Podcasts about Computer science

In this episode, Dave and Jamison answer these questions: I stayed too long at my first company and now my career is ruined? Hi both, long time listener. (Since I graduated university 4 years ago actually and felt I could never find a job but listening to you guys made me feel not like such an outcast in our field.) I graduated in 2022. Didn't really apply around much and almost immediately accepted the full time offer from the company I did my internship with during my degree. And fast forward to middle of 2026… I am still here. I've long stopped growing as an engineer and have actually been stuck on a simple CLI tool for almost 4 years now with little to no cloud/backend/etcetera experience to show in my 5 year career. I don't feel I am desirable in the job market at all due to this and waited way too long to look for a job because I was comfortable and happy. I feel paralyzed (no need to put on your space therapist hats BUT some career advice would be wonderful!) (Also did I mention I am in Canada and want to move to Europe and live the rest of my life there but visa sponsorship with my level of experience is impossible? Maybe that'll be for my next question…) Thanks for all you do, cheers! I have a non-CS engineering degree, and am looking to transition into Software Engineering. I have the option of pursuing a degree with Tuition Reimbursement from my job, but am in a bit of a strange situation deciding which degree. Basically, I've figured that with my current Engineering background I could pursue either a second Bachelor's degree through Universities offering a “Post-Baccalaureate” program in Computer Science, or a Master's degree, with maybe only a slightly longer program to get the Master's as opposed to the Bachelor's. Otherwise the total length/cost of the programs would be roughly the same. I have heard though that it might not be a great idea to go into a Master's program unless you know what specifically you want to study. I am curious what you think would be more “hire-able” between the two options for someone pursuing the career change into Software Engineering?

These sources examine the multifaceted impact of artificial intelligence on the global education landscape and the subsequent workforce. Research from Frontiers in Computer Science highlights a growing digital divide, noting that while AI offers personalized learning, it can also perpetuate cultural and linguistic biases against marginalized communities. Conversely, perspectives from Howard University and the University of New Hampshire frame AI as a critical intellectual partner that enhances doctoral research and shifts faculty roles from traditional lecturers to active facilitators. Economic analysis from Stanford further suggests that AI may actually level the professional playing field by simplifying complex tasks, allowing lower-skilled workers to compete for higher wages. Ultimately, the collection argues that inclusive design and proactive training are essential to ensure AI serves as a tool for equity rather than a driver of further stratification.

In Episode 144, Todd Brun, Professor of Electrical Engineering, Computer Science, and Physics at the University of Southern California, returns to break down where quantum error correction stands today. The team cover the transition from theoretical thresholds to real experimental demonstrations, why decoding latency matters as much as code quality, and the counterintuitive insight at the heart of quantum error correction — that you can measure what went wrong without measuring the data itself. Todd also weighs in on the trade-offs between modalities when it comes to implementing error correction in hardware, and closes with a look at how far the field has come since the early nineties when quantum computing was just an idea.

Scientific Sense ® by Gill Eapen: Prof. Scott Aaronson is professor of Computer Sciences at the University of Texas, Austin. His research interests include the capabilities and limits of quantum computers and Computational complexity theory Please subscribe to this channel:https://www.youtube.com/c/ScientificSense?sub_confirmation=1

In this episode, Kelly Schuster-Paredes speaks with Mahmoud Harding about his work in data science education and the way he thinks about teaching Python, R, and statistics. Mahmoud explains that he is the instructional design director at Data Science for Everyone, where the goal is to make data science available to more students and to connect it to meaningful, real-world contexts. A major part of the conversation focuses on how students learn best through curiosity and project-based work. Mahmoud describes the ADAPT model, including its emphasis on project-based learning and common learning elements, and he argues that students should begin working with their own data early in a course. Kelly and Mahmoud discuss how choosing their own datasets helps students become more engaged, notice mistakes, and ask better questions. The discussion also compares R and Python as tools for data science. Mahmoud explains that R was designed by statisticians for statistical analysis, while Python became popular as a general-purpose language that later grew into a strong data science ecosystem through libraries like NumPy and pandas. He also describes Jupyter Everywhere, a browser-based notebook environment designed to reduce barriers for schools and allow students to use R or Python without complicated setup. Later, the conversation turns to judgment, nuance, and the role of data in learning. Mahmoud argues that students need domain knowledge and human judgment to interpret data responsibly, and that data projects can help them develop those skills. Kelly extends this idea to other subjects, suggesting that books, history, and other classroom materials can also be treated as data for analysis and discussion. The episode closes with Mahmoud sharing ways to connect with him through Data Science for Everyone and with mention of an upcoming Data Science Education K–12 event in Atlanta in February.Special Guest: Mahmoud Harding.

July 16, 2026 ~ Chris Renwick and Lloyd Jackson discuss the UAE's AI government services with Karthik Nandakumar, Associate Professor of Computer Science and Engineering at Michigan State University, on JR Morning. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

What happens when the founder of Mint.com takes on one of healthcare's most broken experiences—patient communication? In this episode of Bright Spots in Healthcare, Eric Glazer sits down with Aaron Patzer, Founder and CEO of Vital, to explore how simplicity, clarity, and human-centered design can drive real impact in healthcare. Drawing from his journey building Mint, Aaron shares why most healthcare technology misses the mark, how better communication improves outcomes and ROI, and what leaders must do to design experiences people actually use. The conversation goes deep on: Why simplifying complexity—not adding more tech—is the real innovation How better patient communication drives measurable ROI for hospitals What healthcare leaders can learn from consumer tech about trust, adoption, and engagement The leadership principles Aaron relies on when innovating inside highly regulated, slow-moving systems If you're a healthcare leader navigating digital transformation, AI investment decisions, or experience strategy, this episode offers clear thinking, hard-earned lessons, and proof that when you make it easier for people to understand what's happening, everything works better.   References: Book Reference - The Design of Everyday Things by Don Norman About Aaron: Aaron Patzer is a renowned entrepreneur, engineer, and innovator best known as the founder of Mint.com, the personal finance platform that revolutionized money management for millions of users. After launching Mint in 2007, Patzer led it to rapid success, growing the user base to over 25 million and overseeing its acquisition by Intuit in 2009. A passionate advocate for user-centered design and simplicity in complex systems, Patzer built Mint.com by combining his technical acumen with a deep understanding of user experience and behavioral finance. He holds degrees in Electrical Engineering, Computer Science, and a Master's from Princeton University. Following Mint, Patzer continued to push boundaries in tech and health innovation. He co-founded Vital, a healthcare startup focused on improving hospital emergency room, urgent care, and inpatient experiences using AI and design thinking. Ranked by KLAS as #1 in patient experience, Vital achieves concrete results: 30–50% fewer LWOBS/AMA, 10–15% higher NPS, stronger HCAHPS scores, reduced ED bounce- back, and 10% lower 30-day readmissions. Designed to integrate seamlessly with existing EHR systems, Vital provides a user-friendly interface that engages patients, resulting in 60%+ adoption rates, 5-10x higher than the competition. View our product overview. Partner with Bright Spots Ventures: If you are interested in speaking with the Bright Spots Ventures team to brainstorm how we can help you grow your business via content and relationships, email hkrish@brightspotsventures.com   About Bright Spots Ventures: Bright Spots Ventures is a healthcare strategy and engagement company that creates content, communities, and connections to accelerate innovation. We help healthcare leaders discover what's working, and how to scale it. By bringing together health plan, hospital, and solution leaders, we facilitate the exchange of ideas that lead to measurable impact. Through our podcast, executive councils, private events, and go-to-market strategy work, we surface and amplify the "bright spots" in healthcare—proven innovations others can learn from and replicate. At our core, we exist to create trusted relationships that make real progress possible. Visit our website at www.brightspotsinhealthcare.com. Visit our website:  www.brightspotsinhealthcare.com. Follow Bright Spots in Healthcare: https://www.linkedin.com/company/shared-purpose-connect/  

What if your teams became 10x more productive — and your business got nothing out of it?Dr. Mik Kersten has the data to prove it's already happening. After studying more than 8,000 value streams across enterprises, he found that only 8% of end-to-end delivery time is teams actually creating value. The rest disappears into planning, approvals, reviews, and coordination. Which means you can multiply team productivity by 2x or 10x with AI, and deliver nothing faster to your customers.Mik started his career as a research scientist at Xerox PARC, completed his PhD in Computer Science, and founded Tasktop, which he led as CEO until its acquisition by Planview in 2022. He's the creator of the Flow Framework and the bestselling author of Project to Product. His new book, Output to Outcome: An Operating Model for the Age of AI, launches July 14, and it argues that the constraint on knowledge work is gone. What's left is your organizational structure. And for most companies, it's the thing standing in the way.In this episode, Mik joins Jessica Neal and co-host Peter Clarke to break down why AI productivity gains aren't showing up in business results, what happens to companies that spend big on tokens without rewiring how they work, and why the future of leadership means every manager becomes a maker again.You'll learn:- Why only 8% of enterprise delivery time is actual value creation — and where the other 92% goes- Why 10x team productivity means nothing if your organization can't absorb it- The four competing structures inside most companies: org chart, value streams, incentives, and architecture- What Netflix got right about aligning technology, teams, and leadership- The "outcome tree": one unified structure replacing the matrix- Why humans should keep reporting to humans — even as agents join teams- How incentives quietly sabotage transformation (and why Mik wrote half a chapter on them)- Why outputs are easier to measure than outcomes — and why that's now a fatal trap- The dark factory thought experiment: what happens when production cost trends toward the price of electricity- Zero bonuses for engineers: what Mik learned from the experiment- Why planning still matters — but on weekly and monthly cadences, not annual- Managers to makers: why the first-line manager role is changing completely- The middle managers whose roles are gone — and the new role that replaces them- Why companies that get this right are hiring more people, not fewerMik's message to leaders: get hands-on with the latest models now. The only way to make AI work for your teams — instead of the other way around — is to lean in.Output to Outcome: An Operating Model for the Age of AI is available now wherever books are sold.Truth Works is hosted by Jessica Neal, former Chief Talent Officer at Netflix.

