means to define and measure supply chain excellence, moving from rigid historical spreadsheets to data-driven, dynamic benchmarking and human-AI partnership. The panel highlights how 32 top-performing companies outperformed the market by focusing on metrics that correlate directly to market cap rather than a simple popularity contest. Dave draws on nearly four decades of global leadership to make the case for focusing on portfolio rationalization and network design while bypassing traditional distractions like massive ERP implementations. Meanwhile, Wael shares how agentic AI platforms can condense 15 years of industry-leading research into minutes, creating a powerful learning engine that works alongside humans to scale organizational insights. The guests share the core operational pillars that separate top performers from the rest of the market: leadership alignment, clear strategic direction, customer focus, and balanced performance scorecards. By embracing data objectivity and the power of dynamic orbit charts, they demonstrate how leaders can have tough, uncomfortable conversations at the board level to navigate macroeconomic headwinds and unlock real, sustainable growth. Jump into the conversation: (00:00) Intro (02:29) The journey behind Ask Lora (03:39) Dave Winstone's background at Dow (08:18) Divisional benchmarking and collaboration history (09:16) The data-driven origins of Supply Chains to Admire (11:59) Building relevant industry sectors and peer groups (13:30) Improvement vs. performance in maturity (14:26) Measuring what matters over popularity contests (15:58) Comparing Supply Chains to Admire with the Gartner Top 25 (16:36) Looking at industry headwinds through orbit charts (19:45) Stripping out subjectivity in industry lists (20:36) Why small companies outperform large ones (21:42) Traditional best practices vs. historic pitfalls (23:27) Revealing the 2026 Supply Chains to Admire winners (26:05) Core pillars: What the top performers have in common (30:27) Ask Lora: Dynamic benchmarking through agentic AI (33:32) Wael Abdelmalek's deep tech and cloud architecture background (37:32) Leveraging proprietary algorithms and agentic behavior (41:45) Demonstration: How to use Ask Lora (47:36) Testing scalability and breaking the model (51:05) Shifting the cross-functional dialogue at the board level (54:22) Key lessons from the panel Additional Links & Resources: Connect with Lora Cecere: https://www.linkedin.com/in/loracecere/ Connect with Dave Winstone: https://www.linkedin.com/in/dave-winstone-79337a34/ Connect with Wael Abdelmalek: https://www.linkedin.com/in/wwael/ Learn more about Supply Chain Insights: http://www.supplychaininsights.com Learn more about Dow: https://www.dow.com/en-us.html Learn more about Uthereal: https://www.uthereal.ai/ Learn more about our hosts: https://supplychainnow.com/about Learn more about Supply Chain Now: https://supplychainnow.com Watch and listen to more Supply Chain Now episodes here: https://supplychainnow.com/program/supply-chain-now Work with us! Download Supply Chain Now's NEW Media Kit: https://supplychainnow.com/media-kit/ WEBINAR- The Future of Supply Chains: Where Talent Meets Technology: https://bit.ly/4uUuxkc WEBINAR- Peak Reality Check: What Shippers, Analysts, and AI Models Are Predicting for 2026: https://bit.ly/4aTlsRv WEBINAR- From Volume to Resilience: How Automotive Supply Chains Are Adapting to a New Market Reality: https://bit.ly/4f6SUGA WEBINAR- The Automotive Industry's Next Digital Breakthrough: https://bit.ly/4vhUwT4 WEBINAR- From Disruption to Stability: Building Resilient Logistics Solutions in a Rapidly Changing Global Market: https://bit.ly/3TguZMt This episode was hosted by Scott Luton and produced by Trisha Cordes, Joshua Miranda, and Amanda Luton. For additional information, please visit our dedicated show page at: https://supplychainnow.com/supply-chains-admire-2026-winners-dynamic-benchmarking-opportunities-1609 The content in this episode, including all audio, videos, visuals, and graphics, is the property of Supply Chain Now and is protected by copyright law. Unauthorized use, reproduction, distribution, modification, or re-uploading of this content in any form is strictly prohibited without explicit written permission from Supply Chain Now.For licensing inquiries or permissions, please contact us at production@supplychainnow.com© 2026 Supply Chain Now. All rights reserved. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
How are large language models changing the way security vulnerabilities are found? Richard chats with Sami Laiho about the rapidly changing landscape in security exploits. Certain LLM models like Anthropic's Mythos and Microsoft MDASH are optimized to find software vulnerabilities - and potentially fix them. And so there is an arms race of sorts, repairing old vulnerabilities before LLMs in the hands of black hats can exploit them. But what about everyone else? Sami talks about getting LLMs working for your organization to test for potential security risks and assess the impact of new vulnerabilities as they appear. Links Palo Alto Networks Claude Mythos Microsoft MDASH Zero Day Clock Security Update Guide Recorded June 19, 2026
See more: https://thinkfuture.comConnect with Andreas https://artios.io ---What if Google isn't your biggest audience anymore... AI is?In this episode of thinkfuture, host Chris Kalaboukis speaks with Andreas, CEO of Artios.io, about one of the biggest shifts happening online: the transition from traditional SEO to AI-powered search.For years, businesses optimized content for Google's algorithms.Now they're competing for something entirely different:AI's attention.Andreas explains why today's internet is overflowing with low-value, AI-generated content—and why that's becoming a major problem for Large Language Models. As the web fills with recycled information, AI systems struggle to distinguish original insight from repetition.His solution?Create research-grade content with genuine information gain.We explore:- Why traditional SEO is rapidly losing effectiveness- How AI search engines decide which sources to trust- Why "research-grade content" outperforms generic AI-written articles- The growing problem of AI hallucinations and synthetic content- How companies can become trusted sources for AI systems- Why Reddit, Quora, and online communities contain untapped market intelligence- The evolution from Large Language Models (LLMs) to Large World Models (LWMs)- How real-world sensory data could dramatically improve AI reliability- Why advanced robotics may become programmable by anyoneAndreas believes the next decade won't simply be about better AI.It will be about better knowledge.If you're interested in AI search, content strategy, SEO, marketing, knowledge management, or the future of AI, this conversation offers a fascinating glimpse into where search is headed next.
Sean Hopwood, Founder and CEO of Day Translations, joins SlatorPod to talk about building a global language solutions integrator (LSI) over the past 20 years, adapting to AI, and why a passion for languages continues to shape the LSI's strategy.Sean reflects on how his entrepreneurial mindset and fascination with languages led him to launch Day Translations, which has grown from handling small community projects into serving enterprise, legal, medical, and government clients while remaining bootstrapped.He explains why human expertise remains central as the LSI adopts AI across its workflows, develops its own large language model for enterprise and government procurement, and plans to commercialize these capabilities while continuing to invest in technology.He discusses the DayInterpreting app, which integrates with Zoom and Microsoft Teams, supports rapid interpreter connections, and is already prepared for AI interpreting when customers require it.He argues that constant learning, business growth, and technological adaptation are essential for long-term success, while also stressing that translation plays a vital role in preserving cultures and protecting linguistic diversity.He concludes by outlining plans to expand the interpreting platform, strengthen the LSI's B2B focus, secure additional compliance certifications, and continue combining human expertise with AI-powered language solutions.
Battlefield medicine is as much an enabler and force multiplier as good logistics. Whilst this is acknowledged by many, including those in the US Army, there is a peculiar absence of consideration for Battlefield Health in selection and development of its new command and control system. Major General (retired) Edward Dorman, a proven combat leader and master logistician, digs into what is needed for medical C2 as an operational consideration in the future, about which lessons are relevant from both US experiences in Iraq and Afghanistan and from partners experiences in Ukraine and wider contemporary conflict. Structured data alone is not the answer, neither is agentic AI, Large Language Models, or boutique systems. The conversation has a realism about Battlefield Medicine and Healthcare that has been absent for too long.
