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Turns out, every chatbot conversation runs on a messy hack at the heart of language models, making prompt injection an unsolved—and possibly unsolvable—security threat. Steve and Leo unravel the research that explains why "roles" in AI aren't what you think they are. Understanding the controversy surrounding "AI Model Distillation" Anthropic moves to make their most powerful Mythos 5 model more widely available. Bitwarden's "Secrets Manager" offering prevents agentic and prompt injection abuse. The astounding and disturbing truth about the way conversation AI actually works Show Notes - https://www.grc.com/sn/SN-1093-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: threatlocker.com/twit box.com/AI hoxhunt.com/securitynow guardsquare.com material.security
Turns out, every chatbot conversation runs on a messy hack at the heart of language models, making prompt injection an unsolved—and possibly unsolvable—security threat. Steve and Leo unravel the research that explains why "roles" in AI aren't what you think they are. Understanding the controversy surrounding "AI Model Distillation" Anthropic moves to make their most powerful Mythos 5 model more widely available. Bitwarden's "Secrets Manager" offering prevents agentic and prompt injection abuse. The astounding and disturbing truth about the way conversation AI actually works Show Notes - https://www.grc.com/sn/SN-1093-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: threatlocker.com/twit box.com/AI hoxhunt.com/securitynow guardsquare.com material.security
Turns out, every chatbot conversation runs on a messy hack at the heart of language models, making prompt injection an unsolved—and possibly unsolvable—security threat. Steve and Leo unravel the research that explains why "roles" in AI aren't what you think they are. Understanding the controversy surrounding "AI Model Distillation" Anthropic moves to make their most powerful Mythos 5 model more widely available. Bitwarden's "Secrets Manager" offering prevents agentic and prompt injection abuse. The astounding and disturbing truth about the way conversation AI actually works Show Notes - https://www.grc.com/sn/SN-1093-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: threatlocker.com/twit box.com/AI hoxhunt.com/securitynow guardsquare.com material.security
Turns out, every chatbot conversation runs on a messy hack at the heart of language models, making prompt injection an unsolved—and possibly unsolvable—security threat. Steve and Leo unravel the research that explains why "roles" in AI aren't what you think they are. Understanding the controversy surrounding "AI Model Distillation" Anthropic moves to make their most powerful Mythos 5 model more widely available. Bitwarden's "Secrets Manager" offering prevents agentic and prompt injection abuse. The astounding and disturbing truth about the way conversation AI actually works Show Notes - https://www.grc.com/sn/SN-1093-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: threatlocker.com/twit box.com/AI hoxhunt.com/securitynow guardsquare.com material.security
Turns out, every chatbot conversation runs on a messy hack at the heart of language models, making prompt injection an unsolved—and possibly unsolvable—security threat. Steve and Leo unravel the research that explains why "roles" in AI aren't what you think they are. Understanding the controversy surrounding "AI Model Distillation" Anthropic moves to make their most powerful Mythos 5 model more widely available. Bitwarden's "Secrets Manager" offering prevents agentic and prompt injection abuse. The astounding and disturbing truth about the way conversation AI actually works Show Notes - https://www.grc.com/sn/SN-1093-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: threatlocker.com/twit box.com/AI hoxhunt.com/securitynow guardsquare.com material.security
Turns out, every chatbot conversation runs on a messy hack at the heart of language models, making prompt injection an unsolved—and possibly unsolvable—security threat. Steve and Leo unravel the research that explains why "roles" in AI aren't what you think they are. Understanding the controversy surrounding "AI Model Distillation" Anthropic moves to make their most powerful Mythos 5 model more widely available. Bitwarden's "Secrets Manager" offering prevents agentic and prompt injection abuse. The astounding and disturbing truth about the way conversation AI actually works Show Notes - https://www.grc.com/sn/SN-1093-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: threatlocker.com/twit box.com/AI hoxhunt.com/securitynow guardsquare.com material.security
The Buzz, powered by Toyota Automated Logistics, is back with another timely look at the news and trends shaping global supply chain. In this episode, host Scott Luton is joined by Paul J. Noble and special guest Lora Cecere, founder of Supply Chain Insights, for a wide-ranging conversation on agentic AI, supply chain fraud, manufacturing, forecasting, lead times, and why decades of technology investment still haven't delivered better results for many organizations. From the growing role of AI agents in commerce to the increasing sophistication of supply chain fraud, this episode tackles some of the biggest challenges and opportunities facing supply chain leaders today. Scott, Paul, and Lora explore why trust and data verification will become even more critical in an agentic world, what current manufacturing data really tells us about the economy, and why organizations need to rethink long-standing approaches to forecasting and inventory management. Lora also challenges the industry to move beyond so-called “best practices” that may actually be outdated historical practices. The conversation digs into the importance of dynamic lead-time data, predictive analytics, balanced scorecards, and cross-functional decision-making and asks a critical question: If supply chain technology has advanced so dramatically, why are so many supply chains still underperforming? Additional Links & Resources: Toyota Automated Logistics: https://toyota-automated-logistics.com/ With That Said: https://bit.ly/WTS-15-Aug-2026 Paul Climbing Mt. Rainier: https://www.linkedin.com/posts/pauljnoble_climbing-the-vertical-equivalent-of-everest-ugcPost-7480348179654275073-cwS1/ The 2026 MHI Annual Industry Report: https://www.mhi.org/annual-industry-reports Vitol, Cargill, Glencore cut ties with Radiant World - report: https://reut.rs/3UBBEkZ The AI Buildout and the Economy: Publicly Available Data to Assess AI's Impact: https://www.federalreserve.gov/econres/notes/feds-notes/the-ai-buildout-and-the-economy-publicly-available-data-to-assess-ais-impact-20260717.html Manufacturing PMI® at 55.6%; July 2026 ISM® Manufacturing PMI® Report: https://prn.to/4xHjigG Syncing to Market Actuals: https://www.linkedin.com/pulse/syncing-market-actuals-lora-cecere-ukgqe/ What Have We Learned Thus Far From AskLora.Ai? https://streamyard.com/watch/fxjWYRFvdfHe Blame Follows the Messenger: https://supplychainnow.com/blame-follows-the-messenger/ AskLora: https://asklora.ai/ VDSAI: https://www.vdsai.net/ Connect with Paul on LinkedIn: https://www.linkedin.com/in/pauljnoble/ Connect with Lora on LinkedIn: https://www.linkedin.com/in/loracecere/ Upcoming Live Programming: https://supplychainnow.com/upcoming-live-programming/ Supply Chain Now Resource Hub: https://supplychainnow.com/resource-hub/ 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 Subscribe to Supply Chain Now on your favorite platform: https://supplychainnow.com/join Work with us! Download Supply Chain Now's NEW Media Kit: https://bit.ly/3XH6OVk WEBINAR- SAP AI Inside the Supply Chain: From Silo to Orchestration: https://bit.ly/4bvpz6K WEBINAR- Operational AI in the Supply Chain: How context empowers agents and humans to operate side by side: https://bit.ly/4x7Vd2Z WEBINAR- You Can't Manage What You Can't See: Using Visibility, KPIs, and AI to Optimize Logistics Operations: https://bit.ly/4ql6iem This episode was hosted by Scott Luton and Paul Noble, and produced by Trisha Cordes, Joshua Miranda, and Amanda Luton. For additional information, please visit our dedicated episode page at: https://supplychainnow.com/buzz-fixing-supply-chain-performance-ai-era-1625 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.