Artificial intelligence is changing how health coaches and wellness professionals manage their businesses, communicate with clients, and deliver personalized support. In this episode, Cathy Sykora speaks with AI education and workforce transformation leader Ben Tasker about using AI responsibly while keeping human judgment at the center of the coaching relationship. Ben shares practical ways coaches can use AI for client education, call summaries, marketing, lead management, content creation, data analysis, and administrative tasks. He also explains why coaches must review AI-generated information, protect client privacy, obtain appropriate consent, and avoid relying on full automation for complex or high-risk decisions. This conversation offers a balanced look at how health coaches can build AI skills, save time, create new revenue opportunities, and strengthen the human-centered work that makes coaching valuable. In this episode, you'll discover: How AI can personalize client education while keeping the coach involved in reviewing and guiding the information Why AI should be treated as an assistive system rather than a replacement for human expertise, empathy, and common sense Practical ways health coaches can use AI for transcripts, client notes, content creation, marketing, scheduling, and lead follow-up How coaches can experiment with AI through low-risk tasks before using it in more complex client workflows Why consent, privacy, data protection, and responsible AI policies are essential when working with client information How AI upskilling and reskilling can help coaches improve efficiency, expand their services, and create new revenue opportunities Which AI applications may carry greater risks, including unsupervised chatbots, complex scheduling, and automated client decisions Memorable Quotes: "AI doesn't have common sense. It just has prediction information." "Just because you have an AI tool doesn't mean you really have an AI strategy." "You want to engage with it so you're not left behind, but at the same time, you have to understand that there's risks and opportunities with it." Bio: Ben Tasker is a recognized leader in AI education, workforce transformation, and responsible AI adoption. He currently leads a Data & AI Academy focused on upskilling and reskilling 36,000 employees in the public utility sector, ensuring the workforce is AI-ready for the future. He also serves as a Technical Advisor for uCertify, a global leader in workforce certification and reskilling. Previously, Ben was the Dean of AI at Southern New Hampshire University, where he spearheaded Applied AI programs and pioneered a skills institute focused on workforce AI + Human upskilling and reskilling. He also teaches as a part-time faculty member at Northeastern University's Khoury College of Computer Sciences, one of the world's top universities for AI education. Earlier in his career, Ben was a project manager at Northeastern's Experiential AI Institute, creating technical and responsible AI products for companies like Two Sigma and Unum Insurance. He also served at MaineHealth as a Data Scientist, where his integration of AI products enabled predictive diagnostic tools that directly contributed to saving lives. Mentioned in This Episode: Ben Tasker's Website: https://www.bentaskerai.com/ Ben Tasker on Instagram: https://www.instagram.com/bentaskerai/ Ben Tasker on LinkedIn: https://www.linkedin.com/in/bentaskerai/ Links to Resources: Health Coach Group Website: thehealthcoachgroup.com Special Offer: Use code HCC50 to save $50 on the Health Coach Group website Leave a Review: If you enjoyed the podcast, please consider leaving a five-star rating or review on Apple Podcasts.  

Arvind Jain is the Founder & CEO of Glean, the enterprise AI leader valued at $7.2 billion after raising more than $770 million from investors including Kleiner Perkins, DST Global, and more. Before Glean, Arvind co-founded Rubrik, helping build it into one of the world's leading cloud infrastructure companies before its successful IPO. Prior to that, he spent over a decade at Google as a Distinguished Engineer, working across Search, Maps, and YouTube. AGENDA: 00:00 – The Shocking Truth About Frontier AI: 90% Is Already a Commodity 02:04 – Can OpenAI & Anthropic Own Enterprise AI? The Battle for the Workplace Begins 10:18 – Will OpenAI and Anthropic Win the App Layer 18:03 – Microsoft Is the Real Enemy… Not OpenAI? 20:53 – "Where's the ROI?" Why Enterprises Are Starting to Question the AI Hype 26:00 – Will AI Replace Your Job? Harry & Arvind's Heated Clash Over the Future of Work 33:43 – The Billion-Dollar Mistake Every AI Company Is Making on Token Spend 39:20 – The AI Land Grab Is On: Why Founders Must Move Now or Lose Forever 42:20 – China vs America: Who Really Wins the AI Race? 47:20 – Rapid Fire: The Future of Computer Science, Hiring, Fundraising & AI's Biggest Winners  

We're excited to share a special feed drop from The a16z Crypto Show. In the first episode of First Principles: The Scientific Roots of Blockchain Technology, Tim Roughgarden and Ittai Abraham trace the decades of computer science research that laid the foundation for modern blockchains. Long before Bitcoin, researchers were studying one of distributed computing's hardest challenges: how independent machines can reliably agree on a shared state, even when some participants are faulty or malicious. Bitcoin didn't invent that problem, but it introduced a breakthrough solution in a radically different, permissionless setting. The conversation explores Byzantine agreement, state machine replication, proof of work, proof of stake, Tendermint, Casper, DAG-based protocols, and why concepts developed decades ago continue to shape the design of today's fastest and most secure blockchain networks.   Resources: Follow Tim Roughgarden on X: https://x.com/Tim_Roughgarden Follow Ittai Abraham on X: https://x.com/ittaia Follow a16z Crypto on X: https://x.com/a16zcrypto Subscribe to The a16z Crypto Show: https://a16zcrypto.substack.com/subscribe/ 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.

The Roundtable Panel: a daily open discussion of issues in the news and beyond. Today's panelists are Fran Berman, the Stuart Rice Honorary Chair at the University of Massachusetts Amherst's College of Information and Computer Sciences and faculty associate at the Berkman Klein Center for Internet and Society at Harvard University; Theresa Bourgeois, a public policy and communications expert; and Donna Welton, a diplomat in residence at Bard College who retired from the U.S. Foreign Service in 2025 after over 30 years in public service. Her last post was as ambassador to the Southeast Asian country, Timor-Leste.

How do you store a TON of data in a very small package for 250 years? Do you copy it onto a flash drive? Record it onto a voice message? Or, heaven forbid, write it down on a piece of paper? That’s a question that the Library of Congress considered when it put together a time capsule meant to be opened in the year 2251. We don’t know what the world will look like in that year and technology like servers and USB drives may be out of date. They could go the way of the floppy disc or CD. So, to give the time capsule the best chance of being understood by future generations, the Library of Congress turned to an archiving technology that is as old as life itself: DNA. And they did it with the help of a team from the University of Washington. GUEST: Chris Takahashi - Principal Investigator at the Paul G. Allen School of Computer Science & Engineering. RELATED LINKS: With a ‘hello,’ Microsoft and UW demonstrate first fully automated DNA data storage Library Treasures Stored on Synthetic DNA Demonstration of End-to-End Automation of DNA Data Storage Thank you to the supporters of KUOW, you help make this show possible! If you want to help out, go to kuow.org/donate/soundsidenotes Soundside is a production of KUOW in Seattle, a proud member of the NPR Network.See omnystudio.com/listener for privacy information.

Language serves as the vital intersection of cultural identity and technological innovation, yet the rapid rise of AI reveals a significant representation gap for the nearly many million ways the Arab world communicates. Professor Nizar Habash, a computer science professor and director of the CAMEL Lab at NYU Abu Dhabi, explores the historical anxieties surrounding technological shifts, drawing a direct parallel between the 150-year delay of the Arabic printing press and contemporary concerns regarding data bias in large language models. The conversation navigates the inherent challenges of modeling a language characterized by immense dialectal variety and non-standardized orthography, shifting the focus from perceived linguistic complexity to the practical need for bespoke, regional data sets. As the field transitions from rigid, rule-based systems to sophisticated neural models capable of abstract meaning through embeddings, the dialogue underscores the urgency of building localized, open-source tools like JAIS and FAMAR to ensure the Arab world's history and diverse voices are accurately represented in the digital age.   00:00 Introduction 02:15 How AI Models Understand Diverse Arabic Dialects 05:48 Debunking Myths About Arabic's Linguistic Complexity 08:21 The Historical Construction of Modern Standard Arabic 11:00 Impact of Technology on Arabic Script and Printing 15:19 The Journey into Computational Linguistics 17:35 The Evolution of Machine Translation and LLMs 23:51 Explaining Hallucinations in Statistical Language Models 31:14 Cultural Representation and Bias in Image Generation 38:13 Dialect Support and Limitations in Translation Tools 50:02 Camel Lab's Mission for Open-Source Arabic NLP 01:03:42 Descriptive vs. Prescriptive Views of Arabic   Nizar Habash is a Professor of Computer Science at New York University Abu Dhabi (NYUAD), and the director of the Computational Approaches to Modeling Language (CAMeL) Lab. Professor Habash specializes in natural language processing and computational linguistics.  He received his PhD in Computer Science from the University of Maryland College Park in 2003. He has two bachelors degrees, one in Computer Engineering and one in Linguistics and Languages from Old Dominion University. His research includes extensive work on machine translation, morphological analysis, and computational modeling of Arabic and its dialects. Professor Habash has been a principal investigator or co-investigator on over 25 research grants. And he has over 250 publications including a book entitled "Introduction to Arabic Natural Language Processing". Professor Habash is one of the recipients of the King Salman Academy for Arabic Language Award (2022); and he is the recipient of the Antonio Zampolli Prize (2024). His website is www.nizarhabash.com.   Connect with Nizar Habash