Certain forms of AI are increasingly being experienced as personal contact. In a time of growing anxiety and loneliness, more and more people are turning to LLMs for easy and convincing companionship and advice. What will help me more? Something that mimics personality, sycophantically made in my image? Or someone truly ‘Other', in whose image I am made, offering true sympathy and the challenge of healing and growth? In the Bible this very contrast is literally the difference between an idol and the true Creator and Redeemer. What might that mean for us today? The Copyright for all material on the podcast is held by L'Abri Fellowship. We ask that you respect this by not publishing the material in full or in part in any format or post it on a website without seeking prior permission from L'Abri Fellowship. Also, note that not all views expressed in the lectures or in the discussion time necessarily represent the views of L'Abri Fellowship. © Canadian L'Abri 2020
Law professor Julian Nyarko has drawn attention for his studies using large language models to investigate and improve legal education and explore AI's biases. He hopes AI can become a reliable, always-on legal learning and assistance tool to lower costs and expand access to legal services. In one recent study, he asked a group of law professors to evaluate written answers to student questions. Three-quarters of the time, the professors preferred AI-generated answers to those of their human colleagues. “AI is good at law,” Nyarko says, the challenge now is to use it most effectively, he tells host Russ Altman in this episode of Stanford Engineering's The Future of Everything podcast. Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to thefutureofeverything@stanford.edu. Episode Reference Links: Stanford Profile:Julian Nyarko Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / Facebook Chapters: (00:00:00) Introduction Russ Altman introduces guest Julian Nyarko, a professor of law at Stanford University. (00:02:31) Path into AI and Law How Nyarko's early work led him to legal AI. (00:05:03) Law, Economics, and Computation How Nyarko's training, methods, and self-taught coding shaped his research. (00:07:23) Building the LIFT Lab Why a law professor started a lab. (00:09:06) Evaluating Legal AI How AI raises fundamental questions about what counts as good lawyering. (00:10:22) Improving Legal Services Using AI to work faster, reduce errors, and make informed decisions. (00:10:57) Rethinking Legal Education How AI may change the way future lawyers learn (00:11:51) AI in Office Hours How AI answers law students' questions compared with human professors. (00:15:18) Surprising Results Why AI answers were often preferred (00:16:16) What the Study Shows The findings support AI tutoring, but don't prove AI improves learning. (00:18:48) Limits of One-Shot Answers Why real teaching often depends on dialogue, clarification, and productive struggle. (00:20:59) AI for Social Science How AI can become both an object of study and a tool. (00:22:43) Research Agents Using AI to test claims and make previously impossible research scalable. (00:24:51) Agentic AI in the Lab How Socratic dialogue with AI can sharpen research ideas. (00:26:07) Fairness and Bias How computational tools can be audited for bias and used to audit decision-making. (00:27:29) Discrimination in Models Exploring bias and how it can be reduced. (00:30:16) Disparate Impact How policies and systems disadvantage groups even without explicit intent. (00:32:53) From Evidence to Policy How Nyarko's lab works with stakeholders to surface disparities. (00:34:49) Future In a Minute Rapid-fire Q&A: justice, talent, and the future of legal AI. (00:36:57) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
If life were a video game, then the goal would be to figure out how to manage the circumstances you've been "spawned" into to be happy. So says the Art3mis character in Ready Player Two (I've paraphrased of course). I agree completely which is why I have so many tools to keep my mindset positive, because the reality is, by the time you get to my age (52), life has thrown a lot of curveballs at you and if you don't figure out how to work with them, it's easy to feel beatdown and become negative.In this episode I share with you five of my favorite mindset tips in the hopes that it will help make every day a little bit easier for you.Existential Kink https://amzn.to/3SR8IoAThe Gap and the Gain https://amzn.to/3SR8IoAFour Great Americans https://amzn.to/3SR8IoAHarriet Tubman: The Road to Freedom https://amzn.to/3SR8IoANEXT EPISODE07/16/2026 [SELF-CARE] The Brain Science Behind "Forest Bathing"RESOURCEShttp://5calls.org: make your voice heard!Season of Self-Care: https://bywdreams.mailerpage.com/seasonselfcareWebsite: http://BYWDreams.comMy books: http://TinyURL.com/BYWDbooksI do not give consent for AI or Large Language Models (LLM) to read or be trained on any/all of my content ever no matter what form or platform it is distributed on.
"You want to own the message and your narrative."Strong communication is about more than delivering a message—it's about building trust over time. As Zoom's Chief Marketing Officer, Kim Storin has helped shape communication at one of the world's most recognizable brands, balancing empathy, transparency, and consistency in an era of rapid technological change. In this episode of Think Fast, Talk Smart, Storin joins Matt Abrahams to discuss how leaders can communicate with authenticity, navigate crises with clarity, and build cultures rooted in transparency. They explore the art and science of shaping perception, maintaining connection in hybrid workplaces, and creating messages that solve problems—not just capture attention.Key Takeaways:Lead with authenticity and transparency. Clear, honest communication builds trust—especially during periods of change or crisis.Own your narrative. Consistent messaging and a clear story shape how others understand your brand, team, or ideas.Activity:Before your next team update or difficult conversation, ask yourself: "What information can I share that will build trust?" Include one additional point of context or reasoning that helps your audience better understand the decision.Printable Expanded Takeaways & ActivitiesEpisode Reference Links:Kim StorinEp.82 It's Not About You: Why Effective Communicators Put Others FirstConnect:Premium Signup >>>> Think Fast Talk Smart PremiumEmail Questions & Feedback >>> hello@fastersmarter.ioEpisode Transcripts >>> Think Fast Talk Smart WebsiteNewsletter Signup + English Language Learning >>> FasterSmarter.ioThink Fast Talk Smart >>> LinkedIn, Instagram, YouTubeMatt Abrahams >>> LinkedInChapters:(00:00) - Introduction (01:37) - Leading Through a Global Crisis (03:36) - Changing Brand Perception (06:50) - Building Culture at Scale (09:00) - Virtual Communication Gains & Losses (11:24) - Creating Meaningful Moments (12:34) - Communicating Through Difficulty (16:03) - The Final Three Questions (21:33) - Conclusion ********Thank you to our sponsors. These partnerships support the ongoing production of the podcast, allowing us to bring it to you at no cost.Most Work Platforms Help People Communicate. Some help you organize, but Zoom turns conversations into outcomes. Try Zoom Mate today
These sources explore the evolving landscape of Explainable AI (XAI) and the practical frameworks used to maintain human oversight in automated systems. One source distinguishes between human-in-the-loop, where people must approve actions before execution, and human-on-the-loop, which involves retrospective monitoring of autonomous processes. The other source provides a comprehensive survey on using Large Language Models (LLMs) to translate complex "black box" algorithms into understandable natural language narratives. Together, they address critical architectural tradeoffs regarding latency, risk, and transparency across high-stakes industries like healthcare and finance. By examining various interpretability techniques and oversight patterns, the texts illustrate how to build trust and ensure ethical accountability in artificial intelligence. Ultimately, the materials emphasize that combining automated reasoning with human judgment is essential for creating reliable, user-centric AI workflows.
Relying entirely on the insular viewpoints of dense urban ad hubs can expose enterprise brand campaigns to immediate audience alienation and irreversible reputation damage.Dylan Conroy sits down with Matt Mazzone, Chief Creative Officer at LSKR, to map out the corporate framework used to ground creative assets in nationwide consumer data and business fundamentals.Restructuring Insights: How to gather balanced market facts that capture Middle America demographics to de-risk multi-market funnels.The AEO Optimization Playbook: The technical strategy needed to secure authoritative brand citations inside Large Language Model layouts.Risk and Reputation Defense: Utilizing academic data filters to screen creative concepts and avoid catastrophic campaign blunders.Protecting Shareholder Value: Why C-suite marketing directors must prioritize bottom-line financial health over insular design trends.Matt Mazzone is a prominent public relations executive and the Chief Creative Officer at LSKR, where he directs international brand development, crisis management strategy, and platform-agnostic media deployment.Connect with Matt Mazzone on LinkedIn: https://www.linkedin.com/in/matthew-j-mazzone/Explore the LSKR Corporate Strategy Catalog: https://wearelskr.com/Scale your multi-channel automated performance media investments with Strike Social: https://strikesocial.com/guaranteed-paid-social-media-ads-outcomes/Follow host Dylan Conroy on LinkedIn: https://www.linkedin.com/in/dylanconroy/
As chatbots trained on Large Language Models become more sophisticated, their responses can sometimes seem uncanny, as if they come from a source that is mysterious, inexplicable, or even divine. Webb Keane, Professor of Anthropology at the University of Michigan, examines what happens when people treat artificial intelligence as a kind of “metahuman.” He explains how this reflects a broader human tendency to project authority onto technologies we do not fully understand. Keane explores how that sense of authority emerges through social interaction, and how the unequal ways humans and metahumans address one another can make AI's power feel intuitively real. Series: "Ethics, Religion and Public Life: Walter H. Capps Center Series" [Humanities] [Science] [Show ID: 41542]
