Podcasts about ML

Maney came across an article where a man in India found a snake unconscious and gave it mouth-to-mouth CPR. He brought it back to life! We asked each other what animal we'd give CPR to. Plus, Maney wants to know why LauRen is not in the holiday spirit yet, and our "Momtern" tells us which age is harder to parent, toddler or teenager? Listen every week to the Wrap Party for an unscendored ML podcast! See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Our guest on this week's episode is Marc Schaffer, principal economist at Breakthrough Fuel. Sometime in the new year we will likely find out whether the huge mega-merger between two historic railroads will go through. Union Pacific and Norfolk Southern aim to join forces to create a true transcontinental railroad. But it's not without controversy. What will the effects be on our nation's supply chains? This week's guest offers some insights. Warehouses are getting smarter every day. A study released just after Thanksgiving shows that artificial intelligence (AI) and machine learning (ML) are no longer just experimental tools but are becoming core drivers of productivity, accuracy, and workforce evolution in the warehouse. This is according to a study from Mecalux and the MIT Intelligent Logistics Systems Lab at MIT's Center for Transportation and Logistics. This week we reported on a story about the people behind AI and other leading edge technologies. It wasn't about the software coders who write the instructions for AI and large language models and other platforms. But rather it was about the electricians and manufacturing experts who keep all this stuff running. The reports came from Siemens USA, the American arm of the German industrial technology provider, and they announced a plan to train 200,000 electricians and manufacturing experts by 2030. Supply Chain Xchange  also offers a podcast series called Supply Chain in the Fast Lane.  It is co-produced with the Council of Supply Chain Management Professionals. A new series is now available on Top Threats to our Supply Chains. It covers topics including Geopolitical Risks, Economic Instability, Cybersecurity Risks, Threats to energy and electric grids; Supplier Risks, and Transportation Disruptions  Go to your favorite podcast platform to subscribe and to listen to past and future episodes. The podcast is also available at www.thescxchange.com.Articles and resources mentioned in this episode:Breakthrough FuelStudy: AI now imbedded in 60% of warehousesSiemens USA plans to hire 200,000 electricians and manufacturing experts by 2030Visit Supply Chain XchangeListen to CSCMP and Supply Chain Xchange's Supply Chain in the Fast Lane podcastSend feedback about this podcast to podcast@agilebme.comThis podcast episode is sponsored by: ID LabelOther linksAbout DC VELOCITYSubscribe to DC VELOCITYSign up for our FREE newslettersAdvertise with DC VELOCITY

This episode examines a new CNA model that can help government officials optimally deploy unmanned systems, and how it overlaps with our existing tools. Guest Biographies Arpita Verma is an expert in optimization, modeling, and simulation in CNA's Data Science for Production Program. John Crissman is an expert in artificial intelligence (AI), machine learning (ML) and natural language processing in CNA's Center for Data Management Analytics. Rebekah Yang is an expert in artificial intelligence and machine learning (AI/ML) for FAA NextGen and a specialist in data visualization and modeling in CNA's Center for Data Management Analytics. Further Reading UAS Cooperative Airspace Traffic Simulation (UCATS) First Responder Awareness Monitoring during Emergencies (FRAME) 

Thanks to Prosus Group for collaborating on the Agents in Production Virtual Conference 2025.Abstract //The discussion centers on highly technical yet practical themes, such as the use of advanced post-training techniques like Direct Preference Optimization (DPO) and Parameter-Efficient Fine-Tuning (PEFT) to ensure LLMs maintain stability while specializing for e-commerce domains. We compare the implementation challenges of Computer-Using Agents in automating legacy enterprise systems versus the stability issues faced by conversational agents when inputs become unpredictable in production. We will analyze the role of cloud infrastructure in supporting the continuous, iterative training loops required by Reinforcement Learning-based agents for e-commerce!Bio // Paul van der Boor (Panel Host) //Paul van der Boor is a Senior Director of Data Science at Prosus and a member of its internal AI group.Arushi Jain (Panelist) // Arushi is a Senior Applied Scientist at Microsoft, working on LLM post-training for Computer-Using Agent (CUA) through Reinforcement Learning. She previously completed Microsoft's competitive 2-year AI Rotational Program (MAIDAP), building and shipping AI-powered features across four product teams.She holds a Master's in Machine Learning from the University of Michigan, Ann Arbor, and a Dual Degree in Economics from IIT Kanpur. At Michigan, she led the NLG efforts for the Alexa Prize Team, securing a $250K research grant to develop a personalized, active-listening socialbot. Her research spans collaborations with Rutgers School of Information, Virginia Tech's Economics Department, and UCLA's Center for Digital Behavior.Beyond her technical work, Arushi is a passionate advocate for gender equity in AI. She leads the Women in Data Science (WiDS) Cambridge community, scaling participation in her ML workshops from 25 women in 2020 to 100+ in 2025—empowering women and non-binary technologists through education and mentorship.Swati Bhatia //Passionate about building and investing in cutting-edge technology to drive positive impact.Currently shaping the future of AI/ML at Google Cloud.10+ years of global experience across the U.S, EMEA, and India in product, strategy & venture capital (Google, Uber, BCG, Morpheus Ventures).Audi Liu //I'm passionate about making AI more useful and safe.Why? Because AI will be ubiquitous in every workflow, powering our lives just like how electricity revolutionized our society - It's pivotal we get it right.At Inworld AI, we believe all future software will be powered by voice. As a Sr Product Manager at Inworld, I'm focused on building a real-time voice API that empowers developers to create engaging, human-like experiences. Inworld offers state-of-the-art voice AI at a radically accessible price - No. 1 on Hugging Face and Artificial Analysis, instant voice cloning, rich multilingual support, real-time streaming, and emotion plus non-verbal control, all for just $5 per million characters.Isabella Piratininga //Experienced Product Leader with over 10 years in the tech industry, shaping impactful solutions across micro-mobility, e-commerce, and leading organizations in the new economy, such as OLX, iFood, and now Nubank. I began my journey as a Product Owner during the early days of modern product management, contributing to pivotal moments like scaling startups, mergers of major tech companies, and driving innovation in digital banking.My passion lies in solving complex challenges through user-centered product strategies. I believe in creating products that serve as a bridge between user needs and business goals, fostering value and driving growth. At Nubank, I focus on redefining financial experiences and empowering users with accessible and innovative solutions.

In this episode of the Technology & Security podcast, host Dr. Miah Hammond-Errey is joined by Kate Carruthers. Kate is currently the head of data analytics and AI at the Australian Institute of Company Directors. She shares her journey from defending Westfield against state and non-state cyber attacks to leading UNSW's enterprise data, AI, and cybersecurity efforts, including delivering the university's first production AI system in 2019 and re-architecting its cloud data platform for AI and ML. She notes boardrooms are evolving from basic cyber literacy to probing AI risks like models, data, and risk registers.  Carruthers outlines some real-world examples, such as UNSW's enterprise AI program, including a machine learning model that predicted which students were likely to fail a course, with 95%+ accuracy, so the university could design careful, humane intervention protocols to reduce self-harm risk. She argues that while frontier models like OpenAI and Gemini have a place, their compute costs, water intensity and general-purpose design make them poorly suited to some business problems, and that the future lies in smaller, industry-specific models trained on highly relevant data. The conversation covers the rise of agentic AI coding tools, the risk of deskilling junior developers, and the need for diverse, product-focused teams to translate technical systems into workable human processes.​ On security, she prioritizes CIA triad integrity over confidentiality, warning of data alterations in cars, medical devices, and government systems via poisoning or underinvestment in encryption. Carruthers urges Australian AI sovereignty—opting for open-source like Databricks over proprietary stacks—amid US-China model contrasts and outage risks from providers like AWS or CrowdStrike. Throughout, she encourages leaders not just to read about AI but to use multiple systems themselves, understand their limitations as probabilistic tools in deterministic business environments, and ground every deployment in clearly defined problems, ethics, and user needs.​

As the Women in Machine Learning Workshop (WiML) marks its 20th annual gathering, cofounders, friends, and collaborators Jenn Wortman Vaughan and Hanna Wallach reflect on WiML's evolution, navigating the field of ML, and their work in responsible AI.Show notes

In this episode of The Identity at the Center Podcast, hosts Jim McDonald and Jeff Steadman catch up with John Tolbert, Director of Cybersecurity Research at KuppingerCole Analysts, to talk about the rapidly evolving world of Fraud Reduction Intelligence Platforms (FRIP).They explore:The six capabilities of modern fraud reduction systemsHow AI and machine learning are both helping and hurting fraud preventionWhy shared signals and orchestration are critical for financial and e-commerce use casesHow identity verification, device intelligence, and behavioral biometrics work togetherThe role of usability and integration in FRI adoptionPlus, stick around for a fun discussion about concerts, classic rock, and which legendary bands they wish they'd seen live.Listen now to learn how identity, fraud, and AI are colliding — and what's next for fraud intelligence.Connect with John: https://www.linkedin.com/in/john-tolbert/Fraud Reduction Intelligence Platforms - Finance (KuppingerCole Report): https://www.kuppingercole.com/research/lc80841/fraud-reduction-intelligence-platforms-financeFraud Reduction Intelligence Platforms - eCommerce (KuppingerCole Report): https://www.kuppingercole.com/research/bc81030/fraud-reduction-intelligence-platforms-ecommerceConnect with us on LinkedIn:Jim McDonald: https://www.linkedin.com/in/jimmcdonaldpmp/Jeff Steadman: https://www.linkedin.com/in/jeffsteadman/Visit the show on the web at http://idacpodcast.comChapter Timestamps:00:00 – Jim's passwordless rant and setup woes05:00 – Introducing guest John Tolbert06:30 – Catching up: four years since John's last appearance07:30 – What is CIAM and how has it evolved?09:30 – Understanding Fraud Reduction Intelligence Platforms (FRIP)10:00 – The six core capabilities of FRI solutions13:00 – Are most vendors point solutions or full platforms?14:00 – How identity verification is improving16:00 – SaaS and API-driven fraud detection models18:00 – What kinds of fraud can (and can't) FRI prevent?21:00 – The growing problem of bots and automation22:00 – Fraud trends in finance: scams, account takeovers, and synthetic identities25:00 – Information sharing and the role of shared signals28:00 – Collaboration vs. competition in fraud prevention31:00 – Fraud in e-commerce: bots, loyalty points, and returns abuse34:00 – Streaming and citizen fraud use cases36:00 – Where do FRI capabilities fit within IAM platforms?43:00 – The importance of orchestration and integration44:30 – The role of AI and ML in fraud prevention47:30 – Smart questions for evaluating FRI vendors50:30 – Concert talk: Pink Floyd, Metallica, and the ones that got away58:00 – Wrap-up and where to find John Tolbert's reportsKeywords:Fraud Reduction Intelligence, FRI Platforms, John Tolbert, KuppingerCole, Identity at the Center, IDAC, IAM, CIAM, Cybersecurity Research, Fraud Prevention, Machine Learning, Artificial Intelligence, Behavioral Biometrics, Device Intelligence, Identity Verification, Risk Orchestration, API Security, Financial Fraud, E-Commerce Fraud, Shared Signals, Jim McDonald, Jeff Steadman, IDAC Podcast

Ram Ramanathan, Vice President of Product at Ribbon Communications, joined Doug Green, Publisher of Technology Reseller News, to discuss Acumen, Ribbon's new AI-powered platform designed to accelerate autonomous networking for service providers and enterprises. Ramanathan explains that rapid shifts—5G adoption, cloud-native architectures, heightened security demands, and a retiring telecom workforce—have created urgent pressure for automation. “We focus on practical, pragmatic AI that delivers real ROI—not hype,” he noted. Practical Automation Across the Service Lifecycle Acumen provides end-to-end observability and automation using real-time data and ML. It is vendor-agnostic, spans OSI layers 0–7, and includes a low-code/no-code Builder that allows Ribbon to tailor automation workflows and chatbots to each customer's environment. Real Deployments Already Underway Ribbon is working with several tier-one operators, including a major mobile provider moving from 4G to 5G across a multi-vendor network. Acumen is helping automate fault management, speed root-cause analysis, and proactively inform customer-facing teams. “It's not just fixing issues faster—it's keeping everyone, including the customer, informed,” Ramanathan said. Looking Ahead Ramanathan cautions organizations to avoid AI hype by setting realistic expectations and focusing on high-ROI outcomes first. “Break it into stages and show progress along the way,” he advised. Learn more at ribboncommunications.com.

