Podcasts about Machine learning

In this classic episode of Research Insights, the discussion centers around the growing impact of predictive analytics and machine learning in actuarial science. The episode explores how actuaries are applying these tools in real-world modeling scenarios to uncover insights, improve decision-making, and navigate complex data environments. Listeners will gain a deeper understanding of what's possible with these technologies, as well as important considerations and potential pitfalls. Perfect for Pi Day—or any day you want to celebrate the power of numbers—this episode offers valuable takeaways whether you're a seasoned modeler or simply curious about how machine learning is shaping the business landscape. Tune in to revisit this insightful conversation and discover how data-driven innovation is transforming actuarial work.

We've spoken with many guests about clinical and technological trends impacting healthcare providers, but less so about the trends on the business side of practicing medicine.  So on this episode, we're going to make up for that by spending our time with Dr. Alexander Vaccaro, an influential spine surgeon and president of one of the largest musculoskeletal practices in the U.S. -- Rothman Orthopaedic Institute -- which treats patients at over 40 locations in Pennsylvania, New Jersey, New York and Florida. While Dr. Vaccaro understands the desire for financial stability that's increasingly driving young physicians into the arms of hospital systems, he worries about what's being lost with the resulting decline in the number of independent practices.  “If you didn't have private practice advocating for the doctor, the insurance companies would bully the healthcare profession.” Join Raise the Line host Michael Carrese for a candid and lively conversation that also covers: How physician autonomy and entrepreneurship can drive innovation; The economic and policy forces reshaping private practice medicine; The role of research partnerships between private practices and universities. Mentioned in this episode:Rothman Orthopaedics If you like this podcast, please share it on your social channels. You can also subscribe to the series and check out all of our episodes at www.osmosis.org/podcast

Sourish Samanta, Director AI and ML at Advance Auto Parts, joins The Tech Trek for a grounded conversation on where machine learning still creates the most business value, where generative AI fits, and why many teams are chasing the wrong solution. This episode is worth your time if you want a clearer view of how serious operators think about AI strategy, product delivery, and practical use cases that can ship now. This conversation cuts through the noise around AI and gets back to first principles. Sourish explains why machine learning remains the foundation behind today's AI wave, how to choose between deterministic and creative systems, and what it actually takes to build production ready products that solve real business problems.In this episode:Why machine learning is still the core layer behind modern AIWhen to use machine learning, when to use generative AI, and when simple analytics is enoughWhat a real product mindset looks like for AI and ML teamsHow pod based teams can ship faster with better cross functional alignmentWhy AI and ML talent need to spend time continuously reskillingTimestamped highlights:00:00 Why machine learning remains the foundation of today's AI stack01:57 The difference between ML teams, AI teams, and agent focused workflows05:56 Choosing the right solve, from forecasting and inventory to creative content generation10:09 The product mindset required to turn AI ideas into working systems13:51 Why some business problems need analytics, not AI15:52 Why AI teams need to spend part of their time learning, testing, and staying currentStandout line:AI is not the strategy. Solving the right problem is.Practical takeaway:If you are leading an AI initiative, start by classifying the problem. If the outcome needs consistency, prediction, or forecasting, machine learning may be the better path. If the outcome needs creativity or flexible generation, generative AI may be a better fit. And in some cases, the best answer is still a clean dashboard and strong analytics.Follow The Tech Trek for more conversations on AI, data, engineering, and how technology actually gets applied inside real businesses.

Realities Remixed, formerly know as Cloud Realities, launches a new season exploring the intersection of people, culture, industry and tech.After years of remote‑first work built on swift trust, companies are asking a harder question: what does a organization really stand for when people rarely show up together? As AI accelerates change, leaders are rethinking presence, team design, and collaboration to fuel trust, innovation, and growth. This week, Dave, Esmee, and Rob are joined by Dr. Tim Currie, disruptor, author, innovator, and advisor, to examine transformation versus trust, the role of AI, and whether organisations can truly build culture without deeper human connection. TLDR00:42– Introduction01:10 –  Hang out: New film releases07:17 – Dig in: The trust gap in remote work17:57 – Conversation with Dr. Tim Currie54:07 – The Wizard of Oz at the Sphere in Las Vegas and staying connected GuestDr. Tim Currie: https://www.linkedin.com/in/dr-tim-currie-37756a/Book Swift Trust: https://swifttrustbook.com/HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Discover how enterprise AI and data strategy are operationalized at scale in one of the most highly regulated industries in the world. Louis DiModugno, Global Chief Data Officer at Verisk, shares how he builds AI-ready data foundations across 40+ petabytes of insurance and risk data, and the best practices behind embedding AI into enterprise products. He discusses unstructured data, deepfakes, and the shift from governance to observability, offering practical insights for data leaders scaling AI responsibly. Key Moments: From Military Leadership to Chief Data Officer: Data Integrity as a Competitive Advantage (03:02): Louis shares how his experience as a U.S. Air Force Colonel has shaped his approach to data governance, data quality, and enterprise AI leadership. He explains why integrity, service, and operational excellence are essential foundations for modern CDOs building trusted, decision-ready data environments. Building AI-Ready Data Foundations at a 40+ Petabyte Scale (17:13): Managing more than 40 petabytes of insurance and risk data, Louis breaks down how Verisk transforms complex, multi-source data into AI-ready infrastructure. From entity resolution and master data management to benchmarking and predictive analytics, he outlines what it takes to prepare enterprise data for AI and advanced analytics at scale. Designing an AI-First Data Strategy for Enterprise Decision Intelligence (20:00): Louis breaks down how Verisk evolved toward an AI-first data strategy across more than 150 insurance and analytics products. Rather than treating AI as an add-on, he explains how embedding AI into core workflows enables smarter underwriting, pricing, regulatory reporting, and risk management. He also discusses the strategic role ThoughtSpot plays in delivering natural language search, embedded analytics, and scalable AI-driven decision making. AI Fraud, Deepfakes, and Risk Management in Financial Services (26:11): As AI-generated images and synthetic claims become more sophisticated, Louis discusses how the insurance industry is combating deepfake fraud and AI-driven manipulation. He shares best practices around AI risk management, vendor partnerships, and regulatory collaboration to protect policyholders and maintain trust. Unstructured Data and AI: Why Governance Still Matters (29:28): Louis explores how expanding beyond structured data is reshaping enterprise AI. He explains why incorporating unstructured data into vector databases, graph models, and knowledge systems can significantly improve model accuracy and decision confidence. At the same time, he emphasizes that stronger governance (or observability as he reframes it) is essential as organizations scale AI across regulated industries. Key Quotes: “The more data that you bring to the equation, the more elements that you have in the algorithm, the higher level of accuracy you should be able to reach with your outcomes.” - Louis DiModugno “I've tried to move away from using the word governance as much as I like to use the word observability, because I really think observability shows more aspects of what it is that we are doing with the data.” - Louis DiModugno “The underlying aspect of what ThoughtSpot's delivering to them is our insights that not only give them their answer, but also give them insights that maybe they weren't looking specifically for. One of the big benefits of ThoughtSpot is that it's trying to anticipate what you're asking for.” - Louis DiModugno “We've partnered with ThoughtSpot, which brings AI embedded within its product. By having our data available through the data sets that we populate through the ThoughtSpot products, we've got the opportunity to utilize Spotter and the natural language processing capabilities to interact with the data, so that you can ‘talk with your data'.” - Louis DiModugno Mentions From Months to Weeks: How Verisk Scaled Embedded Analytics Breaking Down Digital Media Fraud for Claims in the AI Era Randy Bean's 2026 AI & Data Leadership Executive Benchmark Survey Guest Bio  Louis DiModugno brings more than 20 years of career experience in data and analytics to his new role. He has held several leadership positions in insurance and (re)insurance at firms including The Hartford and AXA US, where he served as the company's inaugural Chief Data & Analytics Officer. Most recently, DiModugno pioneered the role of Chief Data and Technology Officer for Hartford Steam Boiler. Before entering the private sector, DiModugno served with distinction as a Colonel in the U.S. Air Force and Air Force Reserves. He has held teaching positions at Rensselaer Polytechnic Institute, and he currently serves on the Chief Data Officer Advisory Council for the George Mason University School of Business. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