As chatbots trained on Large Language Models become more sophisticated, their responses can sometimes seem uncanny, as if they come from a source that is mysterious, inexplicable, or even divine. Webb Keane, Professor of Anthropology at the University of Michigan, examines what happens when people treat artificial intelligence as a kind of “metahuman.” He explains how this reflects a broader human tendency to project authority onto technologies we do not fully understand. Keane explores how that sense of authority emerges through social interaction, and how the unequal ways humans and metahumans address one another can make AI's power feel intuitively real. Series: "Ethics, Religion and Public Life: Walter H. Capps Center Series" [Humanities] [Science] [Show ID: 41542]
As chatbots trained on Large Language Models become more sophisticated, their responses can sometimes seem uncanny, as if they come from a source that is mysterious, inexplicable, or even divine. Webb Keane, Professor of Anthropology at the University of Michigan, examines what happens when people treat artificial intelligence as a kind of “metahuman.” He explains how this reflects a broader human tendency to project authority onto technologies we do not fully understand. Keane explores how that sense of authority emerges through social interaction, and how the unequal ways humans and metahumans address one another can make AI's power feel intuitively real. Series: "Ethics, Religion and Public Life: Walter H. Capps Center Series" [Humanities] [Science] [Show ID: 41542]
As chatbots trained on Large Language Models become more sophisticated, their responses can sometimes seem uncanny, as if they come from a source that is mysterious, inexplicable, or even divine. Webb Keane, Professor of Anthropology at the University of Michigan, examines what happens when people treat artificial intelligence as a kind of “metahuman.” He explains how this reflects a broader human tendency to project authority onto technologies we do not fully understand. Keane explores how that sense of authority emerges through social interaction, and how the unequal ways humans and metahumans address one another can make AI's power feel intuitively real. Series: "Ethics, Religion and Public Life: Walter H. Capps Center Series" [Humanities] [Science] [Show ID: 41542]
Fable 5 is out, but it'll be gone (again) before you know it. While Anthropic's powerful Mythos 5 is out for the masses for another 5 days, it might be their Sonnet 5 model that's your next daily driver. Even better news? If you're an iPhone user, your OpenClaw and Cursor accounts are gonna get a lot more use. Yeah, it's a short Holiday week in the U.S., but the AI companies didn't stop shipping. From new models to new ways to work, these are 7 new AI features available now that you should be using. Fable 5 and Sonnet 5 Released, OpenClaw on Your iPhone, NotebookLM's New Video Format and 7 More AI Features You Need NowNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Anthropic Sonnet 5 Model OverviewSonnet 5 vs Opus 4.8 PerformanceAnthropic Model Naming Confusion ExplainedSonnet 5 Pricing and API Cost AnalysisSonnet 5 Use Cases for Daily WorkNotebookLM 60-Second AI Video GenerationNotebookLM Cinematic Video Format ReviewChatGPT Finance Feature: Plaid IntegrationChatGPT Finance Rollout and Security DetailsTwitter/X MCP Model Context Protocol LaunchMCP API Access for AI Agents ExplainedOpenClaw iOS and Android App LaunchOpenClaw Mobile Bridge Setup and UsageCursor iOS App for AI Code AgentsCursor Cloud Agents and Mobile NotificationsAnthropic Fable 5 Limited-Time AvailabilityFable 5 Cost Structure and GuardrailsAnthropic Frontier Models and US RegulationsTimestamps:00:00 Recent AI developments and updates05:54 API pricing and usage strategies07:19 Choosing the right AI model11:17 Notebook LM paid user rollout16:17 ChatGPT's new personal finance tool17:35 Integrating ChatGPT with Plaid for Finance21:35 Streamlining MCP setup for developers24:40 Introducing the OpenClaw monitoring app29:33 Talking about upcoming super apps32:03 Fable 5 availability announcement34:43 Building projects with Fable 5Keywords: Anthropic, Fable 5, Sonnet 5, Opus 4.8, Haiku 4.5, Mythos 5, Large Language Models, AI model naming, AI benchmarks, agentic models, adaptive thinking, 1 million context window, token output, AI hallucination rates, Anthropic subscription plan, AI API pricing, AI free plans, ChatGPT Finance, Plaid integration, finance AI assistant, OpenAI personal finance, financial data privacy, iOS AI apps, Android AI apps, OpenClaw, open source AI agent, AI mobile companion app, NotebookLM, AI video generation, vertical video, cinematic video, Gemini paid users, educational AI videos, doom scrolling video format, AI-powered coding agents, Cursor, cloud AI agents, remote desktop AI, iOS live activities, PR merge on mobile, X API, Twitter MCP server, social listening AI, developer AI tools, AI super app, project Glasswing, US AI export controls, government AI regulation, classifier guardrails, secure AI data, AI for marketers, subscription replacements, Codex, Claude cowork, Claude code, Codex remote control, always-on AI.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner
Send us Fan MailWhat does AI literacy actually look like for pathologists, researchers, and future clinicians? And how do you teach it in a way that is practical, not abstract?In this episode, I talk with Candice Chu, DVM, PhD about something I think a lot of people in digital pathology and computational pathology are feeling right now: AI is moving fast, but education is still catching up.Candice is a clinical pathologist, veterinarian, and educator building AI-focused teaching and research at Texas A&M. We worked together before on digital pathology and image analysis projects, so this conversation felt especially grounded. We talk about her AI literacy curriculum framework for veterinary education, why she decided to build it, and what it takes to teach AI in a way that is useful, ethical, and realistic.This episode is about understanding what AI tools are good for, where they can waste your time, and why hands-on experience matters. Candice explains why she sees AI as a set of tools, not a belief system. Try them. Learn them. Keep what improves your workflow. Drop what does not.We also talk about the difference between putting educational content online and building formal institutional teaching. That matters because social media can move quickly, but curriculum changes, research, and professional organizations shape longer-term adoption. Candice shares how her course started as a low-stakes elective, then grew into a more structured framework that combines education with publishable research.A big part of this conversation is the curriculum itself. We go through what students actually learn: AI fundamentals without heavy math, machine learning and image analysis, large language models, prompt engineering, chatbot building, ethics, literature research, and final projects where students evaluate real tools and workflows. I liked that the course does not stop at theory. It asks students to use tools, question them, and explain where they help and where they do not.We also get into something that matters far beyond veterinary medicine: professional responsibility. If AI is involved in a workflow, the clinician is still responsible. That includes fabricated citations, bad outputs, weak prompts, and the temptation to trust tools too quickly. Candice makes a strong case that AI education needs ethics, legal context, and interdisciplinary teaching built in from the start.If you are trying to think more clearly about AI in pathology, education, workflow design, or professional training, this episode gives you a concrete example of what responsible AI literacy can look like.Episode Highlights00:00 – Why AI tools are just tools, and why trying them matters even if you later decide not to keep using them00:33 – Who Candice Chu is and why her work on AI literacy in veterinary medicine is worth paying attention to02:33 – Why going back to Texas A&M changed the scale of Candice's AI research and teaching07:53 – How the AI course was designed as a low-stakes elective first, and why that helped student engagement11:16 – Where veterinary AI education stands now, and what professional organizations like ACVP are doing13:08 – Why AI adoption in veterinary medicine is still slow, and what skepticism usually sounds like in practice15:19 – Real examples of how Candice uses LLMs and computer vision in pathology, medical records, and research19:58 – What is actually inside the 15-week AI literacy curriculum, from fundamentals to final projects24:16 – Why ethics and legal responsibility are not optional in AI education31:35 – Why no-code tools and vibe coding are entering the curriculum already38:50 – The AI tools Candice is testing in her own workflow, including Claude, Codex, and PerplexityResources mentionedCandice Chu's AI literacy curriculum framework paper in Frontiers in Veterinary ScienceCandice's earlier work on ChatGPT in veterinary medicineTexas A&M and the institutional setting where Candice is building AI research and teachingMr. Don Riddick and the AVMA AI working group, mentioned in the ethics and legal contextClaude, Codex, and Perplexity as AI tools Candice is actively testingDigital Pathology 101, mentioned in the conversation as a teaching resourceCandice's online educational work on Instagram.Support the showGet the "Digital Pathology 101" FREE E-book and join us!
Dr. Siddhant Dogra sits down with Dr. Su Hwan Kim to discuss how reader experience influences the performance and real world utility of large language models for brain MRI differential diagnosis. Together they explore AI assisted decision making, automation bias, radiology training, and why strong AI performance does not always translate into meaningful clinical benefit. Performing Best When Needed Least: Reader Experience ShapesAccuracy Gains in Large Language Model–assisted Brain MRIDifferential Diagnosis. Schramm et al. Radiology 2026; 319(2):e253477.