New Study: Vitamin D Reduces Recurrent Heart Attacks by 50%? Ep. 1269 NOV 2025________________________________________Prevent Recurrent Heart Attacks, Targeted Vitamin D Dosing, Acute Coronary Syndrome Treatment, TARGET-D Trial Results 2025, Vitamin D Levels for Heart Health, Reducing MACE Risk, Intermountain Health Study.In this episode, we dive into the groundbreaking TARGET-D trial (presented at AHA 2025) that shows how "treating to target"—adjusting Vitamin D dosage to reach specific blood levels—may significantly reduce the risk of recurrent heart attacks. While the overall cardiovascular risk (MACE) didn't change statistically in the broad group, the study found a significant reduction in repeat heart attacks (Myocardial Infarction) for those in the treatment group. Learn the difference between "Intention to Treat" and "Per Protocol" analysis and what this means for secondary heart prevention.Source: May HT, Le VT, Anderson JL, et al. A Randomized Clinical Trial Evaluating Vitamin D Normalization on Major Adverse Cardiovascular-Related Events Among Acute Coronary Syndrome Patients: The TARGET-D Trial. Abstract presented at: American Heart Association Scientific Sessions 2025; November 9, 2025; New Orleans, LA.Disclaimers:• This information is for educational purposes only and should not be interpreted as medical advice.• The study discussed was conducted on Acute Coronary Syndrome patients (survivors of heart attack or unstable angina). These findings may not apply to the general healthy population.• Always consult with a qualified healthcare professional before making any changes to your diet, supplement regimen, or treatment plan.#VitaminD #HeartAttack #TARGETD #Cardiology #MedicalResearch________________________________________citation,TARGET-D trial,Vitamin D3 supplementation,Acute Coronary Syndrome,myocardial infarction reduction,heart attack prevention,treat to target vitamin D,cardiovascular health,25-hydroxyvitamin D,randomized clinical trial 2025,MACE outcomes,vitamin D deficiency,heart failure hospitalization,recurrent heart attack,vitamin D dosing algorithm,nutrition and heart disease,secondary prevention cardiology,vitamin D levels 40 ng/mL

Artificial Intelligence and Machine Learning in Human Resources: A Concise Guide by Dr. C. Rasmussen https://www.amazon.com/Artificial-Intelligence-Machine-Learning-Resources/dp/B0FWZQXHMG Curtisrasmussen.focalpointcoaching.com What if a computer could help find the perfect employee or predict who might leave a job? This exciting idea opens the door to a new way of working. Overview This guide explains how artificial intelligence (AI) and machine learning (ML) are transforming human resources (HR). Smart computer programs can quickly review thousands of job applications to find the best candidates, suggest training tailored to employees’ needs, and predict which workers might quit, helping managers take action to keep them. The book includes real-world examples, like how large companies use AI to save time, and covers benefits, such as improved hiring, as well as key concerns, like protecting personal information. At just 61 pages, it's concise by design, following Richard Feynman's wisdom: “If you can’t explain something simply, you don’t understand it well enough.” More pages don't equal more value; in fact, lengthy texts can bury useful insights. Since every organization is unique, this book equips HR professionals and managers with the right questions to ask rather than a rigid roadmap, making it a practical tool for anyone curious about the future of work. About the author Dr. Curtis “Curt” Rasmussen is a leading expert in industrial-organizational psychology with a Ph.D. from Walden University. He specializes in blending human skills with artificial intelligence (AI) and machine learning (ML) to make workplaces better and more efficient. With years of experience in research, consulting, and government roles, he helps businesses use data and tech wisely. His career highlights include owning Cyber-Human Performance Tech, LLC, where he advises small and mid-sized companies on adding AI to hiring and daily tasks while keeping things ethical. He also guides students in George Mason University’s Data Engineering program, focusing on AI tools like natural language processing and computer vision. At the Cybersecurity and Infrastructure Security Agency (CISA), he led workforce planning as a senior I/O psychologist, creating surveys and frameworks that improved employee satisfaction by 45% and helped with smarter hiring. Earlier, he reviewed AI and data science proposals for the Department of Commerce, National Academy of Medicine, and the Office of the Director of National Intelligence, making sure projects were strong and fair. Dr. Rasmussen has invented patent-pending tools like the Multidimensional Algorithm Structure (MAS), which picks the best AI methods by checking data and company needs, and the eXplainable Artificial Intelligence Construct (XAIC), which makes AI easy to understand and trust by involving people in decisions. These ideas help fix common AI problems, like failures or hidden biases.

At Qdrant Conference, builders, researchers, and industry practitioners shared how vector search, retrieval infrastructure, and LLM-driven workflows are evolving across developer tooling, AI platforms, analytics teams, and modern search research.Andrey Vasnetsov (Qdrant) explained how Qdrant was born from the need to combine database-style querying with vector similarity search—something he first built during the COVID lockdowns. He highlighted how vector search has shifted from an ML specialty to a standard developer tool and why hosting an in-person conference matters for gathering honest, real-time feedback from the growing community.Slava Dubrov (HubSpot) described how his team uses Qdrant to power AI Signals, a platform for embeddings, similarity search, and contextual recommendations that support HubSpot's AI agents. He shared practical use cases like look-alike company search, reflected on evaluating agentic frameworks, and offered career advice for engineers moving toward technical leadership.Marina Ariamnova (SumUp) presented her internally built LLM analytics assistant that turns natural-language questions into SQL, executes queries, and returns clean summaries—cutting request times from days to minutes. She discussed balancing analytics and engineering work, learning through real projects, and how LLM tools help analysts scale routine workflows without replacing human expertise.Evgeniya (Jenny) Sukhodolskaya (Qdrant) discussed the multi-disciplinary nature of DevRel and her focus on retrieval research. She shared her work on sparse neural retrieval, relevance feedback, and hybrid search models that blend lexical precision with semantic understanding—contributing methods like Mini-COIL and shaping Qdrant's search quality roadmap through end-to-end experimentation and community education.SpeakersAndrey VasnetsovCo-founder & CTO of Qdrant, leading the engineering and platform vision behind a developer-focused vector database and vector-native infrastructure.Connect: https://www.linkedin.com/in/andrey-vasnetsov-75268897/Slava DubrovTechnical Lead at HubSpot working on AI Signals—embedding models, similarity search, and context systems for AI agents.Connect: https://www.linkedin.com/in/slavadubrov/Marina AriamnovaData Lead at SumUp, managing analytics and financial data workflows while prototyping LLM tools that automate routine analysis.Connect: https://www.linkedin.com/in/marina-ariamnova/Evgeniya (Jenny) SukhodolskayaDeveloper Relations Engineer at Qdrant specializing in retrieval research, sparse neural methods, and educational ML content.Connect: https://www.linkedin.com/in/evgeniya-sukhodolskaya/