This week on Catalyst, Tammy is joined by AI Empowerment Solutions Leader at NTT DATA Christen Bell. Christen's work focuses on how intelligent systems affect humans in the workplace and, more recently, human's fears of AI. Christen shares her fascinating findings with Tammy on how AI adoption differs between industries and regions and what makes people more or less trusting of AI. Christen and Tammy also talk about how leaders can quell the perceived threat of AI in their workplaces - no surprise, it's by being human first! Please note that the views expressed may not necessarily be those of NTT DATALinks: Christen Bell Learn more about Launch by NTT DATASee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Co-founders Dr. Salman Avestimehr and Dr. Aiden He join the podcast to discuss their new "agentic" company, Teamily AI. They dive into how their platform is disrupting the social landscape by weaving multi-agent AI into group chats, enabling groups, friends, and families to interact with virtual friends, essentially creating a collaborative environment where AI acts as a participant that anticipates needs and remembers the full context of a conversation.This conversation explores the core value proposition of an AI-first social platform—not just making an individual superhuman, but enabling a collective of human and AI agents to do "fascinating things together." The founders detail their technology, which is built on deep expertise in distributed machine learning and multi-agent systems, and their long-term vision to IPO and evolve the very nature of social networks by bridging the gap between human and artificial intelligence.In the news segment, Charlie Fink and Rony Abovitz unpack the week's biggest AI stories: Ben Affleck selling his stealth AI film company, Interpositive, to Netflix; Anthropic's Claude briefly dethroning OpenAI's ChatGPT in the app store; and a deep dive into Jack Dorsey's company Block cutting 4,000 employees. The hosts also discuss the social fallout of AI acceleration, particularly the counter-movement seeking tactile, real-world connection and the economic risk of displacing white-collar data analysts.Key Moments00:03:00 – App Store War: Discussing Anthropic's Claude topping the app charts and why the US Department of Defense will use the best AI system regardless of corporate objection.00:04:00 – Hollywood's AI Play: Netflix acquiring Ben Affleck's AI company, Interpositive, which uses unedited film dailies to train an AI for editing and optimization.00:05:00 – The Mediocrity Threat: Rony Abovitz's take on the risk of AI creating a "very, very long tail of Okay" content, leading to a cultural sameness.00:07:00 – Counter-Culture: Exploring the growing emotional need for "something real" and a massive movement away from purely digital experiences.00:09:00 – The White-Collar Risk: The hosts argue that the white-collar data analyst is the worker "most easy to replace" by AI, contrasting with the high value of blue-collar workers.00:11:00 – The "Oh Wow" Moment: Charlie Fink describes his first experience with Teamily AI, noting the immediate power of real-time, multi-person and multi-agent prompting.00:13:00 – The Science Behind Teamily: Dr. Aiden He, PhD in Machine Learning, explains how Teamily is built upon his previous research in distributed learning and multi-agent systems.00:26:00 – Global Memory: Aiden details Teamily's unique "cross domain, long horizon memory," which allows the AI to combine human-human chat context with human-AI memory for a more natural interaction.The biggest takeaway is the conceptual shift from using AI as a solo productivity tool to using it as a collaborative team member. The path to the next phase of social networking hinges on building platforms where AI is not isolated but is a natural, evolving part of a human community.This episode of The AI XR Podcast is brought to you by Zappar, the folks behind Mattercraft, a leading visual development environment for building immersive 3D web experiences for mobile headsets and desktop. Start building smarter at mattercraft.io. Listen and subscribe to the AI XR Podcast wherever you get your podcasts! Watch the full thing on YouTube https://youtu.be/s78WZJSfGeo.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What does it mean to secure the world's largest hyperscale cloud, while AI rewrites the rules of identity, threat detection, and security culture? In this episode of AWS Executive Insights: Security Series, Clarke Rodgers sits down with Amy Herzog, Chief Information Security Officer at AWS, for a candid conversation on what it takes to lead security at scale in the age of AI.Amy draws on her experience leading consumer AI products to argue that security should accelerate innovation, not hinder it. She explores how AWS is deploying AI for defense, why agentic AI demands a rethink of identity, and how the Security Guardians program embeds security culture across the entire organization.

AI is reshaping global power, from chip manufacturing and computing power to AI governance and US-China relations.  In this episode, Ben Buchanan, Assistant Professor at The Johns Hopkins University and former White House Special Advisor for AI, explores how AI policy, geopolitics, and international cooperation intersect with AI  innovation and AI safety. We discuss the strategic importance of computing power, the future of AI governance, and what it will take for democracies to lead responsibly in the age of AI.Featuring:Ben Buchanan – LinkedIn Chris Benson – Website, LinkedIn, Bluesky, GitHub, XLinks:The AI Grand BargainUpcoming Events: Register for upcoming webinars here!