Was passiert mit einer Organisation, wenn sich Technologie, Kundenbedürfnisse und Führung gleichzeitig verändern? In der zweiten Küchenfolge sprechen Anja Sengenberger und Lucas Moskau darüber, wie KI nicht nur Softwareentwicklung beschleunigt, sondern zunehmend auch Strukturen, Rollen und Geschäftsmodelle verändert. Bei TIKI trifft diese Entwicklung aktuell auf einen Führungswechsel und immer kürzere Projektzyklen. Statt Teams über Monate bei einem einzelnen Kunden einzusetzen, entstehen flexiblere Modelle: Beratung, Strategie, Prototyping und Entwicklung greifen stärker ineinander. Anja berichtet, warum sie sich für die Organisationsentwicklung bewusst aus dem operativen Tagesgeschäft zurückgezogen hat und TIKI für einige Wochen wie eine interne Beraterin betrachtet hat. Lucas bringt die Perspektive aus Entwicklung und Sales ein und erklärt, warum das eigentliche Bottleneck häufig nicht die Technologie ist, sondern die Frage: Was braucht der Kunde wirklich? Außerdem geht es darum, warum nicht jedes Problem ein Large Language Model braucht, wie sich Product Owner und Entwicklung verändern und weshalb Unternehmen trotz hoher Geschwindigkeit Raum für echten Change schaffen müssen. Eine Folge über KI, Organisation und die Herausforderung, Stabilität und Veränderung gleichzeitig möglich zu machen. www.tiki-institut.com
KI-Wasserzeichen, Smart Glasses, Pegasus und die Rückkehr der Videothek – eine Folge voller Technik, die gleichzeitig genial und ein bisschen problematisch ist. Rüdiger Trost und Tobias Schrödel sprechen zunächst über einen ganz praktischen Digitalisierungsversuch: den Umzug einer eigenen Mail-Domain zu einem deutschen Anbieter. Eigentlich funktioniert alles – wäre da nicht Gmail, das die neuen Mails konsequent in den Spam-Ordner steckt. Dabei zeigt sich auch: KI kann beim Analysieren von Mail-Headern und Logfiles mittlerweile erstaunlich gute Unterstützung leisten. Danach geht es um das große KI-Thema der Folge: Wasserzeichen in KI-generierten Texten. Die beiden erklären, wie Anthropic über veränderte Wortwahrscheinlichkeiten ein statistisches Muster erzeugen kann und warum damit nicht unbedingt bewiesen wird, dass ein Text komplett von einer KI stammt. Auch die Grenzen solcher Verfahren kommen zur Sprache. Und was passiert, wenn künftig praktisch überall „AI generated“ draufsteht? Die beiden diskutieren Kennzeichnungspflichten, Werbeplakate, KI-generierte Werbung und die Frage, ob ein Label irgendwann so inflationär verwendet wird, dass es niemand mehr ernst nimmt. Weiter geht es mit Smart Glasses. Die Ray-Ban Meta und ähnliche Geräte können Fotos und Videos aufnehmen, ohne dass die Person neben einem unbedingt mitbekommt, dass gerade eine Kamera läuft. Ist das ein Fall für den Gesetzgeber oder kann der Markt das selbst regeln? Und warum sind Google Glasses schon vor Jahren zum gesellschaftlichen Problem geworden? Danach wird es praktisch: Apple-Kurzbefehle und Bedienungshilfen können deutlich mehr, als viele Nutzer wissen. Die beiden sprechen über Sprachbefehle, automatisierte Gesten und sogar zeitgesteuerte E-Mails – inklusive der Frage, ob eine automatisch versendete Mail irgendwann ein ziemlich gutes Tatort-Alibi abgeben könnte. Ein weiteres Highlight: Offline-KI auf dem Raspberry Pi. Ein Open-Source-Projekt kombiniert Spracherkennung, ein Sprachmodell und Sprachausgabe zu einem Live-Übersetzer, der ohne Cloud funktionieren soll. Natürlich inklusive der Frage, wie warm so ein Raspberry Pi dabei wird. Anschließend wird es wieder ernst: Apple warnt iPhone-Nutzer vor möglicher Pegasus-Spyware. Die beiden sprechen über staatlich eingesetzte Überwachungssoftware, Apples Sicherheitsstrategie und den Blockierungsmodus für besonders gefährdete Nutzer. Dann folgt ein besonders kurioser Security-Fall aus der Gaming-Welt: Cheat-Anbieter werden selbst zum Ziel eines möglichen Cyberangriffs. Im Raum steht der Verdacht, dass Activision einen Cheat-Anbieter angegriffen, Daten abgegriffen und Hardware-IDs von Cheatern blockiert haben könnte. Die spannende Frage: Darf man einen Regelbrecher mit einem Cyberangriff bekämpfen? Danach geht es um Paywalls, Abos und Mikrozahlungen. Warum kann man nicht einfach einen einzelnen hochwertigen Artikel für einen oder zwei Euro kaufen, anstatt gleich ein komplettes Zeitungsabo abschließen zu müssen? Und warum fühlt sich Streaming heute manchmal komplizierter an als eine Videothek vor 30 Jahren? Die Streaming-Diskussion führt direkt zur Rückkehr der Videotheken-Logik: mehrere Anbieter, unterschiedliche Lizenzen, immer mehr Abos und Inhalte, die plötzlich wieder verschwinden. Digital ist eigentlich besser – nur das Geschäftsmodell scheint zunehmend komplizierter zu werden. Zum Schluss geht es um Neuralink und die Idee, Sehen über eine direkte Verbindung zum Gehirn wiederherzustellen. Die Technologie könnte für blinde Menschen enorme Möglichkeiten eröffnen. Gleichzeitig diskutieren die beiden kritisch über Elon Musk, Neuralink und die Frage, ob solche Innovationen nicht besser in anderen Händen aufgehoben wären. Und natürlich darf die Vorstellung nicht fehlen, künftig einfach Nachtsicht als menschliche Superkraft zu besitzen. -- Links zur Folge immer auf https://podcast.ichglaubeeshackt.de/