NEET (National Eligibility cum Entrance Test) is a high stakes, high pressure exam that can make or mar the careers and fortunes of entire families. At least 14-NEET-linked suicides were reported this year, and the Tamil Nadu government's official position is that NEET should be scrapped. In Part 1 of this series, we looked at whether NEET as a system is aligned with India's social goals. In the second episode, we unpacked NEET's real relationship with merit. And in Part 3, we drill down to the examination itself, and the paper leak that sparked a retest. Guest: Professor Rajeev Kumar, who has taught Computer Science at IIT, Kharagpur and IIT Kanpur, among other places, and has been a whistleblower against malpractices in our higher education system. Host: G Sampath Producer and editor: Jude Weston Learn more about your ad choices. Visit megaphone.fm/adchoices

What does it take to become the first?In this bonus live episode of The Brand is Female, Eva Hartling sits down with Dr. Gina Cody, engineer, entrepreneur, philanthropist, Chancellor of Concordia University, and the first woman in Canada to earn a PhD in Building Engineering.Recorded live at the Gina Cody School of Engineering and Computer Science, this conversation traces Dr. Cody's remarkable journey from arriving in Canada from Iran with just $2,000 to building one of the country's leading engineering firms and becoming one of Canada's most influential champions for women in STEM.But this episode is about much more than career milestones. Dr. Cody reflects on the mentors who changed her life, why kindness is one of the most powerful leadership skills, how she overcame fear and self-doubt, and why being "the only woman in the room" became an advantage rather than a limitation.She also shares her philosophy on leadership, lifelong learning, balancing ambition with family, and the importance of giving back once you've achieved success.Whether you're an engineer, entrepreneur, student, or leader, this conversation offers timeless lessons on courage, resilience, generosity, and building a career with purpose.In this episode, you'll learn:-Why courage isn't the absence of fear—it's acting despite it. -How to turn obstacles into opportunities. -The leadership power of listening, humility, and kindness. -Why women belong at the forefront of engineering and innovation. -How Dr. Cody defines success after a lifetime of achievement.Today's episode is part of a mini-series highlighting the journeys of inspiring women in engineering, presented by Gestion FÉRIQUE and Services d'investissement FÉRIQUE. Visit ferique.com for more! Follow The Brand is Female on Instagram: instagram.com/thebrandisfemale

Andrew Moore, CEO of Lovelace, former head of Google Cloud AI, and former dean of Carnegie Mellon's School of Computer Science, joins the podcast to discuss YottaGraph, a knowledge graph growing by a billion facts a week that serves as a context engine for enterprise AI agents. He explains why fully automatic knowledge graph construction is the only viable path at scale, why entity resolution remains a brutal engineering problem, and how graph theory tricks make million-node queries answerable in under a second.Subscribe to the Gradient Flow Newsletter

Qdrant Roundtable episode: The Current State of Agentic RetrievalJoin the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletterMLOps GPU Guide: https://go.mlops.community/gpuguideBig shout-out to Qdrant for the collaboration!// AbstractAI agents are only as good as the information they can find, retrieve, and remember. In this community roundtable with the Qdrant team, we explored the latest advances in agentic memory, vector search, retrieval systems, and production AI architectures.As AI agents move beyond simple chatbots into systems that can reason across large amounts of information, retrieval is becoming one of the most important layers in the AI stack. The discussion covered the real-world challenges of building agents that remember what matters, forget what doesn't, and consistently retrieve the right context at the right time.If you're building AI agents, RAG systems, or production AI applications, this conversation offers practical insights into where retrieval is headed and what it takes to build reliable, scalable agentic systems.// BioEwa SzyszkaEwa is a Developer Relations professional based in San Francisco with a background in Computer Science and Hardware Engineering, passionate about bridging the gap between technology and the developer community. She holds a BSc in Computer Science and an MSc in Electronics, bringing a strong blend of deep technical foundations and communication skills to her work.Dylan CouzonDylan is based in New York City, and he helps developers build better AI applications. He is passionate about AI, programming, open source, and robotics, and enjoys sharing what he's building and learning along the way.Neil KanungoNeil is an experienced professional with expertise in data science, developer relations, and product growth. Currently serving as the Head of Developer Relations at Qdrant, Neil previously held the position of VP of Product Led Growth & Developer Relations at KX, where significant increases in product registration and user activation were achieved. At TIBCO, Neil managed a team focused on enhancing the adoption of TIBCO Spotfire through various initiatives, including tutorial videos and live webinars. With a strong technical background, Neil has developed innovative solutions in analytics, machine learning, and data visualization across multiple roles, including Engineering Data Analyst and Asset Integrity Engineer at Enterprise Products. Neil holds a Bachelor of Science in Radiation Physics from The University of Texas at Austin, a Master of Science in Mechanical Engineering from Texas Tech University, and is pursuing a Master in Applied Data Science from the University of Michigan.Evgeniya SukhodolskayaDeveloper Relations at Qdrant with 8 years of IT experience across software engineering, machine learning, and technical management, and 4 years in Developer Relations. Holds a Master's in Machine Learning, Data Analytics, and Data Engineering. Passionate about NLP, data-centric AI, and the role of vector search in advancing AI technologies.Andrei CristeaAndrei is a Berlin-based Developer Relations Engineer at Qdrant, a prominent open-source vector database. With a Master's degree in Artificial Intelligence from TU Munich, his expertise bridges AI, data infrastructure, and knowledge engineering.Hosted by Demetrios// Related LinksWebsite: https://qdrant.tech/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]

Our June 2 webinar with Code in Motion by SPARKS was so vital that we adapted it into a podcast episode to share their inspiring work with our entire community. In this episode, the project's leaders and coaches discuss how they are reimagining computer science education for students experiencing housing insecurity through community-led, dignified pathways to success. Access the full podcast transcript at: tinyurl.com/CodeInMotion 

What if optimizing for AI output is actually slowing your company down? When code becomes nearly free to produce, the organizations still measuring productivity by output are solving the wrong problem.In this episode, Mik Kersten, author of “Project to Product” and the forthcoming “Output to Outcome,” shares why the real challenge of the AI era isn't generating more code — it's building organizations that can turn that output into customer and business value. Drawing on Carlota Perez's model of technological revolutions and the theory of constraints, Mik explains how AI has removed the output bottleneck that software organizations were built around, and where the new constraints now live.He introduces three core models from the book — the outcome loop, the product operating model, and the outcome tree — as a framework for adapting how organizations plan, fund, and deliver value. Mik also addresses one of the most pressing decisions leaders face today: whether to cut headcount based on AI productivity gains, and why doing so without outcome visibility is a dangerous bet. The conversation covers how organizational structure, decision-making accountability, and leadership roles all need to shift — not just development practices.Timestamps:(00:00:00) Trailer & Intro(00:02:40) What Makes Output to Outcome Different From Project to Product?(00:05:02) Why Did Mik Write Every Word of This Book Without AI?(00:08:18) How Do the AI Prompts at the End of Each Chapter Work?(00:11:53) What Happens to Organizations When AI Makes Software Output 10 to 100 Times Cheaper?(00:15:03) How Do Past Technological Revolutions Help Us Understand the AI Era?(00:19:25) Is the Traditional Software Developer Role Gone for Good?(00:23:30) Why Do Some Companies Experience an AI Productivity Paradox?(00:27:47) What Does “Outcome” Mean in Outcome Management?(00:31:50) Has the Product Operating Model Finally Become the Industry Norm?(00:34:24) How Do You Apply the Cynefin Framework to Your Organization?(00:37:18) Why Should AI Augment Human Decision Making in Complex Domains?(00:40:52) Why Are AI-Driven Layoffs a Risky Bet Without Outcome Visibility?(00:43:32) How Can Leaders Increase the Feedback Loop for Strategy and Budgeting?(00:46:07) What Is the Optimal Organizational Structure for an Outcome Management Model?(00:49:50) How Can We Apply Architectural Modularity to Organizational Design?(00:53:17) What Are the Seven Shifts in the Output to Outcome Model?(00:55:10) Will AI Make Middle Management Obsolete?(01:00:55) 3 Tech Lead Wisdom_____Mik Kersten's BioDr. Mik Kersten is an independent technology strategist and creator of the Flow Framework, best known for his bestselling book Project to Product. He founded Tasktop and led it as CEO until its acquisition by Planview in 2022.Mik began his career at Xerox PARC, where his team created the first aspect-oriented programming language. He then earned his PhD in Computer Science at UBC, pioneering the integration of software development and collaboration tools — work that laid the foundation for Tasktop and the field of Value Stream Management.Today, he helps leaders shift from output-driven to outcome-driven operating models, enabling organizations to harness AI in a human-centric way.Follow Mik:LinkedIn – linkedin.com/in/mikkerstenSubstack – mikkersten.substack.com Preorder Output to Outcome - https://a.co/d/0aPlI2IFBook's Website – outputtooutcome.orgLike this episode?Show notes & transcript: techleadjournal.dev/episodes/262.Follow @techleadjournal on LinkedIn and Instagram.Buy me a coffee or become a patron.