We've had many conversations on Raise the Line about the challenges of health communication in today's world of information overload, but none of our guests have the kind of expertise Dr. Tesfa Alexander has acquired in a career that has taken him from Madison Avenue to the halls of government and academia. From guiding tobacco education research at the FDA to leading public health initiatives at MITRE, Dr. Alexander has developed a deep understanding of the science and strategy behind effective health communication. “Successful campaigns keep the long game in mind where you want to develop a lasting relationship with your target audience,” he tells host Lindsey Smith. That relationship needs to be built on understanding culture, beliefs, priorities and daily realities, and only then can you develop messaging that will resonate, he explains. Dr. Alexander also believes these relationships can be leveraged to help people sort out facts from misleading or inaccurate claims. “I strongly recommend shifting our focus from combating misinformation head on, and instead working with the communities who we are seeking to serve.” This fascinating look at communication science also covers: How stories drive belief; The importance of working with community partners who are trusted messengers;  The power of audience segmentation. Tune in as Dr. Alexander unpacks what it takes to influence beliefs, and ultimately behaviors, in an era defined by misinformation and institutional mistrust. Mentioned in this episode:Lerner Center for Public Health Advocacy If you like this podcast, please share it on your social channels. You can also subscribe to the series and check out all of our episodes at www.osmosis.org/podcast

On this episode of The Association Podcast, we welcome Ravi Rooprai, Director of IT and PMO at the Million Dollar Round Table (MDRT). Ravi shares his unique journey from molecular microbiology and pharmaceutical consulting into association technology leadership, bringing a scientific mindset to digital transformation and innovation.The conversation explores how MDRT is modernizing association technology by decoupling legacy systems, building scalable data ecosystems, and experimenting with AI-driven personalization. Ravi explains how his team approaches technology through experimentation, feasibility studies, and agile thinking to improve member experiences and operational efficiency.We also dive into MDRT's cutting-edge meeting technology, including large-scale multilingual interpretation powered by AI and the infrastructure required to support thousands of attendees simultaneously streaming translated sessions. Ravi discusses how associations can better leverage data, personalization, and experimentation to drive engagement, retention, and measurable member value.From building a culture of innovation to applying e-commerce thinking to membership value, this episode offers practical insights for association leaders navigating digital transformation.00:01:00 Introduction to Ravi Rooprai and MDRT00:01:30 Rapid Fire Questions00:02:40 Ravi's Career Journey from Science to Association Technology00:04:30 Lessons from Industry Applied to Associations00:05:30 Using ROI and Value Metrics in Association Technology Decisions00:07:00 Measuring Member Lifetime Value00:08:30 The Value of MDRT Membership for Financial Professionals00:10:30 Reworking Legacy AMS Systems Through Decoupled Data Architecture00:12:00 Building a Modern Data Ecosystem Around Legacy Platforms00:13:30 Scaling Membership Systems to Handle Peak Demand00:14:45 Managing 60–70K Membership Applications During Renewal Season00:16:00 Leveraging AI and Technology at Large Global Conferences00:17:00 Simultaneous Translation and Multilingual Meeting Experiences00:18:30 Solving Conference Connectivity and Infrastructure Challenges00:20:00 Improving the Member Experience Through Technology00:21:00 Favorite Tools: AI, Copilot, and Power Apps00:23:30 Empowering Staff to Experiment with Technology00:24:30 Personalization and Data-Driven Engagement00:26:00 Using Engagement Data to Shape Event Programming00:28:00 The Future of Digital Transformation in Associations00:29:00 Applying a Scientific Mindset to Technology Innovation00:31:00 Building a Culture of Experimentation and Safe Failure00:33:00 Feasibility Studies and Agile Technology Testing00:35:00 Applying E-commerce Thinking to Membership Value00:37:00 The Future of AI and Meeting Technology at MDRT00:39:00 Rethinking the Conference Experience00:40:00 Closing Thoughts 

Realities Remixed, formerly know as Cloud Realities, launches a new season exploring the intersection of people, culture, industry and tech.Business messaging is transforming customer engagement by enabling brands to move conversations into familiar, always‑on messaging platforms. The result for customers is greater convenience, quicker resolutions, and more meaningful, personalized interactions. This week, Dave, Esmee, and Rob are joined by Kathleen Tandy, Global Director and Head of Business Messaging Marketing and WhatsApp for Business at Meta , to explore how companies are using messaging platforms to engage customers, what customers expect from these experiences, and the challenges of scaling messaging in tech.TLDR00:35 – Introduction01:00 –  Hang out: The new Remarkable05:25 – Dig in: Using messaging to enhance customer experiences20:49 – Conversation with Kathleen Tandy55:26 – The passion for college football and championship weekend!GuestKathleen Tandy: https://www.linkedin.com/in/kptandy/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Episode: 3357 Backpropagation: The idea that powers modern AI.  Today, backpropagation, the trick behind modern AI.

In Episode 6.13, Dr. Joshua Lowentritt joins host David Mandell to explore the rapidly evolving role of artificial intelligence in medicine. Dr. Lowentritt shares his 25+ year journey as a practicing physician and healthcare leader, highlighting how Hurricane Katrina reshaped his professional outlook and entrepreneurial path. From building physician-owned organizations to investing in startups, his career reflects a deep commitment to improving healthcare delivery. Today, that mission increasingly centers on leveraging AI to enhance both physician experience and patient outcomes. A central focus of the conversation is the use of AI-powered ambient scribes in clinical practice. Dr. Lowentritt explains how tools like AI documentation assistants have reduced administrative burden, lowered cognitive load, and allowed him to reconnect with patients at a human level. Rather than typing throughout visits, he now maintains eye contact, listens more fully, and spends more time counseling patients. Beyond documentation, AI tools assist with chart summaries, clinical decision support, population health prioritization, and genetic testing insights—streamlining workflows and improving proactive care. The episode also explores critical guardrails for AI adoption. Dr. Lowentritt emphasizes the importance of data privacy, informed patient consent, verifying clinical sources, and using multiple evidence-based references when relying on large language models. Drawing on Everett Rogers' Diffusion of Innovations theory, he discusses why physicians—traditionally cautious adopters—have embraced AI more rapidly than expected. Ultimately, he argues that AI will not replace physicians but will supplement them, allowing doctors to focus on judgment, empathy, context, and patient connection—the highest value aspects of medicine. Learn more, including additional show notes, links, and detailed key takeaways, by visiting physicianswealthpodcast.com. Click here to get your FREE copy of our latest book, Wealth Strategies for Today's Physician!

What distinguishes organizations that capture real value from AI from those still experimenting?In this episode of AWS Executive Insights, Roger Premo, Global Head of Strategy at IBM, breaks down the practical lessons behind IBM's own AI transformation. From embedding generative AI into everyday workflows to codifying an agentic development lifecycle, IBM has paired leadership commitment with disciplined execution to drive measurable results.Premo discusses how hybrid cloud architecture enables agents to access data across heterogeneous environments, why data product management is now a business imperative, and how governance must be built into AI systems from the start. This essential discussion offers leaders a framework for moving beyond isolated pilots and building scalable, secure, and value-driven AI capabilities. Thank you to IBM for their partnership and participation in this discussion.

In this episode, we dive into the evolving world of industrial AI, exploring everything from CNC innovation in Tel Aviv to the surprising rise of digital cousins over traditional digital twins. We unpack how startups and established players alike are reimagining automation, robotics, and the very nature of intelligent agents on the factory floor. Along the way, we discuss the parallels between LLMs and the invention of refrigeration, ask who will become the 'Coca-Cola' of AI, and reflect on the real impact of democratizing advanced technology. Join us as we debate the future of humanoid robots, the shifting boundaries between tool and actor, and the practical challenges of bringing AI-driven agents into real-world industry. If you're curious about where industrial automation is headed—and what innovations might define the next era—this conversation is not to be missed.