How separate is the cognition in our heads from cognition with our bodies, our tools, our communities and our ecosystems? What is participatory sense making and why is our world becoming less and less disposed to doing it? What does connecting cognitively with the world beyond our own bodies do for our sense making, and so for the future of our species?In this episode we have the intriguing topic of extended cognition to explore, and in particular the field of participatory sense-making. So we get into the extended component of the 5E's model of embodied cognition; how our technologies, including AI, are much more influential on our cognition than mere tools that we set aside after use; we talk about our co-dependence on the natural world, and what happens to cognition and our society when our sense of “kinship” with it is lost; And we get into detail on the crucial process of participatory sense making, and how important it is to arrive to consensus rather than getting bogged down in polarisation, which in turn allows us to decide on urgent solutions as a species.Fortunately these are the exact specialisations of our guest, psychologist, cognitive scientist and philosopher at the University of British Columbia, Rebecca Todd. With a background also in neuroscience, she's authored nearly 100 academic papers, whilst her substack hosts her much loved writings for the general What we discuss:00:00 Intro.06:05 Extended cognition defined.08:45 Distributed cognition - Edward Hutchins.09:00 Attention, learning and memory are all distributed.10:00 Can we identify the cognitive boundary between self and other?14:30 Heidegger's warning about undermining the influence of technology.17:00 We give our tools too much credit.19:00 Large Language Model's effect on extended cognition.23:00 Individualistic, extractive, competitive motivations for technology.24:00 Self AS relationship rather than IN relationship - Dr. Yuri Celidwen.28:10 Non-verbal communication.29:46 Feedback loops between nature and our minds.33:50 Connection to nature and mental health.37:20 Belonging and ‘kinship' with the natural world.39:45 Objects can have personality - Object personality Synesthesia.44:20 Risk of appropriation, when applying indigenous ideas of ‘belonging'.46:50 The ‘Trim Tab' analogy — small interventions can lead to big changes in direction, Greg Watson.53:15 Participatory Sense-making explained.57:30 Shifts happen before and after moments of synchrony.59:30 Conditions required for participatory sense-making.01:02:20 The 4 R's: Reciprocity, Respect, responsibility and relevance.01:03:05 Neurodivergence: bridging the way we see the world differently.01:12:15 The new lack of bandwidth for complexity and nuance - information overload.01:15:30 Creating the time and space needed to do participatory sense-making.01:19:30 Food together is a magical ingredient.01:23:30 Openness and listening can be trained.01:24:20 Is consensus necessary.01:29:10 Tolerance of diversity rather than unified consensus.References:Beck Todd Substack, “Towards an ecology of mind”Andy Clarke and David Chalmers, “Extended Cognition” paperEdward Hutchins - Distributed Cognition paper.Fernando Rosas - Statistical boundaries between agents.Karen McClean - SPIN Lab (human-robot interactions through the sense of touch)Shirley Turcotte - Indigenous Focusing-oriented Therapy (IFOT)“Participatory Sense-making with the More than Human World” With Yuri Celidwen.An interview with Dr. Greg Watson - Ex US agricultural ministerHannah De Jaegher & Ezequial Di Poalo, “Participatory Sensemaking, An enactive approach to social cognition”. V.J .Kirkness, “First Nations and Higher Education: the four 4's”“The Multiplicity of Worlds” with Penijean Gracefire et al.Ed Young, “An immense world”“Community Out of the Ashes” with Eli Oda Shina.Gabor Mate, “In the realm of hungry ghosts - Encounters with Addiction”
Live at Cannes, Ari Paparo sits down with René Raiss, Founder of SQREEM, to discuss how the company's Large Behavioral Model (LBM) analyzes real-world behavior instead of language to predict intent, improve advertising performance, and power AI-driven insights across industries. Takeaways- Why SQREEM built a Large Behavioral Model instead of a Large Language Model.- How behavioral data provides deeper consumer insights than keywords alone.- Why AI models, not proprietary data, are becoming the competitive advantage.- How brands use SQREEM to improve targeting and lower customer acquisition costs.- Real-world applications of behavioral AI across media, healthcare, finance, and government.- How AI libraries and MCPs are replacing traditional software platforms.- - - Why understanding intent is the future of marketing and advertising. Chapters 00:00 Introduction to René Raiss and SQREEM00:49 The Story Behind the SQREEM Name01:20 What Is a Large Behavioral Model (LBM)?02:11 Why Consumer Behavior Matters More Than Keywords04:21 How SQREEM Collects and Models Behavioral Data05:44 AI Libraries vs Traditional Marketing Platforms06:48 Using Behavioral AI for Better Ad Targeting07:31 Campaign Performance and Lower CPA Results08:11 Applications Beyond Advertising and Marketing09:11 MCPs and the Future of AI Workflows09:43 SQREEM's Growth Strategy and Competitive Advantage10:24 Why the Model Matters More Than the Data11:14 Lightning Round and Closing Remarks Learn more about your ad choices. Visit megaphone.fm/adchoices
With Cori on indefinite hiatus, gender critical statistics aggregator, writer, designer, miracle cancer survivor, and friend o' the pod' Alasdair Gunn humbly offers to serve in his absence. We discuss why we don't want to discuss gender. According to our recording platform's AI assistant, we also talk about:* 00:00 - Introduction to the podcast's themes and hosts* 02:00 - Discussion on gender podcasts and societal fixation* 05:46 - Reflections on aging, identity, and the concept of “crone”* 08:10 - The social and political landscape of pride events and gender activism* 12:49 - Society's treatment of political figures and societal change* 16:37 - Observations on youth, right-wing cringe, and political identity* 20:18 - Personal anecdotes about pets and animal behavior* 25:22 - Critique of education and societal control* 30:45 - Personal health crises, autoimmune diseases, and medical treatment* 40:03 - Reflections on raising children and social conditioning* 48:36 - The societal response to activism and political protests* 52:37 - The influence of societal narratives and the importance of saying no* 60:12 - The history of communism, anarchism, and the personal stories of relatives* 66:00 - Advances in medicine and personal health management* 70:39 - The reality of living after life-threatening health crises* 76:10 - The importance of respecting host, John Corey, and future guest planning* 82:52 - Insights into Rene Girard's work on scapegoating and societal mythsWe miss you John Corey! But with replacements like Alasdair Gunn and Riverside's Large Language Model, we continue on.Resources:* The Anatomy of Revolution by Crane Brinton* Emma Goldman: Living My Life* Rene Girard - The Scapegoat * Nigel Farage | Twitter* Oswald Mosley Get full access to Heterodorx Podcast at heterodorx.substack.com/subscribe
Florian and Esther discuss the language industry news of the past couple of weeks, beginning with the newly released 2026 Slator Language AI 50 Under 50, which tracks emerging startups less than 50 months old. The duo observe how this year's cohort reflects a shift from standalone language technologies toward AI solutions built around complete business workflows.They also highlight seven trends, including the rise of agentic AI, AI-first language solutions integrators, specialist sign language startups, and the growing importance of proprietary customer data as a competitive advantage.Florian covers a stream of language AI announcements from Google, Apple, and Anthropic as the platforms continue to expand their multilingual capabilities.Esther recaps recent investment activity, with Rylo's USD 85m funding round for AI solutions serving deaf users, Dell Technologies Capital's USD 50m investment in voice AI startup Bland, and Gridly's USD 1.5m raise to add agentic AI capabilities to its content management platform.Esther concludes with her M&A corner, where Powerling acquires French language solutions integrator Atlantique Traduction and Sweden-based DigitalTolk expands into Switzerland through its acquisition of legal translation specialist Hieronymus.
In "The Dark Data Trap: Unlocking Logistics Documents with Tungsten Automation's Patrick Van Hull" Joe Lynch and Patrick Van Hull, Supply Chain Industry Consultant at Tungsten Automation, discuss how intelligent document processing eliminates manual data traps to drive logistics efficiency and cost savings. About Patrick Van Hull Patrick Van Hull, widely recognized as the Supply Chain Storyteller, helps organizations transform complexity into clarity. A multi-time "Top 25 Global Thought Leader and Influencer on Supply Chain" and Supply Chain Pro-to-Know, he focuses on supply chain digitalization and capability development, showing how operational details can drive resilience and performance across the value chain. Patrick's career spans more than two decades, with leadership and advisory roles at Apple, Dell, Rio Tinto, and CVS Health, Gartner, Deloitte, and SCM World, he became known for bridging practitioner expertise with executive-level insights to turn data and technology into impactful strategies and programs. Most recently, he has focused on helping enterprises use AI-powered intelligence to strengthen resilience and anticipate disruption. He holds degrees from the University of Michigan and Duke University Fuqua School of Business, and lectures on supply chain strategy at the University of Arkansas Walton School of Business. About Tungsten Automation Tungsten Automation, formerly Kofax, is the global leader in AI-powered document and workflow automation solutions, boasting a 40-year trusted legacy and a team of 2,200 employees across 40 countries, serving over 25,000 global customers. Our commitment to innovation and customer success has earned us industry recognition, including being named a Leader in the 2025 Gartner® Magic Quadrant™ for Intelligent Document Processing. Tungsten has also been recognized by other key analysts in areas such as Intelligent Automation and Process Orchestration. We are trusted to help businesses achieve unprecedented efficiencies and reduce costs through document and workflow automation, allowing them to scale and future-proof their business. Key Takeaways: The Dark Data Trap: Unlocking Logistics Documents In "The Dark Data Trap: Unlocking Logistics Documents with Tungsten Automation's Patrick Van Hull" Joe Lynch and Patrick Van Hull, Supply Chain Industry Consultant at Tungsten Automation, discuss how intelligent document processing eliminates manual data traps to drive logistics efficiency and cost savings. Tungsten Automation Profile: Formerly Kofax, Tungsten is a global leader in AI-powered Intelligent Document Processing (IDP) and advanced workflow automation. Backed by a 40-year legacy, 2,200 employees, and 25,000+ global customers, the company was named a Leader in the 2025 Gartner® Magic Quadrant™ for IDP. Their cloud-based platform sits cleanly over multiple, fragmented ERP and TMS networks to pull and push data seamlessly. Escaping the "Dark Data Trap": Moving a single international ocean container can require upwards of 30 separate documents. Because traditional TMS and ERP