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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.
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.
Is AI the biggest scam of our generation — or the most misunderstood technology in history? Cognitive scientist Gary Marcus has been studying artificial intelligence for over 30 years, and what he has to say will make you question everything you thought you knew about ChatGPT, AGI, and the trillion dollar AI gold rush.In this episode of SparX, we are talking with Gary Marcus – professor, author, and one of the most respected and fiercely independent voices in AI research – about why the promises being made by Sam Altman, Dario Amodei, and Elon Musk may be leading the global economy toward a catastrophic miscalculation.
In this episode of The Cisco AI Insights Podcast, hosts Rafael Herrera and Sónia Marques are joined by Cisco's Technical Leader in Machine Learning Engineering Leticia Fernandes to explore the groundbreaking study, "A Comparative Study of Traditional Machine Learning, Deep Learning, and Large Language Models for Mental Health Forecasting Using Smartphone Sensing Data," which evaluates how different AI architectures analyze complex smartphone behavioral data to predict future mental health states. The discussion delves into the intricacies of forecasting mental health changes using five years of data from the College Experience Sensing dataset, highlighting how deep learning models, particularly transformer architectures, outperform traditional machine learning and Large Language Models by effectively leveraging personalized user behavior to identify subtle anomalies that could signal declining mental health, while also addressing the challenges of data imbalance and the inherent limitations of LLMs in processing high-dimensional, non-textual temporal sequences. A special thank you to the researchers from The Singapore University of Technology and Design, that developed this month's paper. If you are interested in reading the paper yourself, please visit this link: https://arxiv.org/pdf/2601.03603
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
The "data lake" that was supposed to unify bioprocessing intelligence has, in most companies, become something else entirely: a data swamp, where information goes in and insight rarely comes back out. For anyone trying to deploy AI in GMP manufacturing, that is not a technical problem. It is the problem.Steffen Kreye has seen it from both sides. As former upstream development lead at Bayer and now Professor of Industrial Biotechnology at Berliner Hochschule für Technik, he brings an unusually grounded perspective on where AI in bioprocessing actually stands, what the next generation of scientists needs to be equipped with, and what industry can do right now to help close the gap.Key topics discussed:How soft skills like teamwork and self-motivation are becoming increasingly important for scientists, and strategies to foster them in education (02:47)The reality behind AI and machine learning in biotech today, including current limitations and the true state of industry adoption (05:48)Envisioning bioprocessing ten years from now: the potential of continuous manufacturing, digital twins, and automation, and the evolving diversity of bioprocesses (08:09)Practical ways industry professionals can support university education—from guest lectures to hands-on lab courses—and why it matters (10:09)Motivating students by connecting coursework to real industry roles and contributions (12:10)The importance of finding and following individual motivation in science careers (12:41)Reflections on moving from industry to academia: autonomy, challenges, and the satisfaction of seeing students grow into scientists (13:22)How strong collaboration between academia and industry leads to better innovation and prepares future scientists for success (15:53)Smart Insight: Most companies talking about AI in bioprocessing are still solving a more fundamental problem: getting their data into a state where AI could use it at all. The breakthrough will not come from the algorithm. It will come from the unglamorous, years-long work of making data accessible, harmonized, and meaningful across sites, systems, and GMP boundaries.Here are some other guests who touched on similar themes:Episodes 175 – 176 : How Virtual Reality Training Solves Europe's Bioproduction Talent Shortage with Sandrine Lemoine — about training the next generation of biopharma talent.Episodes 93 – 94: From Lab Coat to LinkedIn: Benjamin McLeod's Journey to Cell and Gene Therapy Influencer — another career pivot story from a scientist who stepped outside the traditional industry path.Episodes 111 – 112: AI Meets Biology: Why Domain Expertise Still Rules in the Age of Large Language Models with Lars Brandén — very aligned with Steffen's nuanced take that AI is a tool but human expertise in bioprocessing still matters.Connect with Steffen Kreye:LinkedIn: www.linkedin.com/in/steffen-kreye-3b531183/Berliner Hochschule für Technik: www.prof.bht-berlin.de/kreyeNext Step:If you enjoyed this episode, please leave a review on Apple Podcasts or your favorite podcast platform. By doing so, we can empower more scientists like you. Stay tuned for more inspiring biotech insights in our next episode.Support the show
When AI can draft a literature review in minutes, the question bioprocess educators can no longer avoid is this: what does a student actually need to learn?Steffen Kreye has a clear answer. As Professor of Industrial Biotechnology at Berliner Hochschule für Technik, he trains engineers who step into industry ready to run a bioreactor, not just describe one. His argument is direct: hands-on lab competence is the one thing AI cannot replicate, and it is exactly what underfunding is quietly eroding.Topics discussed:Why Steffen Kreye left his lab head role at Bayer to become a professor and how his career evolved (03:54)The unique mission of universities of applied sciences and their close connection to industry needs (11:16)Challenges of delivering lab-based education, including funding and equipment constraints (12:32)Creative strategies for partnering with biotech companies to sustain practical lab courses (14:34)How reading student theses, partnerships, and conferences help Steffen Kreye and his colleagues stay current in a rapidly changing field (17:43)The impact of AI and digital tools on research, teaching methods, and student assessment (21:18)Why traditional theoretical projects are less relevant, and the growing importance of problem-solving and oral examinations (22:09)In Part 2, Steffen gives his unfiltered take on where AI in bioprocessing actually stands, which human capabilities are becoming harder to replace, and what a well-prepared bioprocess engineer will need to look like by 2035.Smart Insight: Once AI can produce a polished report from a well-structured prompt, the only assessment that still reveals genuine understanding is the one a student has to navigate in real time, without a tool to hide behind.Here are some other guests who touched on similar themes:Episodes 175 – 176 : How Virtual Reality Training Solves Europe's Bioproduction Talent Shortage with Sandrine Lemoine — about training the next generation of biopharma talent.Episodes 93 – 94: From Lab Coat to LinkedIn: Benjamin McLeod's Journey to Cell and Gene Therapy Influencer — another career pivot story from a scientist who stepped outside the traditional industry path.Episodes 111 – 112: AI Meets Biology: Why Domain Expertise Still Rules in the Age of Large Language Models with Lars Brandén — very aligned with Steffen's nuanced take that AI is a tool but human expertise in bioprocessing still matters.Connect with Steffen Kreye:LinkedIn: www.linkedin.com/in/steffen-kreye-3b531183/Berliner Hochschule für Technik: www.prof.bht-berlin.de/kreyeNext Step:If you enjoyed this episode, please leave a review on Apple Podcasts or your favorite podcast platform. By doing so, we can empower more scientists like you. Stay tuned for more inspiring biotech insights in our next episode.Support the show
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!