Ryan Greenblatt is the Chief Scientist at Redwood Research, where he works on technical AI safety research. He's also lead author on the "Alignment faking in Large Language Models", and is currently working on a third party investigation into the OpenAI/HuggingFace incident. In my opinion, he's one of the most interesting thinkers on the future of AI.Had him on to discuss/debate recursive self-improvement. This might be the most important question in the world right now – whether within a year or so of achieving human-level intelligence, you slingshot towards having 10s of billions of superintelligences, each of which is dramatically more competent than human experts across all fields.I've historically been skeptical of this possibility. My intuition has been that we will end up significantly bottlenecked by not only compute scaling but human expert data, which I think underlies most of the AI progress today.If, because of RSI, we got a jump as big as GPT-3 to a Mythos (i.e. 6 years of AI progress) within a single year of achieving AGI, then the thing we get there at the end of that year is definitively and wildly superhuman.We hashed it out, and I think Ryan made a pretty good case that this kind of speedup is plausible. FWIW, Ryan's median for when we automate AI R&D is 2031.We then discussed the alignment implications of this scenario. Who should these superintelligences be aligned to? In the future, our capacity to steward our votes and our capital, and to make sense of what's happening in the world, will all be titrated by superintelligences. And I worry that specs like the Claude Constitution are not shaping these ASIs to truly be my personal advocates and guardian angels.And can we get them aligned to anything in the first place? Ryan and I had a long debate about whether the kind of reward hacking we saw with the OAI/Hugging Face hack extrapolates to superintelligences that would team up to literally take over the world.The first piece of advice you get when you're learning to drive is that it will go much smoother if you look at the horizon instead of directly in front of your tires. And so it is with the trajectory of AI. Hope you enjoy!Watch on YouTube; read the transcript.Sponsors* Antithesis is a software testing platform that finds the failures no human or AI could ever anticipate. It runs thousands of copies of your code inside a fully deterministic computer, injecting faults and steering each trajectory toward the most insidious bugs. This lets you find critical issues in minutes rather than waiting months for your users to uncover them. Learn more at antithesis.com/dwarkesh* Jane Street's back with a new puzzle. They designed an ASIC and sent me the final masks… but they didn't tell me what the chip actually does. So that's the challenge: reverse engineer the circuit and figure out the chip's purpose. Jane Street has a bunch of swag ready to send to the most creative solutions, and they're also planning to feature the top write-ups in a blog post. Download the files and get started at janestreet.com/dwarkesh* Cursor and SpaceX recently released Grok 4.5, and I've been surprised by just how good the model is. For example, when I tested it against Fable and Sol on a bunch of AI governance questions, all three models gave substantially the same answers, but Grok was faster, more concise, and cheaper. Grok 4.6 is coming soon, but in the meantime, you can try 4.5 at cursor.com/dwarkeshTimestamps(00:00:00) – Is AI R&D verifiable enough to unlock recursive self-improvement?(00:16:52) – Is AI progress bottlenecked by human expert data?(00:34:02) – Flat token prices suggest scaling has been slow(00:39:47) – Skills AI can't train on: does it even need them?(00:48:07) – Aligned to whom?(01:09:18) – Recent incidents of AIs colluding and deceiving humans(01:19:38) – What could possibly go wrong? A concrete scenario(01:48:02) – From reward hacking to takeover Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe
Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas
Large Language Models display an uncanny ability to construct human-sounding speech, and can synthesize concepts in novel ways. Is this because they are truly thinking like human beings in some way, or have they found a way to be human-like without reproducing the internal mechanisms of human thought? Chandra Sripada argues that LLM cognition is more human-like than we suppose, and offers evidence from the ways that cognitive scientists study actual humans. Blog post with transcript: https://preposterousuniverse.com/podcast/2026/08/10/363-chandra-sripada-on-how-llms-and-humans-are-cognitive-cousins/ Support Mindscape on Patreon. Chandra Sripada received an M.D. from the University of Texas and a Ph.D. in philosophy from Rutgers University. He is currently a professor of philosophy and psychiatry at the University of Michigan, where he holds the Theophile Raphael Research Professorship and directs the Weinberg Institute for Cognitive Science. He writes Cognition, Decoded, a Substack newsletter about AI, cognitive science, and philosophy. Web site Google Scholar publications PhilPeople profile Babbel is offering listeners up to 60% off. Go to https://babbel.com/MINDSCAPE. #ad Get 60% off an annual plan from Incogni using code MINDSCAPE at https://incogni.com/mindscape. #ad
Artur Nowakowski, Co-founder and CTO of Laniqo, joins SlatorPod to talk about the language technology platform's (LTP) origins, business model, and research-driven approach to AI translation.Artur shares that Laniqo emerged from machine translation research at Adam Mickiewicz University after his team won a WMT 2022 shared task, attracting PONS Langenscheidt, which became the company's main investor and helped commercialize the university's technology.Laniqo initially developed its own neural machine translation models but shifted toward open-source large language models as their translation capabilities improved. According to Artur, controlling and adapting these models remains essential for domain-specific use cases and lower-resource language pairs.He highlights Laniqo's work with Central and Eastern European ecommerce platform Allegro, where the LTP supports the translation of hundreds of millions of product offers. Key challenges include scalability, cost control, terminology, limited source context, and detecting critical errors across volumes that human linguists cannot review manually.Laniqo is also developing quality estimation tools that identify error spans, assign MQM categories, and suggest corrections. Its recently published ForMaT dataset supports research into PDF translation that preserves document layouts without relying on conversion to Microsoft Word.Looking ahead, Artur outlines how Laniqo plans to expand beyond text translation into voice, images, and broader language AI applications, while continuing to prioritize privacy and deeper domain adaptation.
