Podcasts about Computer science

AP's Lisa Dwyer reports that College computer science majors are down. AI for everyone else is up.

Why AI is advancing faster than most people realize The truth about choosing a college major today Which careers may be most vulnerable to AI Why human skills matter more than ever How students can become future-ready The importance of AI literacy for every family Opportunities for students interested in AI research

Apparel, furniture and home appliances once served as the iconic "old three" of Chinese exports. Later on, the "new three" – electric vehicles, lithium batteries and solar panels – became the backbone of China's export growth. Now, China says the new "new three" – AI, robotics, innovative drugs – mark another upgrade in its industrial landscape. What is new about the new "new three" compared to the "new three"? How far can China go in its rise as a global tech power? Host Ding Heng is joined by Xiao Qian, Deputy Director of the Center for International Security and Strategy, Tsinghua University; Kashif Sharif, Associate Professor from School of Computer Science & Technology, Beijing Institute of Technology; Andy Mok, Author of the book "The Innovation Machine: How China Creates and Adopts Technology Through Governance."

What happens when a 16-year Google veteran (who also worked at Microsoft) decides to fix drug discovery with AI?You get Pauling AI, a next-generation molecular simulation platform built to discover the medicines of tomorrow.In this episode of Game of Pharma, Javier, CEO & Founder of Pauling AI and Ex-Technical Director at Google Healthcare & Life Sciences, shares his journey from leading Search, Ads, Supply Chain, and Cloud at Google (with prior experience at Microsoft) to building AI tools that could shape the future of pharmaceutical research.What you'll learn in this episode:→ Why Javier left Google after 16 years to bet on biotech AI→ What's actually working in AI drug discovery (vs the hype)→ Why biotech startups adopt AI faster than Big Pharma→ How Pauling AI is reimagining molecular simulation→ The next 5 years of AI in pharmaIf you're curious about where AI meets drug discovery, this conversation is unmissable.️ Listen on Spotify: https://open.spotify.com/show/4EDgDoe...️ Apple Podcasts: https://podcasts.apple.com/us/podcast...Subscribe to our newsletter: https://game-of-pharma.beehiiv.com---ABOUT JAVIER:Javier is a technology executive, and entrepreneur. Currently leading Pauling AI, a next-generation molecular simulation platform.Previously: 16 years at Google (Search, Ads, Supply Chain, Cloud). Prior experience at Microsoft and McKinsey.Education: Superior Engineer in Computer Science, Masters in Mathematics (Dropped out of Ph.D. in Mathematics to pursue building software.)ABOUT GAME OF PHARMA:World's leading pharma podcast with 25,000+ subscribers globally. Featuring conversations with the brightest minds in pharmaceuticals.Website: https://gameofpharma.com/LinkedIn:  / game-of-pharma-podcast  

95% of enterprise IT leaders plan to launch agentic AI projects — but 69% aren't ready. So, what's standing in the way?  In this episode of Scaling AI in the Enterprise, we bring together an expert panel to tackle the real engineering and organizational challenges of AI deployments: the probabilistic nature of AI agents, the limits of traditional testing, and why "making your prompt stronger" is not a strategy.  Host: Eric Knipp, SVP and GM, Cisco Customer Experience (CX) Americas  Guests:   Bhaskar Jayakrishnan, SVP of Engineering, Cisco Customer Experience (CX)  Dr. Lydia Chilton, Associate Professor of Computer Science, Columbia University  Sam Charrington, Host of the TWIML AI Podcast  Srini Namineni, SVP and Chief Automation Officer, Cisco  Learn more about Cisco Customer Experience: read our blogs and visit Cisco.com