Charu Roy, Chief Product Officer at Enlil, shares her extensive journey in the software industry, which began in the late 1980s and evolved into her leadership role in medtech. Charu discusses her role at Enlil, where she oversees the development of an AI-powered platform to enhance medical device lifecycle management. She emphasizes the importance of understanding customer needs, fostering team potential, and ensuring cybersecurity in medtech software solutions. With profound insights on her career growth, leadership style, and the technological advancements propelling the industry forward, Charu's story is an inspiring tale of innovation and dedication to improving lives.  Guest links: https://enlil.com/ |  https://www.linkedin.com/company/enlil-inc/ Charity supported: ASPCA Interested in being a guest on the show or have feedback to share? Email us at theleadingdifference@velentium.com.  PRODUCTION CREDITS Host & Editor: Lindsey Dinneen Producer: Velentium Medical   EPISODE TRANSCRIPT Episode 069 - Charu Roy [00:00:00] Lindsey Dinneen: Hi, I'm Lindsey and I'm talking with MedTech industry leaders on how they change lives for a better world. [00:00:09] Diane Bouis: The inventions and technologies are fascinating and so are the people who work with them. [00:00:15] Frank Jaskulke: There was a period of time where I realized, fundamentally, my job was to go hang out with really smart people that are saving lives and then do work that would help them save more lives. [00:00:28] Diane Bouis: I got into the business to save lives and it is incredibly motivating to work with people who are in that same business, saving or improving lives. [00:00:38] Duane Mancini: What better industry than where I get to wake up every day and just save people's lives. [00:00:42] Lindsey Dinneen: These are extraordinary people doing extraordinary work, and this is The Leading Difference. Hello and welcome back to another episode of The Leading Difference podcast. I'm your host Lindsey, and today I'm absolutely delighted to introduce you to Charu Roy. Charu is the Chief Product Officer at Enlil, where she leads product strategy, vision, and execution for the company's AI powered medtech development platform. With over two decades of experience building and scaling enterprise software products, Charu brings deep industry expertise in product management, user-centered design, and go to market leadership. Before Enlil, she held senior product roles at industry leaders, including Epicor, Oracle, I-2 Technologies slash Aspect Development, HP and Agile Software, where she drove software innovation across enterprise cloud SaaS and data driven solutions. Known for her ability to align customer needs with business strategy, she is passionate about delivering products that transform complex industries and enable measurable impact. Well, welcome, Charu, to the conversation today. I'm so excited to be speaking with you. [00:01:54] Charu Roy: Thank you so much for having me. I'm very really excited about being here on this podcast. [00:02:00] Lindsey Dinneen: Oh, awesome. Yeah. Well, I would love, if you wouldn't mind starting off by sharing a little bit about yourself, your background, and what led you to medtech. [00:02:10] Charu Roy: Sure. As every other sort of person who gets into the software world, I came in a while back in 1987 to 89, where I did Master's in Computer Science at University of Louisiana. That was my first introduction to America, really. And computer science brought me to the Bay Area where I worked at HP, Hewlett Packard. In those days, it was called Scientific Instruments Division in Palo Alto. And there I programmed robotic hands to, to sort of move that, the vial from samples, drug samples from athletes so that they could get tested for drugs. So, I didn't know the importance of all this. It was my first job. I enjoyed myself seven years, you know, software programming, really, and understood how a large company works. And then slowly I started getting a little bored. So I went on to my next startup and was involved in the same kind of principles that drive things today. So I just sort of built my way up. In terms of the software, I joined different groups, ran consulting services, ran engineering, and sort of worked myself up through the ranks and into sort of more decision making capabilities, and you know, continued to join companies and learn new things and leave them for some better opportunities. So I moved from Hewlett Packard to a startup that was called Aspect Development, which got sold to I-2 Technologies for $9.3 billion in those days. So, you know, I went through that acquisition, trying to understand the market, what kind of software triggers buying, you know-- so sort of just the software aspects of how to sell software, how to develop software, how to deploy it. So in general, I was learning all of the ropes until I came to Agile PLM, which is a company which, very popular company which made it very sort of easy to deploy software, especially software called Product Lifecycle Management. So I was -- here, I was in and out of companies, learning and understanding the world of software until I fell into med device companies being my customers. So med device being our customers meant, you know, a lot more strictness, a lot more process, with the software itself. So here I was trying to now go through those kind of features, trying to understand what med device needed when they were building products. So, from Agile, I went to Conformia. Again, it was the same, it was regulatory product for wine, spirits and pharma --very adjacent to med device. But again, it was the same thing about how to be provide, how to provide a traceable platform where our customers can trace there, the make of the wine or make of the spirit, or make of a pharma drug or make off of med device. All the principles underlying it are the same because it's a regulated product at the end of the day, but so that's how I kind of fell into it, and I enjoyed every bit of that until I got acquired by Oracle. And so I continued at Oracle doing the same thing over and over again; rebuilt the same products again at Oracle in the clouds, and I was managing the old Agile products. So it's an interesting journey where I was, you know, started off as a software programmer. And I didn't know anything about, you know, the use cases until the time I sort of joined Oracle and understood my customers better. And that's how I came in there. And of course I was at Epicor and finally I made my way to Enlil, which is a very small company, and I'm doing the same thing again. It's just with a different set of customers, very small to medium sized companies. So that's how my career sort of spanned 30 years. [00:06:11] Lindsey Dinneen: Wow. Oh my goodness. Well, there is so much to dive into all of that. Thank you for sharing. It's so cool to hear about all of the winding paths that lead us to maybe, you know, where we're meant to be in, in any given season. And yeah, I just love learning about it. So, okay. So I'm curious, you know, way back when did you like growing up, did you always have an interest in computers and computer science? Is this something you knew you wanted to get into? [00:06:40] Charu Roy: Not at all, actually it was a suggestion, and in those days, parents kind of suggested that you be a engineer or a doctor or a chartered accountant. The choices were very limited. And so my father said, "you will do computer science." And I said, "okay." And there I was and there was no, no sort of emotional attachment to any of those professions. And, I liked it well enough to continue, and I found it was easy enough to understand the principles and work at it. So yeah, there was no-- you know, in these days I think kids are training themselves like by seven or eight to program. And I'm seeing, you know, machine language I mean AI, ML, LLMs being taught to seven year olds and sort of trying to shape them, but in those days it was just some very simple choices, I guess. So, yeah, not a very romantic story. I was never programming younger in my younger days, but I think you know, compared to all the choices youngsters have these days, but just fell into it. [00:07:44] Lindsey Dinneen: Sure. Oh, how fun. You know, even though, yes, it was somewhat prescribed for you, at least originally, and I'm so glad that you fell in love and it ended up being a happy place for you because... [00:07:57] Charu Roy: Yeah, and I think I fell in love with the customer, how customers reacted to the software. I didn't fall in love with the software delivery process or anything else, but it was just the way customers said, "oh, I like that. It's gonna make it easier for me to do something. I'm having a tough time tracking it on paper. I just hate it what I'm doing right now, and your software will help." So I think that's a part that makes me feel really pleased that okay it's going into some good hands and it's going to be used. [00:08:30] Lindsey Dinneen: Yes, by people who really appreciate and value what you can contribute, what maybe comes --at this point, I guess-- naturally to you. And so it's, you're able to translate somebody's ideas or dreams into a really tangible solution. [00:08:48] Charu Roy: Yeah. And in fact, somebody's pain points, like they're really sort of, trying their best to use little resources they might have, wasting a lot of time on either tracking something on paper or in emails. And I think those are the kind of pain points that I really like to understand and say, "Hey, will the software help really help your day to day life? Will it make it easier to find things?" I think that's where I find my sort of biggest thrill of when a customer says, "Yes, you shaved off three hours of my time by giving me this efficient system." [00:09:26] Lindsey Dinneen: Nice. Yeah. Oh my goodness. Yes , and the products that you're making are indeed life impacting and make a difference. And that is rewarding because you know that the work you --do all work is important, but it's really fun when you get to know personally the impact that you get to have. [00:09:45] Charu Roy: Right, right. [00:09:46] Lindsey Dinneen: Yeah. Yeah. So, okay, so I'm, I'd love to dive in a little bit more to your current company and role and learn about that, and how you're helping, you're still helping people you know, win through this. [00:10:00] Charu Roy: So, yes, absolutely. Enlil is part of Shifamed, the portfolio. Shifamed invests in med device devices typically, so ophthalmology devices or cardio devices. Enlil came about as an enterprise software company within the portfolio because they realized that they needed some software to throw all their data into, right? So they had early designs, prototype data. They might have had some user requirements, what kind of standards they might have to follow. So all those were floating about, again, in emails and paper. Enlil came in saying that we can store this data more successfully, more cleanly in a structured fashion so that our users can find that data. And this becomes really important as the med device company moves on and tries to apply for regulatory approval at that time, they need all that history and the data behind the device. And they wanna be able to find it easily and present it to auditors. So, Enlil's a structured way of describing all the data that the customer has and being able to find it easily and then run their audits using the data. So it's a very crucial part of their lifecycle, their product lifecycle. And so it's really important for us to be secure, reliable, available, 24/7. All of that applies to us and basically defines how they go about driving their product lifecycle. [00:11:34] Lindsey Dinneen: Yeah. Well, and you know, one thing that stood out to me when you were talking about that was of course the security aspect. And as we all know, we're, we're probably much more so than in the past, hyper aware of the critical need for cybersecurity and the role it plays specifically in medical device technology. And I'm curious if you could speak a little bit more to that particular element. [00:11:55] Charu Roy: Yeah, we have a lot of layers of security, you know, right from the folks who are accessing the software. The software is hosted in a well-known, reputable cloud service environment. So apart from them providing us cybersecurity and access control and everything else, we have another set of layers on top of that. So our users are vetted and they all have a password. People can be invited and not just sort of show up. So, there's a lot of control of what they can see and can do. Every button sort of, you know, has a role behind it or a layer of control. So not everyone can do everything and press any and all buttons. So, security is at many levels. And we also have a lot of audit trails, e-signatures, and so on. So everything is done to protect the data, and audits are run regularly by them and by us to make sure that nobody who's supposed to be, you know, people who are not supposed to see the data, don't see the data. [00:13:01] Lindsey Dinneen: Yeah. Excellent. Yeah, I know that's just something that is, should be at least, on the forefront, especially of startups' minds as they're thinking about this and working towards having a really secure device. So it sounds like you've built in all of that safeguarding really well and really intentionally. So, so, okay, so I know that -- well, there's a few things that really stood out to me on your LinkedIn profile, and I'm just curious if we could dive into a couple things. One was, I love how you said that you're "passionate about teams and people delivering to their full potential," and I was wondering if you could speak a little bit more to that. [00:13:42] Charu Roy: Yeah, so, you know, along the years I've noticed that people in my team, the team members, they're there, they're working hard, but I do like to understand what's making them tick, what might they be wanting to do, which they haven't got gotten to do yet. Can we unlock some potential, some skill, some talent? And I think that comes about by sort of just talking about it , trying to give them openings about, "Hey, look, I've got this cool project or this cool feature. Any thoughts on that?" Just to understand, are they happy doing what they're doing, or is there something more they could do? And so I think that human touch, you know, is -- it was given to me, or at least it was taught to me by some mentors along the way. And I think that's a part that I really like to explore and see how can teams do better, not just in a numbers, not just turnaround features and releases on time, but are they happy doing it? Did they contribute something meaningful along the way? Did they feel they grew in the process? Did they feel they were recognized for some new responsibilities that they may not have stepped up for in some other companies? So that's a feeling I'm trying to always give them and sort of hoping that we contribute to their growth, not just the company and the bottom line. [00:15:02] Lindsey Dinneen: Yeah, that's critical and key,, and really speaks to who you are as a leader. And I'm actually very curious, you know, you mentioned earlier having kind of worked your way up at HP and then, you know, that may be opening some doors for you for of course, your future opportunities, and I'm curious, what has your own leadership journey looked like? Has, does leadership come naturally to you? Have you spent a lot of, you know, time and resources, whatever, developing those skill sets or how did that work for you? [00:15:29] Charu Roy: I think I was thrown into the deep end of the pool several times, you know, like, so I kicked into the pool, so to learn to swim. So similarly I was made to take on responsibility pretty much the very beginning. So I kind of knew that there were certain things expected that I should be doing, can be doing and then this introspection saying that, did I give the right amount of energy to that particular responsibility and did I do well? So just a lot of introspection and being able to understand, did I do well as a leader? But I've been honing it, honing skills. I mean, nothing out of an MBA school, nothing out of, you know, college that helped me. I think it was just about pure interest in psychology, pure interest in humans, you know, just being able to connect and how did I make them feel? How did they make me feel in those interactions? And is that, was that good? Was there something we could do to incorporate more people to get that feeling of ownership or anything? So it wasn't a, you know, by rote or something that I learned in a school. It was more of just sort of. Being thrown into situations where I had to come out of it somewhat gracefully and some somewhat feeling like I had also learned along the way. [00:16:46] Lindsey Dinneen: Yeah. Yeah, that, that's wonderful and incredible. And I think, you know, you mentioned learning along the way, and one thing also that stood out to me was, the recommendations on your profiles are so lovely for you. And two things stood out: they, one thing was somebody mentioned you're always learning, which is a gift in and of itself. And then the other thing was you're always letting others succeed. And that's such a beautiful gift and I'm wondering if you could talk more about both of those as well. [00:17:16] Charu Roy: Yeah, I think it's not about just me being sort of the boss and being able to tell people what to do, though I think success comes from enabling or encouraging the teams to again contribute without any barriers, any levels, or politics. I love the fact that we are in a small company, and I can say safely that, you know, politics --in larger companies there are politics. People are always trying to sort of be showing that they are very valuable. But in a small startup, it's very quickly apparent that there are certain valuable players there and startups, everybody is valuable, right? So I think being able to encourage the team members to do what they think is best for the problem to solve it. And of course, there are reasons why you can't sometimes accept the solution, but the fact that they're thinking about it and the fact they're able to openly express their opinions and say, "No, you're wrong, Charu." I think this is the way to do it. I love that. I think, somebody disagrees with me in a meeting, I just think that's the best thing that could have happened as a style of management. Because I'm not, you know, insecure in that sense. I don't sulk afterwards. I have had bosses and so on who don't like that kind of, you know, disagreements in public. And I think that's a part where I beg to differ, and I want to have people say what they think, what are they feeling, what are the problems, really the truth, and fix it, really. So I think it's less waste of a time when people are honest, and get to the point, and we are able to solve it together rather than hide behind, you know, facades, I guess. [00:19:01] Lindsey Dinneen: Yeah, that's beautiful. And yeah, I've often said for me personally, that, you know, more heads are better than one. I mean, I could have a, an opinion on whatever it is that we're talking about, but really, until we collaborate and start sharing those ideas and those thoughts and opinions , all of a sudden those kinds of sparks happen where, you know, you start with one thing and then it, and then somebody else catches that and they take it even to the next level and it just keeps going. And it's so cool to see the creativity and problem solving and innovation that comes from allowing those conversations. [00:19:36] Charu Roy: Yes, exactly. Creativity and innovation. You've said it so well. That comes with smart people being in the same room, arguing, not agreeing, and then something comes out of that, right? I mean, either your thoughts get clearer because you've seen every side of the coin and you're able to say, "Okay, I know the pros and cons and we can go this way, knowing the full effect of what we are going to do." So I think surrounding myself with smart people who have varied opinions, I think that's a beauty and a blessing really. [00:20:12] Lindsey Dinneen: Yes it is, and you've nailed it with varying opinions. You know, it's easy to get yourself into a situation-- and not necessarily intentionally-- but just it's easy to give into a situation where you've surrounded yourself with people who all kind of have the same opinions on things. And so inviting those conversations to take place that might be difficult, might be challenging, might be frustrating at times, but allowing for that and being open to other points of view and experience. I mean, that's the beauty of a really good collaborative environment is all of those varying opinions that don't necessarily match yours. [00:20:50] Charu Roy: Yes, exactly. Exactly. [00:20:52] Lindsey Dinneen: Yeah. Yeah. So, okay, so looking back, could 10-year-old you have ever imagined where you'd end up today? [00:21:00] Charu Roy: No, absolutely not. I thought I wanted to be a doctor or something vague. 10-year-old me was climbing trees and eating guavas off the trees in Delhi. So it was really crazy childhood. And you know, it wasn't filled with studies and rules and stuff. So I think coming to this, a country when I was young, being able to absorb everything, the culture, the of course the education itself and being able to sort of grow within the companies that I joined, i, I think that was the journey that I was sort of a pointing more towards rather than the childhood me. The childhood me was horrible, I think. [00:21:46] Lindsey Dinneen: Oh man. Honest reflection right there. That's awesome. Yeah, okay. Are there any moments that really stand out to you, perhaps with your current position or, you know, something in your past where you really thought, "Wow, what I'm doing makes a difference. I am in the right industry, at the right time, in the right place." [00:22:07] Charu Roy: I think it's the technology now that, you know, speaking from a technical viewpoint of shipping software, meaning full software, more easily, the time is now. I feel that the culmination of everything I've learned about pain points and users and customers, all of that's culminating in in the product that I'm managing right now, using new technologies, having the right technologies to choose from and being able to propel that software forward to our users. I feel that, "Wow, what a time to be a product officer really, when we have so many choices and being able to be able to apply that to real world problems and real pain points." I had the same pain points 20 years ago, even 30 years ago, but we couldn't do much. We had to, you know, write painful programs. We had to write database queries and, you know, things like that. It was quite painful, I would say. And then now to see all the tools where we can create things overnight and be able to ship it to customers, just hitting the nail on the head. We had to experiment a lot in the old days but I think the time now is is really special. We are on an sort of an industrial revolution or a computer science revolution here with the AI, MML, the LLMs, being able to do so much with probably less resources than before. So. [00:23:39] Lindsey Dinneen: Yeah. So seeing the impact of the work and getting to not have it be so painful. [00:23:45] Charu Roy: Yes. It used be very painful and now I'm thinking, I think we're at the right time, right place now with this product. And it's not just about the products. It's the kind of help we are getting as software professionals to help deliver software and support our users. I think that's really special and I, we are still learning, we're still trying to understand all the technologies that are available to us and how can we make our lives easier and our customers feel that we've solved some problems for them. [00:24:14] Lindsey Dinneen: Yeah, absolutely. And I think that there's just, it is really wonderful again-- just to, to circle back to this kind of been a running theme of getting to be able to experience for the end user or with the end user, that moment of, "Oh wow, I needed this is so helpful and it's gonna make a difference." [00:24:36] Charu Roy: Yeah. I remember in my past, same sort of software tracking wine being made. And that software was pretty cool. It, it used to track where the wine sat and which barrel for how long. And so the pleasure of talking to wine makers, and being able to show them how the software track the progress of the wine and being able to print out a label at the very end for them, saying that "this wine sat in these bottles or these barrels for a while," and that technology application for a simple, naive user, I thought that was it. That was the, you know, the culmination of all the learnings that I had over the years to be able to explain the software so easily to a end user who might be a distiller or a winemaker or somebody, a farmer. I thought that was pretty cool. And that since then, of course, technology has changed, but I think we're beginning to see the effect on a naive user, which we couldn't do, you know, 30 years ago. [00:25:37] Lindsey Dinneen: Yeah, absolutely. Oh my goodness. That is, it is so cool. And I love the work you're doing and just learning all about your history so far and just exciting to see where it's gonna end up too, and as you continue along your career path, but pivoting the conversation a little bit just for fun. Imagine that you were to be offered a million dollars to teach a masterclass on anything you want, could be within your area of expertise, it doesn't have to be. What would you choose to teach? [00:26:06] Charu Roy: I would probably think about teaching psychology of the individual. I don't have a PhD or a even basic courses in psychology, but I just love the fact that, you know, you can apply psychology, figure out how a user might or somebody might react to something that you say, do, think so I, if it was a master class and I'd be teaching you know, teaching more about life interactions, you know, ordinary interactions. How can they be made more meaningful, more fruitful, using psychological tricks or phrases? I don't know all of those things, but I would really think that I could teach that based on, you know, facial expressions, body mannerisms, or body-- what do they call it, sort of, you know, criminal stories. They read your mind based on certain mannerisms of flutter viol. So yes, psychology is a masterclass I would teach, but more applied to daily interactions, maybe work situations and being able to use psychology better to improve your own work relationships with people and even just general interactions. Yeah, so that would be my attempt at being a psychologist and eventually be a criminal psychologist. [00:27:28] Lindsey Dinneen: Yes. Oh my goodness. That would be so interesting. Yeah, I love that idea. And the masterclass sounds fabulous, so I'm signing up whenever you do it. [00:27:37] Charu Roy: Okay, I'll go get my degrees for it then. [00:27:40] Lindsey Dinneen: Right, right, right. Yeah. Ah, details. Awesome. How do you wish to be remembered after you leave this world? [00:27:50] Charu Roy: This is something that I've always felt deeply about. It's not what you say or what you do, it's how you make people feel, that Maya Angelo said that this much nicer than what I'm saying, but and I've had a few people say this to me, saying that, "We worked together 30 years ago, but that day you made me feel good." And I don't even remember what I said, what I did, but the fact that they remember me for what I made them feel. The fact that somebody also told me that they "don't avoid me when I'm walking up to them because, because I make them feel like things are okay, things are good, however bad the problem is." So they say that with other people they would duck and, you know, go away in the opposite direction. But with me they're waiting for me to come up to them. I'd like to continue that, that feeling that somebody feels like, "Hey, you are coming up to them and you just make them feel good in some fashion." Nothing else. I think that feeling, if I could evoke in people, they say, "Oh yeah, she made me feel good that day. I don't know what she said, but she made me feel good." That's enough. [00:29:01] Lindsey Dinneen: Yeah, that, yes, that is more than enough. What a beautiful legacy. Yeah, and then final question, what is one thing that makes you smile every time you see or think about it? [00:29:15] Charu Roy: I think my dogs smile. I would say he's got missing teeth and so when he looks at me when I first come, you know, come back home and he is smiling almost, and he is sniffling and, you know, trying to sneeze and smile at the same time. Oh my God, what kind of a character dog this is? So that makes me smile and laugh the whole time, especially the missing teeth. Poor thing. He doesn't understand that his teeth are missing because of me, and yet he's smiling at me, so. [00:29:50] Lindsey Dinneen: That is so sweet and cute. Oh my goodness. I love, I know somebody at one point said, "You know, dogs don't actually smile." I don't believe them. They smile. [00:30:00] Charu Roy: They smile and they choke while they smile because my dog has a small nose, I guess. So he chokes when he smiles, and so he is choking, and he is smiling, and this missing teeth there. I was like, "Oh my God." [00:30:16] Lindsey Dinneen: Oh my goodness. Yes. I mean, that would just I, yes, I can just sort of picture this. I love, love dogs and so I'm just picturing this and I, that would bring me joy every single day, definitely. Excellent. Well, this has been such a wonderful time spent with you today. Thank you for sharing your stories and your journey and your advice, and I really appreciate some of those in particular, your leadership advice, and the impact that you can have as a leader, inviting the collaboration, having conversations that encourage people to have varying opinions and maybe outright disagree with you. I love what you're wanting to, you know, wanting your legacy to be, and so that's how you're intentionally showing up in the world. And so I just wanna thank you so, so very much for being here. We're really grateful to have you. [00:31:10] Charu Roy: Thank you, and thank you so much for your intelligent questions and insightful questions that go above and beyond just you know, a company and it's gold. It's there, there's something so human about your questions-- and I love when I'm like, "Oh my goodness, this is so, so interesting to see in this day and age, somebody taking the time to ask such questions" and I really appreciate you for that. [00:31:36] Lindsey Dinneen: Oh, thank you. Well, I really appreciate that feedback too, because it's, you know, you come up with an idea-- speaking of sometimes echo chambers, you come up with an idea and you think, "Oh, this is how I'd like to go about this, but does it resonate with somebody else?" So that's delightful to hear. [00:31:51] Charu Roy: Fantastic, thank you, thank you for having me. [00:31:54] Lindsey Dinneen: And we're so honored to be making a donation on your behalf as a thank you for your time today to the American Society for the Prevention of Cruelty to Animals, which is dedicated to preventing animal cruelty in the United States. So thank you for choosing that organization to support Thank you so much, and gosh, I just wish you the most continued success as you work to change lives for a better world. And to all of our listeners for tuning in, I wanna thank you for being here as well. And if you're feeling as inspired as I am right now, I'd love it if you'd share this episode with a colleague or two, and we'll catch you next time. [00:32:31] Charu Roy: Thank you. [00:32:32] Dan Purvis: The Leading Difference is brought to you by Velentium Medical. Velentium Medical is a full service CDMO, serving medtech clients worldwide to securely design, manufacture, and test class two and class three medical devices. Velentium Medical's four units include research and development-- pairing electronic and mechanical design, embedded firmware, mobile app development, and cloud systems with the human factor studies and systems engineering necessary to streamline medical device regulatory approval; contract manufacturing-- building medical products at the prototype, clinical, and commercial levels in the US, as well as in low cost regions in 1345 certified and FDA registered Class VII clean rooms; cybersecurity-- generating the 12 cybersecurity design artifacts required for FDA submission; and automated test systems, assuring that every device produced is exactly the same as the device that was approved. Visit VelentiumMedical.com to explore how we can work together to change lives for a better world.