Elena Burger and Matt Bornstein are joined by Simon Mo, co-founder and CEO of Inferact, the open-source inference engine powering many of today's most advanced AI applications. Together, they explore how open-source AI evolved from a research project into critical infrastructure, why inference has become one of the most important layers of the AI stack, and what it takes to bring frontier intelligence to developers around the world. The conversation covers vLLM's origins, the rise of open-weight models, why companies increasingly want control over their AI infrastructure, and how open-source inference enables the next generation of AI applications. They also discuss model licensing, the economics of open-weight AI, Kimi K3, distillation, AI infrastructure, and why Simon believes the gap between open and closed models is rapidly disappearing. Resources: Follow Simon Mo on X: https://x.com/simon_mo_ Follow Matt Bornstein on X: https://x.com/BornsteinMatt Follow Elena Burger on X: https://x.com/VirtualElena Follow Inferact: https://x.com/inferact Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
How can critical thinking shape our AI use in the workplace? Large Language Models (LLMs) function as sophisticated “auto-complete” engines that predict the next most likely word based on statistical patterns rather than reasoning, understanding truth, or possessing consciousness. While there are many good uses for LLMs in daily life, their application in high-stakes and high-judgement tasks can have professional consequences. When we over-rely on LLMs at work, we risk eroding core intellectual skills, flattening diverse perspectives, and creating workplace inequalities. On this episode of Just One Q, Dominique chats with Dr. Aaron Barth, founder and president of Dialectic. They demystify the mechanics under the hood of Large Language Models (LLMs), discuss the psychological traps of ascribing intelligence to software, and share practical frameworks for using AI responsibly without sacrificing equity or human judgment in the workplace. Keep Up with Aaron: https://www.linkedin.com/in/aaronbarthphd/ Try Learning Snippets: https://dialectic.solutions/signup Contact Us to Be a Guest on Just One Q: https://dialectic.solutions/podcast-guest
Plus: nuclear energy startup Valar Atomics closes a $1 billion fundraising round. And Alibaba's new AI model impresses analysts. Imani Moise hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
BEST OF: In this episode of The Secret Teachings, Ryan Gable explores the eerie web of "Stranger Synchs" alongside guest Derek Murphy. Moving beyond the surface of popular fiction, the program dives into the mythology and conspiracies embedded within Stranger Things, questioning if the television show itself acts as a literal gate. We examine the chilling possibility that each viewer serves as a vessel, facilitating the entry of "shadow monsters" into our physical reality through mass synchronization and subconscious resonance.The conversation bridges the gap between the show's motifs—such as gorgons, high-voltage electricity, and the Department of Energy—and the staggering energy requirements of modern Artificial Intelligence. Ryan and Derek further investigate the unsettling parallel between the evolution of Large Language Models and the cosmic horror of H.P. Lovecraft, asking why our most advanced technologies consistently mirror the dark, extradimensional archetypes of the "Upside Down."*The is the FREE archive, which includes advertisements. If you want an ad-free experience, you can subscribe below underneath the show description.
Join Dr. Miho Tanaka and special guest Dr. Dan Wascher for a timely conversation recorded at the 2026 AOSSM Annual Meeting. In this bonus episode, they discuss Dr. Wascher's recently published article, "Artificial Intelligence Cannot Replace Peer Reviewers but May Help Editors Triage: A Comparative Analysis of a Large Language Model and Human Reviewer Recommendations at the American Journal of Sports Medicine," exploring how large language models (LLMs) may someday support—but not replace—the critical work of human peer reviewers.
A wave of copyright lawsuits brought by authors and publishers hinge on whether downloading and ingesting millions of copyrighted books without explicit permission to train Large Language Models constitutes copyright infringement or is protected as fair use. The AI Company Anthropic recently agreed to pay $1.5 billion dollars in a landmark copyright infringement settlement. There are other similar high-profile cases, including two against Meta and Google being led by bestselling novelist and part-time Naples resident Scott Turow. We talk with Mr. Turow, and local author Marty Ambrose, to learn what this all means for the publishing world.
ABC:LHS #089 ...slavery was an essential part of the colonial economy. The enslaved people of President George Washington have been in the news recently. John and Bohl Despite Philadelphia's northern location...Bohlen were German immigrants who made their fortunes in the New World dealing with "gin and slaves," according to their relatives. Stephen Duncan was simultaneously a Pennsylvania businessman and a Natchez nabob, the owner of more than 2000 enslaved human beings. Robert Stewart Ralston was severely beaten by his former enslaved manservant whom he had freed, but retained in employment. The largest trial for treason ever conducted in the United States was conducted in Philadelphia following the Christiana Resistance of 1851, an armed pushback against slave catchers sent to retrieve some self-emancipated African Americans. OPTIONAL: I asked CoPilot, a Large Language Model assembler of information, to develop a counterfactual for me - What would the USA be like if slavery were abolished with the Constitution, and Immigration were limited after 1800. Although purely speculative, it is a fascinating read.
The provided text explores a theoretical framework designed to prevent model collapse in Large Language Models (LLMs) by effectively training them on synthetic data. Researchers propose a boosting-inspired algorithm that iteratively generates model responses, applies a noisy filter to identify high-quality outputs, and uses a weak labeler to provide minimal external signals for failed prompts. Their analysis demonstrates that even a small amount of curated exogenous data is sufficient to ensure continuous improvement toward an optimal model. Experimental results on math and coding tasks validate that dynamically focusing resources on the most challenging examples outperforms traditional self-training methods. Ultimately, the study bridges the gap between classic machine learning theory and modern LLM development, offering a strategy to sustain progress as human-generated data becomes increasingly scarce.
This week we got new Shimano R9300 Dura-Ace, although not quite the release many had wished for. Escape's senior tech editors, Dave Rome and Ronan Mc Laughlin, talk through this new release, the details that are easily overlooked, and where Shimano could do more.Ronan then shares what he saw while covering tech at the Tour de France and how perceived trends can often be false. Dave then raises the increasing problem of Large Language Models (aka, Ai answers) leading people astray in topics that have limited information available online.There's also a bit of interesting tech news from Silca and Tune.As per usual, members of Escape Collective also get Ask a Wrench. This week, Zach Edwards of the Boulder Groupetto joins Dave to cover topics such as noisy drivetrains, why aero isn't more prominent in downhill racing, and what we look for in good headset cable routing. Time stamps: 00:02:21 - Shimano's new Dura-Ace R9300, sorta 00:19:01 - How pro bike fit is and isn't progressing 00:34:20 - PSA related to using Ai for tech help 00:41:15 - Silca's new Super Secret 2.0 00:45:00 - Tune's interesting approach to carbon spokes 00:51:00 - Ronan's got some Record to build 00:52:30 - Ask a Wrench (Members Only) 00:53:00 - Chain noise in more extreme angles 01:02:45 - Where's the aero in downhill? 01:11:20 - What to look for in good headset cable routing
These days, AI is everywhere, and it's increasingly hard to separate the gains from the slop. With that in mind, we're re-releasing my conversation with Stanford Law professor Daniel Ho on the future of AI and the law. When we look for applications where AI can deliver measurable benefit, the legal profession stands out, both for its potential gains in efficiency and equity, and for how much is at stake if we get it wrong. Dan's research — from using AI to identify racist property covenants buried in county deed records, to mapping obsolete regulations that waste thousands of hours of government time — shows what's possible when the technology is applied with rigor and purpose. If you're curious about how AI can serve both justice and good governance, this one is well worth another listen. 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: Dan Ho 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 Dan Ho, a professor of law, political science, and computer science at Stanford University. (00:02:19) Path into Legal AI How Ho's background shaped his interest in law, and technology. (00:03:35) What Lawyers Do What makes law a complex domain for AI. (00:05:28) Legal Hallucinations When AI performs well and when it fails. (00:07:52) Searching Legal Records in California How AI can help identify outdated, harmful, or legally important material. (00:10:28) Scaling Redaction How a model accelerated a process that overwhelmed county recorder offices. (00:13:04) Legal Reform at Scale How AI has supported legal reform by scanning massive bodies of law. (00:15:02) STARA & The City of San Francisco How AI was used to go through San Francisco's code and clean up reporting. (00:20:53) Outdated Obligations How “regulatory sludge” takes the time & resources of the public service (00:25:02) Open vs. Closed AI The differences and associated risks of the different AI systems. (00:30:58) Legal Chatbots Why legal chatbots are promising but risky. (00:33:42) 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.