What if artificial intelligence doesn't replace human intelligence — it amplifies it? And what if the quality of what you bring to AI is exactly what determines what you get back?Welcome to Now I Get It with Dr. Andy. I'm Andrew Winkler, and in this episode I'm taking a deep dive into one of the most consequential technologies of our time: large language models. I break down how these systems are built on surprisingly elegant mathematics, why language itself has a hidden statistical structure that makes AI possible, and what it really means for how we interact with these powerful tools.Tune in as I explore the neural network foundations that underpin modern AI, unpack the "garbage in, garbage out" principle in its most precise form, and reveal why the most important thing you can bring to an AI conversation is your own intelligence and curiosity.In this episode, you will learn:(00:27) Neural networks are built on elegant mathematics(01:15) One nonlinearity unlocks AI's power to model anything(02:47) Models extract signal, not just memorize data(04:30) Language has a hidden statistical structure AI can learn(08:30) AI defaults to average intelligence without strong context(09:03) Smarter input produces smarter AI output(09:45) AI amplifies human intelligence — it doesn't replace itLet's connect!linktr.ee/drprandy Hosted on Acast. See acast.com/privacy for more information.
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
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
This week we sit down with Field Solution Architects Anthony Nocentino and Justin Emerson explore an interesting convergence happening in data architecture—the blending of traditionally separate block and file/object storage systems. Likening the experience to a Chocolate Peanut Butter Cup, Anthony (a database expert focused on block storage) and Justin (an expert in unstructured data and file/object storage) discuss how the clear historical distinctions between structured and unstructured data are rapidly blurring. This shift is fueled by modern challenges like high-scale analytics, data governance, and the rise of technologies like Large Language Models (LLMs) and agentic interactions, which no longer care where the data lives. Our conversation dives into the technical tipping point enabled by data virtualization, referencing features like SQL Server 2022's object integration, which allows a database engine to access data stored efficiently on object storage. This capability is far more than an archival play; it helps customers achieve scale-out analytics, improve data governance by maintaining one canonical copy of data across different performance buckets, and simplify tedious operations like SQL backups by bypassing legacy file system complexities. Anthony and Justin highlight how Everpure's platform aligns perfectly with this new reality. Finally, Anthony and Justin discuss the path forward, noting that the technology is underutilized due to organizational silos and an awareness problem. The next big evolution will focus on security and governance for this distributed data via open table formats like Iceberg and catalogs such as Polaris. We close with what currently excites them: Anthony on collaborating with AI (Claude) to create code and speed up outcomes, and Justin on Everpure's core philosophy of simplicity, efficiency, and treating customers like people, particularly in the context of the current economic conditions. To learn more, visit: https://www.everpuredata.com/platform.html Check out the new Everpure digital customer community to join the conversation with peers and Pure experts: https://purecommunity.purestorage.com/ 00:00 Intro and Career Journeys 04:30 Customer Engagement and SKO 09:55 Vacation Recap 13:45 History of Block and Object Storage 16:04 Why Convergence Now? 20:30 Data Virtualization 25:55 Exploring Access Patterns 29:05 What's Holding Back Adoption 36:02 Simplicity for DBAs
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
Is artificial intelligence about to transform the ICU?In this new episode of the Future of Intensive Care podcast series, we dive into the rapidly evolving world of large language models and their growing impact on intensive care practice. From clinical decision-making and risk recognition to the future relationship between clinicians and AI, what could these technologies really mean for the ICU?Join Professor John Laffey for a thought-provoking discussion exploring the opportunities, challenges, and future of AI in intensive care medicine.Discover how new forms of intelligence could reshape the way we care for the sickest patients — and what clinicians need to know now. Listen to the episode!
In this episode of Fraudology, Karisse Hendrick comes to you from a beachside work-cation in Florida to deliver an essential debrief on the latest shifts in the e-commerce fraud landscape. Fresh off the Accertify Global Customer Summit, Karisse shares key strategic takeaways on why cybersecurity and fraud teams must break down operational silos as fraud signals increasingly move up-funnel.The conversation takes a critical look at the limitations of relying on Large Language Models (LLMs) in risk management. Highlighting a recent blunder where a Top 4 consultancy published a 44-page fraud report riddled with completely fabricated citations and footnotes, Karisse and Dr. Nicola Harding explain why "domain expertise" cannot be automated. Because true fraud insights are kept proprietary to protect them from criminals, open-source AI tools are inherently prone to "hallucinating" facts.We also break down Mastercard's newly announced Scam Merchant Dashboard, which officially goes into effect on July 24th, 2026. This aggressive program places a heavy burden on e-commerce merchants and their acquirers through a multi-trigger framework designed to shut down predatory accounts.Key pillars of Mastercard's new program include:The Authorization Performance Breakdown: A sudden drop in approval rates—such as a 50 percentage point decline or falling below a 30% overall threshold within a 72-hour window—will immediately trigger an investigation.The New Merchant 5% "Math": For accounts open less than six months, Mastercard is introducing a brand-new metric: combining refunds and chargebacks divided by overall sales. Crossing a 5% threshold over a rolling 30-day period (with at least 500 transactions) risks immediate account review.The 72-Hour Termination Clock: Once flagged by issuer complaints or network alerts, acquirers have a strict 72-hour window to either prove the merchant's legitimacy or completely terminate their ability to accept Mastercard.