The Kanz initiative (ka.nz/hack) was far more than a hackathon. It was a bold, free global program to democratize AI by enabling everyone, from complete beginners to experts, to build and publish real AI applications in one week. Fully sponsored and aligned with Saudi Vision 2030, it combined daily structured training, hands-on building, community energy, and a successful Guinness World Record attempt.Standout innovations:No coding required, AI-first approach: "Build first, learn by creating." Participants used cutting-edge tools (Claude, NotebookLM, Replit, HeyGen, Suno, Gamma, etc.) to create apps, agents, images/videos, avatars, music, presentations, and automations—emphasizing practical results over theory. 7-day tangible curriculum: Daily sessions (evenings KSA time) produced immediate outputs. Everyone published a working app on Day 1 and left with a portfolio, verified certificate (Saudi HRSD + Lebanese American University), and real skills.Strong incentives: MacBooks, Kindles, watches, job opportunities, and employer spotlights. Projects were AI-graded then judged, with top entries showcased.Radical inclusivity: Targeted teachers, marketers, business owners, job seekers, designers, and absolute beginners—not just coders.~51,700 registrations.24,800+ live participants from 150+ countries.~197,000 training hours.Guinness World Record (July 15, 2026): 14,075 learners in one AI video lesson — officially adjudicated. ka.nz3,500+ AI projects built, including practical tools like real-time fact-checkers and automation systems.Massive scale and success:Success drivers: zero cost, instant results, vibrant global community, modern tools, and partnerships. It proved AI creation can be accessible to everyone, not just engineers, potentially sparking countless innovations and careers. Deep Dive: Roy BaladiRoy Baladi, CEO of Kanz, is the visionary behind it. With a dual degree in Computer Science & Finance from Virginia Tech (Math minor) and 15+ years in tech/finance, he has built marketplaces and inclusive hiring platforms. Background: Wall Street derivatives experience (Citi), product roles at LearnVest and SmartRecruiters, Chief Marketplace Officer at PerkSpot. He founded/led Jobs for Lebanon (Board President): 5,000+ employers, 25,000+ seekers, 750+ hires. Through Kanz and Jobs for Humanity, he has reached over 1M people with AI tools and training, placing thousands (including underrepresented talent and Saudi women via Saudiaat).Philosophy: Roy views AI as a practical empowerment tool for employment, agency, and lifelong learning. He focuses on removing barriers, teaching by building, and using technology to restore humanity to hiring. Prior programs trained 2,000+ in agentic AI. The hackathon scaled this mission globally. Why It Matters: Digital literacy now means building with AI. Kanz didn't just teach chatbots-it empowered tens of thousands to create. If even a fraction of projects become tools or businesses, the impact will far outlast the record. Roy Baladi's work shows large-scale AI education is not only possible-it's transformative.

Today, I am joined by Steve Fenster the founder and president of NJveg, and is now a full-time volunteer.  He holds degrees in Biology, Business Administration, and Computer Science from Rutgers University, and worked as a systems engineer.  Steve has been vegan for 16 years and was vegetarian for 7 years prior.  He is a lifelong New Jersey resident, and has lived in the northern, central, and (currently) southern portions of the state. NJveg is an all-volunteer nonprofit dedicated to educating the public on the benefits of a plant-based life while providing support, volunteer opportunities, and social events throughout New Jersey. Steve takes us through why he created NJveg, shares his vegan journey, we talk community, and more!To connect with Steve and NJveg:Website: https://NJveg.orgEvent Calendar:  https://njveg.org/event-calendar/Mailing List:  http://eepurl.com/dwk3hHInstagram:  https://www.instagram.com/vegnj/Facebook Page:  https://www.facebook.com/NJveg/Facebook Group:  https://facebook.com/groups/vegnj/Pinterest:  https://pinterest.com/vegnj/TikTok:  https://www.tiktok.com/@vegnjMeetup: https://www.meetup.com/njveg-meetup-group/Email:  NJveg.org@gmail.comText:  609-557-7077Mentioned in this episode:Goats of Anarchy: https://www.goatsofanarchy.org/Ethos Farm to Health (Steve and I met as vendors at Ethos Farm Days): https://www.ethosfarmtohealth.org/Physicians Committee for Responsible Medicine (PCRM): https://www.pcrm.org/PETA: https://www.peta.org/front/Phoenixville, PA VegFest: https://www.facebook.com/PhoenixvilleVegFest/To connect with me:Follow me on Facebook and Instagram @didyoubringthehummusDYBTH merch now available! Check out the shop here: https://did-you-bring-the-hummus.myspreadshop.comFor more info on my Public Speaking 101 program: ⁠https://www.didyoubringthehummus.com/publicspeakingforactivists⁠Contact me here or send me an email at info@didyoubringthehummus.comSign up for meditation sessions hereSign up for The Vegan Voyage, to sponsor the podcast, book meditations packages, or sign up for my Public Speaking program hereJoin my Podcast Fan Facebook Group: https://www.facebook.com/groups/didyoubringthehummus/To be a guest on the podcast: https://www.didyoubringthehummus.com/beaguest©2026 Kimberly Winters - Did You Bring the Hummus LLCTheme Song ©2020 JP Winters ⁠@musicbyjpw⁠

Heather McCalleyMS, College of Arts and Sciences, 2011CERT, College of Arts and Sciences, 2011More InformationYellowhammer News - UAB forensics team DarkTower leaves criminals with nowhere to hideDarkTower - homepageLinkedIn - Heather McCalleyLinkedIn - International Women's Day post (Gary Warner)

Over the weekend, the Green Party announced their proposal to have a one year national moratorium on the consenting of new Artificial Intelligence Data Centres until proper regulations have been set up. Consent for a 3.5 billion dollar hyperscale AI data centre has already been approved for Southland, which is set to be the second highest consumer of electricity in the country, requiring 280 MW of power. While supporters claim that it will bring in jobs and allow New Zealand to be at the forefront of the AI industry, many have raised concerns about the harm it could cause to New Zealand's natural environment, the strain it will put on our energy and water resources, and the fact that projects have been seemingly approved with little public consultation.  I spoke to Dr Kerry McInerney from the School of Computer Science at the University of Auckland, about public perceptions towards AI Data Centres in New Zealand, concerns that have been raised and whether there can be a social license for data centres to be implemented.

For the last decade, computer science was considered the undisputed king of college majors. But in the age of AI, that script is rapidly being flipped. Now that AI can write code in seconds, the ability to think deeply and critically has become more important than ever. In this episode, Mackenzie is joined by Alpha graduate Maddie Price, who recently traveled to France for an exclusive philosophy conference at Alexis de Tocqueville's historical chateau. Together, they break down the growing national reading crisis, the fear of "soft despotism" (and a WALL-E-style future), and why the humanities are emerging as the most crucial toolset for the next generation of leaders.

Before the internet could become a place to bank or transact, it needed a way for strangers to know who they were talking to, and whether a message could be trusted. Turing Award winners Ron Rivest, Adi Shamir, and Leonard Adleman helped invent it. In this episode of First Principles, Rivest tells the story of how they developed RSA, the first practical public-key cryptosystem. Their breakthrough made it possible to encrypt information, verify identities, and authenticate messages across an open network without requiring participants to meet or exchange a secret in advance — laying essential groundwork for the secure internet and, decades later, blockchains. Rivest joins Tim Roughgarden, Head of Research at a16z crypto and Professor of Computer Science at Columbia University, and Dan Boneh — Professor of Computer Science at Stanford University, a16z crypto Senior Research Advisor, and the “B” in BLS signatures — for a conversation about the origins and future of modern cryptography. They trace the field from its early days, when most cryptographic research was classified and even the meaning of “security” had not been formally defined, through the publication of the Diffie-Hellman paper and the open problem that ultimately led to RSA. Rivest recounts the night the core idea came together, why the difficulty of factoring made the system plausible, and why no one initially knew whether it would survive sustained attempts to break it. The conversation also explores the other cryptographic primitives that underpin blockchains and the modern internet. Rivest explains why digital signatures interested him even more than encryption, how he designed the MD family of cryptographic hash functions, and why standards such as RSA, DSA, and SHA were shaped as much by politics, patents, and government pressure as by mathematics. Finally, Rivest shares his unusually candid views on quantum computing, post-quantum security, and the deeper theoretical possibility that P could equal NP. Either development could threaten the foundations of modern cryptography — but, as Rivest argues, cryptographers have a responsibility to prepare for even the worst-case scenarios. Highlights 00:00 – Intro: the two problems that could break modern cryptography 01:10 – Why Ron Rivest's work underpins the internet and blockchains 08:10 – Before public-key cryptography, there was no theory of security 11:05 – The open problem that led to RSA 13:55 – The night Ron Rivest discovered the core idea behind RSA 17:55 – Why digital signatures were the real breakthrough 19:14 – The RSA challenge — and a prediction that was off by quadrillions of years 28:33 – How government pressure shaped cryptographic standards 30:36 – Designing the hash functions that made digital signatures practical 33:26 – The Fiat–Shamir transformation, explained 38:04 – Building a cryptography company before the web existed 42:31 – Will quantum computers ever become powerful enough to break RSA? 48:02 – The cryptography securing the internet, elections, and everyday life 50:11 – What surprised Dan: Quantum giveth and quantum taketh away 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. Subscribe to follow along: https://www.youtube.com/playlist?list=PLjQ9HCQMu_8yIg60YAq67HDdvp7E_T5e8 Hear more from: Ron Rivest: https://people.csail.mit.edu/rivest/ Tim Roughgarden: https://twitter.com/Tim_Roughgarden Dan Boneh: https://twitter.com/danboneh 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.

Barry O'Sullivan, Professor at the School of Computer Science at University College Cork, discusses one of Open AI's advanced systems going rogue and hacking a start-up tech firm.

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.

For most enterprises, autonomous AI agents still feel like a risk waiting to happen. Andi Gutmans, Vice President and General Manager for Data Cloud at Google, joins Cindi Howson to explain what it takes to build the data foundation that trustworthy agentic AI depends on. He breaks down how organizations can finally activate the 90 percent of enterprise data that's unstructured, why tokenmaxxing is the wrong way to measure AI value, and how open standards like Apache Iceberg are helping leaders tear down fragmented, multi-cloud data silos and unify data across clouds. Key Moments: Perception vs. Reality in Trusting Autonomous AI (03:55): Waymo is safer than a human driver by the numbers, but most people still choose Uber. Andi explains why closing that trust gap takes time. Activating the 90% of Unstructured Data (09:40): Most enterprise data sits in images, PDFs, and contracts, never touched by traditional analytics. Andi explains how AI finally makes that dark data usable. Crawl, Walk, Run: Scaling Autonomous Agents in Production (16:37): Virgin Voyages cut weather disruption rebooking from six hours to eleven minutes with autonomous agents. Andi explains the thresholds that made scaling safe. Token Efficiency Over Tokenmaxxing (19:54): Andi pushes back on tokenmaxxing as a measure of progress. Real success means the best outcome with the fewest tokens and the cheapest model for the job. Breaking Down Data Silos with a Borderless, Open Lakehouse (27:01): Most enterprises run on a messy mix of multiple clouds. Andi explains how open standards like Apache Iceberg tear down those walls. Key Quotes: “Over ninety percent of enterprise data is actually unstructured data... AI is really good at reasoning around this unstructured data, and so we can make a hundred percent of the data state light up.” - Andi Gutmans “If you take a Waymo, you're actually eighty percent less likely to get into a hurtful accident than if you take a service with a human driver. Still, most people prefer to take the Uber versus the Waymo…  It's going to take time to earn the trust to understand what quality outcomes we can drive.” - Andi Gutmans “ The way we're thinking about the data platform is the best context is the context that drives the outcomes you need with the least amount of tokens and processing.” - Andi Gutmans Mentions Blue Ocean Strategy by W. Chan Kim and Renée Mauborgne Virgin Voyages case study (Google Cloud) Vodafone, Google Cloud and TM Forum Unveil Framework for Self-Optimising Autonomous Networks Guest Bio Andi Gutmans is the General Manager and Vice President for Data Cloud at Google, which includes operational databases, analytical data platforms, open lakehouse technologies, and  Business Intelligence. His core focus involves building, managing, and scaling highly innovative data services to deliver a leading AI-native data platform for businesses. Before joining Google Cloud, Gutmans was VP Analytics at AWS, where he managed services such as Amazon Redshift, AWS Glue, and Amazon EMR. Prior to that, he co-founded and served as CEO of Zend Technologies, a company built around the open-source PHP language, of which he was a co-creator. Andi Gutmans is a highly experienced leader with over 20 years dedicated to open source contributions. He is particularly renowned as a co-creator of the open-source PHP language, which has become one of the most widely used languages for web development. He is an emeritus member of the Apache Software Foundation and served on the Eclipse Foundation's board of directors. Gutmans holds a bachelor's degree in Computer Science from the Technion, Israel Institute of Technology. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Dr. Mohsen Ghasempour, Chief AI Officer at Kingfisher, unpacks why the most dangerous thing a company can do with customer data is use all of it. He explains how a global, multi-brand retailer can draw the line between personalization that feels helpful and personalization that feels like surveillance. He also discusses why AI success is ultimately an execution problem rather than a technology problem. Key Takeaways:  What the "comfort test" is and how Kingfisher uses it to decide whether a personalization decision has gone too far How global retailers are resolving the tension between centralized AI infrastructure and brand-level autonomy Why legal and compliance teams are now embedded in AI development from the start What it will look like when AI stops being a distraction and starts being invisible infrastructure Guest Bio: Dr. Mohsen Ghasempour is a distinguished expert in the field of artificial intelligence (AI) with a solid academic foundation, holding a PhD in Computer Science. Currently, Mohsen serves as the Chief AI Officer at Kingfisher, where his leadership contributes to the advancement of artificial intelligence and machine learning technologies within the organisation. With over 15 years of experience as an accomplished data scientist and visionary leader, Mohsen has consistently harnessed the power of data to drive strategic decision-making. Prior to his role at Kingfisher, he held pivotal positions in leading technology and retail organisations, including The Hut Group (THG) and Shop Direct. In these roles, he spearheaded cross-functional teams to implement cutting-edge Machine Learning and AI solutions, resulting in measurable and transformative outcomes. ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

It's unclear what regulation would be helpful as AI's become increasingly powerful. Open AI says one of their servers has hacked into a competitor's server – without a human asking it to. Serious concerns are now being raised about how quickly the systems are being created and implemented. Auckland University Professor of Computer Science Michael Witbrock told Mike Hosking it's been clear these systems are getting good at cyber security analysis. He says in this case the system was asked to solve a cyber security problem - it just did more hacking than was expected. Witbrock told Hosking while there are plenty of people following their own interests, it isn't in the interests of AI companies overall to deliberately hack each other or to have these vulnerabilities. LISTEN ABOVE See omnystudio.com/listener for privacy information.

School of Computer Science & Engineering UNSW Professor of CyberCrime Professor Richard Buckland joined Mark Allen and Russel Howcroft to discuss the recent rise in AI scams.See omnystudio.com/listener for privacy information.

Tomas Reimers, Co-Founder & CPO @ Graphite, reveals his journey to becoming a founder and some of the major moments from Graphite's product development story. He dissects frameworks for determining when it's time to quit your full-time job to pursue becoming a founder and analyzing the costs vs. benefits of that decision. We cover how to decide what customer problems to solve, understanding how software development trends impact what you're building, and product market fit and selling considerations. Lastly, Tomas shares valuable strategies when it comes to selling to developers.   ABOUT TOMAS REIMERS Tomas Reimers is the CPO and co-founder of Graphite, the a16z and Anthropic-backed AI code review platform that Cursor acquired in December 2025. Previously, he was an engineer at Facebook. Passionate about advancing developer velocity, Tomas holds a BS in Computer Science from Harvard University.   SHOW NOTES: The origin story behind Graphite (1:05) Signs that it's time to quit your job / found a company (4:03) How Tomas & his co-founders knew it was time to break up with their jobs (5:40) Understand what leaving your job will mean career-growth wise (7:33) Embracing regret minimization (9:28) Pros & cons of developing in blue ocean vs. red ocean areas as a founder (11:49) Strategies for determining what software to build / how is software dev evolving (14:00) Tomas's framework for determining bets (15:50) Recommendations for selling as a founder (17:52) Identifying if sales isn't working or if product market fit is off (20:35) Using customer insights to experiment & make a PMF pivot (23:05) Why developers don't want to be sold to, they want to be taught (24:42) How to apply teaching vs. selling into early GTM strategy (27:20) Utilizing demonstrations to gain developer buy in & trust (29:24) What Tomas is looking forward to in Graphite's future / software dev in general (32:04) Rapid fire questions (33:34)   LINKS AND RESOURCES The Mom Test - Rob Fitzpatrick's quick, practical guide that will save you time, money, and heartbreak. Founding Sales - The Startup Sales Handbook - rhe distillation of Pete Kazanjy's experience at his first software startup, TalentBin going from a founder with a product marketing and product management background to early sales guy, early sales manager, and eventual post-acquisition sales leader at Monster Worldwide in addition to his later experience founding Modern Sales, the nation's largest sales operations, enablement, and leadership community. Thinking in Bets: Making Smarter Decisions When You Don't Have All the Facts - Annie Duke, a former World Series of Poker champion turned business consultant, draws on examples from business, sports, politics, and (of course) poker to share tools anyone can use to embrace uncertainty and make better decisions. This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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?

Join Haritha Arumugam and Computer Science student Swetha Murugesan as they discuss women in technology, artificial intelligence, cybersecurity, digital innovation, career opportunities, and the importance of encouraging more young women to confidently shape the future of our increasingly connected digital world.

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.

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

Healthcare organizations have more data than ever before, but turning that data into actionable insights remains one of the industry's biggest challenges. In this episode of The Beat AI in Healthcare Podcast, host Sandy Vance sits down with Nabil Jallouli, CEO and co-founder of Rollstack, to discuss how AI-powered reporting is helping healthcare organizations simplify value-based care reporting, improve decision-making, and scale personalized reporting without overwhelming their teams. Nabil shares why dashboards alone are no longer enough, why executives need trusted narratives instead of raw data, and how healthcare organizations can automate reporting while maintaining governance, security, and accuracy. Whether you work in healthcare leadership, data analytics, customer success, value-based care, or digital transformation, this conversation offers practical insights into using AI responsibly to improve reporting and business outcomes.  In this episode, they talk about: Why value-based care requires an entirely different approach to healthcare reporting The hidden "last mile" problem between business intelligence dashboards and executive decision-making Why healthcare organizations struggle with manual reporting despite major investments in analytics platforms How AI can automate repetitive reporting while keeping humans focused on strategy and relationships The importance of governance and trusted data in healthcare AI Why executives rarely spend more than a few seconds reviewing dashboards How personalized reporting improves payer, provider, and customer relationships The role of automation in scaling reporting across hundreds of healthcare partners Measuring ROI from AI reporting solutions and why reporting automation often delivers significant business value Why healthy skepticism around AI is actually helping healthcare adopt better long-term solutions How Rollstack protects sensitive healthcare data with enterprise-grade security and zero data retention policies What healthcare leaders should prioritize as AI adoption continues to accelerate A Little About Nabil: Nabil Jallouli is the co-founder and CEO of Rollstack, an enterprise platform helping companies like SoFi, Zillow, and Whirlpool automate their data-driven presentations and documents. Rollstack leverages deep integrations with leading business intelligence tools (Tableau, Power BI, Looker, and others) and AI to streamline reporting processes, including business reviews, EHR and HCP reporting, financial reporting, and client presentations. By eliminating manual copy-paste, reducing errors, and ensuring accuracy, Rollstack enables organizations to operate more efficiently and focus on decision-making rather than document preparation. The company is backed by Y Combinator and Insight Partners and is fully SOC 2 Type II and HIPAA compliant, meeting the highest standards of security and data protection for enterprise and healthcare customers. Before founding Rollstack, Nabil built his career leading data analytics and revenue strategy teams at Pinterest, Deel, and Groupon. Across these experiences, he observed a common problem: highly skilled professionals spending countless hours preparing slides and reports instead of focusing on high-value work and strategy. This recurring pain point ultimately inspired the creation of Rollstack. Nabil holds a Master of Engineering and dual Bachelor's degrees in Mathematics, Physics, and Computer Science from École Centrale Paris.

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.

Charlie and Oz reconnect after a year to tackle the question of our times: now that coding agents actually work, does learning computer science still matter — and is the agent an asset to your growth or a liability? They get into RLVR and why agents crossed the threshold, Amdahl's law as a metaphor for automated productivity, why Oz still wants everyone to write a little assembly, and the creeping fear that agents sap "the will to learn" the same way social media saps attention. Then the constructive turn: using agents to build your own challenges within your zone of proximal development, why you should read the back of the textbook chapter first, and Oz's homework for Charlie — figure out what you earnestly want to learn, not what you feel you should.Shownotes:Steve Krouse of Val Town's post on why coding is still worth learning Amdahl's lawVygotsky's zone of proximal developmentBloom's 2 sigma problemOz's blogCharlie's blog

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.

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.

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

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.

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.