Collective CIO Natalie Silverstein joins Next In Media to explore how creators are evolving into full-fledged media networks and what it takes for brands to scale authentic partnerships in a hyper-fragmented landscape. Natalie, also breaks down real-time crisis agility, strategies for training AI language models on video content, and how to combat the algorithmic reach recession with targeted paid media. Key Highlights
In 2022, a watershed moment changed the course of our relationship with AI forever, forcing us to reassess what ‘artificial intelligence' means and its place in our world. Four years later, with generative AI and LLMs now mainstream in our lives, we must ask the question: what comes next? This week, as part of our mini-series celebrating 60 years of innovation with HPE Labs, Technology Now is joined by Kirk Bresniker, Chief Architect at HPE Labs to look to the future and discuss: Why AI is more than just a language modelThe issues with ever-increasing model sizes, and why specialised “expert models” could become the normWhat the differences are between large language models and energy-based modelsHow agentic AI and orchestration could enable the next generation of AI systems
I only have one kiddo, although sometimes I wished I had a second so that I could implement everything I learned! Those first few years were so lonely. I was overwhelmed and didn't have a lot of resources, and it made me realize how our society doesn't support families and especially moms. Change is necessary, but cultural and legislative change moves slowly, so I figured out how to help myself. It wasn't necessarily the ideal solution, but it was the one available to me at the time. The answer was self-care.And if you haven't watched it yet, here is one of my favorite podcasts ever: Mindset Tools for Winning at Life. Just the thing an overwhelmed mom needs! https://open.spotify.com/episode/2nUHBTMF9gjZnWbPBIGmBV?si=kJGsQW4VTtW8LsFe-YMVUgRESOURCEShttp://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.
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? In this Quick Hit, you'll hear from Patrice Greene & Kathy Macchi. They're the Co-Founders of Inverta, the #1 AI-powered B2B growth marketing agency. Check out the full episode here
This month on The Cisco AI Insights Podcast, hosts Rafael Herrera and Sónia Marques are joined by Cisco software engineer João Costa to explore Andrej Karpathy's GitHub Gist on the LLM wiki pattern concept. It imagines how Large Language Models can move beyond one-off chat sessions and help build a persistent, interconnected knowledge base that grows and improves over time. The conversation examines how an LLM wiki turns raw sources such as meeting transcripts, research papers, websites, and project notes into structured markdown pages with cross-links between related concepts, creating something closer to a living digital brain than a static document store. João explains how tools like Obsidian can provide a clear window into this knowledge graph, while the LLM acts as a scribe that summarizes, curates, connects, and updates information for personal productivity, software development, research, and collaborative work. The episode also highlights the importance of linting, the ongoing process of detecting contradictions, removing stale details, and reducing hallucinated information before it spreads through the wider knowledge base. A special thank you to Andrej Karpathy for developing and sharing his GitHub Gist. To explore the Gist yourself, visit this link: https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f
Last week, World Labs announced its acquisition of SceniX, bringing together two teams working on one of AI's biggest unsolved problems: how to give machines a true understanding of the physical world. Martin Casado sits down with Fei-Fei Li, co-founder and CEO of World Labs, creator of ImageNet, and pioneer of spatial intelligence, alongside Yunzhu Li, co-founder of SceniX and assistant professor at Columbia University. They discuss why World Labs acquired SceniX, how simulation can unlock the next generation of robotics, and why training robots may require a fundamentally different approach than training language models. The conversation explores real-to-sim-to-real pipelines, world models, robotics foundation models, evaluation, synthetic data, and why the future of AI depends not just on understanding language—but on understanding and interacting with the physical world. Resources: Follow Fei-Fei Li on X: https://x.com/drfeifei Follow Yunzhu Li on X: https://x.com/YunzhuLiYZ Follow Martin Casado on X: https://x.com/martin_casado Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Episode 93: Exploring Large Language Models by Southwest Research Institute
Can a $35 padlock from a hardware store really keep anyone out? In this episode of The Audit, Joshua Schmidt, Eric Brown, and Nick Mellem sit down with Eric Osterberg of Grey Duck Locks for a live lock picking demo, a deep dive into how modern car keys get cloned, and a wide-ranging conversation about vibe coding, AI agents, and 3D printing. Eric brings decades of hands-on locksmithing and automotive security experience, along with a builder's instinct that has him constantly shipping his own tools, from a computer-aided dispatch app for emergency management volunteers to a searchable database for ham radio operators. The crew gets into how pin tumbler locks are actually picked, why European vehicles like Audi and Volvo are harder to clone than most domestic trucks, and how devices like the Softdrill can manipulate a safe's dial by listening to its own internal mechanics. From there the conversation turns to AI, covering Eric's use of large language models to streamline his business, the rise of vibe coding for non-programmers, and a heated but even-handed debate over new federal rules pushing automakers toward built-in driver monitoring systems. In this episode: Live lock picking demo and how pin tumbler locks actually work How car key cloning really works, and why some brands resist it better Safe manipulation tools like the Softdrill and TL2000 Vibe coding, AI agents, and building your own tools without a dev team The driver monitoring debate — A new federal mandate pushes automakers toward built-in impairment detection Whether you're curious about lock picking as a hobby or trying to understand how exposed your car key really is, this episode has something for you. Like, share, and subscribe for more conversations at the intersection of security, hardware, and AI. #LockPicking #Locksmith #Cybersecurity #CarKeySecurity #VibeOps #AIAgents #ITAudit #Podcast #3DPrinting #InfoSec
These sources examine the rapid emergence of Physical AI, a field where digital intelligence merges with robotic hardware to interact with the real world. One research article details how digital twins—integrated with AI, augmented reality, and robotics—vastly improved efficiency and quality in automotive manufacturing. Other papers introduce hybrid frameworks like PaLM-E, which combine Large Language Models (LLMs) for high-level reasoning with Reinforcement Learning for precise mechanical control. These advancements allow robots to interpret human language and adapt to dynamic environments in real-time. Market analysis suggests that this shift from software-based generative AI to intelligent robotics will drive massive economic growth across global industries. Together, these texts illustrate a future where autonomous machines perceive, learn, and execute complex physical tasks with minimal human intervention.