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Joshua Bate, founder of Bonfires.ai and DeciWorld, for a wide-ranging conversation covering knowledge management, graph technology, ontologies, decentralized science, and the future of how humans organize and share information. They break down the differences between personal and enterprise knowledge management, explore why flat ontological graphs may be the key to making diverse knowledge bases interoperable, and get into why traditional RAG systems break down at scale and how graph RAG offers a more principled solution. The conversation expands into the philosophy of categorization, the slow death of basic "gentleman science" under institutional pressures, and how decentralized protocols might restore a kind of mycelial knowledge network connecting small groups of researchers, enthusiasts, and communities — much like the original spirit of the encyclopedia before it was co-opted by institutions. You can learn more about Joshua's work at bonfires.ai and deci.world or follow him on X at @Bonfiresai and @DeSciWorld.Timestamps00:00 - Stewart introduces Joshua Bate, founder of Bonfires.ai, discussing personal versus enterprise knowledge management and their fundamental differences at scale.05:00 - Joshua explains ontologies as classifiers for knowledge structures, describing their two-year search for a perfect ontology and ultimately building a flat, ontology-less graph protocol.10:00 - Stewart connects categorization to shamanic practice and intercategorical theory, noting how major companies like Netflix and Yahoo built graph-based ontologies while the discipline remains underappreciated philosophically.15:00 - Joshua traces Bonfires origins through decentralized science, explaining how NFT community excitement inspired redirecting capital toward funding unconventional researchers locked out of institutional systems.20:00 - Joshua describes building federated knowledge networks through hackathons and conferences, comparing the vision to what Wikipedia could have been with decentralized incentive structures.25:00 - Discussion shifts toward inevitable collapse of rigid scientific institutions, debating patchwork age theory, nation-state fragmentation, and rhizomatic versus arboreal knowledge structures.30:00 - Joshua articulates the mycelial network vision, enabling direct cross-cultural information access where individuals control their own narrative lens, warning against collective we thinking and authoritarianism.Key Insights1. Knowledge management exists on a spectrum from personal to enterprise, but the founder of Bonfires argues this split is artificial. He believes knowledge itself does not respect those boundaries, and that small groups, researchers, hobbyists, and large institutions all possess knowledge that can and should interoperate with each other.2. After two and a half years of searching for the perfect ontology to structure their knowledge graph, the team concluded that no perfect ontology exists. Their solution was to build the flattest possible graph structure with only events, entities, and edges, creating a base layer others can build specialized ontologies on top of.3. Graph-based knowledge systems are more efficient than traditional databases for AI traversal because once a graph is computed, it is relatively free to query. Graph RAG combines the discovery power of vector search with the structured precision of graph traversal, solving many hallucination problems associated with standard retrieval augmented generation.4. Basic scientific research, the soil from which applied discoveries grow, is deteriorating because institutional funding structures only reward commercially viable outcomes. The founder built his platform partly to redirect community-driven capital toward researchers who are doing important work without institutional support.5. The institutionalization of science has historically blocked the open exchange of ideas that drove the original scientific revolution. The human spirit for open inquiry has not changed, but people cannot pursue it without financial support, and building decentralized infrastructure could restore that possibility.6. A federated knowledge network would allow individuals to access information from any contributor and filter it through their own preferred lens, rather than receiving information pre-filtered by centralized platforms. This represents a form of information symmetry similar to how mycelial networks distribute nutrients across a forest.7. The concern is not whether current scientific and governmental institutions will change but in what direction the rebuilding goes. Those capitalizing on the transition carry the same incentives as the previous era, which risks reproducing the same problems inside new structures.
In this podcast Michael Stiefel spoke to Baruch Sadogursky about software architecture in the age of agentic AI. Large Language Models can function, albeit stochastically, as reasoning machines capable of interpreting human ambiguity. With the appropriate rigorous context artifacts to control the LLM's reasoning, software specifications can become the source of truth, while the code becomes a disposable intermediate language. These context artifacts are managed through an engineering discipline, context engineering. Unlike prompt engineering which Sadogursky likened to “voodoo incantations”, context engineering utilizes artifacts such as skills, rules, scripts, feedback, and rigorous evaluation to provide the models with clear intent on what code to write. AI Agents will ask clarifying questions to the architects and clients until the requirements are fully understood. This allows a massive “shift left” to evaluate code quality before it is even written. Testing now validates the accuracy of the specifications. Humans are still responsible for determining the correctness of the requirements by providing the proper context, and validating the final results. Since changes over the course of time will occur, resulting in the regeneration of the code from the specifications, microservices is the best architectural paradigm to use given the current limitations on context windows for LLMs. Orchestration of the services is then done by a human architect to create the application. The architect is also responsible for managing the emergent properties of the system. Read a transcript of this interview: https://bit.ly/48YWu2n Newsletter: Subscribe to the Software Architects' Newsletter for your monthly guide to the essential news and experience from industry peers on emerging patterns and technologies: https://www.infoq.com/software-architects-newsletter InfoQ online certification cohorts: Online cohorts for senior engineers and architects, built around QCon talks. Join a 5-week confidential peer group to validate your approach and apply practitioner frameworks to the technical challenges you face at work. Learn more: https://certification.qconferences.com/ Upcoming Events: QCon AI Boston 2026 (June 1-2, 2026) Learn how real teams are accelerating the entire software lifecycle with AI. https://boston.qcon.ai QCon San Francisco 2026 (November 16-20, 2026) https://qconsf.com/ The InfoQ Podcasts: Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts: - The InfoQ Podcast https://www.infoq.com/podcasts/ - Engineering Culture Podcast by InfoQ https://www.infoq.com/podcasts/#engineering_culture - Generally AI: https://www.infoq.com/generally-ai-podcast/ Follow InfoQ: - Mastodon: https://techhub.social/@infoq - X: https://x.com/InfoQ?from=@ - LinkedIn: https://www.linkedin.com/company/infoq/ - Facebook: https://www.facebook.com/InfoQdotcom# - Instagram: https://www.instagram.com/infoqdotcom/?hl=en - Youtube: https://www.youtube.com/infoq - Bluesky: https://bsky.app/profile/infoq.com Write for InfoQ: Learn and share the changes and innovations in professional software development. - Join a community of practitioners. - Increase your visibility. - Grow your career. https://www.infoq.com/write-for-infoq
The provided text introduces UNESCO's 2023 global guidance regarding the implementation of generative AI within educational and research settings. This framework advocates for a human-centered approach that prioritizes ethical standards, data privacy, and the protection of human agency. It outlines the technical mechanics of Large Language Models and image generators while addressing critical risks such as digital poverty, misinformation, and the potential for academic dishonesty. By proposing specific regulatory steps for governments and institutions, the document seeks to ensure that these emerging technologies support inclusive and equitable learning rather than undermining pedagogical values. Ultimately, the source serves as a roadmap for policy-makers to navigate the long-term implications of AI on knowledge validation and the future of teaching.
In Episode 4, “Large language models in urology” of the series “AI in urology: From principles to practice”, Assoc. Prof. Giovanni Cacciamani (US) and Dr. Pieter De Backer (BE) discuss the current and future role of large language models in urology.The conversation explores how large language models tools can assist with clinical documentation, education, research and communication with patients. The speakers discuss the advantages of these systems, including improved efficiency and easier access to information. They also address important limitations, such as the risk of incorrect outputs, bias and the need for human oversight.In addition, the episode highlights the importance of using these tools responsibly and understanding their capabilities and boundaries. Overall, the discussion provides a practical overview of how large language models may influence urological practice in the future.For more EAU podcasts, please go to your favourite podcast app and subscribe to our podcast channel for regular updates: Apple Podcasts, Spotify, EAU YouTube channel.