Send Bidemi a Text Message!In this episode, host Bidemi Ologunde spoke with data scientist and AI/machine learning (ML) enthusiast Daria Dubovskaia in a wide-ranging conversation about cybersecurity, data analytics, and building robust ML systems in the real world. Daria shares her journey from studying rocket propulsion in Russia to moving to the United States, completing a Master's degree in Data Science at CUNY, and working at a healthcare startup in Tampa, Florida. Along the way, she talks about cleaning messy data, deploying production models in the cloud, protecting sensitive information, and communicating complex insights to non technical stakeholders. This episode is full of practical lessons for anyone interested in data-driven decision-making, career pivots into tech, and the growing intersection of machine learning and cybersecurity.Support the show

Ismael (Founder/CEO) and Nate (Defense GTM) from Lagrange explain why the biggest commercial demand for cutting-edge cryptography might be outside crypto—securing AI in defense, healthcare, and regulated finance. We cover: why they built DeepProof (a zero-knowledge ML library that proves model outputs over private inputs), how this fits the DoD's zero-trust mandates, and why frontier crypto R&D should serve national interest, not just faster token launches. We also dig into GTM with government, what zero-knowledge adds beyond TLS, and how to talk “applied cryptography” without getting stuck in a “crypto” stigma.Key timestamps[00:00:00] Cold Open: Ismael on crypto funding frontier cryptography beyond tokens[00:01:00] Introduction: Sam sets up Lagrange, AI, defense, and applied cryptography[00:03:00] Origin Story: Ismael's path from TradFi and VC to founding Lagrange[00:06:00] Why Defense: Using crypto-funded cryptography for national security and AI safety[00:10:00] DeepProof Explained: Proving AI model outputs over private inputs with ZK[00:15:00] Business Model: “OpenAI sells inference; we sell proofs”[00:18:00] Beyond Crypto: Healthcare, compliance, and dual-use cryptography[00:22:00] Nate's Role: Selling applied cryptography to defense without leading with “crypto”[00:27:00] Lagrange Vision: Cryptographic supremacy and becoming the verifiability layer[00:33:00] Roadmap & Ask: Expansion into defense, partners with serious AI workloadsConnecthttps://www.lagrange.dev/https://www.linkedin.com/company/lagrange-labs/https://www.linkedin.com/in/i20h/https://x.com/lagrangedevhttps://x.com/Ismael_H_RDisclaimerNothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.Get featuredBe a guest on the podcast or contact us – https://www.web3pod.xyz/

In this episode, Rob Aragao welcomes back cybersecurity expert and author Michael Echols to unpack the urgent realities behind his new book, AI Chaos.Michael explains how AI is rapidly entering operational technology (OT) systems—the infrastructure that runs our power grids, water systems, transportation, satellites, and more. But with this transformation comes a critical problem: leaders don't truly understand where AI is operating, how it behaves, or how to control it.Together, Rob and Michael explore:How AI-driven OT systems are reshaping today's critical infrastructure threat landscapeWhy future failures may not come from hackers—but from AI-enabled automation that organizations can't see or shut offThe hidden vulnerabilities created by interconnected sensors, ML models, and autonomous decision loopsHow organizations should rethink resilience, governance, and risk in an AI-powered worldMichael's AIM Frame maturity model and how leaders can assess their readiness for AI incidentsPractical steps security and technology leaders should take now to map AI usage, increase visibility, and prepare for inevitable model drift or autonomous system failuresIf your organization relies on OT, automation, or AI-driven systems, this conversation is a must-listen wake-up call.Follow or subscribe to the show on your preferred podcast platform.Share the show with others in the cybersecurity world.Get in touch via reimaginingcyber@gmail.com As featured on Million Podcasts' Best 100 Cybersecurity Podcast and Best 70 Chief Information Security Officer CISO Podcasts rankings.

No soup for Erika Erickson, whose big scoop about a whistleblower at Campbell's is making national news … and ML, […]

00:20:00: Will the Bills make the playoffs after another loss in Houston? ML breaks it all down. Thanks to Rosie's Corner and CH Insurance. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Most companies don't have an AI problem. They have a decision-making problem. Matt Lea, founder of Schematical and CloudWarGames, has spent nearly 20 years helping tech leaders ship smarter. In this conversation, he breaks down when AI actually makes sense, where AWS costs spiral out of control, and why your "cool demo" keeps dying before launch. If you're tired of AI hype and ready for straight answers, hit play. Join the conversation! Our Discord community is full of ML engineers, researchers, and AI enthusiasts discussing papers, sharing projects, and helping each other level up. Whether you're debugging your first neural net or training your tenth transformer, there's a place for you.      Newsletter https://datascienceathome.substack.com/subscribe Website https://datascienceathome.com   References http://schematical.com https://cloudwargames.com https://schematical.com/posts/we-need-ai_20241028  

Dr. Jure Leskovec is the Chief Scientist at Kumo.AI and a Stanford professor, working on relational foundation models and graph-transformer systems that bring enterprise databases into the foundation-model era.Relational Foundation Models: Unlocking the Next Frontier of Enterprise AI // MLOps Podcast #348 with Jure Leskovec, Professor and Chief Scientist, Stanford University and Kumo.AI.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractToday's foundation models excel at text and images—but they miss the relationships that define how the world works. In every enterprise, value emerges from connections: customers to products, suppliers to shipments, molecules to targets. This talk introduces Relational Foundation Models (RFMs)—a new class of models that reason over interactions, not just data points. Drawing on advances in graph neural networks and large-scale ML systems, I'll show how RFMs capture structure, enable richer reasoning, and deliver measurable business impact. Audience will learn where relational modeling drives the biggest wins, how to build the data backbone for it, and how to operationalize these models responsibly and at scale.// BioJure Leskovec is the co-founder of Kumo.AI, an enterprise AI company pioneering AI foundation models that can reason over structured business data. He is also a Professor of Computer Science at Stanford University and a leading researcher in artificial intelligence, best known for pioneering Graph Neural Networks and creating PyG, the most widely used graph learning toolkit. Previously, Jure served as Chief Scientist at Pinterest and as an investigator at the Chan Zuckerberg BioHub. His research has been widely adopted in industry and government, powering applications at companies such as Meta, Uber, YouTube, Amazon, and more. He has received top awards in AI and data science, including the ACM KDD Innovation Award.// Related LinksWebsite: https://cs.stanford.edu/people/jure/https://www.youtube.com/results?search_query=jure+leskovecPlease watch Jure's keynote:https://www.youtube.com/watch?v=Rcfhh-V7x2U~~~~~~~~ ✌️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/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Jure on LinkedIn: /leskovecTimestamps:[00:00] Structured data value[00:26] Breakdown of ML Claims[05:04] LLMs vs recommender systems[10:09] Building a relational model[15:47] Feature engineering impact[20:42] Knowledge graph inference[26:45] Advertising models scale[32:57] Feature stores evolution[38:00] Training model compute needs[42:34] Predictive AI for agents[45:32] Leveraging faster predictive models[48:00] Wrap up

Ilya & I discuss SSI's strategy, the problems with pre-training, how to improve the generalization of AI models, and how to ensure AGI goes well.Watch on YouTube; read the transcript.Sponsors* Gemini 3 is the first model I've used that can find connections I haven't anticipated. I recently wrote a blog post on RL's information efficiency, and Gemini 3 helped me think it all through. It also generated the relevant charts and ran toy ML experiments for me with zero bugs. Try Gemini 3 today at gemini.google* Labelbox helped me create a tool to transcribe our episodes! I've struggled with transcription in the past because I don't just want verbatim transcripts, I want transcripts reworded to read like essays. Labelbox helped me generate the exact data I needed for this. If you want to learn how Labelbox can help you (or if you want to try out the transcriber tool yourself), go to labelbox.com/dwarkesh* Sardine is an AI risk management platform that brings together thousands of device, behavior, and identity signals to help you assess a user's risk of fraud & abuse. Sardine also offers a suite of agents to automate investigations so that as fraudsters use AI to scale their attacks, you can use AI to scale your defenses. Learn more at sardine.ai/dwarkeshTo sponsor a future episode, visit dwarkesh.com/advertise.Timestamps(00:00:00) – Explaining model jaggedness(00:09:39) - Emotions and value functions(00:18:49) – What are we scaling?(00:25:13) – Why humans generalize better than models(00:35:45) – SSI's plan to straight-shot superintelligence(00:46:47) – SSI's model will learn from deployment(00:55:07) – How to think about powerful AGIs(01:18:13) – “We are squarely an age of research company”(01:20:23) – Self-play and multi-agent(01:32:42) – Research taste Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

Season 7 of Innovators Inside kicks off with Sherwood “Woody” Neiss — entrepreneur, venture capitalist, architect of the JOBS Act, and author of Investomers. Woody walks through how investment crowdfunding went from an eight-bullet framework to a 485-page regulation that opened startup investing to everyday people. He and Ian dig into the rise of the “customer-investor,” why doctors, scientists, and operators are backing the tools they actually use, how crowdfunding is changing access to capital for women and minority founders, and why health tech and biotech are now leading the pack. They also explore how data, AI, and tighter feedback loops are creating new “signals” for VCs, what founders get wrong about valuation and communication, and why lean, disciplined fundraising is back.Topics & Timestamps

00:00-15:00: ML says Duke looks title ready again. Thanks to Byrne Dairy and Marz Motors. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Photo by Tim Wildsmith on Unsplash Published 24 November 2025 e534 with Michael, Andy and Michael – AI and ML training data, camouflage, ppen source Zork, Deadpool VR, NPH movies and a whole lot more. Michael, Andy and Michael start things off with with an intriguing AI analysis of the heist from the Louvre. The Ars Technica article takes the examples of mathematical machine learning and human psychology to show how both were defeated what was considered to be ordinary versus suspicious. This is a terrific reminder on the importance of the training data sets used for AI models and how the “performance of normality became the perfect camouflage”. Michael R highlights the On Intelligence book, and Michael M brings up visual pattern recognition of the human form which ghillie suits help disguise. Switching to a hackster.io article, the die is cast – or rather the die is 3d printed. Andy shares his thoughts on this bluetooth enabled die, and mentions how dice have featured prominently in the the podcast over the years. E132 from 2016 appears to be the earliest reference to dice in the show notes. Next up is Microsoft's announcement to open source the Zork family of text based adventure games from Infocom. Zork is another favorite of the podcast, and e78 from 2014 is the earliest reference! Then the team discusses the Deadpool VR game. The Kotaku article mentions that Neil Patrick Harris does the Deadpool voice acting in the game. This leads the cohosts down the rabbit hole of NPH acting with a number of movies and TV shows. Oh, and the reason for the “I don't want a McRib” part of the show title was because the Kotaku article kept serving up McDonalds McRib ads to Michael M, while Michael R with his PiHole does not get such ads. What is your favorite NPH movie or tv show? Have your bots

In this week's episode, Matthias Reinwarth and Alexei Balaganski discuss the growing importance of AI Data Provenance. The conversation explores why provenance is distinct from traditional logging, the operational gaps between ML engineering practices and regulatory expectations, and the regulatory context driving these requirements. They get into the risks of attempting to retrofit governance after AI systems are already deployed and explain why provenance must be built directly into data and model workflows. Key Topics Covered:✅ AI data provenance is a new and urgent issue.✅ Low-quality data leads to poor AI outcomes.✅ Auditing and compliance are essential for AI systems.✅ Organizations must establish governance for AI data.✅ Data catalogs and traceability are foundational.✅ Prepare for AI regulations like GDPR.✅ Start small and apply a risk-based approach.✅ Never trust, always verify your data sources.