MIT has a new podcast. Announcing Building 32, from MIT CSAIL Alliances. Behind every technological breakthrough is a story. From email to the fax machine to the Roomba and even OkCupid, innovations that shape our daily lives trace back to MIT's Computer Science and Artificial Intelligence Laboratory, or MIT CSAIL. And technology that is years ahead of the market is being developed in CSAIL labs now. Tune into Building 32 from MIT CSAIL Alliances, hosted by Karen Given, to hear the stories of CSAIL. Each episode features conversations with pioneers who helped define the digital age or researchers shaping tomorrow's AI, robotics, computing, and beyond. Subscribe now. The first episode launches July 13, 2026. Learn more: csail.mit.edu/podcast Connect with CSAIL Alliances: On our site: cap.csail.mit.edu/about-us/meet-our-team On LinkedIn: linkedin.com/company/mit-csail #MIT #CSAIL #ArtificialIntelligence #Robotics #ComputerScience #TechPodcast #Innovation #FutureOfTechnology

Summer is officially underway, but in Russian-occupied Crimea, residents are facing fuel shortages, rolling blackouts and cancelled summer camps. It's all part of a new phase in Russia's war, as Ukraine expands its campaign into the invader's heartland. Now the Wall Street Journal reports the Kremlin is pressuring Belarus to open another front as Russia struggles on the battlefield. Joining the show to discuss this is WSJ chief European political correspondent Bojan Pancevski, whose  new book, "The Nord Stream Conspiracy," reveals the inside story about one of the most consequential acts of sabotage in recent history, and the secret team most likely behind it.  Also on today's show: Wafa Mustafa & Waad Al-Kateab, co-directors, "Maybe Tomorrow"; Cal Newport, Professor of Computer Science, Georgetown University / Host, "Deep Questions" podcast    Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode, Ray Cochrane unpacks how two colliding black holes revealed a whirlpool in spacetime, a direct detection of frame dragging hidden in the cleanest gravitational-wave signal ever recorded. Additional stories cover the James Webb Space Telescope, counting 16.5 million stars in the Cigar Galaxy, SpaceX rolling out Starship V3, deadly back-to-back earthquakes in Venezuela, GitHub fighting a California law that could break open source, and Meta engineering a battery narrow enough to live in a pair of glasses. – Want to start a podcast? It’s easy to get started! Sign-up at Blubrry – Thinking of buying a Starlink? Use my link to support the show. Subscribe to the Newsletter. Email Ray if you want to get in touch! Like and Follow Geek News Central’s Facebook Page. Support my Show Sponsor: Best Godaddy Promo Codes Get 1Password Full Summary Cochrane opens with a personal update before the night’s lead story. He recently graduated with a Bachelor of Science in Computer Science from Portland State University, celebrated with family in town, and launched a new site at rayc.world. That site links to a final-project study he built on collaborative filtering using podcasting data, hosted at cohort.rayc.world and drawn from OP3 analytics. He also plans to return to the show’s classic twice-weekly cadence on Mondays and Thursdays. From there, he goes deep on a new black hole discovery, then pivots through space, earth science, climate, biotech, open source, cloud infrastructure, and consumer hardware. Colliding Black Holes Reveal a Whirlpool in Spacetime Two black holes spiraled together, merged, and sent a gravitational wave rippling across the universe. Researcher Neil Lu and colleagues at the Australian National University found the fingerprint of frame dragging buried in GW250114, the cleanest signal LIGO has ever recorded. Frame dragging means a spinning black hole drags spacetime around with it, like a spoon turning in honey, except the honey is reality itself. Remarkably, the wave changed the distance between your nose and your ear as it passed, by far less than the width of a single atom. Sponsor: GoDaddy Economy hosting is $6.99/month, WordPress hosting is $12.99/month, and domains are $11.99. Website builder trial available. Use codes at geeknewscentral.com/godaddy to support the show. Webb Counts the Stars in the Cigar Galaxy NASA released a striking new James Webb Space Telescope view of Messier 82, the edge-on galaxy nicknamed the Cigar Galaxy. Because Webb sees in infrared, it peers straight through the dust that normally hides the galaxy’s interior. Combined with archival Hubble data, the image resolves roughly 16.5 million individual stars. M82 is a starburst galaxy, meaning it forms stars at a furious rate, a frenzy likely triggered when it merged with a neighbor. SpaceX Rolls Out Starship V3 SpaceX officially introduced Starship V3, the third generation of the largest rocket ever built. The vehicle now flies on the Raptor 3 engine, pushing liftoff thrust to around 20 million pounds and making it the most powerful rocket ever flown. More importantly, V3 is designed to carry over 100 metric tons to low Earth orbit while staying fully reusable, roughly triple the previous version. SpaceX also added in-orbit refueling hardware, the capability that finally makes operational Moon and Mars missions realistic. The Asteroid Barrage That Kept Earth From Forming Continents A team led by Curtin University and the Queensland University of Technology argues that relentless asteroid impacts shaped the very young Earth. During the Hadean, more than four billion years ago, the planet was struck far more often than it is today. Each impact dumped heat deep into the interior, repeatedly melting and reworking the crust. Consequently, stable continents formed much later than calmer models assumed, painting a picture of a hotter, weaker, more chaotic early Earth. Back-to-Back Earthquakes Devastate Northern Venezuela Northern Venezuela was struck by two major earthquakes on June 24, a magnitude 7.2 foreshock followed by a magnitude 7.5 mainshock. Both hit only about six miles underground, so the shallow shaking delivered its full force at the surface. Tragically, at least 164 people died, and the region sits along the tangled boundary where the Caribbean and South American plates grind past each other. These were the largest quakes to hit the area since a magnitude 7.7 event near Caracas in 1900. The ‘Guerrilla Solar’ Era Has Arrived A quiet energy shift, nicknamed “guerrilla solar,” is spreading across Europe. These small plug-in panels deliver power to a home’s wiring via a standard wall outlet, with no electrician or permit required. Germany now counts roughly a million of these systems. However, the U.S. payoff remains modest, with savings estimates of around $15 per month against a $500 to $1,500 setup cost. Why a Broken-Up Forest Stores Less Carbon Researchers quantified what foresters long suspected: an intact forest stores far more carbon than the same acreage split into fragments. A hectare inside a large, continuous forest proved about 38 percent more productive than an isolated one. The culprit is edge effects, the extra wind, heat, and direct sun that stress trees at a forest’s boundary. Because a large forest maintains a large protected core while fragments are nearly all edge, planting trees together matters for carbon storage. Edited Human Embryos Reveal a Surprise Researchers used base editing, a precise cousin of CRISPR that rewrites a single DNA letter without cutting the strand, in human embryos. They discovered that a protein called NANOG plays a role in early human development that it does not play in mice. In humans, switching it off still let cells form that seed the placenta and yolk sac. The finding argues that understanding human development requires studying human embryos directly, which reignites a thorny ethical debate. GitHub Fights a California Law That Could Break Open Source GitHub joined Black Forest Labs, Hugging Face, and Mozilla to push for fixes to California’s AI Transparency Act. As written, the bill could force revocation of an open-source license when a downstream user fails to meet certain obligations, which clashes with the permanent, irrevocable promise of open source. Cochrane pointed to curl and its longtime maintainer, Daniel Stenberg, warning that the rule could destabilize the supply chain on which the whole tech world runs. Instead, the coalition points to the EU’s AI Act transparency code as a saner model. Rust Opens Its Maintainers Fund The Rust Foundation launched a Maintainers Fund to pay the people who keep the language’s ecosystem healthy. Backed by RFC 3931, it establishes a funding team and a new Maintainer-in-Residence program for the often thankless work on the compiler, standard library, Cargo, and Clippy. Individuals can donate through GitHub Sponsors, while companies can sponsor there or contact the foundation directly. Cochrane urged any business that depends on open source to invest in the projects it actually uses. AWS Gives Lambda Its Own Isolated Sandboxes AWS introduced MicroVMs inside Lambda, its serverless platform. Each session runs in a dedicated micro virtual machine with no shared kernel and up to eight hours of total runtime. The feature exists for the AI era, in which applications increasingly run code written by an AI agent rather than by the developer. Use cases include AI coding assistants, data analytics platforms, vulnerability scanners, and game servers running user-supplied scripts. Meta Engineers a Battery Narrow Enough for Glasses Meta built custom steel-can battery cells as narrow as seven millimeters to fit the temple arms of smart glasses like the Ray-Ban Meta and Oakley Meta Vanguards. These cells power cameras, speakers, and AI features in a space most engineers would call impossible. To prevent brownouts, Meta swapped wound electrodes for precisely die-cut stacked layers that lower electrical resistance. Now the company is spreading the technology across multiple vendors and eyeing other wearables. Polestar Gets Locked Out of the US Market Starting in 2027, Polestar will not be able to sell its new models in the United States. A federal Connected Vehicle Rule bars cars containing certain Chinese or Russian software or hardware on national security grounds. The painful irony is that Polestar moved production of the Polestar 3 to South Carolina specifically to dodge tariffs on Chinese-built EVs. Because the rule targets the technology’s origin rather than its assembly location, the company is shut out anyway. Retroid’s Pocket Nova Packs Serious Power for $229 Retroid returned with a new retro handheld, the Pocket Nova, starting at $229 with a step-up model around $269. It features a 4.5-inch AMOLED screen in a 4:3 aspect ratio, a shape well suited to classic games. On paper, it should handle GameCube- and PlayStation 2-era titles, though that remains an early expectation rather than a benchmarked promise. Retroid has earned a strong reputation for high-quality, genuinely portable consoles. Cochrane signs off with the usual ecosystem mentions: GNC Insider at geeknewscentral.com/insider, the show newsletter, email at geeknews@gmail.com, and modern podcast app recommendations at podcastapps.com. The post Colliding Black Holes Reveal a Whirlpool in Spacetime #1866 appeared first on Geek News Central.

Few topics generate more debate than elections. But long before voters head to the polls, important decisions have already been made about how communities are grouped into districts and how representation is structured. While redistricting is often discussed as a political issue, it's also a fascinating operations research problem – one involving competing objectives and complex constraints such as geography, population, representation, and legal requirements, as well as competing definitions of fairness. My guest today, Ian Ludden, Assistant Professor of Computer Science and Software Engineering at Rose-Hulman Institute of Technology, will share how computational methods and OR/MS are helping researchers evaluate district maps and better understand the choices that shape our democracy. We'll explore questions of fairness, representation, and how data-driven approaches can help us better understand one of the most consequential – and often controversial – processes in American democracy.