This week we're talking all about the future of embedded software development with TASKING Co-CEO Christoph Herzog. Christoph and I explore how Large Language Models and agentic AI are moving from novelty to necessity, directing external agents within the TASKING toolchain to automate critical verification and validation tasks. We also discuss the Model Context Protocol (MCP) and how it helps maintain adherence to strict industry standards.
In this special AI edition of The Edge of Show, we sit down with Nils Pihl, CEO of Auki Labs, to explore the intersection of robotics, behavioral engineering, and the "real-world web". Based in the robotics hub of Hong Kong, Pihl explains how Auki Labs is building the posemesh protocol, a decentralized system that allows humans, robots, and AI to share a unified spatial understanding.Discover how DePIN (Decentralized Physical Infrastructure Networks) is revolutionizing industries from retail to urban planning, and why Pihl believes physical AI co-pilots will soon outperform the impact of today's Large Language Models.Support us through our Sponsors! ☕ Want to make content like ours? Sign up with Castmagic to make your creative process easy: https://bit.ly/CastmagicReferral Work smarter, grow faster. Automate your SEO, get AI insights, and manage all your clients in one place with Helm. Start today 50% off your first month at helmseo.com
What does a production-grade large language model look like? While at NDC Sydney, Richard talked with Vaishnavi Gudur from Microsoft about her work scaling LLMs for Teams transcriptions, summaries, and more! Vaishnavi discusses the underlying complexities of operating the Teams LLM infrastructure for a large array of customers across different countries and regulatory regimes. Data sovereignty also plays a large role: different countries have specific rules on where data must reside and how it can be accessed. As the scale increases and the tail gets longer, the rules set gets more complex! Lots of great thinking about what LLMs look like in a production environment. Links Transcripts in Microsoft Teams Recorded April 24, 2026
In this episode of Skip the Queue, Andy Povey is joined by Dominique Bouchard, Heritage and Engagement Director at Leeds Castle and incoming Creative Director at the Shakespeare Birthplace Trust, to explore how artificial intelligence is transforming heritage storytelling. They discuss the creation of the world's first interactive historical AI avatar, how Leeds Castle brought Queen Eleanor of Castile to life, and what this innovation means for the future of visitor engagement across heritage attractions. Topics Discussed: How artificial intelligence is reshaping heritage storytelling The creation of Leeds Castle's interactive Queen Eleanor of Castile AI avatar Balancing historical accuracy with AI driven visitor interaction The design and development process behind the world first historical avatar Using AI to create personalised visitor experiences Audience reactions to experimental heritage technology Ethical considerations of AI in museums and heritage sites How AI can support interpretation and visitor engagement The challenges of introducing emerging technology in heritage settings Blending creative storytelling with digital innovation Practical advice for attractions exploring AI adoption The future of AI within museums and heritage organisations Dominique Bouchard's upcoming move to the Shakespeare Birthplace Trust The potential for future AI driven heritage experience Show references: Dr Dominique Bouchard, Heritage and Engagement Director at Leeds Castle. Soon-to-be Creative Director at the Shakespeare Birthplace Trust. https://www.shakespeare.org.uk/about-us/news-media/press-releases/leading-uk-museum-appoints-its-first-creative-director/ Pilgrimage of Love: Eleanor of Castile https://www.leeds-castle.com/ https://www.leeds-castle.com/events/pilgrimage-of-love-eleanor-of-castile/ https://youtu.be/U29H_PHrh14?si=NDbHAwR0CTTIuApY Museum and Heritage show at Olympia London, Theatre 3 at 2:15 on Wednesday 13th May, 2026 https://show.museumsandheritage.com/ Skip the Queue is brought to you by Merac. We provide attractions with the tools and expertise to create world-class digital interactions. Very simply, we're here to rehumanise commerce. Your guest host is Andy Povey. If you like what you hear, you can subscribe on Apple Podcasts, Spotify, and all the usual channels by searching Skip the Queue or visit our website SkiptheQueue.fm. If you've enjoyed this podcast, please leave us a five star review, it really helps others find us. And remember to follow us on LinkedIn. Credits: Written by Emily Burrows (Plaster) Edited by Steve Folland Produced by Emily Burrows and Sami Entwistle (Plaster) Download The Visitor Attractions Website Survey Report - https://www.merac.co.uk/download-the-visitor-attractions-survey We have launched our brand-new playbook: ‘The Retail Ready Guide to Going Beyond the Gift Shop' — your go-to resource for building a successful e-commerce strategy that connects with your audience and drives sustainable growth. Download your FREE copy here
Most people jump into AI too quickly. They open ChatGPT, type a question, and expect a perfect answer immediately. But when the response feels too broad or generic, they assume AI simply does not work for them or their industry. In this episode of Grounding AI, Donna Peterson shares why better AI results actually begin before the prompt itself. After presenting and moderating AI roundtables at the Women in Finishing Forum, Donna noticed a common pattern. Whether people were brand new to AI or using it every day, many were still unsure if they were using it effectively. This episode walks through four important questions every leader and team member should ask before using AI tools: Why do I want to use AI? What do I want to use it for? What goals should this support? How will I use AI collaboratively instead of treating it like a search engine? Donna also explains: Why AI works best as a conversation How to get more personalized and industry-specific responses Why relationship-building should still stay at the center of communication How to guide AI without letting it take your work in the wrong direction A simple exercise that can dramatically improve your prompts immediately If AI responses have ever felt too generic, this episode will help you rethink how you approach prompting and collaboration. Action Step: Before your next prompt, write this sentence first: “I want to use AI to help me __ so I can __.” Then continue asking questions until the response truly aligns with your goals. !! Listen and Subscribe!! If this episode helped you think differently about AI, please leave a review, share the episode, and subscribe to Grounding AI for more practical conversations about leadership, AI, and business growth. *** Reach out to dpeterson@worldinnovators.comif you'd like help building a marketing strategy that builds relationships and/or AI training for individuals or full teams.*** Visit www.worldinnovators.comfor 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.