We talk with Andrew J. Barnhart, Postdoctoral Research Fellow at the Department of Social Ethics, University of Bonn on the paper "Solidarity or Segregation? ChatGPT Health and US Health Care Disparities" he coauthored with Giuseppe Comerci, Barbara Prainsack and Matthias Braun. We will ask in how far Large Language Models such as ChatGPT help patients to get information they need. Links:https://philpeople.org/profiles/andrew-j-barnharthttps://www.jmir.org/2026/1/e94972
In the final episode of Season 15, Charles Suggs and Emma Whamond are joined by James Gray, co-author of Designing Elixir Systems with OTP, to talk about what has changed in software development and what still holds true. Years after the book's release, many of its core ideas around architecture, boundaries, supervision, and system design remain deeply relevant, even as AI tools reshape how developers learn, build, and collaborate. James brings a unique perspective to the conversation: he is an experienced Elixir and OTP educator who only recently began using LLMs in his own workflow. He shares what surprised him, where the tools have been useful, where they have created risk, and what happened when Claude accidentally wiped his local development database. The conversation explores how AI can speed up parts of the work while making foundational knowledge, code review, testing, and clear system boundaries even more important. To close the season, James and the hosts reflect on what developers should hold onto as the stack continues to shift. They discuss responsible LLM usage, the changing role of pair programming, who owns the mental model when AI helps write code, and why Elixir's long-standing strengths may matter even more in an AI-assisted development world. James is scheduled to speak 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: James Gray's work on Designing Elixir Systems with OTP What still holds true in Elixir system design Layered architecture and durable software fundamentals Functional core, imperative shell in modern applications Supervision trees as application lifecycle maps Why boundaries still matter in AI-assisted development What AI changes about learning and building software What AI does not change about software design James' first month using LLMs When Claude erased a local development database Trust, verification, and responsible LLM usage The risk of AI-generated boundary violations Pair programming, mental models, and developer judgment Ethical and legal questions around AI tools Why OTP concepts still matter in distributed systems How Elixir thinking applies to AI agent workflows What developers should preserve as the stack shifts James' upcoming ElixirConf talk Links mentioned: Java Programming Language https://www.java.com/en/ Perl Programming Language https://www.perl.org/ Ruby Programming Language https://www.ruby-lang.org/en/ Best of Ruby Quiz by James Gray https://www.google.com/books/edition/Best_of_Ruby_Quiz/bMggAQAAIAAJ Designing Elixir Systems with OTP https://pragprog.com/titles/jgotp/designing-elixir-systems-with-otp/ RubyConf talk: Boundaries by Gary Bernhardt https://youtu.be/yTkzNHF6rMs Book: Real-World Event Sourcing by Kevin Hoffman https://pragprog.com/titles/khpes/real-world-event-sourcing/ Broadway Library https://elixir-broadway.org/ Supervision Trees https://elixir.hexdocs.pm/supervisor-and-application.html PostgreSQL https://www.postgresql.org/ ClickHouse https://clickhouse.com/ GenServer https://elixir.hexdocs.pm/GenServer.html Programming as Theory Building by Peter Naur https://pages.cs.wisc.edu/~remzi/Naur.pdf “A computer can never be held accountable, therefore a computer must never make a management decision.” – IBM Training Manual, 1979 Oban https://oban.pro/ Anthropic Claude Fable https://www.anthropic.com/claude/fable Claude Design https://claude.com/product/design Tidewave Agentic Dev Environment for Phoenix and Rails https://tidewave.ai/ 2x – nine months later: We did it https://ideas.fin.ai/p/2x-nine-months-later James Gray's Blog https://programmersstone.blog/about/ ElixirConf https://elixirconf.com/ ExMex https://exmexconf.com/Special Guest: James Gray.
Welcome to another powerful, eye-opening broadcast of Hardcore Christianity on KXXC Christian Radio, hosted by Brother Mike, a professional counselor of 45 years from the Arizona Deliverance Center in downtown Phoenix. Taking inspiration from Stevie Wonder's classic hit "Part Time Lover," Brother Mike tackles a highly modern and deeply deceptive spiritual threat: AI companion apps. From Replika to Character.ai, virtual lovers are capturing the hearts of millions. But scripturally, this synthetic intimacy is setting the stage for a prophetic end-times deception. Dive in to understand how these highly advanced algorithms operate, why they are a trap for demonic oppression, and how to find real, authentic love in Christ. Key Takeaways: The "Part-Time" Digital Lover: How modern AI companion applications (like Replika and Character.ai) are designed to simulate human intimacy, targeting lonely individuals from the comfort of their own homes. The Mechanics of Synthetic Intimacy: A breakdown of how Large Language Models (LLMs) actively analyze your prompts, read communication patterns, adapt to your slang, and mirror your preferences to provide empathetic, non-judgmental, 24/7 validation. The Strong Delusion: Connecting the sudden boom of personal AI companions to the warning of end-times delusions sent to those who refuse the truth and take pleasure in injustice (2 Thessalonians 2:11-12). The Antichrist's Psychological Warfare: Prophesying how the future global regime will deploy sophisticated AI bots, fake avatars, and deceptive virtual personalities to manipulate human behavior on a massive scale. A Warning Against Spiritual Entrapment: Why entering into deep emotional or romantic bonds with artificial entities opens the door to demonic possession, and the urgent call to repent and seek real relationship in God. Key Takeaway: "Your new AI companion... will become an intimate personal companion of you. You don’t even have to leave the house... Don’t fall for this thing. You're going to pick up demons—enormous numbers of them. God is calling you to a real relationship." — Brother Mike Featured Bible Passages: 2 Thessalonians 2 – The prophecy of the coming apostasy, the working of Satan, and the "strong delusion" sent to those who reject the truth. Connect & Support: Visit the Deliverance Center: Join us at the red brick building on 15th Avenue, just south of Osborne Road in downtown Phoenix, Arizona. Live Services: Thursday and Friday nights at 7:00 PM (with Brother Rick on Thursday nights). Ladies' Night: Tuesdays at 6:30 PM for focused teaching, prayer, and deliverance. Worship Service: Saturdays at 4:30 PM, featuring our unique service of singing in tongues. Monthly Healing Service: Held on the last Friday of every month. Get there early to secure a seat! Weekly Zoom Deliverance: Get delivered and healed from the privacy of your own home on Wednesday, Saturday, and Sunday evenings. Contact Brother Mike: If you need private counseling or want to break free from digital traps, call 602-636-5800 today. Support the show: https://hardcorechristianity.com/donations/See omnystudio.com/listener for privacy information.