Before blockchains could reach consensus, Leslie Lamport had to define what agreement even meant when computers fail, lie, or disappear.  In this episode of First Principles: The Scientific Roots of Blockchain Technology, Turing Award-winning computer scientist Leslie Lamport joins Tim Roughgarden Head of Research at a16z crypto and Professor of Computer Science at Columbia University, and a16z crypto Research Partner Ittai Abraham to trace the ideas that helped define modern distributed computing.  Lamport's work formalized some of the field's deepest questions: how to reason about concurrent systems, how distributed systems can agree despite failures, and how to prove that protocols do what they are supposed to do. His work on logical clocks, state machine replication, the Byzantine Generals problem, and Paxos has shaped everything from cloud infrastructure to the consensus protocols underlying modern blockchains.  The conversation begins with Lamport's early work on concurrency and the origins of the Byzantine Generals Problem, and then turns to fault tolerance: what happens when machines crash, behave unpredictably, or even act maliciously? We also cover the feedback loop between theory and practice, the long arc of fundamental research, and how blockchains are inheriting and extending decades of distributed systems work.  Highlights  00:00 – Intro: The problem every blockchain is built to solve  02:52 – Why concurrent systems are surprisingly tricky  04:40 – The origins of the bakery algorithm  07:37 – What does it mean for a protocol to be “correct”?  12:03 – The origins of the Byzantine Generals problem — and what happens when some computers fail  17:49 – How Paxos emerged from an attempted impossibility proof  23:47 – Why theory and practice need each other  33:48 – Government funding, DARPA, and the long arc of foundational research  About First Principles  First Principles is a special limited series from a16z crypto about the scientific roots of modern computing — especially blockchains — told through rare conversations with the pioneers who helped shape the foundational ideas behind distributed systems, consensus protocols, economics, mechanism design, cryptography, zero knowledge, and more.  People often tell the story of the Bitcoin whitepaper as if it appeared out of nowhere. But the ideas behind Bitcoin — and blockchains more broadly — come from decades of computer science, economics, mathematics, and cryptography. First Principles is a guide to that lineage, as told by the people who helped build it.  Hear more from:  Tim Roughgarden: https://twitter.com/Tim_Roughgarden  Ittai Abraham: https://twitter.com/ittaia  Follow a16z crypto:  X: https://twitter.com/a16zcrypto  LinkedIn: https://www.linkedin.com/showcase/a16zcrypto/posts/  YouTube: https://www.youtube.com/@a16zcrypto  Substack: https://a16zcrypto.substack.com/subscribe/  ***  As always, none of the following should be taken as investment, business, legal, or tax advice. Please see a16z.com/disclosures for more important information, including a link to a list of our investments. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Are we on the cusp of a new era of robotics? How is AI enabling machines to perform more complex tasks than ever before? And how will these overlapping technologies change the lives of ordinary working people?In this episode, Dr Henrik Christensen, renowned roboticist and Professor of Computer Science, is joined by Axel Belorde, Head of Business Development EMEA & Asia (Indexes) at TMX VettaFi, to separate fact from fiction.This podcast was recorded on 22 June 2026 and was hosted by Matthew Kemp, Wealth Management Sales Manager at L&G.Securities mentioned for illustrative purposes only. Reference to a particular security is on a historic basis and does not mean that the security is currently held or will be held within an L&G portfolio. The above information does not constitute a recommendation to buy or sell any security. Assumptions, opinions, and estimates are provided for illustrative purposes only. There is no guarantee that any forecasts made will come to pass.

Robert Vanderbei is a Professor in the Department of Operations Research and Financial Engineering at Princeton University. From 2005 to 2012, he was chair of the department. In addition, he holds courtesy appointments in the Departments of Mathematics, Astrophysics, Computer Science, and Mechanical and Aerospace Engineering. He is also a member of the Program in Applied and Computational Mathematics, is a founding member of the Bendheim Center for Finance, and a former Director of the Engineering and Management Systems Program. Beyond Princeton, he is a Fellow of the American Mathematical Society (AMS), the Society for Applied and Industrial Mathematics (SIAM) and the Institute for Operations Research and the Management Sciences (INFORMS). Within INFORMS, he has served as President of the Optimization Society and the Computing Society and is the 2017 winner of the Khachiyan Prize for his work in optimization. He also serves on the Advisory Board for the journal Mathematical Programming Computation. He has degrees in Chemistry (BS), Operations Research and Statistics (MS), and Applied Mathematics (MS, PhD). After receiving his PhD from Cornell (1981), he was an NSF postdoc at the Courant Institute for Mathematical Sciences (NYU) for one year, then a lecturer in the Mathematics Department at the University of Illinois-Urbana/Champaign for two years before joining Bell Labs in 1984. At Bell Labs he made fundamental contributions to the field of optimization and holds three patents for his inventions. In 1990, he left Bell Labs to join Princeton University where he has been since. In addition to hundreds of research papers, he has written four books: (i) a textbook entitled Linear Programming: Foundations and Extensions now in its fifth edition and published by Springer, (ii) Welcome To The Universe in 3D, an astronomy book written jointly with Neil deGrasse Tyson, J. Richard Gott and Michael Strauss and published by Princeton University Press, (iii) Sizing Up The Universe, an introductory astronomy book written jointly with J. Richard Gott and published by National Geographic, and (iv) Real and Convex Analysis, a textbook written jointly with Erhan Cinlar and published by Springer.

What happens when a software company building AI tools for HR teams uses those same tools to transform itself? Josh McKenzie, Chief Technology Officer at ELMO Software Group, shares how his team rebuilt their entire software development lifecycle around AI agents and redrew the boundaries of every engineering role. He breaks down how to lead that shift without losing people's trust, why domain expertise is the real SaaS moat, and how the right analytics partner unlocks decisions HR teams have never been able to make before. Key Moments: The SaaS Moat: What AI Can't Erode (06:37): Josh argues SaaS value runs deeper than software. Accountability, compliance, and domain expertise keep purpose-built platforms irreplaceable. How ELMO's AI Journey Started (10:23): ELMO started by mapping every role against AI impact. Turning that lens on their own engineering team set the full transformation in motion. Why ELMO Chose ThoughtSpot Over Building Its Own Analytics (18:42): A homegrown tool requiring too much user expertise led ELMO to look elsewhere. ThoughtSpot Spotter and natural language capabilities closed the gap. Why HR Teams Are the Most Underserved (20:21): Payroll here, benchmarking data there, performance data somewhere else. HR teams have been drowning in spreadsheet hell for years. Josh explains how AI finally closes that gap. From Engineer to CTO: Build a Team of Complements (24:17): Josh reflects on the mindset shift that defined his path to the C-suite. Great leadership means building a team whose strengths cover your blind spots. Key Quotes: “ ThoughtSpot was particularly interesting for us… The big thing for us was the Spotter product. Allowing users to bridge that data analyst gap was really important. So, that product has yielded really, really great results for us.” - Josh McKenzie “I think it's really important that we instill a culture where it's okay to fail, and it's okay to make a mistake. You want to be vocal about your mistakes so others don't repeat the same mistake.” - Josh McKenzie “My belief is you want to focus on your secret sauce. So, what is the thing that makes your business super successful? And for us, that's where we came to look at ThoughtSpot. It has a really nice visual user interface and allows you to create some great dashboards.” - Josh McKenzie Mentions Hiring and Onboarding Taking Longer Despite Widespread AI Adoption, New Australian Research Finds The 5 Levels of AI Coding (Why Most of You Won't Make It Past Level 2) WireGuard: Next Generation Kernel Network Tunnel | Jason A. Donenfeld Guest Bio As the Chief Technology Officer, Josh McKenzie is responsible for both technical strategy and delivery (build, release and operation) of the ELMO product suite. Josh has a proven track record of successfully leading technology teams and implementing transformative strategies that enhance efficiency, drive growth, and elevate overall technological capabilities. Josh has 20 years of experience in technology, primarily in FinTech. Before joining ELMO in 2024, Josh held executive and senior positions at Lendi Group, OFX, ASX and Westpac. Josh holds a Bachelor of Computer Science from the University of Newcastle and an MBA from the University of Sydney. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