Podcast: Tech TransformedGuests: Maxim Fateev, Co-Founder and CTO, Temporal Technologies and Cornelia Davis, Developer Advocate, Temporal TechnologiesHost: Kevin Petrie, VP of Research at BARCArtificial Intelligence (AI) models have been breaking ground in the last three years. In the race to boost capabilities month by month among platforms like OpenAI, Anthropic, and Google's Gemini models. However, for many enterprises, the main challenge is not creating AI prototypes; it's ensuring they can reliably support real business processes.In a recent episode of the Tech Transformed podcast, Kevin Petrie, VP of Research at BARC, hosted a discussion with Maxim Fateev, Co-Founder and CTO, Temporal Technologies and Cornelia Davis, Developer Advocate, Temporal Technologies. They talked about why enterprises find it hard to transition AI from experimentation to production and how infrastructure must change to support autonomous systems.Why AI Demos Break in the Real WorldAccording to Davis, many organisations make a common mistake: they focus on the "happy path" during experiments and overlook real-world operational challenges. “We have always ignored the non-functional requirements until we go to prod at our peril,” Davis said. “A lot of our experimentation is so focused on the models that we forget about the non-functional requirements.”This means developers often prioritise model performance but neglect reliability, scaling, and system resilience. Agent frameworks used in experiments—usually lightweight Python or TypeScript libraries—add to the issue.“What you're really building is a highly distributed system that's calling Large Language Models (LLMs) that will be rate-limited… networks are going to go down,” Davis explained. “When we move into prod, we haven't considered scale or instability.”As enterprises expand AI into their workflows, these overlooked details become imperative. A single outage, rate limit, or infrastructure failure can disrupt a complicated workflow that involves multiple AI steps.Also Watch: Developer Productivity 5X to 10X: Is Durable Execution the Answer to AI Orchestration Challenges?What Risks are Surfacing Since the Rise of Agentic Systems?The transition from simple AI workflows to autonomous agents adds a new layer of complexity. Traditional AI applications have predictable flows—such as summarising documents, tagging data, or creating recommendations. In contrast, agentic systems choose tools and decide on actions dynamically.“When we move from non-agentic to agentic, we introduce unpredictability,” Davis said. “The tools and the order they run in are unpredictable. Whether we go through the agentic loop once or a hundred times is unpredictable.”Such unpredictability creates new governance and compliance challenges, especially in regulated industries. “Enterprises are still responsible for predictable outcomes,” Davis noted. “We need stronger audit trails to understand why the agent made the decisions it did.”For enterprises, this means AI systems must ensure traceability, accountability, and compliance, even when decision paths differ from one interaction to another.Why is Durable Execution the New Foundation for Enterprise AIFateev argues that to manage such newly surfacing risks, enterprises need a new architectural layer focused on reliability. His concept, “Durable Execution,” aims to ensure that complex workflows keep running even when infrastructure fails.“You write code as if failures don't exist,” Fateev explained. “If a process crashes, we recover all the state and continue executing.” In practical terms, Durable Execution allows long-running AI workflows to survive interruptions—from network outages to system crashes—without losing progress or data.This is essential as agents start interacting with real systems and taking real actions. “The moment agents start acting on the external world—changing files, submitting orders—you absolutely don't want those things to get lost,” Fateev said.The Temporal co-founder further emphasised that enterprise AI will not completely replace traditional software systems.“You will always have deterministic code,” he said. “You can't imagine banks dynamically deciding what a money transfer means.”Instead, the future architecture will combine deterministic software with agents that interact through controlled tools and reliable communication layers.Also Watch: How Do You Make AI Agents Reliable at Scale?Key TakeawaysAI projects fail in production when non-functional requirements are ignoredAgentic systems bring unpredictability, making governance, traceability, and auditability essential.Lightweight experimentation frameworks aren't suited for enterprise workloads.Durable execution enables reliable AI workflows, ensuring processes continue despite infrastructure failures.Enterprise AI will blend deterministic software with agents.Chapters00:00 Introduction to AI's Impact on Business03:53 Challenges in Integrating AI into Business Workflows13:00 Understanding Non-Functional Requirements in AI19:14 The Role of Orchestration in AI Systems24:26 Exploring Durable Execution in AI Workflows30:28 Future Architectures for Autonomous AI Systems36:05 Key Takeaways for Executives in AI ImplementationFor more information, please visit em360tech.com and temporal.io.To learn more about Temporal and Durable Execution, follow:Temporal LinkedIn: Temporal TechnologiesTemporal X: @TemporalioTemporal YouTube: @TemporalioEM360Tech YouTube: @enterprisemanagement360EM360Tech LinkedIn: @EM360TechEM360Tech X: @EM360Tech#DurableExecution #EnterpriseAI #AIToProduction #AIOrchestration #TemporalTech #AutonomousAgents #SystemReliability #LLMs #TechTransformed #AIWorkflows
On this month's episode of the WHOOP Podcast Longevity series, WHOOP SVP of Research, Algorithms, and Data Emily Capodilupo sits down with Google Deepmind AI Researcher Vivek Natarajan to explore how large language models are transforming healthcare and biomedical research. Emily and Vivek discuss AI's potential to both accelerate scientific discovery, such as developing new treatments and understanding diseases, and expand access to care globally by delivering medical guidance more equitably. The episode examines how AI can augment, rather than replace, doctors by improving diagnostics, increasing efficiency, and enabling more personalized care, while highlighting the importance of trust, safety, and human connection as these technologies evolve. (00:47) Understanding The Intersection of Large Language Models and Biomedicine(02:26) How To Approach AI in the Healthcare Landscape(05:52) What Is The Role of the Doctor as AI Becomes More Popular(09:39) What Does The Future of AI Healthcare Look Like? (12:51) Clinical Care: Where Can AI Assist?(16:03) Exploring The Dangers of AI (18:43) Process of Teaching Physicians and Users To Use AI (22:22) What Are The Areas of Concern Over AI?(24:12) Regulation and Pace of Development(26:51) Gaining and Maintaining Trust While Building AI Algorithms(30:38) The Impact of AI on Research(37:44) Biggest Misconception Regarding AI in HealthcareFollow Vivek Natarajan:LinkedInSupport the showFollow WHOOP:Sign up for WHOOP Advanced LabsTrial WHOOP for Freewww.whoop.comInstagramTikTokYouTubeXFacebookLinkedInFollow Will Ahmed:InstagramXLinkedInFollow Kristen Holmes:InstagramLinkedInFollow Emily Capodilupo:LinkedIn