Electric Indigo delivers a deep, focused and beautifully constructed mix recorded on November 21, 2025 exclusively for the Decisive Podcast Series. A selection shaped by experience, intention and clarity — weaving together some of her favorite current releases with an all-time ambient classic by Monolake. This mix reflects her perspective as a DJ, composer and cultural force: purposeful, precise and rooted in decades of exploration across the global electronic landscape.Electric Indigo - Decisive Podcast Mix recorded 2025-11-21I decided to mix some of my favorite current releases plus an all-time favorite ambient track by Monolake :-)01. Stenny - Sharp Fragments [Ilian Tape LP23]02. Trismus - Back And Forth [47 047]03. Om Unit - Rolling Stock / Beatrice M. Remix [Acid Dub Studies 003R]04. Wata Igarashi - Terra Incognita [Dekmantel UFO 19]05. Efdemin - Aachen [Ostgut Ton LP38]06. Yeiem - Colares 1977 [Humanoid Gods 37]07. Benales - Ash [Tar Hallow LP3-TH19]08. Efdemin - Microphase [Ostgut Ton LP38]09. Wata Igarashi - Meltzone [Dekmantel UFO 19]10. Torso - Reduced To Nothing [Edit Select 243D]11. Jin Synth - Undersurface [KR3 018]12. Linear System & Subtil - Psychoacoustic Horizon [Modern Minimal 055]13. Denise Rabe - Frozen Sky [30D ExoPlanets LP-003]14. Wata Igarashi - Unleashed [Dekmantel UFO 19]15. MAEDON - Impulse Response [Silencio 002]16. MAEDON - Entelechy IV / Lady Starlight Remix [Rant & Rave 010]17. Denise Rabe - Fifth Guardian [30D ExoPlanets LP-003]18. SSTROM - Förflyttning Av Massa [ROSTEN 11]19. THEGOD01 - Intermodulation Ritual [30D ExoPlanets 021]20. Chloe Lula - Myopia [Mord 120]21. Lukë - Haunted [Holobeat 019]22. BRUX - Ten [Hotflush 097]23. Kassian - Peech Blue (Extended Club Mix) [!K7 447RD]24. Monolake - Inwards [imbalance computer music ML-032]Electric IndigoWebsite: https://indigo-inc.at/Artist profile with links: https://media-loca.com/electric-indigo/Instagram: https://www.instagram.com/electricindigo/YouTube https://www.youtube.com/@decisivepodcastseriesInstagram (Decisive) https://www.instagram.com/decisive_podcast_radioSoundCloud https://soundcloud.com/roberto-q-ingram/sets/decisive-podcast-series-dyApple Podcasts https://podcasts.apple.com/de/podcast/decisive-podcast-series/id364388579#ExperimentalMusic #TechnoCulture #WomenInMusic #WomenInElectronicMusic #SoundArt #AudioVisual #ElectronicMusicPioneer #MusicCreativity #ViennaMusicScene #BerlinElectronic #ArtBeiTon #AdamX #30DRecords #GoetheInstitut #DJCulture #TechnoHistory #ElectronicArtist #MusicConversation #CreativeCulture #UndergroundMusic #CultureTalk #ArtistInterview #DecisiveConversations

Jeff Huber is the CEO of ​Chroma, working on context engineering and building reliable retrieval infrastructure for AI systems. Context Engineering, Context Rot, & Agentic Search with the CEO of Chroma, Jeff Huber // MLOps Podcast #348.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractJeff Huber drops some hard truths about “context rot” — the slow decay of AI memory that's quietly breaking your favorite models. From retrieval chaos to the hidden limits of context windows, he and Demetrios Brinkmann unpack why most AI systems forget what matters and how Chroma is rethinking the entire retrieval stack. It's a bold look at whether smarter AI means cleaner context — or just better ways to hide the mess.// BioJeff Huber is the CEO and cofounder of Chroma. Chroma has raised $20M from top investors in Silicon Valley and builds modern search infrastructure for AI.// Related LinksWebsite: https://www.trychroma.com/~~~~~~~~ ✌️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/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Jeff on LinkedIn: /jeffchuber/Timestamps:[00:00] AI intelligence context clarity[00:37] Context rot explanation[03:02] Benchmarking context windows[05:09] Breaking down search eras[10:50] Agent task memory issues[17:21] Semantic search limitations[22:54] Context hygiene in AI[30:15] Chroma on-device functionality[38:23] Vision for precision systems[43:07] ML model deployment challenges[44:17] Wrap up

00:00-15:00: ML and Joe Jr. are joined by Syracuse head men's basketball coach Adrian Autry to chat about the team's 4-0 start, getting J.J. Starling back, preparing for games at different times, the gauntlet ahead, Kiyan Anthony fitting right in and more. Sponsored by CH Insurance. In your corner. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

20201 Vital Plan & Coffee for Heart Health Podcast | Dare To Be Vital BookFIVE PRIMARY POINTS of the PODCAST1. Vitamin D Dramatically Reduces Heart Attack RiskNew American Heart Association data shows that maintaining vitamin D levels >40 ng/mL for ~4 years cuts recurrent heart attack risk by 52%. Most participants required 5,000 IU/day—far above the current FDA recommendation—to reach optimal levels, making vitamin D testing and personalized supplementation a critical and cost-effective intervention.2. Structured Exercise Improves Cancer SurvivalA large randomized trial in colorectal cancer patients found 90% survival with structured exercise vs. 83% with health education alone (a 42% relative reduction in mortality). Supervised and behaviorally supported exercise—not just information—is required to produce this survival advantage.3. Exercise Should Be Prescribed as Medicine for Cancer PatientsThe transcript highlights mechanisms—myokines, reduced inflammation, better fitness, and increased natural killer cell activity—that explain why exercise reduces cancer mortality. Recommendation: oncologists should prescribe personalized strength and fitness programs as part of cancer care.4. Exercise Is One of the Most Powerful Sleep OptimizersA study of 380 medical students showed:* Low physical activity = poor sleep quality* Being overweight or stressed worsens sleep* Strength training is the most effective exercise modality for improving sleep.The message: Use movement—especially strength training—to break the “doom loop” of poor sleep and inactivity.5. Vitality Is a Skill: Small Daily Choices CompoundThe episode reinforces two overarching themes:* Vitality is a skill you can learn, practice, and improve.* Vitality powers performance—especially through the synergy of exercise, sleep, vitamin D, strength, and connection.The weekly action: Get your vitamin D level checked and optimize it with guidance from your doctor.Copyright VyVerse LLC, All Rights Reserved This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit vitalityexplorers.substack.com/subscribe

00:00-35:00: ML recaps Monmouth-Syracuse. Then a crossover show with ML on Fox Sports Radio with Levack and Goz. Goz and ML chat Bonnies-Siena and the future of the programs, Yanks offseason and more. Sponsored by Byrne Dairy and RV Source of CNY. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Galit sits down with creator and educator Jason Pickett for a real conversation about the shifts happening in today's dance world. Jason shares his path from Utah's freestyle community to building a career outside the traditional LA route, and the mindset behind choosing what actually feels right. They dig into the responsibilities of teachers and influencers online, the short-sightedness that's causing dance studios and conventions business, and a shift in what dancers want to do professionally. Jason and Galit also explore whether competitions are watering down dance, how COVID changed the mentality of young dancers, and why the best teachers don't rely on the “combo.” This episode pulls back the curtain on connecting the generations, talent development, and what it really means to create good dancers - not just good perfectionists. Follow Galit: Instagram - https://www.instagram.com/gogalit Website - https://www.gogalit.com/ On-Demand Fitness Courses - https://galit-s-school-0397.thinkific.com/collections Follow Jason Pickett: Instagram - https://www.instagram.com/heyitspickett/ Jason's Website - https://nsadance.com/

You've been told your AMH is too low or that your egg quality isn't good enough, especially if you're over 40. But AMH doesn't define your fertility; it's a reflection of ovarian reserve, not your ability to conceive. In this episode, we explore how a functional fertility approach can help you uncover the real reasons AMH is low and how to support your eggs, hormones, and body so you can move forward with confidence whether naturally or with IVF. You'll Learn: What AMH really measures and why many women with low AMH still conceive once key systems are supported. The underlying causes that lower AMH: inflammation, gut health, blood-sugar imbalance, thyroid/adrenal dysfunction, and nutrient depletion. Which functional labs reveal what conventional testing often misses (GI-MAP, DUTCH, micronutrients). How to support egg quality after 40 through personalized nutrition, targeted supplements, toxin reduction, and nervous-system regulation. When IVF fits best and how preparing your body 3–6 months in advance can improve response, embryo quality, and implantation. Inspiring success stories, including Samantha (age 44, AMH 0.02 ng/mL), who conceived naturally after addressing gut infections, insulin resistance, and stress. This episode is especially for you if: You've been told your AMH is low and want to understand what that really means for your fertility. You're in your late 30s or 40s and want evidence-based ways to support egg quality naturally. You're unsure if IVF is the next step and want clarity before investing time, money, and hope. Sarah Clark is the founder of Fab Fertile Inc. and the host of Get Pregnant Naturally. Her team specializes in functional approaches for low AMH, high FSH, diminished ovarian reserve, premature ovarian insufficiency, recurrent miscarriage and helping couples prepare their bodies for pregnancy success naturally or with IVF. Next Steps in Your Fertility Journey Subscribe to Get Pregnant Naturally for evidence-based guidance on functional fertility, and share this episode with anyone on their fertility journey. Not sure where to start? Download our most popular guide:  Ultimate Guide to Getting Pregnant This Year If You Have Low AMH/High FSH it breaks everything down step by step to help you understand your options and take action For personalized support to improve pregnancy success, book a call here. --- TIMESTAMPS 00:00 – What Low AMH Really Means for Fertility → Understanding what anti-Müllerian hormone (AMH) actually measures, and why it doesn't define your pregnancy potential. 02:00 – Why Egg Quality Matters More Than Egg Quantity → How mitochondrial health, inflammation, and hormone balance shape egg potential even with low AMH. 03:30 – Inflammation, Stress, and the Type-A Fertility Pattern → The hidden link between hsCRP, stress, and fertility outcomes in high-achieving women over 40. 05:00 – Functional Team Approach: Beyond Hormones and IVF → How the Fab Fertile Method integrates thyroid, gut, and nervous system insights to improve ovarian reserve and egg health. 07:30 – Gut Health and Fertility Connection → What infections like H. pylori mean for nutrient absorption, estrogen balance, and ovarian function. 09:30 – Blood Sugar, Sleep, and Mood Clues to Hormonal Imbalance → Recognizing insulin resistance and blood-sugar swings as hidden drivers of poor egg quality and disrupted cycles. 11:00 – Foundational Fertility Supplements That Actually Matter → How CoQ10, magnesium, vitamin D3/K2, and methylated prenatals support mitochondria and hormone regulation. 12:00 – Samantha's Story: Natural Conception at 44 with AMH 0.02 ng/mL → A real client case showing how addressing gut, thyroid, and adrenal imbalances made conception possible after repeated loss. 15:00 – Functional Tests That Reveal Why AMH Is Low → The key labs: full thyroid panel, hsCRP, ferritin, insulin, GI-MAP, DUTCH, and nutrient testing to find what's missed in conventional care. 18:00 – Creating a Fertile Environment After 40 → Practical steps to support egg quality, anti-inflammatory diet, toxin reduction, nervous system regulation, and realistic IVF timing. --- RESOURCES