platforms can't read unstructured data (like dense PDFs, faxes, or Excel spreadsheets), this critical info becomes trapped "dark data." Tungsten uses IDP to automatically ingest, classify, and extract line-item data from over 40 different logistics document types, turning paper trails into structured, digital assets. Slashing AP Errors & Driving Revenue: Manual touchpoints in freight invoicing lead to constant billing discrepancies and human errors. Through automated multi-way matching, reconciliation, and automated exception handling, Tungsten drives "zero-touch" processing for order management and invoices. In one case study, acting as an automated "quality check" against contracted rates helped a major freight shipper capture an incremental $20 million in annual revenue. Preventing Customs and Shipment Delays: When data errors or missing documents hit customs or a port, shipments grind to a halt, triggering costly penalties, demurrage fees, and port congestion. Tungsten automates data extraction and email ingestion for customs clearance, validating regulatory documentation and compliance checks before shipments ever hit major bottlenecks. Accelerating Carrier and Supplier Onboarding: Traditional onboarding forces procurement teams into a weeks-long "paper chase" of manual risk assessments and compliance reviews. Tungsten uses automated self-service portals paired with automated risk assessments—such as using the platform to instantly verify the legitimacy of bank and credit statements—condensing onboarding timelines from weeks down to a matter of days. Bridging the Gap Between AI Hype and Reality: AI cannot solve supply chain issues without clean, unified data. Patrick notes that trying to run raw, messy documents entirely through an unguided Large Language Model (LLM) can cause the AI to run wild, exhausting months' worth of token allocations in a single week. Tungsten effectively solves this by embedding AI directly into workflows, blending traditional rules-based automation (RPA) for standard patterns with Generative and Agentic AI to manage highly complex exceptions. Elevating the Human Experience: Eliminating rudimentary data entry is ultimately a personal win for the workforce. Moving away from "swivel chair activity" and manual data chasing reduces friction and human error. By shifting repetitive tasks to automated workflows, logistics employees are freed up to use human ingenuity, focus on creative problem-solving, and ultimately enjoy more meaningful, higher-value work. Learn More About The Dark Data Trap: Unlocking Logistics Documents Patrick Van Hull | Linkedin Tungsten Automation | Linkedin Tungsten Automation Tungsten's Summits The Logistics of Logistics Podcast If you enjoy the podcast, please leave a positive review, subscribe, and share it with your friends and colleagues. The Logistics of Logistics Podcast: Google, Apple, Castbox, Spotify, Stitcher, PlayerFM, Tunein, Podbean, Owltail, Libsyn, Overcast Check out The Logistics of Logistics on Youtube
Discover how blind and visually impaired users can harness AI tools like Claude to build accessible solutions, enhance independence, and master screen reader fundamentals—guided by Tony Gebhard's No Sight Required. Tony Gebhard joins Steven Scott and Shaun Preece to discuss his new book, No Sight Required: A Blind User's Guide to AI. Written from a first-hand perspective, the book tackles the lack of consolidated resources for blind users exploring artificial intelligence. Tony explains why screen reader fundamentals are essential before diving into AI projects and shares how tools like Claude and Codex can help create custom solutions, from NVDA training modules to accessible web tools. The conversation covers: Why learning core navigation and assistive technology basics is crucial. How AI can act as a personal assistant, editor, and creative partner. Balancing accessibility, practicality, and patience when experimenting with LLMs. Creating solutions that empower blind users to solve problems independently. Tony also opens up about the writing process, using AI for editing and production, managing community expectations, and the importance of feedback for future editions. Relevant Links NVDA: https://www.nvaccess.org Email Tony for ePub: info@tonygebhard.me Key Quotes “Claude is smart—but you are the programme director. The AI is your worker; you give it the assignment.” — Tony Gebhard “We finally have the tools to build our own solutions. Let's go fill the gaps ourselves.” — Tony Gebhard Hashtags #AccessibleTech #ScreenReaders #AIForGood ----Follow on:YouTube: https://www.doubletaponair.com/youtubeX (formerly Twitter): https://www.doubletaponair.com/xInstagram: https://www.doubletaponair.com/instagramTikTok: https://www.doubletaponair.com/tiktokThreads: https://www.doubletaponair.com/threadsFacebook: https://www.doubletaponair.com/facebookLinkedIn: https://www.doubletaponair.com/linkedinSubscribe to the Podcast:Apple: https://www.doubletaponair.com/appleSpotify: https://www.doubletaponair.com/spotifyRSS: https://www.doubletaponair.com/podcastiHeadRadio: https://www.doubletaponair.com/iheartAbout Double TapHosted by the insightful duo, Steven Scott and Shaun Preece, Double Tap is a treasure trove of information for anyone who's blind or partially sighted and has a passion for tech. Steven and Shaun not only demystify tech, but they also regularly feature interviews and welcome guests from the community, fostering an interactive and engaging environment. Tune in every day of the week, and you'll discover how technology can seamlessly integrate into your life, enhancing daily tasks and experiences, even if your sight is limited."Double Tap" is a registered trademark of Double Tap Productions Inc. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
today we examine the shifting landscape of artificial intelligence, specifically comparing Small Language Models (SLMs) against Large Language Models (LLMs). Research highlights that SLMs consume 60-70% less energy and water, offering a more sustainable alternative for straightforward tasks without sacrificing accuracy. While LLMs remain superior for complex reasoning and abstract puzzles, they demand significant computational infrastructure and financial investment. Enterprises are increasingly adopting SLMs for specialized applications in healthcare and finance to enhance data privacy and operational efficiency. To balance performance with environmental costs, experts suggest a context-aware deployment strategy that switches between models based on task difficulty. Ultimately, the transition toward right-sized AI reflects a maturation of the industry toward pragmatic, governed, and resource-efficient solutions.
In this episode of the HVAC Know It All Podcast, host Gary McCreadie is joined by James Christian, Senior Director of Product at Podium, to discuss how artificial intelligence is helping HVAC and home service businesses operate more efficiently. James explains what large language models are, how AI employees can assist with customer communication, scheduling, dispatching, and lead management, and why AI should be viewed as a tool that supports people rather than replaces them. The conversation covers AI-powered CSRs, technician scheduling, route optimization, business automation, and the growing role of AI in daily operations. Gary and James also explore how AI can reduce workload, improve customer response times, and help business owners focus on growing their companies. In this conversation, James explains what large language models are and how artificial intelligence is being used to support HVAC and home service businesses. He discusses how AI employees can handle customer communication, scheduling, dispatching, and lead management, while helping office staff work more efficiently. James and Gary explore topics such as technician skill matching, route optimization, business automation, and the importance of using AI as a tool to support people rather than replace them. They also discuss how AI can improve response times, reduce workload, and help business owners focus on growth by automating routine tasks and improving daily operations. Expect to Learn: What large language models are and how AI is being used in HVAC and home service businesses. How AI employees can assist with customer communication, scheduling, dispatching, and lead management. Why AI works best as a tool that supports office staff and business owners rather than replacing them. How technician skill matching, GPS data, and scheduling systems can help improve job assignment and efficiency. How AI can reduce workload, improve response times, and help business owners focus on growing their business. Episode Highlights: [00:00] - Sponsor Ad: Factory Direct Filters [00:42] - Intro to James Christian in Part 1 [02:20] - Intro to AI in HVAC for techs & owners [03:54] - What is an LLM? (Large Language Model) [05:57] - AI as a virtual employee [08:54] - Podium's evolution: reviews → AI employees [11:35] - How AI matches techs to calls by skill level [14:02] - AI + GPS for real-time arrival estimates [16:11] - Gary's reaction: Terminator/Skynet joke This Episode is Kindly Sponsored by: Cintas: https://www.cintas.com/hvacknowitall Cool Air Products: https://www.coolairproducts.net/ Factory Direct Filters: https://www.factorydirectfilters.com/ SupplyHouse: https://www.supplyhouse.com/tm Use promo code HKIA5 to get 5% off your first order at Supplyhouse! Follow the Guest James Christian on: LinkedIn Profile: https://www.linkedin.com/in/james-christian-977a28a/ LinkedIn - Podium: https://www.linkedin.com/company/podium/ Follow the Host on: LinkedIn: https://www.linkedin.com/in/gary-mccreadie-38217a77/ Website: https://www.hvacknowitall.com Facebook: https://www.facebook.com/people/HVAC-Know-It-All-2/61569643061429/ Instagram: https://www.instagram.com/hvacknowitall1/ Follow the Podcast on: YouTube: https://www.youtube.com/@HVACKnowItAll Spotify: https://open.spotify.com/show/6LCBJGw0EHG03rdWHxUMce Apple Podcast: https://podcasts.apple.com/us/podcast/hvac-know-it-all-podcast/id1359253455
I put this song together because I feel it represents female infidelity. Disclaimer, I fed in ideas and lyrics and AI did the rest. I don't have a band! Full Name: Rebecca Adams (145171803275265) Email: rebecca.rawtruth@gmail.com This is to certify that Wall of Respect(145195849154561) is an AI music work (145171803275265) using Mureka, via Large Language Model (LLM) on June 19, 2026. The ownership, title and interest in and to Wall of Respect, including, without limitation, all intellectual property rights (if any) contained therein, belong to the user. Mureka, developed and operated by SKYWORK AI PTE. LTD. June 19, 2026
Federico Ortega Nieto explains how BAs can leverage LLMs by mapping business problems before jumping to solutions, and making trade-offs visible to leaders. Plus, LLMs can be used to rapidly build prototypes through vibe coding, and can avoid premature solutioning. Federico highlights that LLMs require structured processes, expert validation, and strong context engineering to deliver real value. Also, requirements can be embedded directly into shared codebases, allowing BAs to co-create with technical teams more precisely and rapidly. This can transform traditional handoffs into real-time, collaborative development. Overall, vibe coding and context engineering are essential emerging skills for senior BAs seeking enterprise influence. YouTube:
The drama around Anthropic's Fable 5 model clogged our collective attention spans.