This week on Catalyst, guest host Jod Kaftan sits down with designer and expert in human-centered AI, Shelley Evenson. Shelley shares her insights on how designers and teams can achieve human-AI flow and how to spot the warning signs that a team is drifting into the realm of AI slop. Jod and Shelley also discuss the need for change management in AI transformations and talk about who in an organization should own an AI transformation? Is it HR? Is it IT? According to Shelley it's a team endeavour that should start at the very top, with the CEO.Please note that the views expressed may not necessarily be those of NTT DATALinks: Shelley Evenson Flow: The Psychology of Optimal Experience Learn more about Launch by NTT DATASee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this #AWSExecutiveInsights conversation, Tom Soderstrom, AWS Executive in Residence, talks with Erin Kraemer, Sr. Principal Technical Product Manager for AWS Agentic AI, who draws on 25 years at Amazon to explore how organizations move from AI experimentation to production, built on observability, guardrails, and bringing your people along the journey.

In this feed drop from the Internet History Podcast, host Brian McCullough speaks with Chris Dixon, general partner at a16z, about his path from 1980s hobbyist programmer to one of the most prominent venture capitalists in tech. Chris traces his career from quantitative finance to founding SiteAdvisor, cofounding Founder Collective, starting an early machine learning company, and eventually building a16z's crypto practice from the ground up. They also discuss his framework for spotting unconventional investments, the current state of crypto regulation, and why New York is becoming a serious tech hub.   Resources: Follow Chris Dixon on X:  https://twitter.com/cdixon Follow Brian McCullough on X:  https://twitter.com/brianmcc Listen to Internet History Podcast: https://www.youtube.com/@internethistorypodcast 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.

What happens when a grieving person finds comfort in a song — and then discovers it was made by AI? That question is the heart of this episode, and it captures everything that matters about the moment we're in as choral musicians.This episode is a deep dive into AI: what it actually is, how we got here, and why Beth believes it represents one of the greatest opportunities choral music has had in a very long time — but only if we're paying attention.In this episode:A brief history of technology and choral music, from the printing press and the Petrucci Collection (1501) to the phonograph, the internet, and social media — and what each shift tells us about where we are nowThe four phases of AI: Classical AI, Machine Learning, Generative AI, and Agentic AI — explained with musical analogiesWhy choral music has historically been a late adopter of technology, and why this time we can choose to do it differentlyThe Industrial Revolution parallel: how a shift in human labor created the conditions for a rise in choral societies — and why agentic AI may do the same thingWhy choral musicians are in the business of unrepeatable human moments — and why that business has never had a bigger marketComing up next: Beth gets practical with 5 specific ways you can start using AI in your choral work right now — with examples and prompts.Interested in going deeper? Beth is putting together a short masterclass: From Basics to Breakthroughs: AI for Choral Artists — covering foundations, practical applications, ethics, and advanced implications for your work and community. 

Adatépítész -az első magyar datapodcast Minden ami hír, érdekesség, esemény vagy tudásmorzsa az  adat, datascience, adatbányászat és hasonló kockaságok világából. Become a Patron! Besértődött AISértődött emberHW

We're marking Rare Disease Month 2026 by highlighting the powerful story of Shanthi Hegde, a young patient advocate working to transform how bleeding disorders are understood, treated, and supported. This work is fueled by her own arduous journey with two rare bleeding disorders and immune dysregulatory syndrome, and an extended diagnostic odyssey marked by dismissal, underdiagnosis, and structural bias. “I was told many times by many providers that these disorders are not common in Indians and that my bruises were there just because I'm brown.” Admirably, Shanthi pushed past this mistreatment, advocated for her medical needs, and devoted herself to tackling a range of issues confronting rare disease patients from mental health access to affordable drug pricing to research equity. In this remarkable Year of the Zebra conversation with host Lindsey Smith, you'll also learn about: Shanti's work with the Hemophilia Federation of America; How gaps extend beyond treatment to include insurance coverage, provider training, and substance use care; What clinicians can do to improve the work they do with rare disease patients. Join us for a conversation that connects patient voice to system change, and explores what real equity for rare disease communities will require. Mentioned in this episode:Hemophilia Federation of AmericaShanthi's LinkedIn Profile If you like this podcast, please share it on your social channels. You can also subscribe to the series and check out all of our episodes at www.osmosis.org/podcast

From covering the front desk as an intern to leading global business strategy, James Waters' career at Booking.com mirrors the company's own transformation. Now Chief Business Officer, Waters reflects on how experimentation, data-driven decision making, and a strong customer focus have powered Booking.com's growth. As generative AI reshapes the travel industry, he shares how the company is evolving its connected trip vision while reinforcing responsible AI principles and strong technical foundations. This episode offers leaders a thoughtful perspective on scaling innovation, sustaining culture through change, and using AI to amplify human ingenuity.

Realities Remixed, formerly know as Cloud Realities, launches a new season exploring the intersection of people, culture, industry, and tech. Energy transportation is a deeply local business, safely delivering gas and electricity, more and more from renewable sources, directly to the communities it serves. Technology and AI help make that possible by strengthening safety, bringing companies closer to customers, and enabling teams to build the future together. This week, Dave, Esmee, and Rob are joined by John Koerwer, CIO of UGI Corporation, to explore explore why “the business” and tech still struggle to speak the same language, nd what helps close the gap.TLDR00:35 – Introduction01:17 – Hang out: new toys and coffee07:55 – Dig in: the business - tech divide21:07 – Conversation with John Koerwer59:40 – The amazing AI technology in The Sphere's version of The Wizard of OzGuestJohn Koerwer: https://www.linkedin.com/in/john-koerwer-46102127/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Send a textTom Griffiths, Henry R. Luce Professor at Princeton University, joins the show to explore the surprising science behind how we actually think. His new book, The Laws of Thought, bridges computational cognitive science and AI—challenging assumptions about decision-making, neural networks, and the path to artificial general intelligence.Show NotesTimestamps 01:21 – Meet Tom Griffiths 05:27 – Tom's Book 06:58 – A Neural Network 09:55 – AGI? 19:10 – Writing the Book 20:45 – The Laws of Thought 27:24 – The Neural Network Surprise 31:33 – Learning from Experts 35:19 – Decision Making vs. Probability 42:36 – Government AI ConsiderationsLinks LinkedIn: linkedin.com/in/tom-griffiths-7b31a0364 Book: The Laws of Thought – Macmillan#TheLawsOfThought, #CognitiveScience, #ArtificialIntelligence, #AGI, #NeuralNetworks, #DecisionMaking, #Probability, #AIResearch, #Princeton, #TechPodcast, #MakingDataSimple, #AIGovernment, #MachineLearningWant to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send a textTom Griffiths, Henry R. Luce Professor at Princeton University, joins the show to explore the surprising science behind how we actually think. His new book, The Laws of Thought, bridges computational cognitive science and AI—challenging assumptions about decision-making, neural networks, and the path to artificial general intelligence.Show NotesTimestamps 01:21 – Meet Tom Griffiths 05:27 – Tom's Book 06:58 – A Neural Network 09:55 – AGI? 19:10 – Writing the Book 20:45 – The Laws of Thought 27:24 – The Neural Network Surprise 31:33 – Learning from Experts 35:19 – Decision Making vs. Probability 42:36 – Government AI ConsiderationsLinks LinkedIn: linkedin.com/in/tom-griffiths-7b31a0364 Book: The Laws of Thought – Macmillan#TheLawsOfThought, #CognitiveScience, #ArtificialIntelligence, #AGI, #NeuralNetworks, #DecisionMaking, #Probability, #AIResearch, #Princeton, #TechPodcast, #MakingDataSimple, #AIGovernment, #MachineLearningWant to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Building a model for an academic paper is one thing. Building a model that has to work perfectly during the Cricket World Cup with millions watching is something else entirely. There's no room for the kind of errors that might be acceptable in research settings or even standard business applications.In this Value Boost episode, Prof. Steve Stern joins Dr. Genevieve Hayes to share practical lessons from deploying the Duckworth-Lewis-Stern method in high-pressure, real-time environments where mistakes have global consequences.You'll learn:Why model simplicity matters more than you think [02:04]The two types of errors you need to understand [03:21]How to test models for extreme situations [05:50]The balance between confidence and humility [07:37]Guest BioProf. Steve Stern is a Professor of Data Science at Bond University, and is the official custodian of the Duckworth-Lewis-Stern (DLS) cricket scoring system.LinksContact Steve at Bond UniversityConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