Review các phim ra rạp từ ngày 07/11/25QUỶ THA MA BẮT: THAI CHIÊU TÀI – T18Đạo diễn: Trần Nhân KiênDiễn viên: NS. Minh Ngọc, NS. Minh Phượng, Hồng Thanh, Tạ Lâm, Ngọc Tưởng, Thuỳ Dương…Thể loại: Bí ẩn, Kinh DịNhơn, một doanh nhân thành đạt nhờ thủ đoạn và mưu mẹo, tìm đến thứ tà thuật mang tên “Thai Chiêu Tài” để giữ lấy tài khí đã vô tình khơi dậy những ám ảnh từ quá khứ và sang chấn liên thế hệ.TRÁI TIM QUÈ QUẶT – T18Đạo diễn: Quốc CôngDiễn viên: Quách Ngọc Ngoan, Xuân Văn, Nhật Linh, Việt HưngThể loại: Kịch tính, Tâm LýMột vụ án mạng tàn bạo làm chấn động thị trấn yên bình. Khi thi thể người phụ nữ bị sát hại dã man được phát hiện, mọi nghi ngờ đổ dồn vào Sơn — có thể là người tình của nạn nhân. Triết, một nhà điêu khắc danh tiếng, rơi vào giằng xé giữa nghi ngờ và tình thân khi anh cùng vợ mình cố gắng tìm cách minh oan cho em trai. Rốt cuộc, Sơn là kẻ giết người, nạn nhân của định mệnh nghiệt ngã, hay một trái tim lạc lối bị cuốn vào tình yêu đến mức tự hủy diệt.QUÁI THÚ VÔ HÌNH: VÙNG ĐẤT CHẾT CHÓC – T16Đạo diễn: Dan TrachtenbergDiễn viên: Elle Fanning, Dimitrius Schuster-KoloamatangiThể loại: Hành Động, Phiêu LưuTrong tương lai, tại một hành tinh hẻo lánh, một Predator non nớt - kẻ bị chính tộc của mình ruồng bỏ - tìm thấy một đồng minh không ngờ tới là Thia và bắt đầu hành trình sinh tử nhằm truy tìm kẻ thù tối thượng. Bộ phim do Dan Trachtenberg - đạo diễn của Prey chỉ đạo và nằm trong chuỗi thương hiệu Quái Thú Vô Hình Predator.GODZILLA MINUS ONE – T13Đạo diễn: Takashi YamazakiDiễn viên: Ryûnosuke Kamiki, Minami Hamabe, Yuki Yamada,...Thể loại: Hành Động, Khoa Học Viễn Tưởng, Phiêu LưuNăm 1945, khi Thế chiến thứ Hai đang đi đến hồi kết, phi công Nhật Bản Koichi Shikishima bất ngờ chạm trán một quái vật biển đến từ cõi ngoài, mà người dân trên đảo Odo gọi là Godzilla. Bị giày vò bởi nỗi tội lỗi của kẻ sống sót — vì không thể bắn hạ con quái vật bằng súng gắn trên máy bay, và vì đã bỏ lại nhiệm vụ cảm tử của mình — Shikishima tìm được chút niềm an ủi mong manh bên Noriko, một người phụ nữ sống sót sau các đợt không kích Tokyo, và Akiko, một bé gái mồ côi. Năm tháng trôi qua, Shikishima dần mở lòng với Noriko và những người xung quanh. Nhưng bóng ma quá khứ — lần chạm trán năm xưa với Godzilla, nay đã biến đổi và nhiễm phóng xạ — lại một lần nữa trỗi dậy, khi toàn bộ nước Nhật chìm trong tuyệt vọng và kinh hoàng.TÌNH NGƯỜI DUYÊN MA 2025 – T13Đạo diễn: Choosak IamsookDiễn viên: Yada Narilya Gulmongkolpech, "Krist" Perawat Sangpotirat, Choosak Iamsook, Phetthai Vongkumlao,…Thể loại: Hài, Kinh Dị, Tình cảmLấy cảm hứng từ truyền thuyết dân gian Thái Lan về hồn ma Mae Nak.LỌ LEM CHƠI NGẢI – T18Đạo diễn: Hadrah Daeng RatuDiễn viên: Yunita Siregar, Dinda Kanyadewi, Thể loại: Kinh DịBộ phim xoay quanh Yuli - cô gái mồ côi phải sống như người hầu trong gia đình của Ambar và mang danh “tiểu tam”. Từ một người hiền lành và chân thành, Yuli dần biến thành kẻ độc ác và nuôi quyết tâm trả thù bằng cách tàn nhẫn nhất. Tìm đến thầy pháp để nhờ yểm bùa hắc ám nhằm huỷ hoại từng thành viên trong gia đình, Yuli bắt đầu thực hiện một nghi lễ ghê rợn: ghi tên những người bị nguyền rủa lên xác chết vừa qua đời. Khi lần lượt từng người bị hãm hại, Yuli cũng phải gấp rút hoàn tất giao kèo với quỷ dữ trong một tuần, nếu không sẽ phải gánh chịu hậu quả khủng khiếp.MỘ ĐOM ĐÓM (CHIẾU LẠI) - KĐạo diễn: Takahata IsaoDiễn viên: Tatsumi Tsutomu, Shiraishi Ayano, Thể loại: Hoạt HìnhGiữa khói lửa chiến tranh tàn khốc, hai anh em Seita và Setsuko mất đi gia đình, buộc phải nương tựa vào nhau để sinh tồn. Trong thế giới đang sụp đổ, họ vẫn cố giữ lấy những khoảnh khắc hồn nhiên cuối cùng như khi cùng nhau ngắm đom đóm bay trong đêm tối. Ánh sáng mong manh ấy vừa đẹp đẽ, vừa đau lòng như chính tuổi thơ ngắn ngủi của hai đứa trẻ giữa chiến tranh. ----------------------------------------------------#8saigon #reviewphimrap #thaichieutai #traitimquequat #quaithuvohinhvungdatchetchoc

Rani Radhakrishnan is a Principal at PwC US, leading work on AI-managed services, autonomous agents, and data-driven transformation for enterprises.The Future of AI Operations: Insights from PwC AI Managed Services // MLOps Podcast #345 with Rani Radhakrishnan, Principal, Technology Managed Services - AI, Data Analytics and Insights at PwC US.Huge thanks to PwC for supporting this episode!Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractIn today's data-driven IT landscape, managing ML lifecycles and operations is converging.On this podcast, we'll explore how end-to-end ML lifecycle practices extend to proactive, automation-driven IT operations.We'll discuss key MLOps concepts—CI/CD pipelines, feature stores, model monitoring—and how they power anomaly detection, event correlation, and automated remediation. // BioRani Radhakrishnan, a Principal at PwC, currently leads the AI Managed Services and Data & Insight teams in PwC US Technology Managed Services.Rani excels at transforming data into strategic insights, driving informed decision-making, and delivering innovative solutions. Her leadership is marked by a deep understanding of emerging technologies and a commitment to leveraging them for business growth.Rani's ability to align and deliver AI solutions with organizational outcomes has established her as a thought leader in the industry.Her passion for applying technology to solve tough business challenges and dedication to excellence continue to inspire her teams and help drive success for her clients in the rapidly evolving AI landscape. // Related LinksWebsite: pwc.com/us/aimanagedserviceshttps://www.pwc.com/us/en/tech-effect.html~~~~~~~~ ✌️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/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Rani on LinkedIn: /rani-radhakrishnan-163615Timestamps:[00:00] Getting to Know Rani[01:54] Managed services[03:50] AI usage reflection[06:21] IT operations and MLOps[11:23] MLOps and agent deployment[14:35] Startup challenges in managed services[16:50] Lift vs practicality in ML[23:45] Scaling in production[27:13] Data labeling effectiveness[29:40] Sustainability considerations[37:00] Product engineer roles[40:21] Wrap up

In this episode of Data Skeptic's Recommender Systems series, host Kyle Polich explores DataRec, a new Python library designed to bring reproducibility and standardization to recommender systems research. Guest Alberto Carlo Mario Mancino, a postdoc researcher from Politecnico di Bari, Italy, discusses the challenges of dataset management in recommendation research—from version control issues to preprocessing inconsistencies—and how DataRec provides automated downloads, checksum verification, and standardized filtering strategies for popular datasets like MovieLens, Last.fm, and Amazon reviews.  The conversation covers Alberto's research journey through knowledge graphs, graph-based recommenders, privacy considerations, and recommendation novelty. He explains why small modifications in datasets can significantly impact research outcomes, the importance of offline evaluation, and DataRec's vision as a lightweight library that integrates with existing frameworks rather than replacing them. Whether you're benchmarking new algorithms or exploring recommendation techniques, this episode offers practical insights into one of the most critical yet overlooked aspects of reproducible ML research.