In this episode of 5 O'Clock Apron Podcast, Claire drives to Oxford to cook with the Professor of Computer Science and Head of the Department of Computer Science at the University of Oxford, Michael Wooldridge. Michael's field of work has been in Artificial Intelligence (AI) since 1989, a landscape which has seen wide-reaching change. Michael's Wikipedia page, and in particular, the awards and honours section is extensive and hugely impressive. He has written over 350 scientific papers and contributed to many academic books, and his most charming, for the layperson, is the bite-sized Ladybird Expert Book on Artificial Intelligence first published by Penguin Random House in 2018.   As with every episode, Claire knocks on the front door of Michael's house having never met or indeed cooked in Michael's kitchen before. Michael is a bean enthusiast, and to keep within a sensible timeframe, but still wanting to cook with dried beans from scratch, has a huge pot of just-cooked black turtle beans ready and waiting on the hob. Together Michael and Claire cook Michael's favourite weeknight black bean chilli, a dish he regularly cooks at home for his wife and two grown up children, the question posed throughout the recording by Michael is, “How hot should we go?” More chilli is generally the answer, with some additional extra spicy seasoning that Michael is a fan of.    With the black beans bubbling, Claire quizzes Michael on the future of big tech, on whether robots cleaning our houses and loading our dishwashers will happen any time soon, will AI help with the future of food and farming and food insecurity, what is easier to program: driverless cars or grandmaster chess players? With the potential of AI a near constant topic in the news these days, it is with trepidation Claire considers the future of the workforce as we know it, only to be told by Michael “not to worry, the robots aren't coming to get us, just yet!” Cooking with Michael Wooldridge in this episode of 5 O'Clock Apron Podcast is a lesson in reassurance. With anxiety levels in society seen to be generally on the up, and for some, at a tipping point, cooking something delicious for dinner, whatever your line of work, is an opportunity for some much-needed calm and - most important of all - something tasty to eat on the table come dinnertime.      Michael's Black Bean Chilli Recipe  Serves 4 Ingredients;  400g dried turtle beans (you can pre-soak the beans in cold water for an hour or two, or overnight, but Michael thinks this is unnecessary, and his beans were, once cooked, delicious) 1 400g tin of chopped tomatoes  1 whole red chilli 1 large red onion, peeled and finely diced  150g diced chorizo 2 tbsp of olive oil 2 - 3 cloves garlic, peeled and finely chopped  1 tbsp smoked paprika  2 tsp ground cumin 1 tsp dried oregano, or more to taste  Dried chilli flakes, to taste  Jerk seasoning, Michael used Dunns River Jerk Seasoning, to taste  The juice of 1 lime Small bunch of coriander, stalks finely chopped, leaves roughly chopped  Method; Put the beans in a large saucepan and cover with plenty of water, bring to the boil, skim off any frothy residue, reduce the heat to a simmer and cook for around 1 – 1 ½ hours. Keep an eye on the water levels, top up with more water, if necessary, the beans should be fully submerged, at all times. Add the tin of the tomatoes and the whole chilli and continue cooking until the beans are fully cooked through and the sauce is thickened and creamy, not too soupy, just right. Put to one side. In a frying pan, add the olive oil and the onions and fry over a moderate heat for around 5 minutes to soften, add the diced chorizo and the garlic and fry for a further 3 - 4 minutes, until the fat from the chorizo begins to exude in the pan.  Add the ground spices and the oregano and cook for 1 minute more.  When the beans are a good consistency in the pan, thick and creamy, add salt to taste and the chorizo, spices and onion mix in the pan. Add the finely chopped coriander stalks and stir to combine and keep warm. Check the seasoning on the beans, adding salt and more chilli, to taste, if necessary, then add the lime juice and the chopped coriander leaves to serve.      Learn more about your ad choices. Visit podcastchoices.com/adchoices

Barry O'Sullivan, Professor of Computer Science at University College Cork, reacts to a warning from security experts that AI models that could take down governments are months away.

Scientific Sense ® by Gill Eapen: Prof. Charles Yang is Professor of Linguistics and Computer Science and Director of the Program in Cognitive Science at the University of Pennsylvania. His research interests include Language and Communication, Numerical Cognition, Language acquisition and change; Morphology and the mental lexicon, Computational linguistics and The evolution of language and cognition.Please subscribe to this channel:https://www.youtube.com/c/ScientificSense?sub_confirmation=1

What can small language models teach us that the largest AI models cannot? Kelly and Julian are joined by Microsoft Cloud Advocate Gwyneth Peña-Sigüenza to explore why working with small language models (SLMs) may be one of the best ways to understand AI. Rather than relying on increasingly capable models that hide complexity, Gwyneth argues that constraints build stronger fundamentals. From prompt engineering and context management to deployment and security, SLMs force learners to think more carefully about how AI actually works. The conversation extends beyond AI models into learning itself. Gwyneth shares her self-taught journey from growing up on a remote farm in Ecuador with limited internet access to becoming a Microsoft Cloud Advocate and creator of the Learn to Cloud platform. Along the way, the group discusses productive struggle, mentorship, cloud engineering, Python, security, and what educators should prioritize as AI becomes part of every student's learning experience. The episode closes with a thoughtful discussion about AI dependency, judgment, and whether we would actually flip the switch and turn AI off if given the choice. Show Notes Wins of the Week Gwyneth celebrates the New York Knicks reaching the NBA Finals after more than 50 years. Julian shares that he has accepted a new role as a Fractional CTO. Kelly reflects on taking her first real vacation in over a year—and how stepping away from work sparked unexpected ideas. Small Language Models Why SLMs are valuable teaching tools Learning prompt engineering through constraints Running models locally on everyday hardware When local AI makes sense for classrooms Understanding tokens, context windows, and model limitations Why bigger models can sometimes hide important lessons Learning Through Constraints Learning to drive in an old manual pickup truck as a metaphor for learning AI fundamentals Why difficult learning experiences often create lasting understanding Building strong habits before relying on more capable tools Consistency versus constantly chasing the newest resource Self-Taught Learning Growing up without reliable internet in rural Ecuador Downloading YouTube playlists to learn programming offline Developing discipline through limited access The value of repetition and focused practice Why mentorship accelerates learning Python Journey Transitioning from cloud engineering to Python advocacy Learning Python beyond scripting Discovering what "Pythonic" really means Wrestling with list comprehensions and other advanced syntax Favorite learning resources: Fluent Python Effective Python Learn to Cloud Building an open-source cloud engineering curriculum Hands-on labs and automated verification AI-assisted assessment Supporting self-taught learners around the world Creating accessible technical education Cloud, AI, and Security Deploying AI applications to the cloud Containers, virtual machines, and serverless deployments Why operations and security deserve more classroom attention Introducing secure development practices early The importance of authentication, secrets management, and responsible deployment Teaching in the AI Era Helping students understand how AI works instead of simply using it Why productive struggle still matters The changing role of educators Balancing AI assistance with independent thinking Preparing students for a future where AI is always available Final Thoughts AI dependency versus capability Judgment as the skill that matters most Human connection in an AI-driven world Would we actually turn AI off? Finding balance between technological progress and intentional learning

Bitcoin often gets credited with inventing trustless consensus. It didn't.  The problem was named decades earlier — in the world of distributed computing — and researchers spent years studying how machines could reach agreement even when some participants were faulty, adversarial, or corrupt. What Bitcoin did was something different: It solved a classic Byzantine agreement problem in a radically new, permissionless setting. And it took the research world years to fully recognize what Satoshi had done. In this episode of First Principles, a16z crypto Head of Research and Columbia professor Tim Roughgarden is joined by a16z crypto research partner Ittai Abraham — one of the world's leading researchers in Byzantine agreement and consensus protocols, a founding member of VMware's blockchain project, and founder of the technical blog Decentralized Thoughts — to unpack the scientific roots of blockchain consensus.  Together, Tim and Ittai trace the line from classic distributed systems research to Bitcoin, proof-of-stake, Tendermint, Casper, DAG-based protocols, Solana's Alpenglow, and the modern race for higher throughput and lower latency. Along the way, they explain why concepts like Byzantine fault tolerance, state machine replication, safety, liveness, and partial synchrony are not just academic abstractions — they are the language and design principles behind today's blockchain protocols.  This conversation kicks off First Principles: The Scientific Roots of Blockchain Technology — a special, limited series from a16z crypto on the scientific ideas behind modern computing — especially blockchains — told through conversations with the pioneers who helped create them, including Barbara Liskov, Leslie Lamport, and more. Hosted by Tim Roughgarden, the series explores the foundational concepts behind distributed systems and consensus protocols; economics, mechanism and market design; and cryptography, from digital signatures to zero knowledge. People often tell the story of the Bitcoin whitepaper as if it appeared out of nowhere.  But the ideas behind Bitcoin — and behind blockchains more broadly — come from decades of computer science, economics, mathematics, and cryptography. First Principles is a guide to that lineage, told by the people who helped build it.  Highlights  00:00 Introduction to First Principles: The Scientific Roots of Blockchain Technology  00:56 Why consensus matters for blockchains  02:30 Byzantine agreement: The old computer science problem Bitcoin made practical  04:34 Blockchains as a shared system of record: State machine replication and blockchain state  06:41 How two research worlds — distributed computing and crypto — began to converge  07:49 Proof of work vs. proof of stake  09:27 Why Ethereum's move to proof-of-stake took years  11:08 When crypto rediscovered decades of distributed systems research  11:50 Why BFT became practical 12:49 Throughput, latency, and modern consensus design  14:05 DAG-based protocols and faster blockchains  15:25 Peace time vs. war time: why modern blockchains need two modes  16:47 Theory, practice, and the future of blockchain research    Follow:  Tim Roughgarden: https://twitter.com/Tim_Roughgarden  Ittai Abraham: https://twitter.com/ittaia  Follow a16z crypto:  X: https://twitter.com/a16zcrypto  LinkedIn: https://www.linkedin.com/showcase/a16zcrypto/posts/  YouTube: https://www.youtube.com/@a16zcrypto  Substack: https://a16zcrypto.substack.com/subscribe/  **  As always, none of the following should be taken as investment, business, legal, or tax advice. Please see a16z.com/disclosures for more important information, including a link to a list of our investments. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

No Driver, No Problem: Inside The Rise Of Waymo Driverless cars are no longer a futuristic experiment but are already picking up passengers in cities across the country. We look at how the fast expanding rideshare company Waymo works, why some people trust it more than human drivers and the questions that remain as autonomous vehicles become part of everyday life. Guests:  Grayson Brulte, Founder, The Road to Autonomy & Co-Founder, Autonomy AI Ashim Bose, Professor of Artificial Intelligence & Product Management, University of Texas at Dallas  Linktr.ee | Apple Podcasts | YouTube | SpotifyFacebook: @ViewpointsOnlineX: @viewpointsradioInstagram: @viewpointsradioFull ArchiveContact UsAffiliates & National Syndication Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

After Miranda: One Mother's Journey Living With Loss After the sudden death of her daughter, journalist Danielle Crittenden found herself questioning nearly everything she thought she knew about grief. We explore what loss and grief look like when it doesn't follow any sort of timeline.   Guest: Danielle Crittenden, Journalist & Author, Dispatches from Grief: A Mother's Journey Through the Unthinkable   No Driver, No Problem: Inside The Rise Of Waymo Driverless cars are no longer a futuristic experiment but are already picking up passengers in cities across the country. We look at how the fast expanding rideshare company Waymo works, why some people trust it more than human drivers and the questions that remain as autonomous vehicles become part of everyday life. Guests:  Grayson Brulte, Founder, The Road to Autonomy & Co-Founder, Autonomy AI Ashim Bose, Professor of Artificial Intelligence & Product Management, University of Texas at Dallas Linktr.ee | Apple Podcasts | YouTube | SpotifyFacebook: @ViewpointsOnlineX: @viewpointsradioInstagram: @viewpointsradioFull ArchiveContact UsAffiliates & National Syndication Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Is your phone correcting words like "were" to "we're" and "public" to "pubic"? If so, you're not alone. More and more, predictive text seems to have a mind of its own. Marcus Frean is an Associate Professor at Victoria University's School of Engineering and Computer Science. A specialist in statistical and probability-based machine learning. He talks to Mihingarangi about why he thinks auto correct is out of control.