As we prepare for these juggernauts to go public, I'm reminded of Yahoo, Excite, and AOL who dominated the first four years of the internet. Despite their lead, Google stole the market away. Could the same thing happen again? The argument is not that these companies aren't powerful, but rather that they're so committed to their current path that they may miss the big opportunity in the future. If you look at HR 2030 and what we want to do with enterprise AI, the ability to generate code, graphics, and text may not be what we need. And our new research on Galileo business modeling is starting to pan this out. Now that AI prices are high, we all have to look for bigger use-cases for agents. In this podcast I explain what “Dynamic Enablement for Growth” really means and how LLMs only take us so far, with a new frontier yet to come. As always I welcome opinions and feedback on this thesis. Additional Information To Come…. Get Galileo and see business modeling in action. The New Global HR Excellence Certification – Join the Inaugural Cohort! Chapters (00:00:00) - AI Hype Has Some Limits(00:00:45) - In the Elevation of Large Language Models(00:03:57) - A Hackers Bought a Hacker's Card(00:05:25) - Beyond the Frontier: The Business Value of AI(00:09:52) - What HR 2030 Agents Need to Do(00:14:41) - What Does This Mean for AI in HR?
Should you convert your website into Markdown to help Large Language Models (LLMs) understand your content better? Is "llms.txt" worth the effort for SEO? In this episode of Search Off the Record, Martin Splitt and John Mueller from the Google Search Relations team dive deep into the history of Markdown, its rise in the AI era, and whether it holds any real weight for search engine discovery. In this episode, you'll learn: The Origins of Markdown: From John Gruber and Aaron Swartz to its status as the "language of GitHub." Markdown vs. HTML: Why the "cleanliness" of Markdown is tempting for developers but potentially risky for site structure. LLMs & Markdown: Do AI crawlers actually prefer Markdown, or are they already experts at parsing HTML? The "Parallel Version" Trap: Why creating a separate text/Markdown version of your site for AI can lead to the same maintenance nightmares as dynamic rendering. Use Cases that Make Sense: When Markdown is actually superior (like developer documentation) and when it's totally unnecessary (like your shoe catalog). Key Takeaways for SEOs & Developers: Crawlers are built for the "messy" web: Google and other engines have decades of experience parsing HTML. Don't sacrifice discovery: Headers, footers, and sidebars in HTML provide critical context for site structure that a raw Markdown file might lack. Maintenance is king: Avoid the complexity of maintaining two versions of the same content. Chapters 0:00 - Introduction: Should we all be using Markdown? 3:45 - The history and purpose of Markdown. 7:15 - Why developers love it: Separation of style and content. 11:20 - Do crawlers need Markdown to understand your site? 14:50 - The danger of "parallel versions" and dynamic rendering lessons. 17:30 - Discussing the "llms.txt" proposal and AI agents. 21:00 - Where Markdown actually makes sense (Developer Docs). 24:00 - Final verdict: Stick to HTML for the web. Resources Mentioned: Google Search Central: https://developers.google.com/search Are you using Markdown for your site's frontend or just as a backend source? Let us know in the comments! Episode transcript → https://goo.gle/sotr111-transcript Listen to more Search Off the Record → https://goo.gle/sotr-yt Subscribe to Google Search Channel → https://goo.gle/SearchCentral Search Off the Record is a podcast series that takes you behind the scenes of Google Search with the Search Relations team. #SOTRpodcast #SEO #GoogleSearch Speakers: Martin Splitt, John Mueller
Slator's Anna Wyndham joins Florian on the pod to discuss key highlights from the Slator Data-for-AI Market Report, which sizes the global market at USD 9.3bn and examines the ecosystem supplying the data needed to train, adapt, align, evaluate, and deploy AI systems.Anna explains how the market has evolved far beyond traditional data labeling. While annotation and large-scale training data remain important, she argues that the market's focus has shifted toward helping organizations deploy AI safely and effectively in real-world settings.Anna highlights the growing importance of “deployment data”, data used to adapt models for specific domains, align behavior with policies, conduct adversarial testing, and evaluate performance. She notes that these activities increasingly rely on subject-matter experts, creating demand for professionals such as physicians, lawyers, engineers, and financial specialists.The discussion also explores how frontier AI labs, enterprises, and sovereign AI initiatives are driving demand. Anna shares that buyers increasingly need trusted providers capable of sourcing expert talent, scaling rapidly, and maintaining rigorous governance around data provenance and quality.For language solutions integrators (LSIs), Anna sees both opportunity and challenge. Existing strengths in multilingual operations and workforce management provide a natural advantage, but success requires new capabilities, including expertise in machine learning workflows and AI evaluation.
Tyler Foreman, the Vice President of AI at Rocket Lawyer, joins the show to discuss the intersection of artificial intelligence and the legal industry. Foreman shares his untraditional legal tech career path, spanning engineering at Intel, drone data analytics, and ultimately making the move to legal via contract lifecycle management (CLM) at DocuSign, before diving into his current work at Rocket Lawyer helping to provide legal resources for small-to-medium businesses and individuals. The conversation focuses on how modern generative AI and Large Language Models (LLMs) act as a legal operating system to simplify contract reviews, document drafting, and client intake, while maintaining essential connections to human attorneys.
A mass extinction event approaches, but not because of a meteor or global warming. The culprit this time is AI, and in particular, Large Language Models like ChatGPT and Claude. In their crosshairs are a slew of vendors selling analytical functionality: dashboards, visualizations, analyses, semantic layers, OLAP cubes and the like. For decades, these vendors have dominated enterprise decision-making, commanding 5, 6, even 7-figure pricetags to provide the scaffolding needed for insights. The LLMs now threaten that entire landscape, disrupting the foundation of data-driven workflows. True, the results of GenAI can be inaccurate, but their ease of use and relatively low cost will trump those concerns. Check out this hard-hitting session to hear DM Radio Host, Eric Kavanagh explain what's happening and why it matters to analysts everywhere. He'll examine the impact on the analytics industry, and explore ways that these vendors can stay relevant. He'll also offer advice for businesses looking to remain data-driven, and why data prep is where the action will be.
If it was possible to have a coin with three sides, this might be it. We discuss the Discovery of the remains of an employee of Los Alamos National Laboratory, who had gone missing 11 months ago. She reportedly performed a factory reset on both her phones and walked out into the desert. Melissa Casias is one of at least 11 people who have disappeared or died with connections to sensitive government programs related to the UFO phenomenon. Investigators say there is nothing to indicate foul play, but we remain skeptical. Meanwhile, the archbishop of Washington, D.C. removed a priest as an exorcist for the archdiocese after Monsignor Stephen Rossetti posted a video to his Facebook page connecting demons to the UFO phenomenon. While we don't entirely agree with Monsignor Rossetti's understanding, he's not entirely wrong. We also discussed a call by the cofounder of Anthropic, the developers of Claude, AI, for a pause on development of artificial intelligence because of his concern that Large Language Models are on the verge of full recursive self-improvement, meaning artificial intelligence could soon escape any restraints placed on it by humans. In other words, AI is closer to achieving the singularity than we think. Finally, we discussed strange news reports from New York City of men in full protective gear, wearing night goggles, descending into the sewer system at night and re-emerging several hours later. Police don't know what they've been doing down there, but they say at this point there is no threat to public safety. Again, we remain skeptical. Sharon's niece, Sarah Sachleben, is fighting stage 4 bowel cancer, and the medical bills are piling up. If you are led to help, please go to GilbertHouse.org/hopeforsarah. Follow us! X (formerly Twitter): @pidradio | @sharonkgilbert | @derekgilbert | @gilberthouse_tvTelegram: t.me/gilberthouse | t.me/sharonsroom | t.me/viewfromthebunkerSubstack: gilberthouse.substack.comYouTube: @GilbertHouse | @UnravelingRevelationFacebook.com/pidradio JOIN US IN ISRAEL (NOTE NEW DATES)! We will tour the Holy Land October 25–November 6, 2027 with an optional three-day extension to Jordan. For more information, log on to GilbertHouse.org/travel. Thank you for making our Build Barn Better project a reality! Our 1,200 square foot pole barn has a new HVAC system, epoxy floor, 100-amp electric service, new windows, insulation, lights, and ceiling fans! If you are so led, you can help out by clicking here: gilberthouse.org/donate. Get our free app! It connects you to this podcast, our weekly Bible studies, and our weekly video programs Unraveling Revelation and A View from the Bunker. The app is available for iOS, Android, Roku, and Apple TV. Links to the app stores are at pidradio.com/app. Video on demand of our best teachings! Stream presentations and teachings based on our research at our new video on demand site: gilberthouse.org/video! Think better, feel better! Our partners at Simply Clean Foods offer freeze-dried, 100% GMO-free food and delicious, vacuum-packed fair trade coffee from Honduras. Find out more at GilbertHouse.org/store/.