In this episode of The Founder's Sandbox, host Brenda McCabe sits down with Chris Daden, CTO of Criteria Corp, to explore what it takes to scale purpose-driven businesses in the era of Work 4.0. Chris shares his fascinating origin story—starting with a childhood shaped by tech-savvy parents and leading to multiple exits, international teams, and leadership at a global talent success platform. He breaks down how Criteria uses science and AI to remove bias from hiring, why soft skills matter more than ever, and how to future-proof your workforce in an AI-augmented world. Learn about his nonprofit, SoCal Tech Forum, and why building trust is essential for AI adoption at scale. transcript: 00:18 Welcome back to the Founder's Sandbox. The Founder's Sandbox is in its fourth season. I'm here, your host, Brenda McCabe, and I'm live this month's podcast is 00:31 from the Founders Space in Pasadena. And I'm joined with my guest, Chris Daden of Criteria Corp. um And a colleague of mine in the startup ecosystem. Welcome, Chris. Thanks for having me. I'm really excited to be here. So am I. So um I want to briefly give some background on the Founder Sandbox for those that are listening in today. um 00:56 Each episode features in-depth conversations with founders of small and mid-sized owner-operated companies and operators that support the ecosystem. And together, through storytelling, we explore how to build scalable, resilient, purpose-driven businesses with great corporate governance. And you're going to discover today with Chris, his origin story. I always like to start with how the person 01:24 that's a guest to my podcast, really started getting involved with the ecosystem of startups. And your story is quite fascinating. I'm gonna give a spoiler alert here. You and I met, I guess two years ago, at a Thai con event where you were on a panel. I was the MC em and we got to talking over dinner and just your origin story and the multiple exits you've had. 01:53 really um lit up a bulb in my mind. said, Chris, you have to be in my podcast. So it's two years later, and I'm so glad that we're making this happen. Lucky to be here. Thank you. forward to it. So this podcast, again, we're going to talk about a lot of things because Chris, not only are the CTO of Criteria Corp, a talent success company, where you help organizations meet objective evidence-based 02:23 talent decisions that both reduce the bias and drive better outcomes. But also, you're a two times 40 under 40. You've had multiple exits of prior companies. You're a speaker, a founder, a board member, and recently you started your own nonprofit in SoCal called the SoCal Tech Forum. 02:51 Oh, and I forgot you're a member of the Forbes Technology Council. we're going to have... Couldn't have said it better. Thank you, Brenda. So with that, again, my episodes on particularly Spotify, we have a title that's on each episode and we've chosen Scaling Work 4.0 for this month's podcast. Again, it's Chris Daden, CTO of Criteria. So let's start. What would you... 03:21 Call your tagline. Tell us about your origin here in Southern California. Sounds great. Well, just a little bit about myself personally. I've been in tech for ah quite a while now. It's really the only career I've ever had working in tech. So I started in my youth, frankly. My father was a member of the British Merchant Navy. you can imagine with that career involved, he traveled all around the world. uh 03:50 Also, of course, gave me lot of inspiration for the global companies that I run today and the teams that I've started around the world. So although my father wasn't directly in computer science, you know, that career of being in the merchant Navy definitely shaped my global perspective. when he stopped working in the merchant ship Navy as an officer, he started developing his own software for weather routing for large 04:21 merchant ships and container ships. So what was amazing about that was it was ran out of a spare bedroom in my parents' house just upstairs while I was growing up there. And uh we used to even have a rack of kind of four by four Dell just desktop computers that were stacked on top of each other with a switch to switch between them. And we're running the workload that my dad made with the software there on those computers. 04:51 It was very visible and evident in my childhood. My first kind of internship was maybe when I was 13 or so ah in the closet of that office. We pulled the doors off and put a desk in it and that was like my internship desk for the summer. started with programming in the dotnet ecosystem. So what year is that more or less? Yeah, it's probably like 2005, 2006. uh 05:21 So it uh was a great introductory language. Fun fact, there's a YouTube video online of me when I'm about that age doing a tutorial of how to make a calculator. So very few people have found that. I'll leave it to the public to find. But you can hear my very young 12-year-old voice in a YouTube video. it's still there. So anyway, that's part of my origin story for sure. That's what got me into computer science. 05:48 My first company, started my senior year of high school. I was aqua hired into an organization in Irvine. And then I got to join what I would call kind of a real company at that time. um One that had, you know, engineers around the globe working on solving problems and SAS for organizations of all kinds. So that's kind of where I kick started my career. I'm spending the next maybe eight to 10 years in Orange County building companies and 06:16 Now I find myself as the CTO of Criteria, which of course I'm not a founder of, but the energy that I like to bring to the team and the passion I have for what the next era of work has to offer gives me that founder-like energy. Yes. So um how long have you been with Criteria? Were you the first CTO? Were you an aqua hire? Tell us a little bit about that. Yeah, great question. So Criteria has a great history, almost 20 years of science and 06:46 um just developing a great core platform that's been used by thousands of customers around the world. I've been there as CTO for the last three and a half years. So when I joined, was right after acquisition of a couple companies in Australia that were great additions to our product portfolio. And one of my roles right away after joining was to help integrate those teams, finish retiring some of the technical debt that comes with acquisitions. um 07:15 really just all the excitement around building for the next chapter of criteria and making sure that I can contribute in my many ways to our success. So back to that tagline that due to your father's um origins in the Navy, m you have a wide global perspective. Tell me about those teams that you had in India before Criteria. 07:41 Yeah, look, I started doing business in India a little over 10 years ago. I was just reflecting on that last week. I had the luxury of visiting my team again. We also just created a new team for criteria. So I was able to go visit them. We all got together for the first time. It was a lot of fun. But about 10 years ago, I started in a city named Indore and that's in the state Madhya Pradesh. And when I started, it was a tier three city. And, you know, I really stumbled across 08:09 who is now my general manager for my last company. I stumbled across meeting him through like a development agency and we really hit it off and you know at the time I was 18 years old and you know was willing to take some risk I guess because I wanted to work with an engineer and had to build my product and company and you know what it's like being a scrappy founder and I just rolled the dice and said sure like 08:34 Why don't you come work for me full time? Let's find your friends as well and let's start a company together. And his name is Vikram. And to this day, he's still the general manager of my last company in automotive SaaS that I had recently exited in like 2021 timeframe. He's still operating that team. Company's going great. So that's been a lot of fun to see that success. But yeah, over a period of 10 years, it's become... 09:00 from a tier three to a tier two city. So things like basic infrastructure have been developed. So just so much fun and so much reflection there. I'm lucky to have, know, that's my, Criteria's new team is now my fourth India venture. So this is my fourth generation. Oh my goodness. It's a scaling work 4.0. So let's go back to Criteria. again, over dinner a couple years ago, 09:29 You started talking about how the science of finding talent is really the bedrock of criteria. And you've been there three and a half years. Talk to us about that, the talent and the science that is driving this company's technology and being used today in hiring across the world. Yeah, I think. 09:58 Hiring is one of those things that we don't always teach hiring managers or people in organizations. I think we were laughing about that. If you're, say, a great senior software engineer and you've been coding for 15 years or something, I think it's assumed that when you get promoted into, say, an engineering manager role, you're now going to be a great hiring manager. And I think hiring science is something that is often... 10:22 underappreciated in organizations, particularly startups and mid-market companies who may not have the resources, right? Because to be good at hiring science, you also have to invest resources in it, right? So really you don't see most really advanced hiring science or like, you know, psychology teams being involved in hiring until the enterprise level. for criteria, we're all about using technology to harness as many what we call talent signals as possible. So we have a 10:52 an assortment of assessment tests that can measure things like your cognitive ability, your adaptiveness, your personality fit to a job role. And we do that in rigorous and scientific ways. I think there are probably more ways to do hiring wrong than to do it correctly. And we take a lot of pride in making sure that our products are always designed to measure those talent signals and even compound them. So as you find 11:19 multiple talent signals across the life cycle of that pre-employment hiring engagement, you get a compounding, really almost like a talent blueprint of the person you're looking to hire, or maybe even like the candidate DNA of that person. And it gives you a depth of information and data about the likelihood they are to succeed for that specific job role you're hiring. And that's really, really valuable to us. And we can talk a bit about why 11:46 that matters more as we enter into this new era of work. Before we go there though, I'm fascinated. What types of talent can Criteria be used for in the hiring process? Is it across all verticals? mean, tell me a bit about that. Criteria is a pretty diverse company. So with 4,000 customers around the world, we are really present in maybe 20 different verticals. So that makes us pretty... 12:15 pretty broad in who can use us for hiring. So, you know, we joke around anything from, you know, hiring for truck drivers all the way to rocket scientists. Like there's customers across the whole spectrum in engineering, venture capital, uh you know, executive management, truck drivers for uh companies, uh frontline workers, all the way up to rocket scientists at companies. 12:45 So recently you were a keynote speaker in London and you provided your closing thoughts on AI in the workforce. So I'm going to steal your thunder right now because you gave this to me and set it up. So work 4.0 belongs to those who pair adaptive mindsets with distinctively, yeah, human skills. Workplace. 13:14 AI will be our most tireless colleague, but the future's real competitive edge is still human potential, continuously renewed. Wow, unpack that for my listeners. Because we're all getting a bit nervous about will we have job security, what do we need to do to retool, and is everybody suitable? Yeah, I think what's kind of amazing is 13:44 um You look at some reports from the World Economic Forum or other entities and they're saying things like by 2030, 39 % of skills related to kind of the current candidate applying in the workforce will be obsolete. Wow, that's a lot. That's a lot. It's almost half, right? And what's amazing about that is then what are we hiring for, right? Because the last few decades of us 14:12 hiring has been so focused on how many years of experience did you have, what degrees do you hold. And it doesn't mean for many people who, right, college is the best fit, getting a degree is the best fit for many people. But ah I think what it highlights is there's more to being workforce ready than only getting these static credentials. And for people like me, I've dropped out of college twice. Both times I had some... 14:41 transactional event with one of my businesses. And that was obviously the right choice for me, right? And I've reflected on that and I feel good about where I'm at and where I came from. But I think workforce readiness these days is going to continue to index on the more dynamic talent signals and the more dynamic credentials we have as opposed to static credentials. So what that means is my ability to think on my feet, critical thinking, adaptive reasoning. 15:11 Those are all things that we kind of measure, if at all, we measure them kind of secondarily in our current process. And these other core talents like digital fluency, AI literacy, self leadership, resilience, those are all things that are more of these dynamic credentials that we need to make sure we measure really, really well, because the reality is with the advent of AI in the work 15:40 place, hard skills are more immediately attainable. And what I mean by that is maybe if I'm hiring for an accountant role, I care more about is that accountant a strategic thinker? Do they understand the tax code to the right depth? Do they understand the strategy for valuation of the business? And then of course they have to click some buttons in QuickBooks or NetSuite or other systems. But I think AI is going to... 16:09 augment the hard skills of our workforce. And that's going to make us more index on the softer skills, emotional intelligence, the adaptability, right? Those dynamic credentials as opposed to how many years have you been clicking buttons in QuickBooks? And it will require, I guess, more critical thinking, right? True. Right? Because you will be your... uh 16:36 day-to-day job will be augmented by AI, leaving you time to upskill or to make those critical decisions, more, I don't know, avenues of strategic development in the company. that's right. Yeah, redeploy to higher value opportunities for sure. think if 30 to 40 % of your day is... 17:04 tasks that can be augmented with AI, then that 30 to 40 % of your human first excellence can be redeployed to other parts of the business. an example is at Criteria, we serve uh tens of millions of assessments, um about 10 to 12 million per year. And we have about five or six million candidates that come through that process. 17:31 when they need technical support or help with the software, they often reach out to our live chatbot. we at Criteria um want to make sure we prioritize a five-star candidate experience. So even though candidates aren't the ones paying for the service, our customers are, we know that our customer satisfaction is tightly linked to how satisfied our candidates are. Got it. uh 17:54 One of the things we had was thousands and thousands of tickets every month from those five million plus candidates coming into our support system. And what we were able to do was augment our support staff with uh AI chat bots that are trained on deep knowledge bases of criteria and past candidate issues and technical troubleshooting. we were able to achieve about a 94 % candidate ticket deflection, which is really, really massive. And it didn't mean that we 18:24 know, laid off half of our support team or something, it means that, you know, those support team members moved into other high value roles in the organization or were able to now redirect their energy to making long lasting materials like help docs and guides that can then further retrain the AI to make that even better. So that's just an example of augmentation of skill and then redeploying that human excellence to another part of the business to help you grow. So it has criteria use the same time. 18:54 methodology for their staff? For our staff, every single person at Criteria goes through our assessment products, of course. We drink our own champagne. I had to ask that question. I'm a little biased, but I think I didn't know about the category before joining Criteria. And again, with my origin story, I've hired hundreds of people around the world. And I will never run another team without using 19:22 a criteria talent success platform to hire those people. So I'm a firm believer and because I didn't know about it before and now I'm using it, it's a big gap in my knowledge. So I would say most of our market potential for criteria doesn't actually know that these tools exist. A lot of them have a retention challenge or they're having an issue hiring the right people and people like me before I joined criteria don't actually know that this tool set is available. part of my mission is to... 19:51 make sure that startups and founders and mid-market companies are aware that this is available because it solves a big problem for us building the best teams. so uh last plug for Criterion, then we're going to move on in the interview here. uh How do um customers experience Criterion? How do they uh get onboarded? mean, what is it, the HR department? Where does, where's the origin? Yeah, really great. So 20:19 We call ourselves a talent success platform because we help people pre-hire with our assessments and video interviewing products. And that's normally the HR talent acquisition leader. So someone who's in charge of recruitment for a company or essentially all the pre-employment functions. And then because we have this rich data set that comes from those pre-employment activities, we have a post-hire product that we call Develop by Criteria. And Develop is designed to use all of that psychometric data 20:48 weekly check-ins with your employees, uh frameworks for behavior to help grow those team members after they're hired using all of that data and science. So a lot of our customers experience criteria on the pre-employment side and then continue to follow through on the post-employment side with our develop product. Wow. Is there patent protection with all of the science that you have developed over the years? I think there's obviously copyright. 21:17 um of our assessment tests. think patents and software are inherently tricky, but we feel really good about the protection of our IP. Excellent, excellent. So let's switch gears. um I met you at the TICON. um You haven't been our keynote speaker yet, but you have moderated panels, and I've seen you in other events. Tell us about what do you enjoy, what do you like to talk about when you're keynote speaker? 21:47 For me, it's just such an honor to share my learnings as an entrepreneur, as an executive with the world. I still am in this phase where when I give a keynote or moderate a panel, it doesn't really feel like a real thing. It just feels like another discussion for me. That's just kind of my style. I just think that the world stays connected by sharing information like that. And for me, 22:16 I'm lucky to be at the convergence of 20 years of Criteria's product, helping people make hiring decisions and this once in a lifetime emergence of generative AI intersecting with our workforce skills. So I talk a lot about that. Of course, I'm building my own teams to build the Criteria software and platform. 22:42 So I'm also thinking about what is next for my team, how do I upscale and enable? And then of course I'm talking to our thousands of customers on a regular basis trying to make sure that we are leaders in the industry. those are areas I really love talking about. I'm an engineer at heart as well. So I tend to be quite good at bridging kind of the commercial and business side with like core engineering. So I have a deep background in 23:11 AI and ML um even more traditionally prior to the generative AI boom and now even more so post generative AI boom. We're applying generative AI in ways that um we are on the frontier fine tuning models for our uh really predictive models at criteria. So those are all areas I love to talk about and it's really an honor to be able to share that with people no matter the forum. Well maybe there'll be a podcast episode two with Chris on this. 23:41 What about, you you love to share, I don't know where you find the time. You've recently started a nonprofit, the SoCal Tech Forum. So share with my audience the types of activities, where's the venue, who is gathered, and what made you start a nonprofit, right? Yeah, it's a great question. I didn't know I would be starting a nonprofit either, but that tends to be how these things go. 24:11 It's been just a journey. ah We started off as a meetup group. my goal for the meetup group was in the Inland Empire specifically here in Southern California, we don't have many tech meetups. I'm of course networked well in Orange County and Los Angeles. And I think that particularly with these technologies that are 24:35 in our day-to-day life, it's very important that we build community around information and knowledge sharing so we can all learn and get up to speed on AI. A lot of business owners are going through transitions with their workforce, with their team that just were never really imagined. for us, we started this meetup group in the Inland Empire because there was definitely a market gap in getting together. I started off 25:02 paying for and hosting the events, breakfast, etc. And we had so much good interest. had sponsors that decided to volunteer to support, starting with a company called Clutch Coffee and Rancho Cucamonga, who has a deep history of roasting coffee and brewing technology in Rancho. And uh we've since got some other great partners to support us. And in just a little under two years, we've... 25:30 surpassed 750 members in the group. uh that was the reason once we started getting sponsors involved that it made sense to have a 501c3 nonprofit formed. And we have a leadership board now, which I'm really proud of. And we host an event at least once every month on the first Saturday of every month. And they're always technology or technology adjacent topics. They always involve. 25:56 technical and non-technical folks, business owners, entrepreneurs, startups. yeah, it's been really fun. Again, an opportunity to funnel and give back to the community and teach people about disruptive technologies. Well, you heard it here on the Founder's Sandbox, the SoCal Tech Forum. It will be in the show notes, all right, how to um get involved and perhaps attend one of those Saturday meetings. um I wanted to give you an opportunity. 26:25 to provide how people can best contact you, either for speaking opportunities, a CTO of Criteria, the nonprofit. How is it best to contact you, Chris? Yeah, I'd love to hear from you. So you can contact me on LinkedIn. So linkedin.com slash in slash Chris Dayden. All one word. And you can learn more about me as a speaker or CTO of Criteria at chrissdayden.com. excellent. 26:56 have that in the show notes. All right, I want to bring you back to the Founders Sandbox, all right, which is the platform and the podcast. I really get excited about um this part of the podcast. um I work with my clients on resiliency, um scalability, and purpose-driven, right? All with great corporate governance. I always like to ask my guests what... 27:24 the meaning of each of those three words has for them. And each of my guests has a different oh interpretation. And it's just a lot of fun to listen to what I resiliency, what's resiliency for you? I think it's appropriate that I answer that in light of kind of work 4.0. So for me, when it comes to resiliency in work 4.0, um it's about the art of constantly reinventing yourself. 27:53 but in faster cycles. And I think what's really important to everyone is that in Work 4.0, hard skills can become obsolete quicker than before. And that reinvention is critical to really being resilient in this new market. How about scalable? You've scaled a couple of companies, you've been an aqua hire. What does scalable mean to you, Chris? In Work 4.0, scalable will mean 28:22 adequately augmenting the talent you have in humans in your organization with the ability to harness the true power of AI and to do that without losing culture or trust. I think many organizations think of the first half of that. Very few of the organizations can execute on human plus agentic AI and also maintain trust. 28:51 and without losing culture. Have you seen any best practices? This is a little bit off script in terms of companies that have, or are scaling, right? Because this is just scaling pretty quickly in the last year or so. Sure. And are there any best practices out there in building that trust? Yeah, I think having a real holistic AI strategy is key. 29:18 One main component of a holistic AI strategy is how can you get tools to the fingertips of every staff member in your organization so that it's embedded in their workflow? Because a lot of the top-down AI strategy from organizations, like a CEO says, you must use AI and we must be 25 % more efficient, is really shallow when it comes to strategy. And it very rarely results in a culture 29:48 sustaining in a company for this AI growth and augmentation. So what I've been really impressed by is, you know, when I host things like AI monthly global office hours at Criteria, or I host one-on-one sessions with employees to learn about how they're using AI, because you're able to push those tools down to your team members and let them use it in a safe and comfortable area, it allows you to see what people creatively do with AI. And most of the time, 30:17 I could say there's probably 60 or 70 % of use cases that I would never have expected my staff to use AI for, and I would have been the bottleneck of creating if they were waiting for me to do it, and instead give them a safe experimentation zone. And I think that is key to a sustaining AI strategy for So your best practice is actually a criteria from what I'm hearing here. And it's very becoming because I'd like to talk about playfulness in the sandbox, right? 30:46 I read recently, was an EY um study, I think it was this last week, that about 40 % of employees that are forced to use AI tools give up after a month. They don't see the utility in their day-to-day tasks they're doing. So there is something to what you just said, building trust, but building it from the bottom up, right? Yeah, I resonate with that for sure. And I think the only way people break that barrier 31:16 is by seeing their colleagues successful with it. Very rarely is a demo from an executive leader going to be, I mean, it might be enough to begin a culture of AI. Like I had to do a lot of demos and show people kind of the art of the possible. And then as soon as I saw pockets of AI intelligence in the organization, the quicker you can elevate those people to lead and present their findings, the faster... 31:45 you build up kind of the natural human competition between your team and everybody all of a sudden will get more behind it. And that's really important. I think you've reached a point of success in your AI strategy when you were once leading the AI learning sessions and now you are not. How cool is that? You heard it here in the founder sandbox. All right. Purpose driven. What's a purpose driven enterprise for you? I think that 32:12 This is timely based on our discussion just now where organizations need to harness AI at the right times. think purpose for criteria, for example, means how do we measure talent signals that are able to give us the best candidate blueprint or the best candidate DNA possible? And for us, 32:40 every single day, regardless of the technology, what fuels us is having that purpose-driven statement of collecting talent signals around the world for any team. And you really do get lost in that sometimes, for good and for worse, when you're just trying to collect as many talent signals as you can. And being purpose-driven means always doing the right thing when it comes to that. 33:09 mission statement that you've set. And for us, it's collecting talent signals. I think that AI can do that well in a lot of areas, but AI can also be very dangerous in those areas. So when it comes to Work 4.0, having that purpose-driven enterprise statement is very, very important because it anchors us for our new product development. It anchors us for how we're using new technology to help people make the best teams. 33:39 Going back to that, to build the trust, we might clip this out, um does criteria maintain a group of scientists to actually peel back the layers and make meaning out of the signals that you are capturing to create new signals? That's one question. The second is, does criteria have an ethicist on board? 34:08 on call or how do you ensure there is guardrails around talent signals? Yeah, those are really great questions. think for criteria, when we say we're rooted in science, it wouldn't mean very much if it was just a bunch of engineers and product managers kind of deciding what science is, right? So for us, we take a lot of pride in our product IO psychology team. So a lot of them are 34:37 industrial organizational psychologists by trade that are working full time for criteria. And their role is assessment development, assessment validation. uh And particularly in the light of fine tuning AI models, they are very, very hands on in creation of those models, validating those models. There's a lot of legislation we have to comply with, not only the normal data privacy stuff like GDPR and CCPA, but also 35:07 industry specific laws like the New York bias laws and others that help protect uh candidates as they are applying for roles. So that is very, very near and dear to our heart. And also we conduct adverse impact studies and we do case studies with customers to make sure that the product is uh behaving the way that they intended to behave. 35:32 You know, we've got norms for all of our assessments and we adjust those norms based on massive populations of data. So all of that is how we ensure scientific signal. This is amazing. Last question. Did you have fun in the Founder Sandbox today, Chris? I had a lot of fun in the Founder Sandbox. Really a pleasure. Thank you for having me. Thank you, Chris. So to my listeners, if you like this episode with the CTO of Criteria, Chris Daden. 36:02 Sign up for the monthly release for more podcasts where I have business owners, professional service providers, and corporate board directors who are all working to build with strong governance, resilience, scalable, and purpose-driven companies. Thank you. Signing off.