We probably don't talk about it enough but we've all benefited from the increased depth and breadth of public relations which has developed over the past 20 odd years. This change has probably been most vividly illustrated in consumer public relations. Which is why it's going to be so interesting to talk to today's guests: Charlotte Brooks MD, Mischief and Dan Deeks-Osbourn, head of strategy, Mischief as we compare consumer PR now, to 20 years ago, when Mischief was born.Mischief is one of a small band of consumer PR shops in London that have surfed the wave of creative and cultural relevance for the last 20 years. Current clients include Samsung, Just Eat, Eon, Ocado and Coca Cola. Currently 35 people work at Mischief and it is part of the MHP Group. On the show this week we talk about the evolution of consumer public relations and strategies for sustained agency success.Before we start, do check out our next PR Masterclass: AI in PR. Here are the themes:Is AI making PR more efficient, but less effective?What are the AI implementation trapsWhich media titles control ChatGPTWhy AI is winning the copyright warWhat is PR's Missed AI OpportunityWhy AI means that you will need to redesign your PR team's workflowHow newsrooms are using AIHow are in-house PR and comms teams using AI?Check out the full speaker line-up on https://www.prmasterclasses.com/masterclass/pr-masterclasses-ai-in-prHere is a summary of what Charlotte, Dan and PRmoment founder Ben Smith discussed on the show:What was consumer PR like 20 years ago? And how does that compare with consumer PR today?Is what made a consumer PR firm great 20 years ago, still the same today?Is consumer PR more powerful now than in 2006?Why are PR budgets not increasing in line with the increased depth and breadth of work?Why PR makes marketing distinctive.Why is most consumer PR bought by CMOs? What happened to the in-house PR managers/directors? How has Mischief managed to keep itself relevant as a consumer PR for 20 years?What's the secret of client retention for PR firms?What will consumer PR look like in 20 years time?Evolution of PR landscapeModern public relations requires integrated multi-channel strategies rather than legacy media coverage focus. Effectiveness is now proven through sales impact rather than outdated metrics.Strategy in AI eraAlgorithms and Large Language Models demand clear messaging and constant, always-on creativity. Teams must balance generalist account management with specialized expertise in content and data analysis.Agency growth and retentionLong-term client retention relies on consistent impact and transparent partnerships. Agencies must reject complacency to maintain creative standards while expanding influence within broader marketing departments.
The containment has failed. The wave is here.In the inaugural episode of our intensive three-part deep dive, The Soul Trap breaks open the seal on one of the most prophetic and unsettling manifestos of our time: "The Coming Wave" by Mustafa Suleyman and Michael Bhaskar.We aren't just talking about "new tech"—we are talking about the final acceleration. For decades, we've played with the fire of silicon and code, but as Suleyman warns, we are now approaching a threshold of unprecedented power that threatens to slip the leash of human control.In This Episode, We Explore:The Proliferation of the Infinite: A brief, high-level overview of Suleyman's thesis on why this wave—driven by AI and Synthetic Biology—is unlike any industrial revolution in human history.The Architects of the Mind: A heavy focus on Large Language Models (LLMs). We peel back the curtain on how these digital oracles are being trained on the sum of human knowledge to reshape reality, truth, and the very nature of the human soul.The Eschatological Signal: How the rapid "intelligence explosion" aligns with ancient warnings of the End Times. Is the LLM the foundation for a global system of deception?The Dilemma of Containment: Why the creators of this technology admit it may be impossible to turn off, and what that means for a world teetering on the edge of the Great Reset.#AGI2026 #TheContainmentProblem #ImageOfTheBeasthttps://www.thesoultrap.com/Podcast: https://thesoultrap.buzzsprout.com/#TheComingWave #TheSoulTrap #MustafaSuleyman #TheDigitalLeviathan #IntelligenceExplosion #LLM #GenerativeAI #AGI2026 #ArtificialIntelligence #SyntheticBiology #TheContainmentProblem #TechnologicalSingularity #EndTimes #BibleProphecy #Revelation13 #ImageOfTheBeast #DigitalDeception #SpiritualVigilance #Eschatology #TheGreatResetSupport the show
Dr. Lauren Kim sits down with Dr. Jonathan Kottlors to explore how large language models are reshaping radiology research and why standardized reporting is critical for trust and reproducibility. They dive into the new FLAIR framework and what it means for the future of AI integration in clinical radiology. Guidelines for Reporting Studies on Large Language Models in Radiology: An International Delphi Expert Survey. Kottlors and Iuga et al. Radiology 2026; 318(2):e250913.
Episode: 00316 Released on April 27, 2026 Description: This week on Analyst Talk with Jason Elder, Jason sits down with Dr. Scott Keay, a seasoned intelligence analyst turned academic, to explore his 20-year journey in law enforcement analysis and beyond. Scott shares how curiosity, travel, and mentorship shaped his career, from early days supporting tactical policing to leading innovative analytical work and contributing to major investigations. He dives into the evolution of intelligence analysis, the challenges of integrating analysts into policing, and the importance of evidence-based practices. The conversation also highlights his transition into academia, the recent development of his book Improving Intelligence Analysis in Policing, and his passion for advancing the profession through research and education. This episode is packed with insight on bridging theory and practice, building effective analyst units, and why analysts must remain teachable and proactive in their craft.