Large Language Models such as ChatGPT definitely have their uses, but embedded in those large language models are some large language biases, as Bill is about to show despite the danger to himself.
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop interviews Joshua Pearce, the John Thompson Chair in Innovation at the Department of Electrical and Computer Engineering and Ivey Business School at Western University, about the revolution in open source hardware for scientific research. They discuss how three-dimensional printing, Arduino controllers, and open source designs are dramatically reducing research costs—often by 85-95%—while democratizing access to lab equipment worldwide. Pearce shares stories from his 2013 book "Open Source Lab" and explains how the movement has exploded since then, covering everything from filter wheel changers and ball mills to metal three-dimensional printers and battery research equipment. The conversation explores recycle bots that turn plastic waste into filament, the role of AI in accelerating hardware development, and how open source licensing creates a global knowledge management system where improvements are shared across the scientific community. For those interested in learning more, Pearce recommends checking out the journal HardwareX, repositories like Thingiverse and My Mini Factory, and appropedia.org for open source scientific tools and appropriate technology designs.Timestamps00:00 Welcome and introduction to Joshua Pearce, discussing his work on open source lab equipment and the evolution since publishing his book in 201305:00 Early development of open source hardware including the breakthrough filter wheel changer project built by a high school student that saved thousands of dollars10:00 Discussion of how Arduino and RepRap three-d printers enabled the democratization of scientific tools, making complex equipment accessible to anyone15:00 Economic impact showing average tool savings of 85 percent, with Arduino and three-d printing combinations reaching mid-90s percent cost reduction20:00 Case study of PhD student Mariam building complete battery research tool chain from scratch using open source designs and three-d printed components25:00 Recycle bots enabling transformation of waste plastic into three-d printer filament for pennies, revolutionizing material costs and sustainability30:00 Collaboration between universities and open source companies creating fluid handlers and acquisition systems, accelerating research capabilities globally35:00 Large language models assisting code translation and research planning, though hallucinations require careful verification and domain expertise40:00 Importance of fundamental knowledge when using AI tools, comparing vibe coding acceleration with necessity for understanding underlying principles45:00 Testing standards and calibration methods for open source equipment, balancing precision requirements against cost-effectiveness for specific applications50:00 Metal and ceramic three-d printing developments including MIG welding techniques and sintering processes for creating functional parts55:00 Knowledge management through open source licenses, repositories like Thingiverse and Apropedia enabling global collaboration and continuous improvementKey Insights1. Open source hardware has evolved dramatically since Joshua Pearce wrote his book in 2012-2013, to the point where he can no longer keep up with all the developments in the field. What started as a collection where every single example could fit in one book has exploded into an entire ecosystem with dedicated journals and thousands of researchers contributing. The vision was that scientific papers would eventually include hyperlinks to equipment designs that anyone could download and replicate, and that future is largely here today. There are now so many open source hardware articles being published that no single person can read them all, which represents a massive success for the movement.2. The fundamental breakthrough enabling open source scientific hardware came from combining several key technologies, particularly the RepRap three-d printer project and Arduino microcontrollers. Pearce's introduction to the field came when he needed a sixty-five dollar plastic part for a solar laptop project and discovered Adrian's open-sourced rapid prototyper that could make its own parts. This led to building equipment like a filter wheel changer for testing solar panels with a high school student in about a week, replacing a device that would have cost two thousand five hundred dollars with five months lead time. The democratization of tools like three-d printing and Arduino, combined with extensive code libraries and shared designs, means that even high school students can now create sophisticated scientific equipment.3. Open source scientific hardware delivers massive economic benefits, with the average tool saving scientists around eighty-five percent compared to commercial equipment, and savings reaching the mid-nineties when using Arduino and three-d printing. The economics are so compelling that the tax paid on a normal scientific tool can cover the cost of an open source alternative. A thousand dollar three-d printer can manufacture scientific tools worth more than a thousand dollars in a single Saturday. This dramatic cost reduction makes sophisticated research accessible to laboratories around the world regardless of their funding levels, fundamentally democratizing scientific capability.4. The knowledge management approach enabled by open source licenses creates a powerful collaborative improvement cycle where thousands of people worldwide contribute to evolving designs. When researchers publish equipment designs with strong reciprocal licenses, anyone can use, modify, or even sell the designs, but improvements must be shared back with the community. This creates a dispersed international engineering effort where equipment continuously improves through contributions from researchers across different institutions and countries. The RepRap three-d printer exemplifies this process, starting as barely functional prototypes but evolving through community contributions to surpass commercial alternatives in speed, resolution, and material capabilities.5. The integration of large language models and AI tools has significantly accelerated open source hardware development, though with important caveats about their limitations. LLMs excel at translating code between languages, suggesting experimental approaches, and helping researchers navigate unfamiliar fields by quickly synthesizing information from scientific literature. However, they suffer from hallucination problems and cannot be trusted for writing scientific articles or conducting complete literature reviews without verification. The key to effective use is having enough foundational knowledge to ask the right questions and verify outputs, using AI as a powerful acceleration tool rather than a replacement for expertise.6. Material science capabilities in open source hardware have expanded far beyond plastic three-d printing to include metals, ceramics, semiconductors, and composites through innovative adaptations of basic equipment. Pearce's lab has developed methods for metal three-d printing using modified MIG welding for as little as twelve hundred dollars, created slot-die coating systems for seventeen nanometer semiconductor layers using converted three-d printers, and developed techniques for ceramic printing through various material mixing approaches. The recycle bot technology enables converting waste plastic into high-quality filament for twenty-five cents instead of twenty-five dollars per roll, dramatically reducing material costs while enabling circular manufacturing practices.7. The infrastructure for sharing and discovering open source hardware designs has matured into a robust ecosystem spanning academic journals, commercial repositories, and specialized communities. Hardware X and the Journal of Open Hardware publish peer-reviewed designs alongside traditional scientific journals increasingly incorporating open hardware sections. Repositories like Thingiverse recently returned to hardcore open source principles after ownership changes and contains millions of designs, while Appropedia serves as a wiki for appropriate technology with thousands of open source designs. The GOSH community hosts annual conferences bringing together university researchers, companies, and independent hardware hackers, while field-specific communities have formed around technologies like the OpenFlexure microscope, creating networks where knowledge accumulates and never gets lost.
On this Thursday edition of What's On Your Mind, host Scott Hennen is broadcasting live from behind the Petroserve USA microphones, tracking critical dynamics ahead of Tuesday's highly anticipated primary election. The high stakes of low-turnout cycles take center stage as the show highlights how an underwhelming voter showing allows minor localized factions to completely dictate state trajectories. The premiere segment features an intensive discussion with freshly appointed Public Service Commissioner Jill Kringsted, who pulls back the curtain on how a background in auditing has empowered her to challenge out-of-state environmental mandates and protect North Dakota ratepayers. Later in the hour, Minnesota House Minority Leader Lisa Demeth stops by to break down her historic decision to bypass the chaotic GOP convention endorsement process in Duluth and take her gubernatorial campaign directly to a statewide primary vote. Plus, dynamic insights from Theodore Roosevelt Presidential Library Executive Director Robbie Lauf on the historic tech integration dropping in Medora, and an on-air debate with Fargo mayoral candidate Josh Boschee regarding budget metrics and out-of-state fundraising. Standout Moments & Timestamps The Reality of the June Primary: Scott challenges the electorate on voter apathy, detailing why municipal choices directly shape the lion's share of local property tax burdens. Fact-Finding at the Public Service Commission: Commissioner Jill Kringsted describes the judicial role of the PSC, explaining why commissioners must strictly evaluate infrastructural applications based on state law rather than shifting political winds. Securing the Nation's Lowest Electric Rates: Kringsted drops a staggering statistic showing that North Dakota leads the country in energy affordability, saving local consumers over a quarter-billion dollars compared to neighboring regions. Defending the Grid from Minnesota's Mandates: Jill details her first six months on the commission, which included launching an essential federal lawsuit to block states like Minnesota and Illinois from passing green energy infrastructural compliance costs onto North Dakota families. Sifting Through the Candidate Field: Scott evaluates the technical qualifications required to manage massive utility oversight, officially endorsing Jill Kringsted for the six-year term. The Tragic Turning Point in the Badlands: Theodore Roosevelt Presidential Library Director Robbie Lauf shares the moving backstory behind TR's historic dairy entry on Valentine's Day in 1884 and his subsequent rebirth in North Dakota. The First AI-Integrated Presidential Library: Lauf previews the groundbreaking Large Language Model framework opening on July 4th, which will allow visitors to hold real-time, interactive, hours-long conversations with a digital reflection of Teddy…
No matter your role, experience or industry, we all (mostly) waste hours a week doing the same thing: manually creating slides.