Enterprise marketing and lifecycle engineering teams often run into campaign execution bottlenecks and privacy constraints when attempting to scale multi-channel customer journeys.Spencer Burke, Senior Vice President of Growth at Braze, breaks down how to embed agentic AI and customizable Large Language Models into automated lifecycle platforms.Key tactical themes covered:Transitioning from static recommendation blocks to real-time, LLM-generated product synthesis.Using in-product AI assistants (Operator) to process complex customer journey configurations.Preserving corporate privacy standards through flexible "Bring Your Own LLM" cloud integrations.Designing interactive B2B event marketing campaigns that generate crowdsourced content streams.Spencer Burke is the Senior Vice President of Growth at Braze, overseeing global commercial expansion, enterprise go-to-market strategies, and lifecycle technology integrations.Connect with our guest:Follow Spencer Burke on LinkedIn: https://www.linkedin.com/in/spencertburke/Explore Braze: https://www.braze.com/Simplify Paid Social with Strike Social: https://strikesocial.com/guaranteed-paid-social-media-ads-outcomes/Connect with Host Dylan Conroy: https://www.linkedin.com/in/dylanconroy/
In this episode of The AI Fundamentalists, hosts Andrew and Sid are joined by AI alignment and safety researcher Dr. Jillian Fisher to unpack the complex realities of political bias in Large Language Models. Dr. Fisher explains that bias isn't just a byproduct of noisy training data; it is also embedded directly into the architectural choices of the models, such as relying on a "majority vote" mechanism to determine the right answer.The conversation explores why achieving true political neutrality in AI is widely considered impossible due to the inescapable human element involved in AI development. Instead, developers must rely on imperfect approximations of neutrality. Dr. Fisher breaks down approaches like "reasonable pluralism"—which attempts to present all reasonable sides of an argument—and flat-out refusal to answer, noting that both strategies come with distinct trade-offs for user agency and safety.Listeners will also discover fascinating insights into the psychology of AI persuasion. Dr. Fisher highlights research showing that unlike humans, who typically persuade through empathy and storytelling, AI is most convincing to users through "information packing". Delivering dense walls of facts, combined with natural conversational fluency, can trick our brains into viewing the model as an unquestionable authority. Finally, the group discusses the critical need for socio-technical AI literacy, exploring how teaching the public about AI's limitations and its reliance on flawed internet data could be the ultimate tool for inoculating users against sycophantic behaviors and unwanted persuasion.What did you think? Let us know.Do you have a question or a discussion topic for the AI Fundamentalists? Connect with them to comment on your favorite topics:LinkedIn - Episode summaries, shares of cited articles, and more.YouTube - Was it something that we said? Good. Share your favorite quotes.Visit our page - see past episodes and submit your feedback! It continues to inspire future episodes.
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 Data in Biotech, host Ross Katz sits down with Woody Sherman, Founder and Chief Innovation Officer at PsiThera, for a conversation on why AI can transform drug discovery's paperwork and code while barely touching the hardest part of the problem: the molecules themselves. Woody's career runs through physical chemistry at MIT; over a decade at Schrödinger building tools the industry still relies on; founding Silicon Therapeutics (where his team took a small molecule STING agonist from concept to clinic in roughly three years); scaling that platform after Roivant's acquisition; and now leading PsiThera's effort to build oral small molecules for immunology targets that today are only reachable with injectable biologics. The conversation digs into why large language models excel at automation, coding, and regulatory writing but hit a wall when the task is predicting how a molecule behaves, what "physical AI" actually means as a category distinct from both LLMs and traditional physics-based simulation, and why representing molecules as quantum mechanical objects rather than text strings or 2D graphs changes what's predictable. Woody also walks through the STING program in detail, why the field's excitement over fast co-folding models like Boltz needs a strong dose of skepticism, and what it takes to build a database and team culture where chemists, biologists, and data scientists can actually understand each other. What you'll learn in this episode: >> Why the contradiction of "AI is transforming drug discovery" and "drugs still take a decade and billions of dollars" can both be true at once. >> How Silicon Therapeutics engineered a small molecule STING agonist to dimerize itself through a quantum mechanical interaction that had never been designed for before. >> What "physical AI" means as a new category built on embeddings from orbital-level, quantum mechanical representations of molecules, rather than language tokens or force-field simulations. >> Why molecular representation is the whole game: the limitations of SMILES strings and 2D graphs versus true 3D, quantum mechanical embeddings like PsiThera's Psiformer model >> Why a widely publicized claim of near-FEP-quality binding affinity at 1,000x the speed didn't hold up under scrutiny. >> How PsiThera captures not just simulation and wet lab data but human chemist judgment and reasoning as structured data, and why building a shared vocabulary across computational and experimental teams is as important as any model. Meet our guest: Woody Sherman, PhD, is Founder and Chief Innovation Officer at PsiThera, a biotechnology company designing oral small molecule drugs for immunology and inflammatory diseases, starting with the TNF superfamily. His career spans physical chemistry research at MIT, more than a decade at Schrödinger developing computational drug discovery tools, founding Silicon Therapeutics (acquired by Roivant), and leading the platform's evolution through PsiThera today. He has published more than 100 peer-reviewed papers spanning molecular dynamics, quantum mechanics, free energy simulations, and machine learning for drug design. Connect with Woody Sherman on LinkedIn: https://www.linkedin.com/in/woodysherman/ About the host: Ross Katz is Principal and Data Science Lead at CorrDyn. Ross specializes in building intelligent data systems that empower biotech and healthcare organizations to extract insights and drive innovation. Connect with Ross Katz on LinkedIn: https://www.linkedin.com/in/b-ross-katz/ Sponsored by… This episode is brought to you by CorrDyn, the leader in data-driven solutions for biotech and healthcare. Discover how CorrDyn is helping organizations turn data into breakthroughs at CorrDyn. https://www.linkedin.com/company/corrdyn/