In this week's episode, Leslie Heaney sits down with Vasant Dhar—professor at NYU Stern School of Business and the Center for Data Science at New York University, founder of SCT Capital, and author of Thinking with Machines: The Brave New World of AI.Together, they explore how artificial intelligence evolved, why language prediction changed everything, and what it means now that machines can think alongside humans. The conversation examines the growing divide between those who use AI to sharpen judgment and those who rely on it to think for them, as well as the broader implications for work, education, power, and responsibility.This is a grounded, honest conversation about the power of AI—and how we choose to live with it.Hosted on Ausha. See ausha.co/privacy-policy for more information.

In this episode, I sit down with Andre Sagodi, a manufacturing and innovation expert at Audi, to explore how artificial intelligence is transforming the car production process. We dive into Audi's journey from piloting AI-based crack detection in sheet metal parts to scaling these solutions across multiple global sites. Andre shares practical insights on overcoming challenges like data consistency, model scalability, and workforce collaboration, all while aligning with Audi's strategic vision. Together, we discuss what it really takes to turn promising AI pilots into production-ready systems that deliver real business value. If you're curious about the future of industrial AI and want a behind-the-scenes look at innovation inside a world-class manufacturer, this episode is for you.

This week on Catalyst, Tammy speaks with Nate Berent-Spillson, the SVP of Engineering at Launch by NTT DATA. Nate is the type of guy who is always using technology in new and inventive ways. This week Nate and Tammy discuss the evolution of AI tools and Nate introduces the power of command line interfaces. Nate shares how using AI in innovative new ways can reduce cognitive load and reimagine user interfaces to enhance productivity and efficiency in the workplace. Please note that the views expressed may not necessarily be those of NTT DATALinks: Nate Berent- Spillson Markdown Guide Learn more about Launch by NTT DATASee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

On this episode of The Association Podcast, we are thrilled to welcome Mike Moyer, Executive Director of the National Wrestling Coaches Association (NWCA). Mike shares his journey from wrestling coach to leading the NWCA, detailing the organization's mission to develop transformational coaches and advocate for wrestler safety through groundbreaking initiatives such as the creation of a weight management system. We delve into NWCA's innovative strategies, including coaching development programs and the Wrestlers in Business Network (WIBN), which connects wrestlers with career opportunities. Mike also highlights the challenges and triumphs of expanding wrestling programs nationwide and the critical role of technology in achieving their goals.

In this episode of The Effortless Podcast, Dheeraj Pandey speaks with Dr. Abhishek Bhowmick about how quantum mechanics reshaped our understanding of determinism and why that shift matters for AI today.  From the Einstein–Bohr debates to the idea that nature is fundamentally probabilistic, they explore how the collapse of “if-then” thinking began nearly a century ago. The discussion draws parallels between quantum superposition and modern LLM behavior. At its core, the episode reframes AI as a rediscovery of how reality computes. The conversation then moves from physics to computing architecture, tracing the evolution from scalar CPUs to GPUs, TPUs, tensors, and eventually quantum computing. They examine why probabilistic systems and vector math feel more natural than purely deterministic software. Hybrid computing models show that classical systems still matter. The episode also unpacks what quantum computers are truly good at, especially in cryptography and simulation. Ultimately, it reflects on whether the future of computing lies in embracing probability rather than resisting it. Key Topics & Timestamps 00:00 – Welcome, context, and how Dheeraj & Abhishek met 04:00 – Abhishek's journey: IIT, Princeton, Apple, Snowflake 08:00 – The 1927 Solvay Conference and physics at a crossroads 12:00 – Einstein vs. Bohr: determinism vs. probability 16:00 – Superposition and the collapse of the wave function 20:00 – Fields vs. particles: what is an electron really? 25:00 – Matter particles, force particles, and the Standard Model 30:00 – Transistors, voltage, and the rise of deterministic computing 35:00 – From scalar CPUs to vectors and matrices 40:00 – Tensors, linear algebra, and modern AI systems 45:00 – Principle of Least Action and gradient descent parallels 50:00 – Hallucinations, probability mass, and LLM behavior 55:00 – Vector databases, embeddings, and KNN search 59:00 – GPUs vs. TPUs: matrix vs. tensor architectures 1:05:00 – What quantum computers are actually good at 1:10:00 – Post-quantum cryptography and the future of computing Host -  Dheeraj Pandey Co-founder & CEO at DevRev. Former Co-founder & CEO of Nutanix. A systems thinker and product visionary focused on AI, software architecture, and the future of work. Guest -  Dr Abhishek Bhowmick                                                                                                                                                                                                                Co-Founder and CTO of Samooha, a secure data collaboration platform acquired by Snowflake. He previously worked at Apple as Head of ML Privacy and Cryptography, System Intelligence, and Machine Learning, and earlier at Goldman Sachs. He attended Princeton University and was awarded IIT Kanpur's Young Alumnus Award in 2024. Follow the Host and Guest - Dheeraj Pandey: LinkedIn - https://www.linkedin.com/in/dpandey Twitter - https://x.com/dheeraj Abhishek Bhowmik  LinkedIn –  https://www.linkedin.com/in/ab-abhishek-bhowmick Twitter/X – https://x.com/bhowmick_ab Share Your Thoughts Have questions, comments, or ideas for future episodes?