David Chalmers, one of the most preeminent philosophers and researchers in cognitive science, argues that nothing prevents machines from becoming truly conscious. Chalmers, who has studied the mind for decades, points out that there is a real possibility of AI creating a next stage of intelligence that is even capable of redesigning itself. He joins WITHpod to discuss what consciousness is and the possibility of AI systems becoming fully conscious. Sign up for MS NOW Premium on Apple Podcasts to listen to this show and other MS podcasts without ads. You'll also get exclusive bonus content from this and other shows. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
This week, we're joined by writer, academic and creator John Duncan to talk about the effects Large Language Models are having on academic writing and research. John talks about the growing number of AI hallucinations that are appearing in academic papers and articles and what it reveals about the poor working and pay conditions of academics in the UK and around the world. John also talks about the dangers this poses to future research and knowledge production, which might be bad if we ever face a public health crisis again. We also talk about the Pope's Encyclical on the AI industry, why it's less radical or revolutionary than has been reported, and why any notion of ‘ethical AI' should be disregarded. Subscribe to John's channel: https://www.youtube.com/@JohntheDuncan support John on Patreon! : https://www.patreon.com/johntheduncan ------- PALESTINE AID LINKS -You can donate to Medical Aid for Palestinians and other charities using the links below. https://www.map.org.uk/donate/donate https://www.savethechildren.org.uk/how-you-can-help/emergencies/gaza-israel-conflict -Palestinian Communist Youth Union, which is doing a food and water effort, and is part of the official communist party of Palestine https://www.gofundme.com/f/to-preserve-whats-left-of-humanity-global-solidarity -Water is Life, a water distribution project in North Gaza affiliated with an Indigenous American organization and the Freedom Flotilla https://www.waterislifegaza.org/ -Vegetable Distribution Fund, which secured and delivers fresh veg, affiliated with Freedom Flotilla also https://www.instagram.com/linking/fundraiser?fundraiser_id=1102739514947848 -Thamra, which distributes herb and veg seedlings, repairs and maintains water infrastructure, and distributes food made with replanted veg patches https://www.gofundme.com/f/support-thamra-cultivating-resilience-in-gaza -------- PHOEBE ALERT Okay, now that we have your attention; check out her Substack Here! Check out Masters of our Domain with Milo and Patrick, here! -------- Ten Thousand Posts is a show about how everything is posting. It's hosted by Hussein (@HKesvani), Phoebe (@PRHRoy) and produced by Devon (@Devon_onEarth).
What is actually happening to the media relations tools publicists rely on daily? In this episode of the PR Pace podcast, host Annie Scranton sits down with Brett Farmiloe, founder and CEO of Featured, to discuss the major shifts happening at the intersection of PR, artificial intelligence, and brand visibility.Brett shares the exclusive backstory behind his acquisition and relaunch of Help a Reporter Out (HARO) and Connectively, revealing his vision for preserving the nostalgia and product-market fit of the traditional three-times-a-day email newsletter while scaling a unified platform.Annie and Brett dive deep into the reality of AI-generated pitching, how journalists really feel about AI in their inboxes, and how PR professionals can navigate the shift from traditional SEO to GEO (Generative Engine Optimization). Learn how authoritative press releases and earned media mentions are becoming the ultimate "secret weapons" for training Large Language Models (LLMs) and securing AI visibility for your clients.Here's what we're talking about:The HARO Timeline: What happened to Help a Reporter Out and Connectively, and what their return looks like today.AI vs. Human Pitching: How 35% of journalists are actively opting out of 100% AI-generated pitches, and why a "human in the loop" is essential.The Evolution of Featured: How Featured is building the first true AI "co-pilot for PR" to solve inbox overload and unify journalist requests, podcasts, and speaking opportunities.GEO Strategy & AI Visibility: Direct tactics for landing your brand on the "new front page of the internet"—from authoritative news wires to GEO audits.Connect with the Guest:Visit Featured: Featured.com Visit Connectively: Connectively.us
Full article: Human-in-the-Loop Large Language Model–Augmented Diagnostic Reasoning in Thoracic Imaging: Impact of Radiologic Expertise Use of LLMs in the diagnostic reasoning process can either improve or hinder performance. Pranjal Rai, MD, discusses the AJR article by Song et al. exploring the association of reader expertise and reader performance when using LLMs as a diagnostic aid.
Conversational AI is increasingly being used as a source of emotional support, even though general-purpose chatbots were never designed for that purpose. Concerns about AI's mental health impact, up to and including suicides, have moved onto the public policy agenda. Munmun De Choudhury, who has been studying the intersection of digital technology and mental health longer than almost anyone, walks through what researchers know, what they don't, and why the answers keep moving. The conversation centers on the difficulty of governing technologies whose capabilities and patterns of use are both changing every few weeks. De Choudhury invokes the cautionary tale of Google Flu Trends as a warning: any framework that assumes user behavior is fixed will eventually break. She argues that the harms and benefits of conversational AI are not just person-dependent but task-dependent, which makes general-purpose chatbots fundamentally harder to evaluate than the narrow medical AI systems researchers built for decades. She lays out a multi-stakeholder agenda to address AI's mental health risks, and argues that foundation models need to take into account principles from psychotherapy. Dr. Munmun De Choudhury is the J.Z. Liang Professor in the School of Interactive Computing at Georgia Tech, where she founded and directs the Social Dynamics and Wellbeing Lab (SocWeB). She is one of the most cited researchers in digital mental health and is widely credited with pioneering the computational use of social media data to study mental health outcomes. She co-leads the Patient-Centered Care Delivery research pillar at the Children's Healthcare of Atlanta Pediatric Technology Center, serves on the advisory board for the Australian government's eSafety panel, and was inducted into the SIGCHI Academy in 2024. Her honors include the 2023 SIGCHI Societal Impact Award and the 2021 ACM-W Rising Star Award. Transcript Benefits and Harms of Large Language Models in Digital Mental Health From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agents
Large Language Models can generate a lot of text - but is it any good? Carl and Richard talk to Vishwas Lele about his ongoing efforts at pWin.ai to build tools for responding to government RFPs. Vishwas focuses on the quality problem - both the quality of the incoming RFP and the quality of the responding proposal. How do you determine the key requirements of an RFP reliably? And when it comes to the response, how do you provide measurable results for a response? The conversation digs into a change in workflow that benefits the RFP process regardless of tooling - and gives hints to the patterns of success with LLMs!
OpenAI, Microsoft, and Google are racing to unleash next-gen AI that hunts for software vulnerabilities and hacks at scale. This episode explores how these advancements could shake up everything we thought we knew about cybersecurity. Microsoft rethinks Edge's "intended behavior" after it gets press. Chaotic Eclipse hacker strikes again with a Bitlocker bypass. Google's threat analysis group documents malicious AI use. Canada hasn't learned the lessons of the EU and the UK. AI chatbots may be far more addictive than social media. Project: Hail Mary now available to stream. An apparently-serious zero-point quantum vacuum energy source. A bit of listener feedback. OpenAI's & Microsoft's vulnerability discovery systems Show Notes - https://www.grc.com/sn/SN-1079-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: outsystems.com/twit hoxhunt.com/securitynow zscaler.com/security meter.com/securitynow canary.tools/twit - use code: TWIT joindeleteme.com/twit promo code TWIT
OpenAI, Microsoft, and Google are racing to unleash next-gen AI that hunts for software vulnerabilities and hacks at scale. This episode explores how these advancements could shake up everything we thought we knew about cybersecurity. Microsoft rethinks Edge's "intended behavior" after it gets press. Chaotic Eclipse hacker strikes again with a Bitlocker bypass. Google's threat analysis group documents malicious AI use. Canada hasn't learned the lessons of the EU and the UK. AI chatbots may be far more addictive than social media. Project: Hail Mary now available to stream. An apparently-serious zero-point quantum vacuum energy source. A bit of listener feedback. OpenAI's & Microsoft's vulnerability discovery systems Show Notes - https://www.grc.com/sn/SN-1079-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: outsystems.com/twit hoxhunt.com/securitynow zscaler.com/security meter.com/securitynow canary.tools/twit - use code: TWIT joindeleteme.com/twit promo code TWIT
OpenAI, Microsoft, and Google are racing to unleash next-gen AI that hunts for software vulnerabilities and hacks at scale. This episode explores how these advancements could shake up everything we thought we knew about cybersecurity. Microsoft rethinks Edge's "intended behavior" after it gets press. Chaotic Eclipse hacker strikes again with a Bitlocker bypass. Google's threat analysis group documents malicious AI use. Canada hasn't learned the lessons of the EU and the UK. AI chatbots may be far more addictive than social media. Project: Hail Mary now available to stream. An apparently-serious zero-point quantum vacuum energy source. A bit of listener feedback. OpenAI's & Microsoft's vulnerability discovery systems Show Notes - https://www.grc.com/sn/SN-1079-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: outsystems.com/twit hoxhunt.com/securitynow zscaler.com/security meter.com/securitynow canary.tools/twit - use code: TWIT joindeleteme.com/twit promo code TWIT
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