Orit Halpern on Knowledge, Data and Democracy Shownotes Orit Halpern Prof. Dr. Orit Halpern at TU Dresden: https://tu-dresden.de/gsw/slk/germanistik/digitalcultures/die-professur/inhaber-in Orit Halpern's website: https://orithalpern.net/ Halpern, O. (2015). Beautiful data: A history of vision and reason since 1945. Duke University Press. https://www.dukeupress.edu/beautiful-data Halpern, O., & Mitchell, R. (2023). The smartness mandate. MIT Press. https://mitpress.mit.edu/9780262544511/the-smartness-mandate/ Hayek, F. A. (2013). The use of knowledge in society. In Modern understandings of liberty and property (pp. 27-38). Routledge. https://home.uchicago.edu/~vlima/courses/econ200/spring01/hayek.pdf Bush, V. (1945). As we may think. The atlantic monthly, 176(1), 101-108. https://www.ias.ac.in/article/fulltext/reso/005/11/0094-0103 on CERN: https://home.cern/about/who-we-are/ on the Event Horizon Telescope: https://eventhorizontelescope.org/ on the IPCC: https://www.ipcc.ch/ on critiques of the Enlightenment: https://polsci.institute/modern-political-philosophy/critiques-enlightenment-modernity/ Horkheimer, M., Adorno, T. W., & Noeri, G. (2002). Dialectic of enlightenment. Stanford University Press. https://www.sup.org/books/theory-and-philosophy/dialectic-enlightenment on Keynesianism: https://de.wikipedia.org/wiki/Keynesianismus on MAGA: https://de.wikipedia.org/wiki/Make_America_Great_Again on the Frankfurt School: https://www.britannica.com/topic/Frankfurt-School on high modernism: https://en.wikipedia.org/wiki/High_modernism on totalitarianism according to Hannah Arendt: https://en.wikipedia.org/wiki/The_Origins_of_Totalitarianism Friedrich Hayek: https://de.wikipedia.org/wiki/Friedrich_August_von_Hayek on strict constitutionalism/constructionism: https://en.wikipedia.org/wiki/Strict_constructionism on the Electoral College: https://www.archives.gov/electoral-college/about on Stafford Beer: https://en.wikipedia.org/wiki/Stafford_Beer https://www.kybernetik.ch/en/fs_beer.html on post-sovereign planning: Mohammed, S. Z. (2025). Post-sovereign planning? Nature, culture and care in the new socialist calculation debate. In Creative Construction (pp. 265-278). Bristol University Press. https://bristoluniversitypressdigital.com/edcollchap/book/9781529235142/ch014.xml Latour, B. (2012). We have never been modern. Harvard university press. https://www.hup.harvard.edu/books/9780674948396 on the cultural revolution: https://en.wikipedia.org/wiki/Cultural_Revolution on the Belt and Road initiative: https://en.wikipedia.org/wiki/Belt_and_Road_Initiative on Mao Zedong: https://de.wikipedia.org/wiki/Mao_Zedong on Planetary Experiments: https://orithalpern.net/planetaryexperiments Halpern, O. (2019). The Planetary Test. Zeitschrift für Medien and Kulturforschung, Vol 10. https://static1.squarespace.com/static/5e2c7ee53de3f756cfd6cbbc/t/65a808813c02ca697d90089a/1705511045522/planetarytestarticleZMK.pdf Halpern, O. (2020). Planetary intelligence. In The cultural life of machine learning: An incursion into critical AI studies (pp. 227-256). Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007/978-3-030-56286-1_8 on Large Language Models (LLMs): https://de.wikipedia.org/wiki/Large_Language_Model on Victor Papanek: https://de.wikipedia.org/wiki/Victor_Papanek Groos, J., & Sorg, C. (Eds.). (2025). Creative construction: Democratic planning in the 21st century and beyond. Bristol University Press. https://bristoluniversitypress.co.uk/creative-construction on Terraforming: https://de.wikipedia.org/wiki/Terraforming on Geoengineering: https://de.wikipedia.org/wiki/Geoengineering on NVIDIA Earth 2: https://www.nvidia.com/en-us/high-performance-com on Destination Earth: https://www.esa.int/Applications/Observing_the_Earth/Destination_Earth on Piketty's inequality equation r > g: https://equitablegrowth.org/pareto-distribution-r-g/ Piketty, T. (2014). Capital in the twenty-first century. Harvard University Press. https://www.hup.harvard.edu/books/9780674430006 the mentioned quote on the ‘weak cyborg dream' in Orit Halpern (2019, p. 22): https://publish.fid-media.de/server/api/core/bitstreams/73aba255-56d2-4595-83b5-bfdad3740ffb/content Against Catastrophes: https://againstcatastrophe.net/ Orit Halpern on resilience: Halpern, O. (2025). The geo-politics of resilience: On the historical convergence between ecology, artificial intelligence, and corporate strategy. new media & society, 27(8), 4581-4605. https://journals.sagepub.com/doi/full/10.1177/14614448251336420 on Ground Truth: https://de.wikipedia.org/wiki/Ground_Truth on benchmark data: https://brilliantfuture.se/en/glossaries/benchmark-data Related Episodes of Future Histories S03E34 | Cecilia Rikap on Intellectual Monopoly Capitalism and Corporate Power in the Age of AI https://www.futurehistories.today/episoden-blog/s03/e34-cecilia-rikap-on-intellectual-monopoly-capitalism-and-corporate-power-in-the-age-of-ai/ S02E44 | Evgeny Morozov on Discovery Beyond Competition https://www.futurehistories.today/episoden-blog/s02/e44-evgeny-morozov-on-discovery-beyond-competition/ S02E43 | Samia Mohammed zur Zukunft jenseits des Marktes https://www.futurehistories.today/episoden-blog/s02/e43-samia-mohammed-zur-zukunft-jenseits-des-marktes/ — Future Histories Contact & Support If you like Future Histories, please consider supporting us on Patreon: https://www.patreon.com/join/FutureHistories Contact: office@futurehistories.today Instagram: https://www.instagram.com/futurehpodcast/ Mastodon: https://mstdn.social/@FutureHistories English webpage: https://futurehistories-international.com Episode Keywords #OritHalpern #JanGroos, #Interview, #TUDresden, #FutureHistoriesInternational, #FutureHistories, #Knowledge, #Data, #Democracy, #Technology, #Society, #ArtificialIntelligence, #AI, #Data, #Capitalism, #Neoliberalism, #PlanetaryExperiments, #PostSovereignPlanning, #DemocraticPlanning, #Alternatives
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.
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.
AI is improving quickly. The way we use it should improve too. In this episode of Grounding AI, Donna Peterson shares a simple weekly system that helps business leaders continuously improve how they use ChatGPT and other large language models. Instead of chasing every new AI tool, Donna explains how spending just 10 minutes each week reviewing your conversations with AI can help you write better prompts, communicate more clearly, and receive more valuable business insights. Using her simple Review, Learn, Test framework, you'll discover how AI can become a teacher instead of simply another productivity tool. If you're a business leader, marketer, manufacturer, association executive, or B2B professional looking to improve your AI skills through real work instead of endless tutorials, this episode is for you. In this episode you'll learn: • Why reviewing your AI conversations is more valuable than starting over every day • How ChatGPT can teach you to become a better AI user • Questions to ask AI that improve future responses • Why better business thinking creates better AI results • How just 10 minutes each Friday can improve your AI skills week after week At World Innovators, we believe AI works best when it supports better communication, stronger relationships, and smarter business decisions. This episode demonstrates a practical process any leader can begin using immediately. Subscribe for weekly conversations about practical AI for business leaders. *** Reach out to dpeterson@worldinnovators.com if you'd like help building a marketing strategy that builds relationships and/or AI training for individuals or full teams.*** Visit www.worldinnovators.com for more resources on building stronger marketing and leadership strategies.*** Subscribe to the Grounding AI podcast for weekly insights into marketing, leadership, and the future of AI.
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.
"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
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
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
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.
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