How did we go from digital computers to AI seemingly everywhere? Neil deGrasse Tyson, Chuck Nice, & Gary O'Reilly dive into the mechanics of thinking, how AI got its start, and what deep learning really means with cognitive and computer scientist, Nobel Laureate, and one of the architects of AI, Geoffrey Hinton. Subscribe to SiriusXM Podcasts+ to listen to new episodes of StarTalk Radio ad-free and a whole week early.Start a free trial now on Apple Podcasts or by visiting siriusxm.com/podcastsplus. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

“The major pitfall of machine learning of any kind is to be overly confident in the results. We run the risk of garbage in gospel out.” This discussion offers a rare chance to go a little deeper into a Leading Edge article and hear directly from the authors about the thinking behind their workflow. Satinder Chopra and Kurt Marfurt walk through how unsupervised machine learning, careful attribute selection, and simple preprocessing steps can reveal subtle channel features in a deepwater New Zealand example. It feels less like a theory lesson and more like practical guidance on using machine learning as a helpful partner in everyday seismic interpretation. KEY TAKEAWAYS > Small workflow choices have big impact. Clean input data, thoughtful attribute selection, and simple normalization steps often determine whether machine learning highlights geology or just amplifies noise. > The value is in the combination of tools and judgment. Unsupervised methods quickly expose patterns, but interpreters still need to compare results with seismic sections, wells, and regional context to confirm what is real. > PCA and SOM make complex attribute sets easier to explore. By reducing dozens of attributes into clearer clusters, they help interpreters see channel shapes and reservoir variability that might otherwise be overlooked. LINKS * Read the December 2025 special section - https://pubs.geoscienceworld.org/tle/issue/44/12 * Seismic characterization with unsupervised machine learning applications for facies classification by Satinder Chopra and Kurt Marfurt - https://doi.org/10.1190/tle44120934.1 ABOUT SEISMIC SOUNDOFF Seismic Soundoff showcases conversations addressing the challenges of energy, water, and climate. Produced by the Society of Exploration Geophysicists (SEG) and hosted by Andrew Geary of 51 features, these episodes celebrate and inspire the geophysicists of today and tomorrow. Three new episodes monthly. See the full archive at https://seg.org/resources/podcast/.

Few issues have tested public trust in medicine as deeply as vaccines, and few individuals have influenced that dialogue more than Dr. Paul Offit, director of the Vaccine Education Center at the Children's Hospital of Philadelphia and a longtime member of the FDA's Vaccine Advisory Committee. In this timely and candid interview with Raise the Line host Lindsey Smith, Dr. Offit points to this year's severe flu season and a resurgence of measles as alarming proof points of how a changing federal perspective on vaccine policy is having a real impact on public health. “You'd like to think you can educate about the importance of vaccines, but I fear at this point the viruses themselves are doing the educating.” In this wide ranging discussion, Dr. Offit also addresses: The rigorous and painstaking process of developing vaccines, based on his experience co-inventing the rotavirus vaccine. Shifting levels of public trust in scientific organizations. Promising innovations in vaccine development. Don't miss this deeply-informed perspective on the interplay of science, policy, and public education, and his encouraging message to young clinicians about managing the current challenges in public health.  Mentioned in this episode: Vaccine Education Center at Children's Hospital of PhiladelphiaPerelman School of Medicine If you like this podcast, please share it on your social channels. You can also subscribe to the series and check out all of our episodes at www.osmosis.org/podcast

Dr. Ruba Borno, AWS Vice President of Global Specialists and Partners, shares her journey from refugee to technology leader and reveals what drives purpose-driven leadership. As a daughter of Palestinian refugees who came to the U.S. during the first Gulf War, she learned early that opportunity is a gift—and believes in "leaving the ladder there" for others to climb.In this conversation with host Richard Taylor, Dr. Borno discusses building high-performing teams, leading 18,000 engineers through COVID-19, and scaling customer support through AI innovation. She shares critical leadership lessons: ask the right questions rather than having all the answers, trust your instincts, and create environments where teams can safely innovate and fail.

Realities Remixed, formerly know as Cloud Realities, launches a new season exploring the intersection of people, culture, technology, and society. Hosts Dave Chapman, Esmee van de Giessen, and Rob Kernahan unpack 2026's defining trends, from AI and sovereignty to adaptability and automation, offering fresh insight, candid reflections, and forward‑looking conversations shaping the year ahead. TLDR00:20 – Introduction of Realities Remixed02:30 – Why the show evolved?04:50 – Dig in with the team: Predictions for 202606:40 – Macro trends13:00 – Sovereignty 17:40 – Agentic AI22:17 – Human–AI interaction26:06 – Cloud trends30:42 – AI scaling, domain‑specific models35:03 – Adoption lag39:34 – Physical AI43:47 – Quantum computing48:21 – Hardware acceleration50:30 – Cybersecurity52:38 – Season outlook HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

What if your data platform could power both critical business decisions and real-time product features at scale? In this episode, host Benjamin sits down with Magnus Dahlbäck, Senior Director of Data and Platform at Voi, to explore how a metrics-first approach and semantic layers transform data accessibility, why traditional ML and LLMs require different strategies for different problems, and how to balance FinOps costs while processing billions of IoT events daily. Whether you're building data infrastructure for a high-growth company or rethinking how your organization consumes data, this conversation is packed with practical strategies for unlocking data value and preparing your platform for AI. Tune in to discover how Voi ditched traditional BI tools and revolutionized their approach to enterprise analytics.

As AI accelerates innovation and adoption, leaders are facing rising cognitive load, shifting systems, and new emotional realities inside their organizations. In this episode, Deloitte's Chief Innovation Officer Deborah Golden joins us to explore how AI is reshaping leadership, why vulnerability and empathy are critical in this moment, and how anti-fragility, not just resilience, will define the future of work.Featuring:Deborah Golden – LinkedIn Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:DeloitteSponsor: Framer - The website builder that turns your dot com from a formality into a tool for growth. Check it out at framer.com/PRACTICALAIUpcoming Events: Register for upcoming webinars here!

This week on Catalyst, Tammy speaks with Graeme Cuthbertson, Director of IT Operations and End-User Systems at Neurocrine Biosciences. They explore Graeme's career across industries, including banking and biotech, and what those experiences have taught him about building empathy into technology. Graeme also highlights the importance of meeting customers where they are, the role of family support in personal and professional growth, and how human connection and thoughtful technology can elevate both employee and customer experiences.Please note that the views expressed may not necessarily be those of NTT DATALinks: Graeme Cuthbertson Learn more about Launch by NTT DATASee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Antonia and Andrew discuss the February 18, 2026 issue of JBJS, along with an added dose of entertainment and pop culture. Listen at the gym, on your commute, or whenever your case is on hold! Link: JBJS website: https://jbjs.org/issue.php Sponsor: This episode is brought to you by JBJS Clinical Classroom. Subspecialties: Knee, Oncology, Pediatrics, Shoulder, Hand & Wrist, Orthopaedic Essentials, Trauma, Spine Chapters (00:00:03) - Case is On Hold(00:00:45) - Episode 100(00:03:03) - Sneak Preview: Miller Review Course(00:03:42) - AI Generated Text in Orthopedics(00:05:36) - AI in Orthopedics: The Promised Land(00:13:44) - Artificial Intelligence in orthopedic and sports medicine(00:16:27) - Osteo and Sports Medicine Editorial Policies on AI(00:24:42) - How to Write a Paper With a Computer(00:25:16) - Deep Learning Model for Differentiating Neoplastic Fractures from Non(00:31:36) - The Ms. Cleo Phone Paradigm(00:32:34) - Machine Learning and Neoplastic Fractures(00:37:05) - AI-driven CT MRI Image Fusion and Automatic ACL Reconstruction(00:39:05) - A 100 Episodes of JBGS: Thank You!(00:40:46) - Aisha Abdeen Is The Next Co-Host!