Intern to Founder | Justin Collins | Breaking Into CyberEpisode SummaryIn this episode, Justin Collins shares his unique journey from a PhD student in Computer Science to becoming a key figure in the application security space. Justin explains how a funding shortage led him to a life-changing internship at AT&T Interactive, where he combined his passion for compiler theory with cybersecurity to create the open-source tool Brakeman. We dive into how he balanced a full-time job while co-founding a startup and the importance of preparation when breaking into a new field.Key Takeaways- Preparation as a Differentiator: Justin secured his first security role simply by researching the specific topics (SQL injection and XSS) the interviewers mentioned beforehand—a step many other candidates neglected.- Applying Niche Skills to Security: Rather than starting from scratch, Justin leveraged his deep knowledge of programming languages and compilers to build a static analysis tool, proving that specialized non-security backgrounds are highly valuable.- The Power of Open Source: Developing and open-sourcing Brakeman during an internship served as a massive career catalyst, eventually leading to a business acquisition.- The "Side-Hustle" Startup Model: Justin highlights that successful startups don't always require VC funding or fancy offices; his company was built while the founders maintained their "real" jobs.- Negotiating Flexibility: Early in his career, Justin successfully negotiated a part-time security role, which allowed him to support his family while simultaneously building his own business.Resources Mentioned- Brakeman: The open-source static analysis security tool for Ruby on Rails created by Justin.- OWASP: Cited as a critical resource for learning about web vulnerabilities like SQL injection and XSS.- Ruby on Rails: The programming framework that served as the foundation for Justin's early work.- Black Duck (formerly Synopsys): The company that eventually acquired Justin's startup.About the GuestJustin Collins is a cybersecurity expert and the creator of Brakeman, a widely used static analysis tool for Ruby on Rails. With an extensive background in Computer Science and programming languages, Justin transitioned from academia to entrepreneurship, co-founding a boutique security firm that was later acquired by Synopsys. He is a specialist in application security and program analysis.Sponsored by CPF Coaching LLC - http://cpf-coaching.comCheck out our books:

Episode Topic: ND Perspectives: Guardians of AI InnovationArtificial intelligence is no longer a distant concept; it is actively reshaping how we live, work, and connect right now—whether your daily life is high tech, low tech, or completely unplugged. But as this technology accelerates, who is ensuring it ultimately serves humanity? Claim your front-row seat to the future and unpack complex issues like data privacy, massive marketplace recalibrations, human autonomy and ethics. Bring your most pressing questions to this panel of faculty and alumni experts for discussion and audience Q&A. You will leave with renewed clarity on how the ND family is a force for good in the digital age.Featured Speakers:Dolly Duffy '84, Executive Director, Notre Dame Alumni Association, University of Notre DameAdam Kronk '02, '09 MNA, Director of Research and External Engagement, Institute for Ethics and the Common Good, University of Notre DameNitesh Chawla, Frank M. Freimann Professor of Computer Science and Engineering, Lucy Family Director for Data & AI Academic Strategy, Founding Director of the Lucy Family Institute for Data and Society, University of Notre DameGina Ayala Claxton '01, Corporate Vice President, U.S. Retail & Consumer Goods, MicrosoftHeng Xu, Professor of Information Technology, Analytics, and Operations, Mendoza College of Business, University of Notre DameJosh Zavilla '11, Head of National Security, Palantir TechnologiesThis podcast is a part of the ThinkND Series titled Reunion 2026.Thanks for listening! The ThinkND Podcast is brought to you by ThinkND, the University of Notre Dame's online learning community. We connect you with videos, podcasts, articles, courses, and other resources to inspire minds and spark conversations on topics that matter to you — everything from faith and politics, to science, technology, and your career.Learn more about ThinkND and register for upcoming live events at think.nd.edu.Join our LinkedIn community for updates, episode clips, and more.

Tonight on America at Night with McGraw Milhaven: Dr. Hany Farid, Professor of Computer Science at UC Berkeley, CEO of GET Real Security, and one of the world's foremost experts on digital forensics and deepfakes, joins the show to discuss the rapidly evolving threat posed by AI-generated content. As deepfake technology becomes increasingly sophisticated, Farid explains why even experts are finding it harder to distinguish reality from fabrication and what individuals, businesses, and governments can do to protect themselves in an era of digital deception. Later, Catherine Townsend, President and CEO of the Trust for the National Mall, joins the program to discuss the importance of preserving America's most iconic public space. Townsend highlights ongoing efforts to maintain and improve the National Mall and Memorial Parks, the role these landmarks play in American history, and what visitors can experience when exploring the nation's front yard. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Dr. Mina Sartipi was taught by her parents that there were no limits, and that's truly been the case throughout her life. In this episode, Mina shares how she earned one of the 100 spots at Iran's top engineering university, why the Argentinian tango led her to plant roots in Chattanooga, and how she has helped lead some of UTC's most ambitious research initiatives, such as the MLK Smart Corridor. Dr. Mina Sartipi is the Interim Vice Chancellor for Research at UTC, the Executive Director of the UTC Research Institute, the Guerry Professor and UTC Foundation Professor in UTC's Computer Science and Engineering Department, and the Joint Faculty Appointee with Oak Ridge National Laboratory. You can connect with her on LinkedIn (https://www.linkedin.com/in/mina-sartipi-86267a1/).  If you like this episode, we think you'll also like: Charlie Brock's Morning Cup (E95) Dr. Lori Mann-Bruce's Morning Cup (E158) Janet Rehberg's Morning Cup (E163) Subscribe to the weekly newsletter and be the first to know who upcoming guests are: http://eepurl.com/iGJzII  My Morning Cup is hosted by Mike Costa of Costa Media Advisors and produced by SpeakEasy Productions.

Why does it seem so difficult to cancel an online subscription, delete an account, or opt out of data tracking? You might think it's just bad luck or a confusing online interface, but more often than not, it's by design. In this episode of Big Brains, we speak with Marshini Chetty, Professor in the University of Chicago's Department of Computer Science. As a leading expert in human-computer interaction, Chetty reveals the science behind "dark patterns” online—the subtle, manipulative design choices woven into the apps and websites we use every day. We explore how these deceptive interfaces weaponize human psychology to keep us clicking, spending and sharing our data. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Jure Leskovec, Professor of Computer Science at Stanford University and Chief Scientist at Kumo.ai, speaks with host Sriram Panyam about relational and graph language models and their transformative impact on enterprise decision-making and predictive modeling. Jure begins by establishing the critical importance of predictive modeling across industries - from fraud detection in financial institutions to customer churn prediction, lifetime value estimation, product recommendations, and healthcare risk assessment. He notes that while AI has made remarkable advances in natural language understanding and computer vision, predictive modeling over enterprise operational data stored in relational databases has been largely left behind, still relying on 30-year-old machine learning approaches that are expensive, time-consuming, and require manual feature engineering. His proposed solution to the fundamental problem with current approaches is relational deep learning and relational transformers. The discussion explores how this approach differs from traditional graph neural networks (GNNs), which Jure pioneered and deployed successfully at Pinterest. Jure concludes with practical guidance for software engineers and data scientists interested in exploring this technology.

In this episode, Python Developer Advocate and author Will Vincent joins the hosts to discuss the lasting appeal of Django, changes in how people learn web development, and the ways AI is reshaping software engineering. While modern AI tools can generate working code in seconds, Django's opinionated design and emphasis on maintainability help developers avoid many of the security and architectural problems that often emerge as projects grow. Drawing on his background as an educator, author, and Developer Advocate at JetBrains, Will shares his perspective on the challenges facing today's developers and computer science students. The conversation touches on "vibe coding," the misconception that a successful prototype automatically translates into a production-ready application, and the increasing burden AI-generated content is placing on open-source maintainers. Will also discusses the rise of specialized AI models, the importance of human trust in technical communities, and why foundational software engineering skills remain valuable despite rapid advances in AI tooling. Key Topics Covered Why Django Still Matters A look at why Django continues to be a strong choice for building production applications, even if it doesn't receive the same level of attention as newer frameworks. The Reality Behind "Vibe Coding" Exploring the gap between generating code with AI and understanding the systems, tradeoffs, and architecture required to build reliable software. Learning to Program as an Adult Will reflects on his path from book editing and startup leadership to becoming a self-taught programmer, educator, and author. AI and Programming Education A discussion about how AI changes the learning process, why fundamentals still matter, and how concepts like music theory can help explain the value of understanding code beneath the surface. The Growing Burden on Open Source How maintainers are dealing with an influx of low-quality AI-generated issues, pull requests, and content, and what that means for community-driven projects. Local and Specialized AI Models Why privacy concerns, lower inference costs, and better hardware may drive adoption of smaller, task-focused models rather than ever-larger general systems. Developer Concerns in the AI Era How engineers are responding to growing pressure from leadership teams eager to adopt AI, and what trends JetBrains is seeing across the developer ecosystem. Resources Mentioned LearnDjango, Will Vincent's platform for learning Django and web development. Hello World 5 Different Ways, a Django tutorial that introduces key concepts through practical examples. Django Chat, the podcast Will co-hosts covering the Django ecosystem and web development. Django News, a weekly newsletter highlighting updates from the Django community. JetBrains, the software development company behind tools such as PyCharm and IntelliJ IDEA.Special Guest: Will Vincent.