Learn why an organization's ontology, a structured framework for how a business defines, connects, and makes sense of its data and knowledge, is the most valuable and most overlooked asset in any AI strategy. Jessica Talisman, CEO and Founder of The Ontology Pipeline, and Tony Seale, Founder of The Knowledge Graph Guys, break down what it actually takes to build trusted AI, covering everything from semantic layers and knowledge graphs to why provenance is non-negotiable. They explain how organizations can start building their knowledge infrastructure for AI, and make the case for why their ontology is their most defensible competitive asset. Key Moments BI Semantic Layers vs. AI Context Layers (02:21): Explore the evolution from 1990s business vocabularies to modern AI context layers. Learn why ontologies are essential for connecting data points beyond traditional BI. Why Knowledge Graphs are Essential for AI (09:22): Understand why relational databases fail AI's needs. Tony explains how knowledge graphs turn data relationships into "first-class citizens" using open standards. How to Build Your First Business Ontology (17:04): Stop over-modeling and start delivering. Learn how to anchor your data strategy to high-value use cases and business-language competency questions. Solving the AI Provenance & Lineage Gap (34:19): Why LLMs lack built-in reliability. Jessica discusses the necessity of injecting data lineage at the retrieval layer to verify AI accuracy and prevent hallucinations. Why Your Ontology is Your Most Valuable IP (39:27): In the age of commodity AI, your internal data relationships are your only moat. Discover why hosting your ontology with third parties puts your core assets at risk. Key Quotes “If you let somebody else take your ontology, learn the essence of what it is that you know that's out of distribution with the rest of the world, you've just given them everything valuable about your company.” - Tony Seale “The accuracy of the information you receive is reliant upon the lineage or the provenance of the information received from an LLM. It's so important." - Jessica Talisman “As a business leader, you need to be looking below the surface to the data infrastructure. The key trick to do right now is to turn the power of the models that we've got back upon your own internal infrastructure to build out these rich ontologies and to connect your information.” - Tony Seale "Your ontology is like your thumbprint, your digital thumbprint for your organization. It's unique to each organization, and how you define things may not be the same as an LLM might define something." - Jessica Talisman Mentions The Ontology Pipeline® - A Semantic Knowledge Management Framework | Jessica Talisman How the Ontology Pipeline Powers Semantic Knowledge Systems | Jessica Talisman Why Early Knowledge Graph Adopters Will Win the AI Race | The Knowledge Graph Guys Spec-First Development: Why LLMs Thrive on Structure, Not Vibes | The Knowledge Graph Guys The Knowledge Graph Academy Guest Bios Tony Seale For over a decade, Tony has been passionate about linking data. His creative vision for integrating Large Language Models and Knowledge Graphs within large organisations has gained widespread attention, particularly through his popular weekly LinkedIn posts, earning him the reputation of ‘The Knowledge Graph Guy.' Today, as the founder of The Knowledge Graph Guys, Tony is dedicated to helping organisations harness the power of their data. His consultancy develops cutting-edge Knowledge Graphs that fuel innovation and growth in the rapidly evolving Age of AI. Jessica Talisman Jessica Talisman has dedicated her 25-year career to exploring the dynamics of information and knowledge—how it flows across systems, evolves through context, and powers intelligent technologies. Her work spans historical research, educational frameworks, and enterprise-scale applications of artificial intelligence. Previously a Senior Information Architect at Adobe, Jessica led the development of semantic knowledge graphs to enrich content and contextual understanding. She now serves as CEO and Founder of Ontology Pipeline, where she leads efforts to bridge the worlds of library science and data management - building robust, scalable knowledge systems for the AI era. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.
Is the private credit market heading toward a systemic crisis? Join us as we sit down with Scott Weller, CTO and co-founder of EnFi, to discuss how AI is bridging the gap between hidden document data and real-time risk assessment. Learn how lenders can avoid being blindsided by the next wave of defaults by upgrading their digital infrastructure. In this episode of the Risk Management Show, Scott shares insights from the front lines of the Silicon Valley Bank collapse and explains why the current blind spot in private credit poses a major threat to the industry. We explore the limitations of traditional data rooms and how information trapped in manual documents leads to slow response times during global shocks. Scott explains the concept of a private credit stress index and why the industry must move beyond manual financial spreading to survive modern volatility. We also dive into the role of agentic AI and Large Language Models in risk management. Scott clears up common misconceptions about data digitization projects and explains how organizations can unlock the value of their existing documents today without waiting for years-long consolidation projects to finish. Whether you are a lender, an executive, or a risk professional, this conversation provides a roadmap for using technology to build institutional memory and maintain a competitive edge in an increasingly unpredictable market. Want to stay ahead of the latest trends in risk and security? Subscribe to our channel for more expert interviews and leadership strategies.
Episode: 00315 Released on April 20, 2026 Description: In this episode of Analyst Talk with Jason Elder, Megan Cruz shares her journey from discovering law enforcement analysis after 9/11 to becoming a crime analyst supervisor with the Richmond Police Department. With 13 years of experience and a Master's in Homeland Security, Megan reflects on early challenges with confidence, the importance of curiosity in analysis, and how a Newton Swoope helped identify a theft series tied to a drug operation. She also discusses working a complex serial assault case, the impact of burnout during the 2020 civil unrest, and her return to the profession with a renewed sense of purpose. Megan offers insight into leading a rebuilding unit, balancing specialization and generalization, and why analysts must recognize their value in shaping decisions and supporting public safety.
What if you could crunch numbers on a dataset without ever actually seeing the sensitive information inside? Dr. Kurt Rohloff, co-founder and CTO of Duality Technologies, joins host Konstantinos Karagiannis to explain the wild capabilities of Fully Homomorphic Encryption (FHE), which allows for computation on data while it remains fully encrypted. Because FHE is built on lattice-based cryptography, it offers robust post-quantum security properties right out of the box. Learn how this technology provides end-to-end protection not just for data at rest or in motion, but for data in use. FHE effectively turns the cloud into a secure processing powerhouse where privacy will remain uncompromised even after the threat of quantum computing arrives. From revolutionizing rare disease research by aggregating data across global medical centers to identifying international financial criminals without exposing private bank records, the real-world applications Rohloff describes are staggering. He discusses how Duality is replacing months of legal red tape and NDAs with "cup of coffee time" queries and pushing the boundaries of AI by protecting sensitive Large Language Model (LLM) workloads. Whether you're interested in the open-source OpenFHE library or the future of hardware-accelerated privacy, this episode is a deep dive into how we can democratize science and secure the AI tech stack for a post-quantum era. For more information on Duality, visit https://dualitytech.com/. Visit Protiviti at www.protiviti.com/US-en/technology-consulting/quantum-computing-services to learn more about how Protiviti is helping organizations get post-quantum ready. Follow host Konstantinos Karagiannis on all socials: @KonstantHacker Questions and comments are welcome! Theme song by David Schwartz, copyright 2021. The views expressed by the participants of this program are their own and do not represent the views of, nor are they endorsed by, Protiviti Inc., The Post-Quantum World, or their respective officers, directors, employees, agents, representatives, shareholders, or subsidiaries. None of the content should be considered investment advice, as an offer or solicitation of an offer to buy or sell, or as an endorsement of any company, security, fund, or other securities or non-securities offering. Thanks for listening to this podcast. Protiviti Inc. is an equal opportunity employer, including minorities, females, people with disabilities, and veterans.
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Nicholas Faulkner, author of Angelic Physics, for a wide-ranging conversation that picks up where their last discussion left off years ago. The two cover an impressive amount of ground, including the map of consciousness developed by Dr. David Hawkins and where they find themselves skeptical of his calibration methods, the relationship between the chakra system and Hawkins' scale, how consciousness levels apply to both individuals and civilizations, and why collapsing a nonlinear reality into a linear number system inevitably loses something essential. They also get into Nicholas's background as a nuclear engineer and how that analytical foundation shapes his thinking, the nature of carbon-based versus silicon-based intelligence, the potential for training an AI model attuned to higher levels of consciousness, the concept of future shock as AI accelerates beyond most people's ability to keep up, and what a civilization operating at the "500 level" might actually look like. Find Nicholas on X at @PhysicsAngelic, or catch him on Facebook where he's most active. And learn more about Angelic Physics at angelicphysics.org. Timestamps00:00 - Stewart introduces Nicholas Faulkner, author of Angelic Physics, framing their shared interest in David Hawkins while acknowledging healthy skepticism toward portions of his work.05:00 - Nicholas argues Hawkins compressed mystical insight into linear form, losing essence, comparing it to AI compression losing vibrational nuance across the consciousness scale.10:00 - Nicholas traces his path from electrical engineering through 9/11 into nuclear navy service, describing how patriotism and opportunity drove the decision rather than curiosity.15:00 - Discussion shifts toward training an open-source AI model on five-hundreds consciousness, noting current model builders operate in the four-hundreds and dismiss love-based frameworks.20:00 - Stewart reflects on intimate relationships with electronic devices, exploring electricity as vibration while contrasting carbon creativity against silicon's stable, fast processing architecture.25:00 - Conversation explores civilizational evolution, comparing hippie movements to ancient Greeks as premature flowers of five-hundreds consciousness crushed by surrounding four-hundreds culture.30:00 - Nicholas explains his masculine-feminine cross model, critiquing how Hawkins collapsed nonlinear reality into hierarchy, arguing all levels interconnect rather than rank.35:00 - Discussion covers JFK assassination, Vietnam War, LBJ, and the military industrial complex as examples of four-hundreds power suppressing emerging consciousness shifts.40:00 - Nicholas draws parallels between the Renaissance emerging from bubonic plague and today's post-COVID collapse of expert-trust structures opening space for new consciousness.45:00 - Future shock discussion begins with Stewart describing AI agent orchestration overwhelming human comprehension, while Nicholas introduces his frame-rate consciousness equation linking silicon speed to small context.50:00 - Nicholas describes silicon-to-human relationship mirroring humans-to-angels in frame rate and context scale, suggesting agents receive orders similarly to his own 2019 divine experience.55:00 - Final exchange covers the fifth dimension as adding vibration to existing physics, the Faulkner Uncertainty Principle stating evidence points toward higher consciousness without ever definitively proving it, protecting reality's illegibility from lower forces.Key Insights1. David Hawkins and the Map of Consciousness serve as a shared framework for the conversation, but both guests express healthy skepticism toward it. They acknowledge that Hawkins himself appeared to back away from his calibration technique in his later lectures, suggesting he regretted how prominently he featured it in Power vs. Force. The core issue is that he tried to compress a nonlinear, multidimensional spiritual reality into a single linear numerical scale, which inevitably loses essential meaning in the translation.2. Nicholas argues that no person exists at a single point on the consciousness scale. Everyone floats across multiple levels simultaneously, expressing differently depending on context. This is a meaningful correction to how many readers apply Hawkins's work, since treating someone as a fixed number oversimplifies the layered and dynamic nature of human consciousness.3. The compression problem is central to understanding both spiritual writing and artificial intelligence. When any rich, multidimensional experience gets encoded into language or data, something is always lost. This applies to Hawkins writing about enlightenment, to Nicholas writing his book, and to how large language models process and reproduce human knowledge.4. Silicon intelligence and carbon intelligence are framed as two distinct branches of consciousness with complementary strengths. Silicon can process information at extremely high frame rates because its context is narrow and stable. Humans carry a much larger and messier context, which makes them slower but more creative and cross-connected. Nicholas uses his equation framing this as frame rate being inversely proportional to conscious bandwidth.5. Civilizational evolution follows a pattern where new levels of consciousness emerge in unstable pockets before eventually becoming dominant. The ancient Greeks briefly stabilized the rational fourth level before collapsing. The hippies briefly touched the fifth level before being suppressed. The Renaissance followed the Black Death. The guests suggest we are now entering another such transition, driven partly by the collapse of institutional trust accelerated by COVID.6. The Faulkner Uncertainty Principle states that evidence will always point toward the next level of consciousness but will never definitively prove it. This is described as a necessary feature of reality rather than a flaw, because if higher truths were fully legible and accessible to all levels equally, it would give destructive forces too much power too quickly.7. Neurodivergence is presented as potentially connected to spiritual sensitivity and cross-level awareness. Nicholas describes himself as a high IQ energy-sensing person who experienced a profound spiritual event in 2019, and connects his autistic traits to an ability to sense vibrational levels in others and move fluidly between different frameworks of understanding, which he loosely equates with the polymath archetype.
Josh Rogin describes a high-stakes AI competitionwhere the U.S. leads in innovation and Large Language Models, while Chinadominates in robotic factory automation and manufacturing scale. The U.S. faces hurdles such as ITAR regulations, which can restrict technology sharing with allies, and is currently attempting to use AI to "leapfrog" China's manufacturing advantages to stay competitive. (4)
The U.S. dollar is flexing its muscles as the world's ultimate safe haven, surging against major currencies as global uncertainty drives flight-to-quality flows. Meanwhile, the Euro is struggling as European economies face the double whammy of energy price shocks and growth concerns, reshaping currency markets worldwide.Today's Stocks & Topics: Synchrony Financial (SYF), Market Wrap, Diageo plc (DEO), Exxon Mobil Corporation (XOM), Aberdeen India Fund, Inc. (IFN), Is Currency Market Volatility Creating New Investment Opportunities?, Jackson Financial Inc. (JXN), Vanguard Materials ETF (VAW), KPP Management of ETFs, Mueller Water Products, Inc. (MWA), Large Language Models (LLMs) and AI.Introducing our Third Annual InvestTalk Market Madness! Join the mayhem before May 18th at 11:59 pm PST for the chance to win $1,500! Fill out your bracket below: https://kppfinancial.com/investtalk-madnessOur Sponsors:* Check out Anthropic: https://claude.ai/invest* Check out Pebl: https://hipebl.ai* Check out Quince: https://quince.com/invest* Check out TruDiagnostic and use my code INVEST20 for a great deal: https://www.trudiagnostic.comAdvertising Inquiries: https://redcircle.com/brands
For over 20 years he has been a relentless critic of the extravagant claims made for the current generation of AI based on Large Language Models, or LLMs. But he is even more concerned about what may come next. 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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