On this episode of The Association Podcast, we welcome industry veteran Liam O'Malley from Path LMS by Momentive. Liam shares his extensive journey in the association market, highlighting key experiences from the American Bar Association to his current role at Momentum. The discussion covers the evolving landscape of online learning, microlearning strategies, and the importance of data-driven decision-making. Liam also introduces the exciting launch of Momentive IQ, a tool designed to centralize data and integrate various association technologies. Tune in to hear insights on managing nano markets and the future of AI in associations.

What does it take to migrate the heart of a nation's banking system to the cloud?In this AWS Executive Insights fireside chat, Ben Cabanas sits down with Simon Davies, GM of Core Banking at Commonwealth Bank of Australia, to unpack one of the most mission-critical cloud transformations in financial services. With nearly 40% of Australia's liquidity flowing through CBA's core platform, the stakes were enormous.Simon shares how CBA migrated the world's largest SAP core banking deployment to AWS while improving reliability, reducing infrastructure costs by 30%, and enabling real-time customer experiences. Beyond the technical achievement, he reveals how transparency, cultural alignment, and a rallying cry of “believe” helped mobilize thousands across the organization to deliver change at national scale.

AI is moving fast from research to real-world deployment, and when things go wrong, the consequences are no longer hypothetical. In this episode, Sean McGregor, co-founder of the AI Verification & Evaluation Research Institute and also the founder of the AI Incident Database, joins Chris and Dan to discuss AI safety, verification, evaluation, and auditing. They explore why benchmarks often fall short, what red-teaming at DEF CON reveals about machine learning risks, and how organizations can better assess and manage AI systems in practice.Featuring:Sean McGregor– LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:AI Verification & Evaluation Research InstituteAI Incident Database38th convening of IAAIBenchRiskState of Global AI Incident ReportingUpcoming Events: Register for upcoming webinars here!

Check out host Bidemi Ologunde's new show: The Work Ethic Podcast, available on Spotify and Apple Podcasts.Email: bidemiologunde@gmail.comIn this episode, host Bidemi Ologunde sits down with Damilola "Dammy" Gbenro, a Data Analytics and Machine Learning professional and talked about what it really means to build and maintain an online presence in the age of algorithms and AI. How do you utilize the benefits of social media without letting it consume you? What does online safety look like when your life is also your brand? And as AI reshapes trust, attention, and creativity, how do we protect our identities and our peace?Quick question: when you buy something handmade, do you ever wonder who made it, and where your money really goes? Lembrih is building a marketplace where you can shop Black and African-owned brands and learn the story behind the craft. And the impact is built in: buyers can support vendors directly, and Lembrih also gives back through African-led charities, including $1 per purchase. They're crowdfunding on Kickstarter now. Back Lembrih at lembrih.com, or search “Lembrih” on Kickstarter.Support the show

“I do not believe we should be testing to test. We have to know, is this test going to change management and is it going to make a difference,” says pediatric allergist-immunologist Dr. Zachary Rubin. His knack for providing that sort of straightforward guidance explains why Dr. Rubin has become a trusted voice on allergies, asthma, and vaccines for his millions of followers on social media platforms. It's also why we couldn't ask for a better guide for our discussion on the rise in allergies, asthma, and immune-related conditions in children, and how families can navigate the quickly evolving science and rampant misinformation in the space. On this episode of Raise the Line, we also preview Dr. Rubin's new book, All About Allergies, in which he breaks down dozens of conditions and diseases, offering clear explanations and practical treatment options for families. Join host Lindsey Smith for this super informative conversation in which Dr. Rubin shares his thoughts on a wide range of topics including: What's behind the rise in allergic and immune-related conditions.Tips for managing misinformation, myths and misunderstandings. How digital platforms can be leveraged to strengthen public health.How to build back public trust in medicine.Mentioned in this episode:All About Allergies bookBench to Bedside PodcastInstagramTikTokYouTube Channel If you like this podcast, please share it on your social channels. You can also subscribe to the series and check out all of our episodes at www.osmosis.org/podcast

This week on Catalyst, Tammy is joined by Mark Curtis, the co-founder of Fjord and a pioneer in the design, strategy and thought leadership space. Tammy and Mark discuss his extensive career and delve into the evolution of design over the past 3 decades. They also look to the future and explore how AI is transforming design and why it still can't beat the human brain in some applications. Mark also talks about this new venture Full Moon, a project focused on the intersection of humans, technology, and business, and the resurgence of service design in response to the complexities of modern challenges.Please note that the views expressed may not necessarily be those of NTT DATALinks: Mark Curtis Full Moon Moving Beyond “AI is just a Tool”: Shifts in AI Communication in 2026 - Medium Learn more about Launch by NTT DATASee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Promising new cancer screening methods are pivoting toward multi-cancer early detection (MCED) blood tests (liquid biopsies) and AI-enhanced imaging, which aim to detect multiple cancer types from a single, non-invasive sample, often before symptoms arise. These technologies, including the Galleri test and Novelna's protein-based tests, analyze DNA, proteins, or methylation patterns to identify cancer signals.  Multi-Cancer Early Detection (MCED) Blood Tests: These tests, often called liquid biopsies, detect DNA or proteins shed by cancer cells into the bloodstream, identifying early-stage cancers (e.g., ovarian, pancreatic) that lack standard screening protocols. Galleri Test: Analyzes chemical methylation patterns to detect over 50 types of cancer, with the potential to indicate the cancer's origin in the body. Novelna's Test: An experimental test analyzing protein signatures, showing high accuracy in identifying 18 early-stage cancers, including 93% of stage 1 cancers in men. TriOx Test: A new, Oxford-developed test showing high sensitivity in detecting trace cancer DNA. AI and Machine Learning in Screening: AI is enhancing existing imaging techniques (e.g., mammography) to improve accuracy and efficiency in reading scans, reducing false positives. Other Liquid Biopsies: Research into analyzing blood, breath, and urine for early signs of cancer, offering a less invasive alternative to tissue biopsies.  While offering immense promise for reducing cancer mortality, many of these technologies, including MCED, are still in research or early implementation phases, and they can produce false positives. 