What if the biggest problem in education isn't intelligence, but language?In this episode of Living The Red Life, Aditya Nagrath, founder of Elephant Learning and a PhD in Mathematics and Computer Science, reveals why four out of five students begin school already behind in math and how that single gap can shape an entire future. After building software companies, leading engineering teams, and navigating devastating business setbacks, Aditya uncovered an opportunity far bigger than technology: transforming the way children learn mathematics.He shares the unconventional thinking behind Elephant Learning, the science of teaching math as a language, and the performance-driven system producing measurable gains in just minutes per week. This conversation explores education innovation, entrepreneurship, STEM success, learning psychology, and the power of solving massive societal problems through scalable systems.Key Takeaways• Why mathematics should be taught as a language, not memorization• The hidden kindergarten gap affecting millions of students• How a business collapse led to a mission-driven education company• Why algebra is the foundation for success across STEM fields• The leadership principle that helped build a scalable education platformNotable Quotes• "Mathematics is happening everywhere, even when people don't realize it."• "If the student understands the teacher, the education system works."• "The goal is understanding, not repetition."• "We've measured about a year and a half of math growth in just ten weeks."• "Empowerment means giving people power where there was none before."Connect with Rudy Mawer:LinkedInInstagramFacebookTwitter

Show Summary:    Mudita Khurana — Tech Lead at Airbnb and the person who always says, “I got this” No Password Required Season 7: Episode 6 - Mudita Khurana   Mudita Khurana is a Tech Lead for Automated Tooling and Vulnerability Management at Airbnb, where she focuses on building modular, scalable security systems in an era of rapidly evolving AI threats. Before Airbnb, she spent nearly a decade in security roles across Accenture, Meta, and PwC, making bold career pivots along the way, including turning down a PwC return offer to join Facebook's product security team. In this episode, Mudita shares her journey from a family of doctors in India to Carnegie Mellon and into the heart of Big Tech security. She discusses what it means to thrive as a non-traditional engineer in a deeply technical field, why she stepped back from management to get closer to the work, and how she thinks about building security tooling that won't be obsolete in three months. Jack Clabby and co-host Kayley Melton, recording live from Tampa B-Sides at the University of South Florida, talk with Mudita about imposter syndrome, AI's curveballs for security teams, leadership without a leadership title, and the importance of community in staying on top of a field that never stops moving. She also reflects on what great mentorship looks like early in a career and why clarity, ownership, and consistency are the leadership qualities she keeps coming back to. In the Lifestyle Polygraph, Mudita firmly plants her flag in the Harry Potter universe as Hermione, explains why Deadpool doesn't qualify as a superhero, debates gym vs. nature as a reset strategy, and reveals her dream remote work base: a high-altitude Buddhist mountain town in the Himalayas.   Follow Mudita on LinkedIn: https://www.linkedin.com/in/muditakhurana/     In this episode: Mudita shares her unconventional path into cybersecurity, highlighting the importance of mentorship and curiosity (0:25 - 1:37) The significance of mentorship, especially Vandana Verma, in her career development (2:26 - 4:00) Transition from management to technical IC roles and why staying close to technical work matters (9:29 - 10:23) The influence of her education at Carnegie Mellon and how it broadened her problem-solving skills (6:23 - 7:41) Navigating imposter syndrome and embracing challenges as growth opportunities (3:26 - 5:29) How AI is changing cybersecurity strategies—building modular, layered systems for agility (15:31 - 16:26) The importance of community, trust, and consensus in cybersecurity decision-making (17:06 - 17:47) Mudita's favorite places for remote work and balancing planning with spontaneity in travel (23:01 - 24:13) Her personal approach to wellness, exercise, and resets during busy days (21:32 - 22:36) Her unique perspective on superhero characters, favorite places, and cultural roots (18:54 - 19:36, 25:19 - 26:21) Timestamp Highlights: (00:25) Mudita's 10-year journey into cybersecurity starting from India (02:26) Mentorship's critical role in her growth and her admiration for Vandana Verma (09:29) Transition from management back to technical roles and why staying close to the work matters (15:31) How AI fosters layered, modular security systems for faster adaptation (17:06) The importance of community and trusted information sources in security (21:32) Reset routines—gym versus nature hikes—and staying grounded during busy days (25:19) Leh, Ladakh: Mudita's ideal remote work location nestled in Himalayan beauty Resources & Links: Vandana Verma - Influential mentor in cybersecurity ThreatLocker - Supporter of this podcast Cyber Florida – The Mother Ship

Autonomous vehicles may be the closest real-world example of AI operating in life-and-death situations at scale. Justin Norden believes healthcare has a lot to learn from how that industry approached safety, testing, adoption, and trust. This week, Michael and Halle sit down with the founder and CEO of Qualified Health, fresh off the company's $125 million Series B, to discuss why healthcare organizations need to think differently about deploying AI. Justin shares how his experience at Stanford, Apple, Waymo, and in healthcare investing shaped his view that health systems need AI infrastructure, governance, and workforce buy-in, not just another point solution.We cover:What healthcare can learn from Waymo's approach to safe AI deploymentWhat founders need to understand about building around EpicWhy health systems need to treat AI as a CEO-level priority, not an innovation projectHow Qualified Health is helping systems deploy, monitor, and measure AI workflowsWhy governance, safety, and ROI matter as much as model performanceWhy clinicians are right to be skeptical about AI liabilityAbout our guest:Justin Norden, MD is Co-Founder and CEO of Qualified Health building the trusted platform for health system AI. Additionally, he has been an Adjunct Professor at Stanford Medicine in the Department of Biomedical Informatics Research where his research and teaching focused on AI in medicine and digital health where he founded and still teaches courses on digital health and generative AI in medicine. Previously, Dr. Norden was Co-Founder and CEO of Trustworthy AI, a company focused on algorithm safety and trust, which was acquired by Waymo (Google Self-Driving). He was a Partner at GSR Ventures leading investments in healthcare and AI, worked on the healthcare team at Apple, and helped start the Stanford Center for Digital Health. Dr. Justin Norden received an MD and MBA from Stanford University, an MPhil in Computational Biology from the University of Cambridge, and a BA in Computer Science from Carleton College.—

From Brexit negotiations and the Cuban Missile Crisis to elections, auctions and everyday decision-making, game theory can offer powerful insights into how we navigate a world shaped by competing interests, cooperation and strategic choices. In this episode, Professor Michael Wooldridge joins Carl Miller to explore the surprising life lessons hidden within one of mathematics' most influential fields. Drawing on ideas from his new book Life Lessons from Game Theory: The Art of Thinking Strategically in a Complex World, Wooldridge explains how game theory can help us better understand conflict, human behaviour and truth.  Professor Michael Wooldridge the Ashall Professor of the Foundations of Artificial Intelligence in the Department of Computer Science at the University of Oxford, and a Senior Research Fellow at Hertford College. Carl Miller is an author, speaker and researcher at Demos, a think tank based in London, where he co-founded the Centre for the Analysis of Social Media in 2012. --- If you'd like to become a Member and get access to all our full conversations, plus all of our Members-only content, just visit intelligencesquared.com/membership to find out more. For £4.99 per month you'll also receive: - Full-length and ad-free Intelligence Squared episodes, wherever you get your podcasts - Bonus Intelligence Squared podcasts, curated feeds and members exclusive series - 15% discount on livestreams and in-person tickets for all Intelligence Squared events  ...  Or Subscribe on Apple for £4.99: - Full-length and ad-free Intelligence Squared podcasts - Bonus Intelligence Squared podcasts, curated feeds and members exclusive series … Already a subscriber? Thank you for supporting our mission to foster honest debate and compelling conversations! Visit intelligencesquared.com to explore all your benefits including ad-free podcasts, exclusive bonus content and early access. … Subscribe to our newsletter here to hear about our latest events, discounts and much more. https://www.intelligencesquared.com/newsletter-signup/ Learn more about your ad choices. Visit podcastchoices.com/adchoices Learn more about your ad choices. Visit podcastchoices.com/adchoices

For as far as we've come with AI and robotics, there's still a huge gap when it comes to combining the two. AI excels in the digital space, and in the physical world, robots are often pre-programmed. That's where physical AI comes in. It's critical for things that can't tolerate the kinds of mistakes that are common in today's statistics based AI, like self driving cars or managing the power grid. In the latest installment of our oral history project, we meet a central figure in these efforts, MIT's Daniela Rus.We Meet:  Daniela Rus is the Director of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Andrew and Erna Viterbi Professor in the Department of Electrical Engineering and Computer Science.Credits:This episode of SHIFT was produced by Jennifer Strong with help from Emma Cillekens. It was mixed by Garret Lang, with original music from him and Jacob Gorski. Art by Meg Marco.

Dr. Roman Yampolskiy is a leading voice in AI safety and a Professor of Computer Science and Engineering. He coined the term “AI safety” in 2010 and has published over 100 papers on the dangers of AI. In today's moment, Roman unpacks the jobs AI might replace, and how the idea of work itself could be challenged. Driverless cars, humanoid robots, superintelligence on the horizon…is it too late to regain control? What will our future actually look like? Listen to the full episode here! Spotify: https://g2ul0.app.link/kM19qMRnG2b Apple: https://g2ul0.app.link/D8XtGbUnG2b Watch the Episodes On YouTube: https://www.youtube.com/c/%20TheDiaryOfACEO/videos Roman: https://www.romanyampolskiy.com/