What if the fastest way to grow your career is to reinvent how you work before the market forces you to? In this episode, I had the pleasure of sitting down with Caitlin Clark-Zigmond, a two-time entrepreneur and former CMO for Intel's global software and SaaS portfolio, to map the leap from hands-on operator to AI-powered brand builder, and why clear value translation beats clever slogans every time.Caitlin takes us from scaling a catering business to shipping Comcast Digital Voice, to leading massive B2B portfolios at Verizon and Intel. We dig into how Intel Tiber emerged to make software visible inside a hardware giant, uniting trust and security, AI and ML, edge and cloud, performance optimization, and developer workflows under a narrative customers could navigate. The result: sharper messaging, analyst clarity, and real pipeline acceleration. If your portfolio feels like a maze, her brand framework shows you how to draw a clean map.Then we get practical with AI go-to-market. Forget tool-chasing—start with painful use cases, build on clean, connected data, and let AI amplify what already moves the needle. Caitlin explains why a CDP or an MCP layer unlocks CRM, marketing automation, analytics, billing, and customer success, enabling them to communicate effectively with each other. We cover intent data for account prioritization, conversation intelligence for coaching, predictive scoring for pipeline, and agents that handle repetitive data pulls and weekly reporting so teams can focus on thinking, not tab-hopping.For leaders and modern marketers, the upskilling path is clear: achieve 30% fluency in core AI concepts, measurement, and understanding how your stack—HubSpot, Salesforce, GA, CDPs, and chat systems —actually works. You don't need to code; you need to understand revenue mechanics. We also share Caitlin's strategic networking system—the 5–5–5 method—that turns coffee chats into an operating system for your career, with value-first follow-ups that work even for introverts.We conclude with candid insights on the value of progress over perfection, investing in relationships before you need them, and redefining success in terms of client transformation, sustainable growth, and work-life integration. Subscribe, share with a friend, and tell us: what's the scary move you're finally ready to make?Resources: Website: www.clarkgp.com  LinkedIn: https://www.linkedin.com/in/caitlinclarkzigmond Upcoming LILive GTM Event: https://www.linkedin.com/events/2026gtmrealitycheck-makemisalig7393722093324107776/Monthly Blog: https://gtmmaven.substack.com/p/why-the-c-suite-must-work-together

• Grasshopper Face   • No Eyebrows In Style Again • The Day I Forgot Myself  • Jackie & The Horse   • What Happened To Sweetie?   .• Dog Near Death Recovers   • Todays WINNER of a Free Reading With Venus, chosen weekly off ML is read on the show   • Private & On Air Reading Comments & Testimonials   • Studio Callers: Terry & The Murk In The Basement & Ann's Dead Family Is Hard To Read   • Instagram: venus_andrecht    Callers always get free On Air readings every live Dear Venus show Wednesdays at 2 pm PAC/5 pm EST. Call the show at (760) 456-7277. Visit godisalwayshappy.com for Radio & Private Reading information. 

00:00-20:00: ML explains why this year might be a throw away year for the Buffalo Bills. Thanks to Rosie's Corner and CH Insurance. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

At KubeCon 2025, the CNCF launched the Certified Kubernetes AI Conformance Program to standardize AI and ML workloads on Kubernetes, ensuring portability across hybrid and sovereign clouds and preventing platform lock-in. Supported by companies like Google, Microsoft, Oracle, Broadcom, and Red Hat, the initiative promotes interoperability, scalability, and efficient production deployment. Arm showcased its Neoverse platform alongside Google Cloud's Axion N4A VMs, enabling energy-efficient, scalable AI workloads, while partnerships with CNCF projects like Harbor, OPA, Kedify, and AuthZed help developers build secure, portable, and cost-effective cloud-native systems from edge to cloud. This and more on the Tech Field Day News Rundown recorded live at Commvault Shift with Tom Hollingsworth and Stephen Foskett. Time Stamps:0:00 - Welcome to the Tech Field Day News Rundown1:17 - VAST Data makes $1.17B Deal with CoreWeave4:42 - Spektrum Labs Uses Cryptography to Prove Cyber Resilience7:37 - HPE Drops Qumulo, Scality, and WEKA to Focus on Its Own Storage10:56 - Red Hat Unveils Major OpenShift 4.20 Updates for AI, Security, and Edge13:57 - AWS Builds Transatlantic Fastnet Cable to Boost Cloud and AI17:31 - Pentagon Expects Industry to Train AI, Not Pay for It20:34 - CNCF Standardizes AI Workloads on Kubernetes25:17 - Arm and CNCF Showcase Efficient Cloud-Native Systems at KubeCon 202529:26 - Thank You Commvault for Hosting Tech Field Day31:01 - The Weeks Ahead32:55 - Thanks for Watching the Tech Field Day News RundownFollow our hosts ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Follow Tech Field Day ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mastodon⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

00:00-15:00: Batavia Downs Gaming's Ryan Hasenauer chats about the weekend Holiday Festival at BD, ML's recent visit, Thurman Thomas meet and greet upcoming and more. Plus, a Breeder's Cup recap. Presented by Batavia Downs Gaming and Western OTB. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome to the 'Securing Our Future' podcast by New North Ventures, where commercial and national security sectors converge to spur innovation. In this episode, host Jeremy sits down with Paul Lwin, the pioneer behind HavocAI, a maritime technology company that's just 21 months old. Paul shares their incredible journey of raising $85 million, growing a team of 80, and generating $3 million in revenue through advanced autonomous maritime vessels. Learn about Havoc'AIs mission to create a 'Hellscape' in the Pacific with thousands of intelligent vessels, overcoming challenges in maritime environments, and utilizing cutting-edge AI and ML technologies. With real-world applications and insights into dual-use innovation, this episode sheds light on the future of maritime domain awareness and autonomous systems. Subscribe to our newsletter for more updates and resources.00:00 Introduction to Securing Our Future Podcast00:44 Welcoming Paul and HavocAI's Journey01:59 Challenges and Innovations in Maritime Autonomy04:19 Technical and Operational Insights09:44 Commercial and Defense Applications14:49 Future Prospects and Industry Impact27:15 Conclusion and Final Thoughts

Modern data analytic methods and tools—including artificial intelligence (AI) and machine learning (ML) classifiers—are revolutionizing prediction capabilities and automation through their capacity to analyze and classify data. To produce such results, these methods depend on correlations. However, an overreliance on correlations can lead to prediction bias and reduced confidence in AI outputs.  Drift in data and concept, evolving edge cases, and emerging phenomena can undermine the correlations that AI classifiers rely on. As the U.S. government increases its use of AI classifiers and predictors, these issues multiply (or use increase again). Subsequently, users may grow to distrust results. To address inaccurate erroneous correlations and predictions, we need new methods for ongoing testing and evaluation of AI and ML accuracy. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Nicholas Testa, a senior data scientist in the SEI's Software Solutions Division (SSD), and Crisanne Nolan, and Agile transformation engineer, also in SSD, sit down with Linda Parker Gates, Principal Investigator for this research and initiative lead for Software Acquisition Pathways at the SEI, to discuss the AI Robustness (AIR) tool, which allows users to gauge AI and ML classifier performance with data-based confidence. 

00:00-15:00: ML recaps SU's win over Binghamton and says it's all about stacking wins, reps and getting better until the gauntlet arrives. Thanks to CH Insurance and Byrne Dairy. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Intro topic: Asymmetric ReturnsNews/Links:NanoChat by Andrej Karpathyhttps://github.com/karpathy/nanochatPydantic AIhttps://www.marktechpost.com/2025/03/25/pydanticai-advancing-generative-ai-agent-development-through-intelligent-framework-design/1000th Starlink this yearhttps://spaceflightnow.com/2025/05/16/live-coverage-spacex-plans-morning-launch-of-starlink-satellites-from-california/ChatGPT Apps SDKhttps://openai.com/index/introducing-apps-in-chatgpt/Book of the ShowPatrickThe Will of the Many by James Islingtonhttps://amzn.to/43IfU8QJasonInterview with DHH (Founder of Ruby on Rails)https://www.youtube.com/watch?v=vagyIcmIGOQPatreon Plug https://www.patreon.com/programmingthrowdown?ty=hTool of the ShowPatrickFactoriohttps://www.factorio.com/ Jasonnip.io Topic: Workflow OrchestratorsWhyBatch jobs (embarrassingly parallel)Long-running tasks (e.g. transcoding video)Checkpointing/resumingHowMessage QueuesContainerizationWorker Pools & AutoscalingHistory & BackfillSteps to run workflows:Containerize the workflow definition and send to the cloudContainerize all the individual tasksSubmit job(s)ExamplesAirflowLegacy but dominantDagsterGreat UX for python developersTemporal: https://temporal.io/The new hotnessRayLow-level but very powerfulKubeflowDesigned for ML workflows, integrated dashboard ★ Support this podcast on Patreon ★

00:00-15:00: Jack Eichel is on a mission. MVP later this year? Another Cup? ML says he has never seen the former Sabre look this good. Thanks to CH Insurance and Rosie's Corner. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

AWS Morning Brief for the week of November 3rd, with Corey Quinn. Links:Beyond pilots: A proven framework for scaling AI to productionNew Amazon CloudWatch metrics to monitor EC2 instances exceeding I/O performanceProcessing Amazon S3 objects at scale with AWS Step Functions Distributed Map S3 prefixWhat's the difference between AWS ParallelCluster and AWS Parallel Computing Service?France Télévisions prepared for 2024 Olympic Games with AWS Countdown PremiumAmazon Kinesis Data Streams now supports 10x larger record sizesAmazon DocumentDB (with MongoDB compatibility) announces upgraded query planner that can run queries up to 10x fasterAnnouncing AWS X-Ray SDKs/Daemon End-of-Support and OpenTelemetry MigrationAmazon S3 adds conditional write functionality to copy operationsIntroducing the Capacity Reservation Topology API for AI, ML, and HPC instance typesHow to deploy a SQL Server Failover Cluster Instance across three Availability Zones using Storage Spaces Direct Reduce CAPTCHAs for AI agents browsing the web with Web Bot Auth (Preview) in Amazon Bedrock AgentCore BrowserUsing Kubernetes Labels to Split and Track Application Costs on Amazon EKSIntroducing AWS Lambda event source mapping tools in the AWS Serverless MCP Server Split Cost Allocation Data for Amazon EKS supports Kubernetes labels

Time for another Sunday of NFL football betting for host Matt Perrault. New week and a new month as Matt tries to break out of the cold spell he has been under. Matt has 4 bets for you including a ML parlay that is a first on the Sunday episode of the Daily Juice podcast presented by Hard Rock Bet. See omnystudio.com/listener for privacy information.

00:00-15:00: CH's Joe Jr. and John Sereno and Earl Staring from Erie/Niagara Insurance join ML from Highmark Stadium ahead of Chiefs-Bills. The boys chat game storylines, chicken wing power rankings, Earl's connection to CH and more. Presented by CH Insurance. In your corner. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Shawn is back talking about a 9th grade rager while ML and Marc are grateful Erika's ears aren't exposed to […]