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Larry Swanson, a knowledge architect, community builder, and host of the Knowledge Graph Insights podcast. They explore the relationship between knowledge graphs and ontologies, why these technologies matter in the age of AI, and how symbolic AI complements the current wave of large language models. The conversation traces the history of neuro-symbolic AI from its origins at Dartmouth in 1956 through the semantic web vision of Tim Berners-Lee, examining why knowledge architecture remains underappreciated despite being deployed at major enterprises like Netflix, Amazon, and LinkedIn. Swanson explains how RDF (Resource Description Framework) enables both machines and humans to work with structured knowledge in ways that relational databases can't, while Alsop shares his journey from knowledge management director to understanding the practical necessity of ontologies for business operations. They discuss the philosophical roots of the field, the separation between knowledge management practitioners and knowledge engineers, and why startups often overlook these approaches until scale demands them. You can find Larry's podcast at KGI.fm or search for Knowledge Graph Insights on Spotify and YouTube.Timestamps00:00 Introduction to Knowledge Graphs and Ontologies01:09 The Importance of Ontologies in AI04:14 Philosophy's Role in Knowledge Management10:20 Debating the Relevance of RDF15:41 The Distinction Between Knowledge Management and Knowledge Engineering21:07 The Human Element in AI and Knowledge Architecture25:07 Startups vs. Enterprises: The Knowledge Gap29:57 Deterministic vs. Probabilistic AI32:18 The Marketing of AI: A Historical Perspective33:57 The Role of Knowledge Architecture in AI39:00 Understanding RDF and Its Importance44:47 The Intersection of AI and Human Intelligence50:50 Future Visions: AI, Ontologies, and Human BehaviorKey Insights1. Knowledge Graphs Combine Structure and Instances Through Ontological Design. A knowledge graph is built using an ontology that describes a specific domain you want to understand or work with. It includes both an ontological description of the terrain—defining what things exist and how they relate to one another—and instances of those things mapped to real-world data. This combination of abstract structure and concrete examples is what makes knowledge graphs powerful for discovery, question-answering, and enabling agentic AI systems. Not everyone agrees on the precise definition, but this understanding represents the practical approach most knowledge architects use when building these systems.2. Ontology Engineering Has Deep Philosophical Roots That Inform Modern Practice. The field draws heavily from classical philosophy, particularly ontology (the nature of what you know), epistemology (how you know what you know), and logic. These thousands-year-old philosophical frameworks provide the rigorous foundation for modern knowledge representation. Living in Heidelberg surrounded by philosophers, Swanson has discovered how much of knowledge graph work connects upstream to these philosophical roots. This philosophical grounding becomes especially important during times when institutional structures are collapsing, as we need to create new epistemological frameworks for civilization—knowledge management and ontology become critical tools for restructuring how we understand and organize information.3. The Semantic Web Vision Aimed to Transform the Internet Into a Distributed Database. Twenty-five years ago, Tim Berners-Lee, Jim Hendler, and Ora Lassila published a landmark article in Scientific American proposing the semantic web. While Berners-Lee had already connected documents across the web through HTML and HTTP, the semantic web aimed to connect all the data—essentially turning the internet into a giant database. This vision led to the development of RDF (Resource Description Framework), which emerged from DARPA research and provides the technical foundation for building knowledge graphs and ontologies. The origin story involved solving simple but important problems, like disambiguating whether "Cook" referred to a verb, noun, or a person's name at an academic conference.4. Symbolic AI and Neural Networks Represent Complementary Approaches Like Fast and Slow Thinking. Drawing on Kahneman's "thinking fast and slow" framework, LLMs represent the "fast brain"—learning monsters that can process enormous amounts of information and recognize patterns through natural language interfaces. Symbolic AI and knowledge graphs represent the "slow brain"—capturing actual knowledge and facts that can counter hallucinations and provide deterministic, explainable reasoning. This complementarity is driving the re-emergence of neuro-symbolic AI, which combines both approaches. The fundamental distinction is that symbolic AI systems are deterministic and can be fully explained, while LLMs are probabilistic and stochastic, making them unsuitable for applications requiring absolute reliability, such as industrial robotics or pharmaceutical research.5. Knowledge Architecture Remains Underappreciated Despite Powering Major Enterprises. While machine learning engineers currently receive most of the attention and budget, knowledge graphs actually power systems at Netflix (the economic graph), Amazon (the product graph), LinkedIn, Meta, and most major enterprises. The technology has been described as "the most astoundingly successful failure in the history of technology"—the semantic web vision seemed to fail, yet more than half of web pages now contain RDF-formatted semantic markup through schema.org, and every major enterprise uses knowledge graph technology in the background. Knowledge architects remain underappreciated partly because the work is cognitively difficult, requires talking to people (which engineers often avoid), and most advanced practitioners have PhDs in computer science, logic, or philosophy.6. RDF's Simple Subject-Predicate-Object Structure Enables Meaning and Data Linking. Unlike relational databases that store data in tables with rows and columns, RDF uses the simplest linguistic structure: subject-predicate-object (like "Larry knows Stuart"). Each element has a unique URI identifier, which permits precise meaning and enables linked data across systems. This graph structure makes it much easier to connect data after the fact compared to navigating tabular structures in relational databases. On top of RDF sits an entire stack of technologies including schema languages, query languages, ontological languages, and constraints languages—everything needed to turn data into actionable knowledge. The goal is inferring or articulating knowledge from RDF-structured data.7. The Future Requires Decoupled Modular Architectures Combining Multiple AI Approaches. The vision for the future involves separation of concerns through microservices-like architectures where different systems handle what they do best. LLMs excel at discovering possibilities and generating lists, while knowledge graphs excel at articulating human-vetted, deterministic versions of that information that systems can reliably use. Every one of Swanson's 300 podcast interviews over ten years ultimately concludes that regardless of technology, success comes down to human beings, their behavior, and the cultural changes needed to implement systems. The assumption that we can simply eliminate people from processes misses that huma...

Arto Minasyan is originally from Armenia. He's a serial entrepreneur, having started 7 companies, selling 4 of them. He used to be into the sciences, having his PhD in Mathematics and Machine Learning. But outside of tech, he's married with 2 kids. He loves to read novels, and in fact writes books himself (mainly his memoirs). He loves to ski, and aligned with his Armenian heritage, he loves to spend time with his big family.Arto and his colleague got breakfast together, and started talking through an idea around clean audio for conferencing and beyond. They built a prototype, and then COVID hit - which made their tool very popular.This is the creation story of Krisp.ai.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiAlcorEquitybeeTerms and conditions: Equitybee executes private financing contracts (PFCs) allowing investors a certain claim to ESO upon liquidation event; Could limit your profits. Funding in not guaranteed. PFCs brokered by EquityBee Securities, member FINRA.Linkshttps://krisp.ai/https://www.linkedin.com/in/artominasyan/Support this podcast at — https://redcircle.com/code-story-insights-from-startup-tech-leaders/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy