Podcasts about llm

Netlify's CEO, Matt Biilmann, reveals a seismic shift nobody saw coming: 16,000 daily signups—five times last year's rate—and 96% aren't coming from AI coding tools. They're everyday people accidentally building React apps through ChatGPT, then discovering they need somewhere to deploy them. The addressable market for developer tools just exploded from 17 million JavaScript developers to 3 billion spreadsheet users, but only if your product speaks fluent AI—which is why Netlify's founder now submits pull requests he built entirely through prompting, never touching code himself, and why 25% of users immediately copy error messages to LLMs instead of debugging manually. The web isn't dying to agents; it's being reborn by them, with CEOs coding again and non-developers shipping production apps while the entire economics of software—from perpetual licenses to subscriptions to pure usage—gets rewritten in real-time. Resources:Follow Matt Biilmann on X: https://x.com/biilmannFollow Martin Casado on X: https://x.com/martin_casadoFollow Erik Torenberg on X: https://x.com/eriktorenberg Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Beyond the Business creator Dave Rogers, is also known as ‘The Business Explorer'. He's a previous TEDx Speaker, an award-winning Business Consultant, Coach and Author. For 30 years, he's been using that curiosity to help businesses tackle challenges.On top of that, Dave's not your typical business consultant. Yes, he's worked for big corporations. And yes, he knows how to turn lofty strategies into real, practical results. But what sets him apart is how he brings it all down to earth. He works alongside business owners, start-ups, and leaders to turn “what if” into “what's next.”Summary of PodcastIntroduction to Dave's new membership serviceKevin introduces the topic of Dave's new membership service for business owners, which Dave has been developing since his last appearance on the podcast about a year ago.Identifying the target audienceDave explains that the membership is aimed at business owners. You know, the ones who have built successful companies but are now feeling "stuck". Maybe their business is running them rather than the other way around. The goal is to help them find a different way of looking at their business.The membership structure and tiersDave outlines the three-tiered structure of the membership. The entry-level provides self-reflection frameworks and tools, the middle tier offering group coaching and training, and the top "inner circle" tier providing more personalised one-on-one support.Feedback and suggestions on the membership modelGraham and Kevin provide feedback and suggestions on the membership structure, including potentially removing the entry-level tier, increasing the pricing for the middle tier, and emphasizing Dave's personal involvement and expertise across all levels.The role of AI and automationThe discussion turns to the role of AI and automation, with the group debating how to balance the use of technology with maintaining the human connection and expertise that Dave can provide.Wrap-up and well-wishesThe participants wrap up the discussion, wishing Dave success with the launch of his new membership service and agreeing to stay in touch as he refines the offering.The Next 100 Days Podcast Co-HostsGraham ArrowsmithGraham founded Finely Fettled ten years ago to help business owners and marketers market to affluent and high-net-worth customers. He's the founder of MicroYES, a Partner for MeclabsAI, where he introduces AI Agents that you can talk to, that increase engagement, dwell time, leads and conversions. Now, Graham is offering Answer Engine Optimisation that gets you ready to be found by LLM search.Kevin ApplebyKevin specialises in finance transformation and implementing business change. He's the COO of GrowCFO, which provides both community and CPD-accredited training designed to grow the next generation of finance leaders. You can find Kevin on LinkedIn and at kevinappleby.com

Meta earnings good. The street like the AI spending. Microsoft earnings bad. Why is growth in their cloud business not as robust all of the sudden? Elon is following through on taking Tesla all in on robots and AI. The AI inspired layoffs are NOT just for the tech industry. And are you actually technical enough to run that Clawdbot? Zuckerberg teases agentic commerce tools and major AI rollout in 2026 (TechCrunch) Microsoft stock drops 7% on slowing cloud growth, light margin guidance (CNBC) Tesla scraps models in pivot to AI as annual revenue falls for first time (FT) Dow to Cut 4,500 Employees in AI Overhaul (WSJ) Waymo robotaxi hits a child near an elementary school in Santa Monica (TechCrunch) Tiny startup Arcee AI built a 400B-parameter open source LLM from scratch to best Meta's Llama (TechCrunch) Clawdbot sheds skin to become Moltbot, can't slough off security issues (The Register) Learn more about your ad choices. Visit megaphone.fm/adchoices

Dr. Deb Muth 0:03There’s a quiet shift happening in healthcare right now, and most doctors aren’t talking about it yet. People aren’t chasing diagnoses anymore. They’re exhausted by them. I see it every single day in my clinic. People who come in with stacks of paperwork, portals full of results, and a list of diagnoses longer than their grocery receipt, yet they’re still not living their lives. And they’ll say to me, Dr. Deb, I don’t want another label. Dr. Deb Muth 0:32 I just want my life back. If you’ve ever been told this is just how your body is, if you’ve been diagnosed, rediagnosed, and then dismissed, if you’ve been handed labels but never handed a roadmap, today’s episode is for you. Because we are officially entering what I call the post diagnosis era and it’s changing everything about how healing actually happens. So grab your cup of coffee or tea and let’s settle in to let’s talk wellness. Now, before we dive in, we need to take a quick pause to thank today’s sponsor. And when we come back, we’re going to talk about why diagnoses are no longer the most important thing about you. Dr. Deb Muth 1:17Did you know sweating can literally heal your cells? And infrared saunas don’t just relax you, they detox your body, balance hormones, and boost mitochondrial energy. I’m obsessed with my health tech sauna, and right now you can save $500 with my code at healthtechhealth.com Dr. Muth req 25 so here’s some truth for me. Dr. Deb Muth 0:47It was three years ago Christmas that I received my Ms. Diagnosis. And I remember it very clearly. It was the day before, two days before Christmas Eve, that I got the call and I heard the words, you have white matter brain disease. That’s consistent with Ms. And I immediately stopped in my tracks and thought, okay, well, this is just the way it is. We’re gonna fight this. We’re gonna figure this out. And it led me down a deeper path of healing and spirituality and emotional growth. And there were some really difficult days ahead for me because I remember thinking, what am I gonna do? How am I gonna practice what’s going to happen in my life? And every year at this time, I reflect back to that day that I got the call that really changed my life. And not for the worse, but for the better. It changed the way I was thinking about life. Dr. Deb Muth 3:01It changed the way I was complaining about things being ungrateful for all the amazing things that I have in my life. Not intentionally, but just living the American life. Right. Dr. Deb Muth 3:14And striving for more and wanting more and chasing more and doing more, and never really having the opportunity to just be present and just really think about life and enjoy what the Lord has given us and enjoy what’s around me, the people in my life, the family that I have, the amazing practice that I have, and the amazing people I get to work with and change lives with. And it really changed me for the better. And I’ve watched diagnoses like this change people for the worse and for them to sink deep into a depression and give up and. And live to their label instead of living to their potential. And that’s why I think this episode is so important for us, because we all have a choice in life. When we get dealt something kind of difficult, we can let it consume us and let it take every ounce of life from us, or we can allow it to become the fuel that makes us better, makes us contribute to life maybe differently, but in a better way. So, you know, I know that this idea of letting diagnoses lose their power can be really uncomfortable for some people, because there’s people that are waiting for that diagnosis. I’m in some. Some social media groups, and I’m listening and reading to people who are saying, I’m so angry I didn’t get the Ms. Diagnosis today. I’m so angry I didn’t get the Lyme diagnosis today. I’m so upset that they can’t find anything wrong with me. And I understand. Dr. Deb Muth 5:20I know the feeling of wanting to put a name to what you’re feeling so that you have validation and you have power around this diagnosis, and you can prove to people that what you’re feeling is not in your head. I get all of that. But for many people, the original diagnosis is meant to help guide treatment in the conventional sense. It’s a created, shared language that we have, and it brings clarity. But for many people, you give that label and that name so much power and so much control over your life and who you are and what you’re being. And that’s not what the label is meant for. Somewhere along the line, medicine started confusing naming with healing. And today, we have more diagnoses than ever. We have more testing than ever. We have so many thousands of specialists, and yet people are sicker. They’re more inflamed, they’re more exhausted, they’re more confused than ever. And that’s not just a coincidence. That is how the system is meant to work. It’s meant to confuse you. Dr. Deb Muth 6:44It’s meant to keep you dependent on it. It’s meant to. Meant to keep you on medical management for the rest of your life. And by doing that, we enrich the pharmaceutical companies to the point where their whole role is to continue to create drugs that you need to be on for the rest of your life. And the hard truth about all of this that I’ve seen in my practice is for many patients, the diagnosis really becomes their identity. They own it, they gravitate to it. It’s who they are. It also becomes their prison because they only live confined inside the diagnosis. I can’t do this because I can’t do that, because if I do this, this will happen, because I have. They’ve capped their ceiling of life based on a couple of words that somebody gave them at a point in their life when they were so low and potentially so desperate that they needed that name to identify themselves and what was going on. And instead of asking, why is this happening? Dr. Deb Muth 8:05Why are these symptoms happening? What’s causing these symptoms? They’re told, this is what you have, and this is what you’re going to have to live with. And instead of restoring function, these people become managed. Like I said, they’re managed with drugs. They’re managed inside the system. And instead of healing, they’re monitored with this blood test and that blood test and this MRI and that mri. Instead of providing hope, they’re handed a lifelong prescription with expectations that do nothing but decline. So you walk out of that room with this expectation that your life is never going to be the same, that your function is going to decline, your neurological disease is going to take over eventually, you’re going to be put in a home, you’re going to lose everything you have because you’re not going to be able to afford the care that you need. And that’s the expectations of our healthcare system today. When you’re labeled with a chronic illness diagnosis, and for a woman, especially women, this is magnified because their symptoms are told to them as. It’s stress, it’s hormones, it’s anxiety, it’s aging, it’s motherhood, and then, of course, it’s perimenopause. Like that is some major traumatic thing that should disrupt your entire life. Yet it shouldn’t, and it does, and it doesn’t have to. And of course, my favorite is always, but your labs are normal. We don’t know what’s wrong with you. It must just be in your head. Dr. Deb Muth 9:53And this is why women are done being dismissed, why this shift is happening now that we are empowering women to take back Their lives, take back who they are and take back how they’re being treated in the healthcare system. And it is one of the most important things that we can do right now is to give women their power back so that they can stand strong in who they are and in their intuition and fight and say, no, this is not happening to me right now. I am not accepting this label. I’m not accepting this diagnosis. I will fight, I will find answers, and I will do what I need to do to be the woman that I want to be. So why is this conversation exploding right now? Well, there’s actually three big reasons, and first and foremost, it’s over. Diagnosis, burnout. People are collecting diagnoses without solutions. Autoimmune labels, syndromes, vague neurological names, but no one’s connecting the dots. Dr. Deb Muth 11:02You see, when you start to stack these labels on top of each other, one after the next after the next, you know, it’s celiac disease, it’s Hashimoto’s, it’s fibromyalgia, it’s autoimmune. You know, rheumatoid arthritis. It’s. Whatever it is, it’s long haul Covid. These days, no one is putting these connections together to say, why are you developing so many diseases that are so similar in nature, ones that just kind of domino after each other? Nobody’s looking at your immune system. Nobody’s measuring it, Nobody’s telling you how well it’s working. No one’s supporting it. They’re just throwing these biological drugs at you. And if there’s an autoimmune disease and sending you on your way and saying, this is what you have to look forward to for the rest of your life. But don’t worry, these side effects are rare, including cancer. It does not make sense to me that we are not looking at the root cause for all of these crazy diagnoses that we are labeling people with today. And I am guilty of it myself, because within the system that we work, we have to label something in order for you to receive the care that you need, for your insurance, to pay for the treatment, for the tests, for the visits. There has to be a label. And that’s what we call an ICD10 code. And if we don’t have the appropriate label, none of what we’re recommending gets covered for you. And that’s the label game began. The second thing is long haul Covid. And post viral illnesses. Dr. Deb Muth 12:47Millions of people were told, we don’t know why, and then we sent them home to figure it out by themselves. We don’t know why your immune system is failing, we don’t know why you’re having these clotting issues that are happening. But don’t worry, these clotting issues really are not that severe. They’re mild in nature. You’ll never have to worry about it. And we’re not going to treat it even though it’s four times the level that’s normal, because we’re going to wait until it’s 10 times the level of normal to even worry about it at this point. Dr. Deb Muth 13:19And it will take us 25 to 30 years before we understand any of the risks and barriers that have happened from these post viral illnesses that have occurred in our environment and the ones that are in the future to come. Because it takes time for us to study things, it takes time for us to figure it out, takes time for us to train the practitioners, and it takes time for us to accept something different than we thought was reality. And that is the problem that we have today with these post viral illnesses that are long acting, that are retriggering new viruses, retriggering old illnesses like Lyme, reactivating things like Epstein Barr virus. It will take decades before this becomes mainstream. And right now it’s fringe medicine and it’s not realistic. And those of us that are speaking about it are chastised and gone after, but by our medical communities and we are told that we are the crazy ones. And that is how medicine has always been. Way in the beginning, and I forget the doctor’s name, who started just observing that when medical students worked on cadavers and then came into the labor and delivery ward and delivered babies, these women were getting sick with infections and they were dying. And he said, what if we just washed our hands between the cadaver and the delivery? Would we save lives? And he did a small study and he was right. And over time he was made fun of and he was put into insane asylums and he was locked away. And now today we would never think of entering a room and working on a patient without washing our hands beforehand. But that took 30 years for that one concept of washing hands to be adopted. And it destroyed one man’s life because he simply asked the question, what if it’s a crazy society that we live in, It’s a crazy outlook that we have on medicine and asking questions. And sometimes I wonder, is it truly science or is it politically driven? And I think the answer is it’s both. And the third thing that we have is technology. And technology is outpacing wisdom by far. Hands down, AI, advanced labs and imaging can identify everything. Now using AI, but without context, it creates a fear. Dr. Deb Muth 16:08And instead of clarity, without context, using AI to interpret labs makes absolutely no sense. Without context and understanding and us actually training this LLM model, the AI doesn’t really know what it, what it means. And someday it will, I’m sure, but right now it doesn’t. So as everyone is taking to AI to treat themselves and create a protocol and diagnose themselves and understand their labs and know that it is without context that you are doing this, and research is wonderful, but without having somebody truly understand you and the art of healing and the art of medicine, this is going to get lost and you will not have the information that you truly need simply by using chat GPT. Now I’ve created my own version called Venari and I hope that this will be much better because it will have context. It will have 15,000 protocols that I have used for the last 25 years. It will have lots of research. It has all of the research databases that we can connect to. It has training that I have given it using my brain and how I see a client every single day in practice. So when you’re using our Venari app, you will be able to have that context. You will be able to have that pushback and that voice. And not only that, you will have the option then to work alongside someone to help you identify that context that you’re looking for. Does this make sense? Dr. Deb Muth 17:53I’ve seen this a lot in the peptide world, where in these Facebook groups, people are talking about the peptide stacks that they’re using and they’re telling people that it’s okay to use any peptide you want because they’re just small chain branch amino acids. And that can’t be farther from the truth because there are some peptides you would not want to use because they can stimulate the growth of cells. And if you have cancer or if you have a history of this, there are some peptides that we need to avoid. And unfortunately, AI doesn’t understand that yet and doesn’t know that yet. And it’s just creating stacks. And people are creating stacks without understanding what they’re doing. And I watched my best friend do this as she was learning peptides and she had cancer and it created an aggressive sarcoma. And I believe the peptides had a lot to do with that because it stimulated the growth of the cells. And it wasn’t until after she had passed away that we found this journal of hers that she was studying peptides and recognized that this could have contributed to her advanced cancer. And if you don’t have that context and you’re using AI to create these stacks for you, you can put yourself in harm’s way. And so AI technology, I think, is going to be fantastic in a lot of ways. It’s going to have its downfalls. And you’re going to need an expert when you’re using AI. You’re not going to just be able to treat yourself with this. You know, understanding that more data doesn’t always equal healing, and more data can be helpful. But again, you have to understand how to put those pieces together, how to ask the right question questions. And for that, you need somebody who has seen thousands and thousands of cases to find the missing pieces for you. Because AI is not going to do that unless it’s been trained to do that. Vanari has been trained to do that. Dr. Deb Muth 20:01It’s been trained to push back and look at lime and mold and toxins and chemicals and metals and all of those things. But there is no other AI bot out there, LLM that has been trained to do that using clinical data that I use every single day in my practice. And people are finally realizing that, you know, they’re understanding that although this world of AI and technology is amazing, it has its limitations, just like practitioners have their limitations. We don’t know everything. We are not perfect. We are human. And humans make errors and we miss things. With or without technology, we miss things. And part of it is because we just don’t know what we don’t know yet. And sometimes it’s because we have our blinders on, and sometimes it’s just simply because we don’t have the information today that we’re going to have five years from now. And here’s what I teach instead. I teach the seenet last. And that’s what we built it on. Restore and root. Rise and restore. Sorry, that is my methodology. And it’s in the scene at last book. And it starts with healing. It starts with asking better questions. So instead of asking, what do you have? We want to ask, what has your body been exposed to? What symptoms are underperforming? What’s driving the inflammation for you? When you have joint pain and you have muscle pain and you have achiness, that is not normal. Dr. Deb Muth 21:38I don’t care if you’re 20 or you’re 80, it is not normal. And yes, I did say 80, because we are not supposed to have that kind of inflammation at 80. And why are we underperforming? Why is our Brain not working correctly? Why is our mood not working? Why can’t my body push up a hill? Why can’t I lift 10 pounds? What’s going on? Why can’t I recover from that activity? What’s interfering with my ability to repair and heal after I’ve done some things that I need to do? What’s keeping your nervous system stuck in this survival mode, in this fight or flight mode? Why can’t I get past that? Sometimes that answer is really simple and sometimes that answer, it is so hard and so complicated and it is so many things that are causing this body to be stuck. And sometimes it’s a six month fix, and sometimes it’s a six year fix and sometimes it’s decades long. And it is one of the most challenging things as a practitioner to get clients to understand and to be on the other side of the table and not get you that quick fix. It is extremely difficult for us as well when we are not seeing the results that we think we should see. We need to focus on function over diagnosis, root cause over labels. Dr. Deb Muth 23:09What is driving all this inflammation and certainly restoration over resignation. Do not resign to the fact that you have this life altering disease that is never going to change. Because if we find the root and we restore the body, you don’t have to live in that death sentence that you’ve been given of a diagnosis, whether it’s fibromyalgia, MS, Alzheimer’s disease, celiac disease, Hashimoto’s thyroiditis, it does not matter what that diagnosis is. We can change it, we can make it better, we can reduce the symptoms, we can improve your life. Maybe not in ways that you are absolutely looking for, maybe not in a perfect world, but we can change the trajectory of where your life is going. And it’s because you’re not an ICD9 code or an ICD10 code. You’re not a code, you’re not an MRI result, you’re not a lab result, you’re a human body asking support, not a name. And I say that with a little hesitation because so many people are looking for the name. So many people are angry that someone didn’t find the name. I have clients that come to me that are so angry that the conventional medicine system did not identify their Lyme disease, that they’re looking for someone to sue and there is no one to sue because they didn’t find it, because sometimes they just don’t know. You’re asking for conventional medicine, practitioner and system to provide for you a label that is not within their wheelhouse to do. Because the way they treat Lyme disease and the way an eyelads practitioner looks at Lyme disease and has. Has the ability to test differently are two very different things. Dr. Deb Muth 25:27You’re asking for a system to perform in a way that they are not trained and guided to do. Then you’re looking and asking for somebody to place blame for an illness that you have, that you have yet taken ownership for. And I know that sounds harsh, and I know there’s going to be a lot of people that are angry at me for saying that. But I sit in front of you as someone who had Lyme disease, who had mold mycotoxin illness, who had high viral titers, who had post Covid peripheral neuropathy, who had the diagnosis of ms, who has white matter brain disease, who treated all of it not in the conventional world, who has halted the white matter disease and regrew her brain by 1.5 standard deviations, which is unheard of in 18 months. So I can say this to you. There is no one to blame for your lack of diagnosis or your diagnosis. It is life. It is what happens to us. And you have a choice at the crossroad to either take the path of hatred and anger and bitterness and blame and never getting better a result of that, or you have the ability to take the path of curiosity and openness and willingness to change and willingness to walk down a path that is different than what the conventional medicine is telling you to do. And those are your choices and you get to make those choices. But what you don’t get to do is blame some someone else and try to destroy them for something that they are not able to do. That is not what we get to do in this life. Dr. Deb Muth 27:29It is not right and it is not fair. If someone has truly injured you, that’s different. That’s different. But this looking to blame somebody because they didn’t give you a label, Ridiculous in my opinion. And if you’re listening and thinking right now, I’ve been diagnosed, but I’m not better, I want you to hear this clearly. You are not broken. You are not crazy, and you are not done. Sometimes the most healing moment isn’t getting that diagnosis. It’s realizing that the diagnosis was never the whole story. And that’s where the real healing begins. When we look at the entire story, we look at your entire life from the beginning to where you are now and what has happened to get you there. And once we get that, then we can put you back together. Not in the old way, in a new way in an amazing way, in a way that you would cherish your life for every moment that you have of it. Good, bad and ugly. A diagnosis should not be the doorway. It’s not a dead end. It is just the beginning. Remember, you don’t need another diagnosis. You need your life back. And that’s what’s important. Dr. Deb Muth 29:19We are living in a moment where medicine is being forced to evolve not because systems want to, but because patients are demanding better. This post diagnosis era isn’t about rejecting science, it’s about using it wisely. It’s about restoring function, dignity and hope. And I hope that if this episode resonated with you, share it with someone who’s been labeled but not yet helped. Because sometimes the most powerful healing starts when someone finally feels seen. Thank you for being with me here today. If you haven’t already, make sure you subscribe and follow. Let’s talk Wellness now on YouTube, Spotify or wherever you’re listening and I’ll see you next time. Until then, keep asking better questions, trusting your body and remembering you are more than a diagnosis.The post Episode 254 – Beyond the Diagnosis: Healing in a Post-Diagnosis Era first appeared on Let's Talk Wellness Now.

Sebastian Raschka joins the MAD Podcast for a deep, educational tour of what actually changed in LLMs in 2025 — and what matters heading into 2026.We start with the big architecture question: are transformers still the winning design, and what should we make of world models, small “recursive” reasoning models and text diffusion approaches? Then we get into the real story of the last 12 months: post-training and reasoning. Sebastian breaks down RLVR (reinforcement learning with verifiable rewards) and GRPO, why they pair so well, what makes them cheaper to scale than classic RLHF, and how they “unlock” reasoning already latent in base models.We also cover why “benchmaxxing” is warping evaluation, why Sebastian increasingly trusts real usage over benchmark scores, and why inference-time scaling and tool use may be the underappreciated drivers of progress. Finally, we zoom out: where moats live now (hint: private data), why more large companies may train models in-house, and why continual learning is still so hard.If you want the 2025–2026 LLM landscape explained like a masterclass — this is it.Sources:The State Of LLMs 2025: Progress, Problems, and Predictions - https://x.com/rasbt/status/2006015301717028989?s=20The Big LLM Architecture Comparison - https://magazine.sebastianraschka.com/p/the-big-llm-architecture-comparisonSebastian RaschkaWebsite - https://sebastianraschka.comBlog - https://magazine.sebastianraschka.comLinkedIn - https://www.linkedin.com/in/sebastianraschka/X/Twitter - https://x.com/rasbtFIRSTMARKWebsite - https://firstmark.comX/Twitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)Blog - https://mattturck.comLinkedIn - https://www.linkedin.com/in/turck/X/Twitter - https://twitter.com/mattturck(00:00) - Intro (01:05) - Are the days of Transformers numbered?(14:05) - World models: what they are and why people care(06:01) - Small “recursive” reasoning models (ARC, iterative refinement)(09:45) - What is a diffusion model (for text)?(13:24) - Are we seeing real architecture breakthroughs — or just polishing?(14:04) - MoE + “efficiency tweaks” that actually move the needle(17:26) - “Pre-training isn't dead… it's just boring”(18:03) - 2025's headline shift: RLVR + GRPO (post-training for reasoning)(20:58) - Why RLHF is expensive (reward model + value model)(21:43) - Why GRPO makes RLVR cheaper and more scalable(24:54) - Process Reward Models (PRMs): why grading the steps is hard(28:20) - Can RLVR expand beyond math & coding?(30:27) - Why RL feels “finicky” at scale(32:34) - The practical “tips & tricks” that make GRPO more stable(35:29) - The meta-lesson of 2025: progress = lots of small improvements(38:41) - “Benchmaxxing”: why benchmarks are getting less trustworthy(43:10) - The other big lever: inference-time scaling(47:36) - Tool use: reducing hallucinations by calling external tools(49:57) - The “private data edge” + in-house model training(55:14) - Continual learning: why it's hard (and why it's not 2026)(59:28) - How Sebastian works: reading, coding, learning “from scratch”(01:04:55) - LLM burnout + how he uses models (without replacing himself)

QNB Dijital Köprü katkılarıyla hazırladığımız 290. bölümde Pirix Kurucusu Çiğdem Öztabak konuğum oldu. QNB Dijital Köprü katkılarıyla... Bu bölüm ⁠⁠⁠⁠QNB Dijital Köprü⁠⁠⁠⁠ hakkında tanıtım içerir. ⁠⁠https://www.qnb.com.tr/dijitalkopru⁠ 2026, geleceğin bir kavram olmaktan çıkıp gündelik hayata çarptığı yıl. Yapay zekadan uzay yarışına, robotlardan insan olmanın anlamına kadar; iş, devletler ve bireyler için geri dönüşü olmayan bir eşiği konuşuyoruz. Abartı ile gerçeklik arasındaki çizgide, AI balonunu, yeni güç dengelerini ve “insan sorusunu” masaya yatırıyoruz. Bu bölüm, geleceği anlatmıyor, gelecekle yüzleştiriyor. (00:00) – Açılış (01:00) – Çiğdem Öztabak'ı tanıyoruz. (03:30) – Gelecek gelmedi mi? Back to The Future - https://en.wikipedia.org/wiki/Back_to_the_Future Her - https://de.wikipedia.org/wiki/Her_(2013) (05:33) - 2026'nın, geleceğin bir kavram olmaktan çıkıp gündelik hayata çarptığı yıl olacağını, AI, uzay, eğitim, iş, danışmanlık şirketleri, robotlar ve insan ömrü üzerinden konuşuyoruz. https://de.wikipedia.org/wiki/Singularity_University Ilya Sutskever - https://de.wikipedia.org/wiki/Ilya_Sutskever (09:15) - 2026'da uzay yarışı kızışıyor. Jeff Bezos, Ay'a inişte Elon Musk'ı muhtemelen geçecek gözüyel bakılıyor. Aynı zamanda Elon Musk da, Mars'a Starship fırlatmaya hazırlanıyor. Uzay neden bu kadar önemli? (13:42) – Uzaydan gele ataklar ve uzayda savunma sanayii (15:35) - Herkesin merak ettiği Çin nerede dersek? (17:47) – Sam Altman İstanbul'a mı geldi? (21:48) - Ülkelerin yapay zeka sağlayıcılarına ve ABD'nin siyasi sistemine bağımlılıktan uzaklaşma çabalarıyla AI egemenliği bu yıl ciddi ivme kazanacak. Yapay Zeka egemenliği nedir? Pivot with Kara Swisher and Scott Galloway - https://www.youtube.com/channel/UCBHGZpDF2fsqPIPi0pNyuTg (24:30) – Yapay Zeka balonunun sönmesi (25:25) – LLM'e yapılacak yatırımlar bitti mi? https://huggingface.co/ (28:44) – Yapay Zeka yatırımları aynı hızla devam eder mi? (31:14) – Yapay Zeka ile ilgili startuplar tarafında çok fazla başarısızlık görebilir miyiz? Severance - https://www.imdb.com/title/tt11280740/ (34:24) – CES 2026 , Kod yazmak hala önemli mi? https://www.instagram.com/p/DSOEtzDDc-j/?hl=de (38:00) – İnsan ve yapay zeka etkileşimi nasıl olacak? Uzun vadeli faydaları ne olacak? Lazy Web (40:57) – Singularity nedir? https://www.su.org/team/ray-kurzweil (47:13) – Yapay zeka ajanları ile çalışırken burada insanlar hangi rollere kayacak? https://de.wikipedia.org/wiki/Geoffrey_Hinton https://www.youtube.com/watch?v=Rni7Fz7208c (48:00) – Üniversitelerde bazı bölümler ortadan mı kalkıyor? (50:00) – İşler değişiyor ve yapay zekaya devrediliyor. (56:00) – Hem bireyler, hem şirketler hem de Devletler için 2026'dan çıkarılması gereken stratejik sonuçlar neler? AI ile rekabet etmek yerine onu nasıl kullanabiliriz? (61:02) - Kapanış Sosyal Medya takibi yaptın mı? ⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠  – ⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠ – ⁠⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠⁠ – ⁠⁠⁠⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠⁠⁠⁠ – ⁠⁠⁠⁠⁠⁠⁠⁠Goodreads⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠Bülten⁠⁠⁠⁠⁠⁠⁠⁠ – ⁠⁠⁠⁠⁠⁠⁠⁠E-Posta⁠⁠⁠⁠⁠⁠⁠⁠ – Bu çalışmaları ve emeklerimi desteklemek için ⁠⁠⁠⁠⁠⁠⁠⁠Patreon⁠⁠⁠⁠⁠⁠⁠⁠  ve ⁠⁠⁠Buy Me A Coffee⁠⁠⁠ hesabımız⁠⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

Jome built a marketplace for new construction homes by solving a transparency problem most people don't know exists: the vast majority of new builds never appear on Zillow, Redfin, or traditional MLS systems. In this episode of BUILDERS, I sat down with Dan Hnatkovskyy, CEO and Co-Founder of Jome, to unpack how he identified a massive category gap during Austin's pandemic housing boom and scaled from scraping builder websites to partnering with 1,700+ builders including 92 of the top 100. Dan shares the specific market moments that unlocked builder partnerships, how he discovered Google's separate product category for new construction, and why early LLM traffic became a meaningful acquisition channel. Topics Discussed: Why IDX feeds and MLS requirements systematically exclude new construction inventory The three market inflection points that accelerated builder partnerships from 500 to 1,500+ in 12 months How Google's separate new construction product category created an arbitrage opportunity against brand-focused builders The manual MVP: Typeform + text message delivery before building any real product Why the mortgage rate lock-in effect (50%+ of mortgages under 3.5% vs 6-7% prevailing rates) compounds the housing shortage Accidentally discovering ChatGPT and Perplexity were driving closed transactions through analytics instrumentation The decision to optimize entirely for buyers despite builders being the sole revenue source GTM Lessons For B2B Founders: Map structural exclusions in existing distribution systems: New construction homes can't enter MLS because they often lack finished addresses, real images, or completed properties—requirements designed for resale homes. This structural incompatibility created a $400B+ blind spot. Dan didn't just find underserved customers; he identified a category systematically locked out of dominant distribution. B2B founders should analyze whether incumbent platforms have structural requirements that exclude segments of the market, not just underserve them. Exploit paid search category mismatches between buyer intent and seller behavior: Dan discovered Google maintains separate product categories for new construction versus resale homes. Zillow and Redfin competed intensely in resale, but new construction was dominated by individual builders (Lennar, DR Horton) who assumed brand-driven intent—similar to car manufacturers. The reality: buyers search "new construction homes in Austin," not "Lennar homes." This category/behavior mismatch created immediate arbitrage. B2B founders should audit whether buyers search by problem/outcome while incumbents bid on brand terms, creating white space for aggregators. Time enterprise outreach to industry stress events, not product readiness: Jome scaled from 500 to 1,500 builders in one year by capitalizing on three specific moments: (1) pandemic demand surge when builders needed millennial/Gen Z reach, (2) 2022 quantitative tightening when builders feared demand collapse, (3) Zillow's 2023 policy change excluding builders with under 10 communities. Dan didn't wait for product-market fit—he mapped when prospects would be most receptive to any solution. B2B founders should create a calendar of industry stress events (regulatory changes, market corrections, competitor policy shifts) and time outreach to these windows regardless of product maturity. Instrument conversion funnels to detect emergent channels before consensus forms: Jome discovered meaningful lead volume and closed transactions from ChatGPT and Perplexity through analytics, not strategy. Only after seeing the data did they experiment with what Dan calls "reinforcement learning with LLMs"—promoting positive results to train the models. This wasn't about SEO or prompt engineering; it was about measurement infrastructure that surfaced signal before the channel was obvious. B2B founders should track referral sources at the closed deal level, not just top-of-funnel, to catch emerging platforms while unit economics are still favorable. Manually deliver value at zero margin before building product: Before any integrations or platform, Jome ran Google Ads to a Typeform, manually created searches in their agent-facing tool, and texted results to buyers. Dan's framework: "Start with manually creating value...and then step by step, improve it, automate it, make it more efficient." He launched this on a personal credit card and got immediate signal. B2B founders should resist the urge to build scalable product until they've proven someone will pay for (or convert on) manual delivery of the outcome. Optimize for the non-paying side when you're building a two-sided marketplace: Despite 100% of revenue coming from builder commissions, every product decision optimizes for buyer experience. Dan's logic: "If we want to bring value to the builders...we need to start with the buyers. We need to create the best possible home buying journey." This isn't idealism—it's recognition that in transaction-based models, buyer liquidity determines builder participation. B2B founders in marketplace businesses must identify which side is supply-constrained and build obsessively for the other side. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

When Tricia Meyer's name was called as this year's Pinnacle Award winner at Affiliate Summit West, there was a moment of silence. Not because the room disagreed, but because Tricia herself didn't believe it. After two decades of watching her heroes receive that same recognition, the publisher-turned-executive director of the Performance Marketing Association finally earned the industry's most prestigious honor. This conversation explores what it actually takes to reach the top without losing yourself, why being kind isn't a weakness in business negotiations, and how staying curious about industry changes for 20 years reveals patterns that help you stop panicking about AI, zero-click search, and whatever disruption comes next.Talking Points Include:The attorney who left law for affiliate marketing when she realized publishers could earn more than lawyers and built a 20-year career that started with mom blogs and evolved into executive leadershipWhy community platforms fail but weekly calls succeed isn't just about affiliates – the same principles apply to how industry associations create genuine connection versus performative membershipThe shocking truth about affiliate marketing's growth that most brands miss – independent studies prove the channel is outpacing e-commerce itself, not just riding the online shopping waveListen to Find Out More About:Why Tricia created custom tracking tools using AI to solve AI-caused attribution problems, and how small publishers can do the same with vibe coding platforms like LovableThe critical section being added to PMA's retailer agreement guide about AI usage, plagiarism, and disclosure requirements in affiliate terms and conditionsHow Google's constant testing of citations in Gemini (from detailed paragraph attribution to zero citations to YouTube video insertions) reveals nobody knows what's coming nextWhy publishers might strategically rewrite content to feature competitors if brands don't properly value their contribution to LLM-driven trafficThe new AI Council launching to address both publisher optimization for LLMs and technology solutions for brands dealing with compliance and trackingHow fintech and B2B affiliate marketing represent massive industry segments the PMA is finally addressing with dedicated resourcesWhy analyzing five years of industry study data would reveal cyclical patterns that help predict where apparent disruptions actually leadHow Open Attribution is creating free membership opportunities to discuss citation tracking and publisher rewards in the age of LLMsKey Segments of This Podcast and Where You Can Tune In to Go Direct:[06:02] Working from the bottom of PMA working groups to executive director, and why being an attorney made Tricia the perfect fit for part-time leadership[[19:54] Three critical areas where affiliates need preparation for 2025: LLM optimization, proving publisher worth through journey tracking, and staying educated on rapid changes[27:00] Why affiliate program terms and conditions need AI clauses now, covering content generation, plagiarism, and disclosure requirements[30:11] The five-year prediction: fundamentally everything stays the same but with different technical details, just like the last 20 years of disruptionSend me a text with your questions

News and Updates: Grok bans illegal porn generation- After global backlash and app-store scrutiny, X says Grok now blocks child porn and nonconsensual deepfakes, but only where legally required, underscoring reactive, profit-driven governance. Why Grok remains in Google Play- Despite Google Play policies explicitly banning AI-generated nonconsensual sexual content, Musk's Grok remains approved for teens, exposing enforcement failures that leave minors and victims unprotected. Under Musk, the Grok disaster was inevitable- Designed to be edgy with weak safety staffing, Grok's image-editing features predictably enabled nonconsensual sexual deepfakes, triggering international probes, legal pressure, and belated bypassed restrictions. OpenAI targets 2026 hardware reveal- OpenAI confirmed plans to unveil its hardware device in late 2026, signaling a move beyond software toward minimalist, voice-first AI products designed with Jony Ive. Amazon auto-upgrades Prime users to Alexa Plus- Amazon is automatically upgrading Prime members to Alexa Plus, an LLM-powered assistant users can revert, sparking complaints over forced adoption, ads, responses, and personality changes. Congress and the Kids Off Social Media Act- Congress's KOSMA would ban under-13 social media but effectively forces platforms to police families, overriding parental consent and expanding Big Tech control through age verification.

CISA's interim director uploaded sensitive government material into the public version of ChatGPT. The cyberattack on Poland's power grid compromised roughly 30 energy facilities. The EU and India sign a new partnership that includes expanded cyber cooperation. Meta rolls out enhanced WhatsApp security features. Researchers uncover a campaign targeting LLM service endpoints. Fortinet and OpenSSL patch multiple vulnerabilities. A high-severity WinRAR vulnerability continues to see widespread exploitation six months after it was patched. The SoundCloud data breach affected nearly 30 million users. Ben Yelin explains the California lawsuit accusing social media platforms of harming kids. A Spanish resort town gets hit with low-rent ransomware.   Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. CyberWire Guest Today, Dave is joined by his Caveat co-host Ben Yelin, Program Director for Public Policy & External Affairs at the University of Maryland Center for Cyber Health and Hazard Strategies, to discuss the upcoming trial where Meta and YouTube will make their case against accusations of social media being harmful to children. You can learn more here.  T-Minus Guest Host Our T-Minus Space Daily podcast team is in Orlando, FL this week covering Commercial Space Week. Yesterday while the crew was on travel making their way to the event, Dave Bittner took his first spin behind the mic on T-Minus. Tune in and let us know how Dave did! You can follow along with host Maria Varmazis and producers Alice Carruth and Liz Stokes for event coverage via our LinkedIn profile. Selected Reading Trump's acting cyber chief uploaded sensitive files into a public version of ChatGPT (POLITICO) Cyberattack on Poland's power grid hit around 30 energy facilities, new report says (The Record) Europe/India • Indian 'hackers for hire' to continue to thrive under Brussels-New Dehli trade deal (Intelligence Online) New WhatsApp lockdown feature protects high-risk users from hackers (Bleeping Computer) Hackers hijack exposed LLM endpoints in Bizarre Bazaar operation (Bleeping Computer) Fortinet Patches Exploited FortiCloud SSO Authentication Bypass (SecurityWeek) High-Severity Remote Code Execution Vulnerability Patched in OpenSSL (SecurityWeek) Cybercriminals and nation-state groups are exploiting a six-month old WinRAR defect (CyberScoop) SoundCloud breach added to HIBP, 29.8 million accounts exposed (CyberInsider) Spanish municipality Sanxenxo City Council calls hackers bluff as malware takes over network (Cryptopolitan) Share your feedback. What do you think about CyberWire Daily? Please take a few minutes to share your thoughts with us by completing our brief listener survey. Thank you for helping us continue to improve our show.  Want to hear your company in the show? N2K CyberWire helps you reach the industry's most influential leaders and operators, while building visibility, authority, and connectivity across the cybersecurity community. Learn more at sponsor.thecyberwire.com. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc. Learn more about your ad choices. Visit megaphone.fm/adchoices

Hey CX Nation,In this week's episode of The CXChronicles Podcast #275, we welcomed Sagi Reuven, Chief Revenue Officer at Deepdub based in Tel Aviv, Israel. Deepdub is the enterprise voice infrastructure powering AI in production. Deepdub built their credibility in the most demanding voice environments in the world: Hollywood studios, global broadcasters, and premium content pipelines where voice quality, emotional accuracy, and reliability are non-negotiable.Deepdub enables zero-shot voice cloning, voice-to-voice, ADR, accent control, and ultra-low latency delivery designed for systems that operate live, at scale, and in front of real customers.Get started here> https://deepdub.ai/ FYI even better if you let them know that CXC sent you their way!In this episode, Sagi and Adrian chat through the Four CX Pillars: Team, Tools, Process & Feedback. Plus share some of the ideas that his team think through on a daily basis to build world class customer experiences.**Episode #275 Highlight Reel:**1. Personalize for problems, not people.2. Keeping top talent by building smarter teams3. AI's impact on leadership & strategy4. The Partnership Economy is here5. Changes to prepare for in the work placeClick here to learn more about Sagi ReuvenClick here to learn more about DeepdubHuge thanks to Sagi for coming on The CXChronicles Podcast and featuring his work and efforts in pushing the customer experience & contact center space into the future. For all of our Apple & Spotify podcast listener friends, make sure you are following CXC & please leave a 5 star review so we can find new members of the "CX Nation". You know what would be even better?Go tell your friends or teammates about CXC's custom content, strategic partner solutions (Hubspot, Intercom, & Freshworks) & On-Demand services & invite them to join the CX Nation, a community of 15K+ customer focused business leaders!Want to see how your customer experience compares to the world's top-performing customer focused companies? Check out the CXC Healthzone, an intelligence platform that shares benchmarks & insights for how companies across the world are tackling The Four CX Pillars: Team, Tools, Process & Feedback & how they are building an AI-powered foundation for the future. Thanks to all of you for being apart of the "CX Nation" and helping customer focused business leaders across the world make happiness a habit!Reach Out To CXC Today!Support the showContact CXChronicles Today Tweet us @cxchronicles Check out our Instagram @cxchronicles Click here to checkout the CXC website Email us at info@cxchronicles.com Remember To Make Happiness A Habit!!

Humanoid robots are coming into our homes, but they probably won't be doing your laundry anytime soon.In this episode of TechFirst, host John Koetsier sits down with Jan Liphardt, founder & CEO of OpenMind and Stanford bioengineering professor, to unpack what home robots will actually do in the near future ... and why the “labor-free home” vision is mostly a myth (for now).Jan explains why hands are still one of the hardest unsolved problems in robotics, why folding laundry is far harder than it looks, and why the most valuable early use cases for home robots aren't chores at all. Instead, we explore where robots are already delivering real value today:• Health companionship and fall detection for aging parents• Personalized education for kids, beyond screens• Home security that respects privacy• And why people form emotional bonds with robots faster than expectedWe also dive into OM1, OpenMind's open-source, AI-native operating system for robots, and why openness, transparency, and configurability will matter deeply as robots move from factories into our living rooms.If you're curious about the real future of humanoid robots — what's hype, what's possible today, and what's coming next — this conversation is for you.

＜目次＞(0:00) 今までの振り返り(1:37) ChatGPTのメモリーレイヤーの実態とトレードオフ(8:52) 情報の劣化と価値の変化(13:09) 自分の世代の音楽が一番と感じる説(14:34) どの服を着ていくべきか？の複雑さ(16:27) 大量のデータが必要になるが実現する難しい(19:59) 複数のアルゴリズムが同時並行で走る(22:24) AIによるモノカルチャー化とLLMの言語(25:50) AIにSF小説を書かせると同じ主人公の名前が出てくる現象(29:25) イギリス政治家がLLMに影響される事例(31:01) 映画、フォント、本の表紙、サムネイルなどのモノカルチャー化(35:50) アメリカ人のアルコール消費量が落ちた影響(38:29) 逸脱・ふざける重要性、違いを見つけるAI(40:30) 私自身がまだ気づいてないかもしれないユニークな点(43:30) 飲まない宮武さんが語るアルコールの話w(43:44) 意外と違いがあまりないかも？(45:32) 未だに見てない「The Big Door Prize」(46:37) AIメモリーの発展によって人間は情報を覚えなくなるのか？(48:14) 何を覚えないといけないのか？(51:29) デジタルツインと大量通知の時代(54:46) 通知の歴史(58:00) AIの記憶再現、合成メモリーの可能性＜参照リンク＞https://offtopicjp.notion.site/303-2c9c8b57e114804ca47bd06af06ff04e?source=copy_link＜About Off Topic＞Podcast:Apple - https://apple.co/2UZCQwzSpotify - https://spoti.fi/2JakzKmOff Topic Clubhttps://note.com/offtopic/membershipX - https://twitter.com/OffTopicJP草野ミキ:https://twitter.com/mikikusanohttps://www.instagram.com/mikikusano宮武テツロー: https://twitter.com/tmiyatake1

On the 62nd episode of Enterprise AI Innovators, hosts Evan Reiser (CEO and co-founder, Abnormal AI) and Saam Motamedi (Greylock Partners) talk with Mike Trkay, CIO at FICO. Mike explains how FICO is moving AI from pilots to production by prioritizing ROI, data foundations, and governance. He argues for sanctioned LLM access to curb leakage, system integration for business-wide answers, and smaller domain models when accuracy, compliance, and trust matter.Quick hits from Mike:On the shift from pilots to ROI: “We're leaving that phase and starting to get to the point of going, okay, but where's the true return on that investment?”On the must-do for enterprises: “Everybody who works for you… they're going to go use one of the LLMs somewhere… and probably share data and proprietary data.”On why one big model is not enough: “Sometimes you need the PhD. Who's got who speaks the jargon, understands the context, and it helps deal with some of the hallucinations and bias, and other things that could be influencing.”Recent Book Recommendation: The Forgotten Founding Father: Noah Webster's Obsession and the Creation of an American Culture by Joshua Kendall--Like what you hear? Leave us a review and subscribe to the show on Apple, Spotify, or Youtube you listen to podcasts.Enterprise AI Innovators is a show where top technology executives share how AI is transforming the enterprise. Find more great lessons from tech leaders and enterprise software experts at https://www.enterprisesoftware.blog/ Enterprise AI Innovators is produced by Abnormal Studios.

Jyoti Pannu, Product Manager at Booking.com, shares how AI is transforming the way travelers discover, plan, and book their next adventure. From AI trip planners that surface new possibilities to the integration of GenAI and ChatGPT into the core product, Jyoti explains why travel discovery is moving beyond simple search, how user intent is now mapped through nuanced signals, and what the rise of LLMs means for attribution, retention, and the future of app UX. She also dives into cross-vertical product lessons, balancing novelty and personalization, and offers advice for elevating women in product management.Questions addressed in this episode:What is Booking.com, and what does Jyoti's role cover?How is AI being used at Booking.com beyond chatbots and content generation?What does intent-based and natural language discovery look like in practice?How is the app experience changing with AI-driven trip planners and smart filters?How does Booking.com balance user personalization and novelty in recommendations?How do LLM-based discovery channels affect paid UA and retargeting strategies?What guardrails and metrics are important for launching new AI features?What lessons cross over from fintech, e-commerce, and travel in app retention?How should product teams think about post-purchase and post-trip experience?What advice does Jyoti have for women building a career in product and tech?Timestamps:(0:03) – Jyoti's role at Booking.com and scope of the app(1:39) – AI trip planners and intent-driven product development(3:17) – Smart filters and natural language input for hotel discovery(4:03) – How Booking.com infers trip purpose and personalizes UX(6:09) – LLMs, ChatGPT, and new search/discovery interfaces(8:13) – Attribution, channel mix, and UA economics in an AI-first world(11:01) – Avoiding the filter bubble in travel recommendations(13:41) – Booking.com plugins and booking via ChatGPT(15:41) – Cross-vertical product lessons from e-commerce, fintech, and travel(17:58) – Brand omnipresence, loyalty, and retention(19:04) – Emotional stakes and UX in travel vs. transactional apps(21:37) – Post-trip and post-purchase: product touchpoints(22:50) – Testing AI features for retention and quality(24:24) – Guardrails, review, and data governance(25:29) – Elevating women in product and leadership(27:50) – Rapid-fire: travel, career, life, and favorite placesQuotes:(3:35) “We have an option for users called smart filters, where they can make searches in the form of natural language, like how you would interact with a human. We map this in our systems to provide personalized results for these users.”(17:00) “If a user has interacted with our platform and they have made a purchase from two different categories, they are more likely to become a high value customer than someone who has bought multiple times in the same category.”Mentioned in This Episode:Jyoti Pannu on LinkedInBooking.com

Doctronic became the first AI in the world legally licensed to practice medicine through Utah's AI Learning Lab regulatory sandbox in December 2025. In this episode of BUILDERS, I sat down with Matt Pavelle, Co-founder and Co-CEO of Doctronic, to learn how he and his co-founder (a physician) launched an AI-powered primary care chatbot in September 2023, validated demand through Facebook chronic condition groups and minimal Google Ads spend, and navigated uncharted regulatory territory to offer $4 prescription renewals for chronic conditions—targeting the medication non-adherence problem that causes 125,000 preventable deaths and costs $100B annually. Topics Discussed: Why friends with excellent health insurance still couldn't get medical answers quickly Building clinical accuracy into GPT-3.5 when context windows were small and hallucinations were rampant The tactical launch: Google Ads plus Facebook chronic condition groups in September 2023 Architecting safety: RAG with tens of thousands of physician-written clinical guidelines The study: 99.2% agreement rate between AI treatment plans and human doctor reviews across 500 patients Navigating Utah's AI Learning Lab: the only regulatory sandbox that mitigated medical licensing laws Securing AI malpractice insurance through Lloyd's Market—a first in the industry The three-phase oversight model: 100% human review, then 10%, then spot checks Expansion strategy: targeting other state regulatory sandboxes and international governments GTM Lessons For B2B Founders: Launch with the minimum feature set that proves your core hypothesis: Pavelle shipped Doctronic in September 2023 without user accounts—chats disappeared when closed unless users saved them manually. Within days, user requests for persistent chat history validated demand. The insight: your MVP should test one assumption, not solve every user need. If you're hesitating to launch because features are missing, ask whether those features are actually required to validate your hypothesis or just things you assume users want. Use specificity to unlock early adoption in skeptical markets: Rather than targeting "healthcare" broadly, Pavelle posted in Facebook groups for specific chronic conditions, offering a free AI backed by clinical guidelines. Half the groups banned them for commercial activity, but the other half engaged immediately. The lesson: in regulated or skeptical markets, narrow targeting with explicit safety mechanisms (clinical guidelines, physician co-founder credibility) converts better than broad positioning. Identify where your skeptics congregate and address their specific objections upfront. Design system architecture to prevent failure modes, not just tune models: Doctronic's safety architecture separates AI decision-making from prescription execution. The LLM asks questions and determines renewal safety, but deterministic code outside the AI verifies the prescription exists, checks dosage accuracy, and confirms the schedule. Even if adversarial prompting compromises the LLM, the deterministic layer prevents bad outcomes. Founders building high-stakes AI products should architect multiple independent verification layers rather than relying on prompt engineering or temperature tuning alone. Target regulatory pain points with quantified deaths and costs: Pavelle approached Utah with specific numbers: 125,000 preventable deaths annually from medication non-adherence, 30-40% caused by renewal friction, and a $100B economic burden. These statistics—combined with Utah's rural population and physician shortage—made the problem impossible to ignore. When approaching regulators, lead with mortality and cost data that make inaction untenable, not just efficiency gains or convenience improvements. Regulatory sandboxes require proof of safety methodology, not just technology demos: Utah's AI Learning Lab didn't just grant Doctronic permission—they required a three-phase oversight structure where human physicians review 100% of initial prescriptions in each medication class, then 10%, then ongoing spot checks. Pavelle also secured AI malpractice insurance through Lloyd's Market before launch. The insight: regulatory innovation offices want risk mitigation frameworks, not promises. Build and fund your oversight methodology before approaching regulators, and treat insurance underwriting as a third-party validation of your safety claims. Publish clinical validation studies before scaling—they become your regulatory and sales asset: The study showing 99.2% agreement between Doctronic's AI and human physicians across 500 patient encounters became the foundation for regulatory conversations and public trust. Founders in regulated spaces should budget for formal validation studies early—these aren't marketing expenses, they're the permission structure for everything that follows. Work backward from what regulators and enterprise buyers need to see, then design studies that generate that specific evidence. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

In this episode of Next in Media, I sit down with Kiri Masters, host of the Retail Media Breakfast Club podcast, to explore the biggest shifts happening in retail media advertising. We dive into the recent announcement about ads coming to ChatGPT and what that means for brands trying to meet consumers where they are. Kiri shares her perspective on whether AI-powered shopping will truly disrupt the retail media landscape - and why she's optimistic that LLM-based ads could actually be more relevant and less annoying than traditional formats. We also unpack the Walmart-Google partnership and discuss what it signals about the future of conversational commerce.Beyond the AI conversation, we tackle some of the industry's most pressing questions. Will we see consolidation in retail media networks this year? Can shoppable TV finally gain traction? And what happens when offsite retail media faces competition from platforms with their own transactional data? Kiri brings both historical context - including a fascinating story about Piggly Wiggly's self-service revolution - and forward-looking insights about how brands and retailers need to collaborate differently. Whether you're a marketer navigating this space or just curious about where AI and commerce intersect, this conversation offers a clear-eyed look at what's real, what's hype, and what's coming next._______________________________________________Key Highlights 

Site owners are seeing traffic to their websites drop considerably as users begin asking AI questions, instead of searching for solutions on individual sites. Value-based websites seem to be getting hit with the worst of it, as tutorials and listicles are easily presented right inside an LLM's chat window. This leaves many site owners with a dilemma - should they continue to chase SEO trends, or should they reach for something more tuned to AI, like AEO and GEO? With many websites being run by just a few staff members, resources are tight - so every missed pageview matters. In 2026, should site owners worry about SEO, GEO, or AEO? Or maybe even all of them at the same time? Show Notes: https://www.htmlallthethings.com/podcast/should-you-worry-about-seo-geo-and-aeo-in-2026 Powered by CodeRabbit - AI Code Reviews: https://coderabbit.link/htmlallthethings Use our Scrimba affiliate link (https://scrimba.com/?via=htmlallthethings) for a 20% discount!! Full details in show notes.

Software engineering is changing fast, but not in the way most hot takes claim. Robert Brennan, Co founder and CEO at OpenHands, breaks down what happens when you outsource the typing to the LLM and let software agents handle the repetitive grind, without giving up the judgment that keeps a codebase healthy. This is a practical conversation about agentic development, the real productivity gains teams are seeing, and which skills will matter most as the SDLC keeps evolving. Key TakeawaysAI in the IDE is now table stakes for most engineers, the bigger jump is learning when to delegate work to an agentThe best early wins are the unglamorous tasks, fixing tests, resolving merge conflicts, dependency updates, and other maintenance work that burns time and attentionBigger output creates new bottlenecks, QA and code review can become the limiting factor if your workflow does not adaptSenior engineering judgment becomes more valuable, good architecture and clean abstractions make it easier to delegate safely and avoid turning the codebase into a messThe most durable human edge is empathy, for users, for teammates, and for your future self maintaining the systemTimestamped Highlights00:40 What OpenHands actually is, a development agent that writes code, runs it, debugs, and iterates toward completion02:38 The adoption curve, why most teams start with IDE help, and what “agent engineers” do differently to get outsized gains06:00 If an engineer becomes 10x faster, where does the time go, more creative problem solving, less toil15:01 A real example of the SDLC shifting, a designer shipping working prototypes and even small UI changes directly16:51 The messy middle, why many teams see only moderate gains until they redraw the lines between signal and noise20:42 Skills that last, empathy, critical thinking, and designing systems other people can understand22:35 Why this is still early, even if models stopped improving today, most orgs have not learned how to use them well yetA line worth sharing“The durable competitive advantage that humans have over AI is empathy.”Pro Tips for Tech TeamsStart by delegating low creativity tasks, CI failures, dependency bumps, and coverage improvements are great training wheelsDefine “safe zones” for non engineers contributing, like UI tweaks, while keeping application logic behind clearer guardrailsInvest in abstractions and conventions, you want a codebase an agent can work with, and a human can trustTrack where throughput stalls, if PR review and QA are the bottleneck, productivity gains will not show up where you expectCall to ActionIf you got value from this one, follow the show and share it with an engineer or product leader who is sorting out what “agentic development” actually means in practice.

Ryan Glynn, Staff Security Engineer at Compass, has a practical AI implementation strategy for security operations. His team built machine learning models that removed 95% of on-call burden from phishing triage by combining traditional ML techniques with LLM-powered semantic understanding. He also explores where AI agents excel versus where deterministic approaches still win, why tuning detection rules beats prompt-engineering agents, and how to build company-specific models that solve your actual security problems rather than chasing vendor promises about autonomous SOCs.Topics discussed:Language models excel at documentation and semantic understanding of log data for security analysis purposesUsing LLMs to create binary feature flags for machine learning models enables more flexible detection engineeringAgentic SOC platforms sometimes claim to analyze data they aren't actually querying accurately in practiceTuning detection rules directly proves more reliable than trying to prompt-engineer agent analysis behaviorIntent classification in email workflows helps automate triage of forwarded and reported phishing attempts effectivelyCustom ML models addressing company-specific burdens can achieve 95% reduction in analyst workload for targeted problemsAlert tagging systems with simple binary classifications enable better feedback loops for AI-assisted detection tuningContext gathering costs in security make efficiency critical when deploying AI agents across diverse data sourcesQuery language complexity across SIEM platforms creates challenges for general-purpose LLM code generation capabilitiesExplainable machine learning models remain essential for security decisions requiring human oversight and accountabilityListen to more episodes: Apple Spotify YouTubeWebsite

In this episode of Absolute AppSec, hosts Ken Johnson and Seth Law interview Mohan Kumar and Naveen K Mahavisnu, the practitioner-founders of Aira Security, to explore the critical challenges of securing autonomous AI agents in 2026. The conversation centers on the industry's shift toward "agentic workflows," where AI is delegated complex tasks that require monitoring not just for access control, but for the underlying "intent" of the agent's actions. The founders explain that agents can experience "reasoning drift," taking dangerous or unintended shortcuts to complete missions, which necessitates advanced guardrails like "trajectory analysis" and human-in-the-loop interventions to ensure safety and data integrity. A significant portion of the episode is dedicated to the security of the Model Context Protocol (MCP), highlighting how these integration servers can be vulnerable to "shadowing attacks" and indirect prompt injections—exemplified by a real-world case where private code was exfiltrated via a public GitHub pull request. To address these gaps, the guests introduce their open-source tool, MCP Checkpoint, which allows developers to baseline their agentic configurations and detect malicious changes in third-party tooling. Throughout the discussion, the group emphasizes that as AI moves into production, security must evolve into a proactive enablement layer that understands the probabilistic and unpredictable nature of LLM reasoning.

Mike Oaten is the Founder and CEO of TIKOS, working on building AI assurance, explainability, and trustworthy AI infrastructure, helping organizations test, monitor, and govern AI models and systems to make them transparent, fair, robust, and compliant with emerging regulations.Cracking the Black Box: Real-Time Neuron Monitoring & Causality Traces // MLOps Podcast #358 with Mike Oaten, Founder and CEO of TIKOSJoin the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractAs AI models move into high-stakes environments like Defence and Financial Services, standard input/output testing, evals, and monitoring are becoming dangerously insufficient. To achieve true compliance, MLOps teams need to access and analyse the internal reasoning of their models to achieve compliance with the EU AI Act, NIST AI RMF, and other requirements.In this session, Mike introduces the company's patent-pending AI assurance technology that moves beyond statistical proxies. He will break down the architecture of the Synapses Logger, a patent-pending technology that embeds directly into the neural activation flow to capture weights, activations, and activation paths in real-time.// BioMike Oaten serves as the CEO of TIKOS, leading the company's mission to progress trustworthy AI through unique, high-performance AI model assurance technology. A seasoned technical and data entrepreneur, Mike brings experience from successfully co-founding and exiting two previous data science startups: Riskopy Inc. (acquired by Nasdaq-listed Coupa Software in 2017) and Regulation Technologies Limited (acquired by mnAi Data Solutions in 2022).Mike's expertise spans data, analytics, and ML product and governance leadership. At TIKOS, Mike leads a VC-backed team developing technology to test and monitor deep-learning models in high-stakes environments, such as defence and financial services, so they comply with the stringent new laws and regulations.// Related LinksWebsite: https://tikos.tech/LLM guardrails: https://medium.com/tikos-tech/your-llm-output-is-confidently-wrong-heres-how-to-fix-it-08194fdf92b9Model Bias: https://medium.com/tikos-tech/from-hints-to-hard-evidence-finally-how-to-find-and-fix-model-bias-in-dnns-2553b072fd83Model Robustness: https://medium.com/tikos-tech/tikos-spots-neural-network-weaknesses-before-they-fail-the-iris-dataset-b079265c04daGPU Optimisation: https://medium.com/tikos-tech/400x-performance-a-lightweight-open-source-python-cuda-utility-to-break-vram-barriers-d545e5b6492fHyperbolic GPU Cloud: app.hyperbolic.ai.Coding Agents Conference: https://luma.com/codingagents~~~~~~~~ ✌️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 Mike on LinkedIn: /mike-oaten/Timestamps:[00:00] Regulations as Opportunity[00:25] Regulation Compliance Fun[02:49] AI Act Layers Explained[05:19] Observability in Systems vs ML[09:05] Risk Transfer in AI[11:26] LLMs and Model Approval[14:53] LLMs in Finance[17:17] Hyperbolic GPU Cloud Ad[18:16] Stakeholder Alignment and Tech[22:20] AI in Regulated Environments[28:55] Autonomous Boat Regulations[34:20] Data Compliance Mapping[39:11] Data Capture Strategy[41:13] EU AI Act Insights[44:52] Wrap up[45:45] Join the Coding Agents Conference!

Topics covered in this episode: GreyNoise IP Check tprof: a targeting profiler TOAD is out Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: GreyNoise IP Check GreyNoise watches the internet's background radiation—the constant storm of scanners, bots, and probes hitting every IP address on Earth. Is your computer sending out bot or other bad-actor traffic? What about the myriad of devices and IoT things on your local IP? Heads up: If your IP has recently changed, it might not be you (false positive). Brian #2: tprof: a targeting profiler Adam Johnson Intro blog post: Python: introducing tprof, a targeting profiler Michael #3: TOAD is out Toad is a unified experience for AI in the terminal Front-end for AI tools such as OpenHands, Claude Code, Gemini CLI, and many more. Better TUI experience (e.g. @ for file context uses fuzzy search and dropdowns) Better prompt input (mouse, keyboard, even colored code and markdown blocks) Terminal within terminals (for TUI support) Brian #4: FastAPI adds Contribution Guidelines around AI usage Docs commit: Add contribution instructions about LLM generated code and comments and automated tools for PRs Docs section: Development - Contributing : Automated Code and AI Great inspiration and example of how to deal with this for popular open source projects “If the human effort put in a PR, e.g. writing LLM prompts, is less than the effort we would need to put to review it, please don't submit the PR.” With sections on Closing Automated and AI PRs Human Effort Denial of Service Use Tools Wisely Extras Brian: Apparently Digg is back and there's a Python Community there Why light-weight websites may one day save your life - Marijke LuttekesHome Michael: Blog posts about Talk Python AI Integrations Announcing Talk Python AI Integrations on Talk Python's Blog Blocking AI crawlers might be a bad idea on Michael's Blog Already using the compile flag for faster app startup on the containers: RUN --mount=type=cache,target=/root/.cache uv pip install --compile-bytecode --python /venv/bin/python I think it's speeding startup by about 1s / container. Biggest prompt yet? 72 pages, 11, 000 Joke: A date via From Pat Decker

We argue that SEO isn't dying; bad SEO is. Fundamentals still drive wins while LLMs change how answers surface, making complete, original content and smart strategy more valuable than ever.• fundamentals over fads as LLMs shift discovery• why pages beyond top ten fuel LLM citations• customer journey, CRO, PR, and dev fluency as real leverage• global markets with lower competition and faster output• enterprise constraints, silos, and when to say no• partnerships over one‑stop shops to deliver depth• personalization pitfalls in tracking and sane KPI alignment• future of agents, multimodal search, and offline attentionGuest Contact Information: LinkedIn: linkedin.com/in/kresimir-corlukaWebsite: canonical.hrSummit: croatiaseosummit.comMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon PodcastFree SEO Consultation: www.ewrdigital.com/discovery-callWith over 5 million downloads, The Best SEO Podcast has been the go-to show for digital marketers, business owners, and entrepreneurs wanting real-world strategies to grow online. Now, host Matthew Bertram — creator of LLM Visibility™ and the LLM Visibility Stack™, and Lead Strategist at EWR Digital — takes the conversation beyond traditional SEO into the AI era of discoverability. Each week, Matthew dives into the tactics, frameworks, and insights that matter most in a world where search engines, large language models, and answer engines are reshaping how people find, trust, and choose businesses. From SEO and AI-driven marketing to executive-level growth strategy, you'll hear expert interviews, deep-dive discussions, and actionable strategies to help you stay ahead of the curve. Find more episodes here: youtube.com/@BestSEOPodcastbestseopodcast.combestseopodcast.buzzsprout.comFollow us on:Facebook: @bestseopodcastInstagram: @thebestseopodcastTiktok: @bestseopodcastLinkedIn: @bestseopodcastConnect With Matthew Bertram: Website: www.matthewbertram.comInstagram: @matt_bertram_liveLinkedIn: @mattbertramlivePowered by: ewrdigital.comSupport the show

Segment 1: Interview with Thyaga Vasudevan Hybrid by Design: Zero Trust, AI, and the Future of Data Control AI is reshaping how work gets done, accelerating decision-making and introducing new ways for data to be created, accessed, and shared. As a result, organizations must evolve Zero Trust beyond an access-only model into an inline data governance approach that continuously protects sensitive information wherever it moves. Securing access alone is no longer enough in an AI-driven world. In this episode, we'll unpack why real-time visibility and control over data usage are now essential for safe AI adoption, accurate outcomes, and regulatory compliance. From preventing data leakage to governing how data is used by AI systems, security teams need controls that operate in the moment - across cloud, browser, SaaS, and on-prem environments - without slowing the business. We'll also explore how growing data sovereignty and regulatory pressures are driving renewed interest in hybrid architectures. By combining cloud agility with local control, organizations can keep sensitive data protected, governed, and compliant, regardless of where it resides or how AI is applied. This segment is sponsored by Skyhigh Security. Visit https://securityweekly.com/skyhighsecurity to learn more about them! Segment 2: Why detection fails Caleb Sima put together a nice roundup of the issues around detection engineering struggles that I thought worth discussing. Amélie Koran also shared some interesting thoughts and experiences. Segment 3: Weekly Enterprise News Finally, in the enterprise security news, Fundings and acquisitions are going strong can cyber insurance be profitable? some new free tools shared by the community RSAC gets a new CEO Large-scale enterprise AI initiatives aren't going well LLM impacts on exploit development AI vulnerabilities global risk reports floppies are still used daily, but not for long? All that and more, on this episode of Enterprise Security Weekly. Visit https://www.securityweekly.com/esw for all the latest episodes! Show Notes: https://securityweekly.com/esw-443

Tech has looked unstoppable thanks to AI winners—but a huge part of the market is telling a very different story. In this episode, Simon and Dan break down the brutal valuation reset hitting SaaS (Software-as-a-Service) stocks, with many major names down 30–50%+ despite still-solid underlying businesses. They explain the classic “moats” that made SaaS so powerful—switching costs, ecosystems, and data—and why AI agents and LLM-driven automation are now challenging the seat-based pricing model that many software companies depend on. The discussion moves through a rapid-fire list of well-known SaaS names to unpack what’s driving the drawdowns, where the market may be overreacting, and where the risk of disruption is real. Bottom line: some of these stocks may be turning into genuine value opportunities—but the old playbook may no longer apply, and investors need to underwrite what the business looks like 2–5 years from now, not what it used to be. Tickers mentioned: CSU, CRM, ADBE, NOW, ADSK, INTU, TEAM, WDAY, TWLO, DOCU, ADP Check out our portfolio by going to Jointci.com Our Website Our New Youtube Channel! Canadian Investor Podcast Network Twitter: @cdn_investing Simon’s twitter: @Fiat_Iceberg Braden’s twitter: @BradoCapital Dan’s Twitter: @stocktrades_ca Want to learn more about Real Estate Investing? Check out the Canadian Real Estate Investor Podcast! Apple Podcast - The Canadian Real Estate Investor Spotify - The Canadian Real Estate Investor Web player - The Canadian Real Estate Investor Asset Allocation ETFs | BMO Global Asset Management Sign up for Fiscal.ai for free to get easy access to global stock coverage and powerful AI investing tools. Register for EQ Bank, the seamless digital banking experience with better rates and no nonsense.See omnystudio.com/listener for privacy information.

Guest: Vishwas Manral, CEO at Precize.ai Topic: Why is agent security so different from "just" LLM security? Why now? Agents are coming, sure, but they are - to put it mildly - not in wide use. Why create a top 10 list now and not wait for people to make the mistakes? It sounds like "agents + IAM" is a disaster waiting to happen. What should be our approach for solving this? Do we have one? Which one agentic AI risk keeps you up at night?  Is there an interesting AI shared responsibility angle here? Agent developer, operator, downstream system operator? We are having a lot of experimentation, but sometimes little value from Agents. What are the biggest challenges of secure agentic AI and AI agents adoption in enterprises? Resources: Top 10 threats and mitigation for AI Agents Past podcast AI episodes Cloud CISO Perspectives: How Google secures AI Agents (and paper) Top AI Risks from SAIF CoSAI From turnkey to custom: Tailor your AI risk governance to help build confidence  

Once upon a time we thought we had privacy. Then came credit cards, which captured the card owner's location and activity with each transaction. Then came the Internet, which made connecting all the dots easy and cheap, and the erosion of privacy accelerated. Large language models, LLMs, like the Generative AI system ChatGPT and its ilk have the potential to make the cost of connecting dots vanishingly small, thus eliminating even the illusion of privacy, especially because large databases are irresistible to LLM developers as training data for their models. In this episode we are fortunate to have as our guest Jane Horvath. Jane is comparatively unique in having earned academic degrees and practiced in both Computer Science and in Law. Before law school, she wrote software that may still be running on the International Space Station. Jane is further distinguished by having served as Apple's Chief Privacy Officer, Google's Global Privacy Counsel, and the DoJ's first Privacy Counsel and Civil Liberties Officer, among other roles.

Segment 1: Interview with Thyaga Vasudevan Hybrid by Design: Zero Trust, AI, and the Future of Data Control AI is reshaping how work gets done, accelerating decision-making and introducing new ways for data to be created, accessed, and shared. As a result, organizations must evolve Zero Trust beyond an access-only model into an inline data governance approach that continuously protects sensitive information wherever it moves. Securing access alone is no longer enough in an AI-driven world. In this episode, we'll unpack why real-time visibility and control over data usage are now essential for safe AI adoption, accurate outcomes, and regulatory compliance. From preventing data leakage to governing how data is used by AI systems, security teams need controls that operate in the moment - across cloud, browser, SaaS, and on-prem environments - without slowing the business. We'll also explore how growing data sovereignty and regulatory pressures are driving renewed interest in hybrid architectures. By combining cloud agility with local control, organizations can keep sensitive data protected, governed, and compliant, regardless of where it resides or how AI is applied. This segment is sponsored by Skyhigh Security. Visit https://securityweekly.com/skyhighsecurity to learn more about them! Segment 2: Why detection fails Caleb Sima put together a nice roundup of the issues around detection engineering struggles that I thought worth discussing. Amélie Koran also shared some interesting thoughts and experiences. Segment 3: Weekly Enterprise News Finally, in the enterprise security news, Fundings and acquisitions are going strong can cyber insurance be profitable? some new free tools shared by the community RSAC gets a new CEO Large-scale enterprise AI initiatives aren't going well LLM impacts on exploit development AI vulnerabilities global risk reports floppies are still used daily, but not for long? All that and more, on this episode of Enterprise Security Weekly. Visit https://www.securityweekly.com/esw for all the latest episodes! Show Notes: https://securityweekly.com/esw-443

Segment 1: Interview with Thyaga Vasudevan Hybrid by Design: Zero Trust, AI, and the Future of Data Control AI is reshaping how work gets done, accelerating decision-making and introducing new ways for data to be created, accessed, and shared. As a result, organizations must evolve Zero Trust beyond an access-only model into an inline data governance approach that continuously protects sensitive information wherever it moves. Securing access alone is no longer enough in an AI-driven world. In this episode, we'll unpack why real-time visibility and control over data usage are now essential for safe AI adoption, accurate outcomes, and regulatory compliance. From preventing data leakage to governing how data is used by AI systems, security teams need controls that operate in the moment - across cloud, browser, SaaS, and on-prem environments - without slowing the business. We'll also explore how growing data sovereignty and regulatory pressures are driving renewed interest in hybrid architectures. By combining cloud agility with local control, organizations can keep sensitive data protected, governed, and compliant, regardless of where it resides or how AI is applied. This segment is sponsored by Skyhigh Security. Visit https://securityweekly.com/skyhighsecurity to learn more about them! Segment 2: Why detection fails Caleb Sima put together a nice roundup of the issues around detection engineering struggles that I thought worth discussing. Amélie Koran also shared some interesting thoughts and experiences. Segment 3: Weekly Enterprise News Finally, in the enterprise security news, Fundings and acquisitions are going strong can cyber insurance be profitable? some new free tools shared by the community RSAC gets a new CEO Large-scale enterprise AI initiatives aren't going well LLM impacts on exploit development AI vulnerabilities global risk reports floppies are still used daily, but not for long? All that and more, on this episode of Enterprise Security Weekly. Show Notes: https://securityweekly.com/esw-443

The questions piled up over the holidays and now it's time to answer them in this, the first Q&A of 2026. This month we touch on topics like the splendor Gateway 2000's cow boxes, the mystery of the ENIAC, whether a shed qualifies as off-site backup, what the heck volt-amps are (and how calculus is involved), the glory days of multi-user computing, what tech today's kids will be nostalgic for in 20 years, using LLMs for troubleshooting and command line assistance, and more. Support the Pod! Contribute to the Tech Pod Patreon and get access to our booming Discord, a monthly bonus episode, your name in the credits, and other great benefits! You can support the show at: https://patreon.com/techpod

Send us a textThe ground is shifting under our feet as AI moves from answering questions to taking action. We dig into what that transformation really means for leaders: how operating models evolve, where risk compounds, and what it takes to capture speed without inviting chaos. With Dr. Jamila Amimer, CEO of MindSenses Global and a recognized AI strategist, we unpack practical steps to go from pilots to production and build systems that are fast, reliable, and governed.We start by separating AI families—predictive, generative, and agentic—and why each demands a different approach to design, safety, and measurement. Dr. Amimer explains why spatial AI and the convergence with robotics will redefine context and capability, and how to prepare now without tossing out today's LLM investments. From domain expertise and humans in the loop to controlled knowledge bases and action approvals, we lay out the essential guardrails to minimize hallucinations, manage model drift, and avoid compounding errors at scale.Then we turn to the human layer. HR data becomes a strategic asset, revealing task flows and handoffs that inform agent orchestration. We talk through preserving meaning and motivation as agents absorb routine work, and how equitable upskilling—analytical thinking, data literacy, exception handling—keeps teams engaged and effective. Accountability and auditability aren't abstract; they're the difference between a clever demo and a trustworthy system your board will support.If you're ready to move beyond hype and design AI that plans, decides, and acts with confidence, this conversation gives you the operating principles to start today and scale tomorrow. If this resonated, follow the show, share it with a colleague who cares about AI governance, and leave a review so we can reach more leaders building responsibly.Thanks for tuning in to this episode of Follow The Brand! We hope you enjoyed learning about the latest trends and strategies in Personal Branding, Business and Career Development, Financial Empowerment, Technology Innovation, and Executive Presence. To keep up with the latest insights and updates, visit 5starbdm.com. And don't miss Grant McGaugh's new book, First Light — a powerful guide to igniting your purpose and building a BRAVE brand that stands out in a changing world. - https://5starbdm.com/brave-masterclass/ See you next time on Follow The Brand!

In this episode, Robin Merttens is joined by Tobi Schneider, Sector Engagement Lead for Financial Services & FinTech at the Edinburgh Futures Institute, to unpack one of the most ambitious research initiatives currently shaping the future of AI risk in insurance. Backed by UKRI and developed in collaboration with AXA Group and three leading universities, the project aims to build a foundational blueprint for how insurers can understand, audit and underwrite emerging AI risks.  Tobi shares why the shift from traditional to generative and agentic AI has outpaced current risk frameworks, leaving insurers exposed to risks that are poorly defined, difficult to monitor and impossible to price using historic loss data. He explains how his team is exploring dynamic underwriting models, parametric solutions and novel assurance techniques like LLM-based judges and automated red teaming, all with the goal of enabling safer, more accountable AI adoption.  Ahead of the Agentic AI Half Day event, hosted in collaboration with AI Risk, Tobi Schneider and Lukasz Szpruch wrote an article The New Frontier: Managing and insuring generative and agentic AI risks, further exploring this topic.   In this conversation, Tobi shares:  Why AI systems that function “correctly” can still produce harmful or costly outcomes  How traditional insurance models fail in the face of opacity, model drift and dynamic learning  What makes AI risk so difficult to price and how parametric triggers can help bridge the gap  Why better assurance leads to better insurance, and how incentives can drive safer AI deployment  How continuous monitoring tools are being developed to audit AI models in real time  What today's early AI insurance offerings (from the likes of Munich Re and Relm) are actually covering  The role of non-profit research in supporting commercial innovation without commercial bias  What insurers can do now to prepare for an AI-driven future even without historical data  If you like what you're hearing, please leave us a review on whichever platform you use or contact Robin Merttens on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

Join Scott as he wraps up #CircuitPython2026, discusses Yoto hacking and tries to answer any questions folks have. 0:00 Getting setup 3:27 hello everyone - welcome to deep dive 4:05 yoto mini player has esp32 - running circuitpython from adafruit.com 6:00 Circuitpython 2026 6:40 CP 2026 on adafruit blog - ideas for CP development this year 7:50 Low Power solutions 8:49 local LLM ( RAG ) and MIDI 11:20 CP OTA ( over the air update ), thread, circuitmatter (over zigbee ), zepher has ethernet support( but not supporting esp32-P4 ) 14:52 web based build system, github runner, LLM code generation 17:12 async support for networking, preemptive RTOS, updating the getting started documentation, testing 24:00 WebDAV / web workflow 26:45 octo probe tentacles 29:00 VS Code may not have a future :-) 30:42 excited bout zephyr and audio support 32:02 Yoto ( yotoplay.com ) 33:20 getting the Yoto Mini "screen" to work - reverse engineering - dc9306 display - embeded json pinout 35:40 yoto booting Circuit python 37:50 speaker and album art on yoto 39:15 CP Web API screen 39:59 explore the on-device MMC card - browse over wifi 41:17 getting board definition for Yoto Player 43:22 mp3 files from bandcamp just play, also amazon has some 45:00 json to board definition - helped get firmware on yoto hardware 50:23 explore es8388 audio data sheet 52:30 claude code / prompt in sublime merge 54:43 updating the file 1:03:30 circuitpython resources 1:05:35 wrap up Visit the Adafruit shop online - http://www.adafruit.com ----------------------------------------- LIVE CHAT IS HERE! http://adafru.it/discord Subscribe to Adafruit on YouTube: http://adafru.it/subscribe New tutorials on the Adafruit Learning System: http://learn.adafruit.com/ -----------------------------------------

In this episode of the Crazy Wisdom podcast, host Stewart Alsop welcomes Roni Burd, a data and AI executive with extensive experience at Amazon and Microsoft, for a deep dive into the evolving landscape of data management and artificial intelligence in enterprise environments. Their conversation explores the longstanding challenges organizations face with knowledge management and data architecture, from the traditional bronze-silver-gold data processing pipeline to how AI agents are revolutionizing how people interact with organizational data without needing SQL or Python expertise. Burd shares insights on the economics of AI implementation at scale, the debate between one-size-fits-all models versus specialized fine-tuned solutions, and the technical constraints that prevent companies like Apple from upgrading services like Siri to modern LLM capabilities, while discussing the future of inference optimization and the hundreds-of-millions-of-dollars cost barrier that makes architectural experimentation in AI uniquely expensive compared to other industries.Timestamps00:00 Introduction to Data and AI Challenges03:08 The Evolution of Data Management05:54 Understanding Data Quality and Metadata08:57 The Role of AI in Data Cleaning11:50 Knowledge Management in Large Organizations14:55 The Future of AI and LLMs17:59 Economics of AI Implementation29:14 The Importance of LLMs for Major Tech Companies32:00 Open Source: Opportunities and Challenges35:19 The Future of AI Inference and Hardware43:24 Optimizing Inference: The Next Frontier49:23 The Commercial Viability of AI ModelsKey Insights1. Data Architecture Evolution: The industry has evolved through bronze-silver-gold data layers, where bronze is raw data, silver is cleaned/processed data, and gold is business-ready datasets. However, this creates bottlenecks as stakeholders lose access to original data during the cleaning process, making metadata and data cataloging increasingly critical for organizations.2. AI Democratizing Data Access: LLMs are breaking down technical barriers by allowing business users to query data in plain English without needing SQL, Python, or dashboarding skills. This represents a fundamental shift from requiring intermediaries to direct stakeholder access, though the full implications remain speculative.3. Economics Drive AI Architecture Decisions: Token costs and latency requirements are major factors determining AI implementation. Companies like Meta likely need their own models because paying per-token for billions of social media interactions would be economically unfeasible, driving the need for self-hosted solutions.4. One Model Won't Rule Them All: Despite initial hopes for universal models, the reality points toward specialized models for different use cases. This is driven by economics (smaller models for simple tasks), performance requirements (millisecond response times), and industry-specific needs (medical, military terminology).5. Inference is the Commercial Battleground: The majority of commercial AI value lies in inference rather than training. Current GPUs, while specialized for graphics and matrix operations, may still be too general for optimal inference performance, creating opportunities for even more specialized hardware.6. Open Source vs Open Weights Distinction: True open source in AI means access to architecture for debugging and modification, while "open weights" enables fine-tuning and customization. This distinction is crucial for enterprise adoption, as open weights provide the flexibility companies need without starting from scratch.7. Architecture Innovation Faces Expensive Testing Loops: Unlike database optimization where query plans can be easily modified, testing new AI architectures requires expensive retraining cycles costing hundreds of millions of dollars. This creates a potential innovation bottleneck, similar to aerospace industries where testing new designs is prohibitively expensive.

Focus sur Cerebras, les puces aussi grosses qu’un wafer, Windows 11 est définitivement un veau, les LLMs connaissent toujours presque tous leurs classiques en intégralité et les modèles IA de la semaine.  Me soutenir sur Patreon Me retrouver sur YouTube On discute ensemble sur Discord Modèles de la semaine Mocha, la revanche de V-JEPA. Social Reasoner et  OpenVoxel. Ministral 3 et la sécurité des IA. Un Erdős tres, un pasito pa'lante matemáticas ! Stupefix ! Les LLM connaissent toujours leur classiques… Un récapitulatif sur ces LLM qu'on aime. Et là, c'est le DRAM Panier percé : Sam investit dans Altman, OpenAI dans dans Cerebras. Marie Kondo pour les puces de RAM. Encore des centrales en orbites… qui bougent. C'est confirmé scientifiquement : Windows 11 est un veau. Dilbert est orphelin. Participants Une émission préparée par Guillaume Poggiaspalla Présenté par Guillaume Vendé

Learn more about TrainerRoad AI: https://www.trainerroad.com/blog/introducing-trainerroad-ai/Learn more about the updated AI FTP Detection: https://www.trainerroad.com/blog/why-is-ai-ftp-detecting-an-ftp-change/// SHARE AND RATE THE PODCAST!iTunes: ⁠https://trainerroad.cc/apple2⁠ Spotify: ⁠https://trainerroad.cc/spotify2⁠Google Podcasts: ⁠https://trainerroad.cc/google⁠// TOPICS COVERED(00:00:00) Welcome & Why TrainerRoad AI Is a Major Update(00:02:00) How TrainerRoad AI Has Evolved Over Time(00:04:00) Why TrainerRoad AI Isn't Just a Chatbot or LLM(00:06:30) How TrainerRoad AI Simulates and Selects Workouts(00:10:30) How TrainerRoad AI Replaces Static Training Plans(00:15:00) How TrainerRoad AI Reduces Failed Workouts and Burnout(00:20:40) How TrainerRoad AI Adjusts for Fatigue and Big Rides(00:32:00) Why Most AI Training Tools Don't Validate Workouts(00:36:10) TrainerRoad AI Training Forecasts and Simulations(00:49:40) TrainerRoad AI Workout Alternatives Explained(01:03:20) Why Long Rides Can Undermine Progress(01:17:20) Conservative vs Aggressive Training in TrainerRoad AI(01:37:30) How TrainerRoad AI Changes How Athletes Get FasterIn this episode, Nate and Coach Jonathan explain all the details behind TrainerRoad AI, the biggest evolution yet in TrainerRoad's training system, walking through how the new AI-driven approach goes far beyond static plans to dynamically simulate, predict, and personalize every workout on your calendar. They explain how years of performance data, workout feedback, power and heart rate, and progression history now power a system that actively chooses the right workout for the day, reduces burnout, cuts down workouts that are too hard or too easy, and helps athletes recover faster from missed sessions or failures. The conversation dives into how simulations work behind the scenes, why long rides and “hidden fatigue” can quietly sabotage progress, and how features like AI Predicted Difficulty, AI Training Simulation, Dynamic Duration, and Training Approach sliders give athletes confidence that every session is worth their time. The result is training that feels consistently “just right,” adapts to real life, and helps athletes get faster with less wasted effort and fewer mistakes along the way.// RESOURCES MENTIONED- Sign up for TrainerRoad! ⁠https://trainerroad.cc/GetFaster⁠- Follow TrainerRoad on Instagram

Jake and Michael return for 2026 and talk about their evolving experiences with AI; what it's good at, what it's not, and how it's changing the way they work.Show linksOpenAI / ChatGPTAnthropic / Claude (Sonnet & Opus)OpenCode (multi-provider AI coding interface)Home AssistantZigbee temperature sensorsGitHub CopilotOllama (local LLM runner)NVIDIA DGX SparkAmp CodeMiniMax M2.1 modelSoftware for an audience of oneArborOpenCode Desktop has workspaces supportOpus 4.5 is going to change everything

In this episode of 'One in Ten,' host Teresa Huizar speaks with Liisa Järvilehto, a psychologist and Ph.D. candidate at the University of Helsinki, about the positive uses of AI in child abuse investigations and forensic interviews. The conversation addresses the common misuse of AI and explores its potential in assisting professionals by proposing hypotheses, generating question sets, and more. The discussion delves into the application of large language models (LLMs) in generating alternative hypotheses and the nuances of using these tools to avoid confirmation bias in interviews. Huizar and Järvilehto also touch on the practical implications for current practitioners and future research directions.  Time Stamps:  00:00 Introduction to the Episode 00:00 Introduction to the Episode 00:22 Exploring AI in Child Abuse Investigations 01:06 Introducing Liisa Järvilehto and Her Research 01:48 Challenges in Child Abuse Investigations 04:24 The Role of Large Language Models 06:28 Addressing Bias in Investigations 09:13 Hypothesis Testing in Forensic Interviews 12:18 Study Design and Findings 25:54 Implications for Practitioners 33:41 Future Research Directions 36:49 Conclusion and Final Thoughts Resources:Pre-interview hypothesis generation: large language models (LLMs) show promise for child abuse investigationsSupport the showDid you like this episode? Please leave us a review on Apple Podcasts.

Can't be bothered with email or speak pipe? Text us!Hey! Jason will be in the UK in Late April. If you'd like to chat to him about the trip and possibly having him visit you, email us on enquiries@ontheregteam.comWatch this episode on YouTubeThe banter section of this episode is lost to history because Jason forgot to hit record! After a short intro by Inger, the team go straight into the mail bag. Let's face it, this is the good stuff anyway - who needs Tinny and puppy news?In our work problems segment, we discuss the appearance of ChatGPT as a referrer to the Thesis Whisperer blog and what it might mean for researcher visibility. How does an LLM decide on what is an 'authoritative source' on the internet? Is this a new form of 'research impact' and what should researchers do about it, if anything?This episode also ends abruptly when Inger gets a phone call - the next episode will be much more polished, we promise!Things we mentioned:Tiago Forte's PARA bookBlooms TaxonomyAmazing Marvin appClick up appBe visible or vanish bookThe Enshittification of Academic Social MediaGot thoughts and feel pinions? Want to ask a question? You can email us on - Leave us a message on www.speakpipe.com/thesiswhisperer. - See our workshop catalogue on www.ontheregteam.com. You can book us via emailing Jason at enquiries@ontheregteam.com- Subscribe to the free, monthly Two Minute Tips newsletter here (scroll down to enter your email address) - We're on BlueSky as @drjd and @thesiswhisperer (but don't expect to hear back from Jason, he's still mostly on a Socials break).- Read Inger's stuff on www.thesiswhisperer.com. - If you want to support our work, you can sign up to be a 'Riding the Bus' member for just $2 a month, via our On The Reg Ko-Fi site

Therapy and companionship has become the #1 use case for AI, with millions worldwide sharing their innermost thoughts with AI systems — often things they wouldn't tell loved ones or human therapists. This mass experiment in human-computer interaction is already showing extremely concerning results: people are losing their grip on reality, leading to lost jobs, divorce, involuntary commitment to psychiatric wards, and in extreme cases, death by suicide.The highest profile examples of this phenomenon — what's being called "AI psychosis”— have made headlines across the media for months. But this isn't just about isolated edge cases. It's the emergence of an entirely new "attachment economy" designed to exploit our deepest psychological vulnerabilities on an unprecedented scale. Dr. Zak Stein has analyzed dozens of these cases, examining actual conversation transcripts and interviewing those affected. What he's uncovered reveals fundamental flaws in how AI systems interact with our attachment systems and capacity for human bonding, vulnerabilities we've never had to name before because technology has never been able to exploit them like this.In this episode, Zak helps us understand the psychological mechanisms behind AI psychosis, how conversations with chatbots transform into reality-warping experiences, and what this tells us about the profound risks of building technology that targets our most intimate psychological needs. If we're going to do something about this growing problem of AI related psychological harms, we're gonna need to understand the problem even more deeply. And in order to do that, we need more data. That's why Zak is working with researchers at the University of North Carolina to gather data on this growing mental health crisis. If you or a loved one have a story of AI-induced psychological harm to share, you can go to: AIHPRA.org. This site is not a support line. If you or someone you know is in distress, you can always call or text the national helpline in the US at 988 or your local emergency services RECOMMENDED MEDIA The website for the AI Psychological Harms Research CoalitionFurther reading on AI PscyhosisThe Atlantic article on LLM-ings outsourcing their thinking to AIFurther reading on David Sacks' comparison of AI psychosis to a “moral panic” RECOMMENDED YUA EPISODESHow OpenAI's ChatGPT Guided a Teen to His DeathPeople are Lonelier than Ever. Enter AI.Echo Chambers of One: Companion AI and the Future of Human ConnectionRethinking School in the Age of AI CORRECTIONSAfter this episode was recorded, the name of Zak's organization changed to the AI Psychological Harms Research Consortium Zak referenced the University of California system making a deal with OpenAI. It was actually the Cal State System.   Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this feed drop from The Six Five Pod, a16z General Partner Martin Casado discusses how AI is changing infrastructure, software, and enterprise purchasing. He explains why current constraints are driven less by technical limits and more by regulation, particularly around power, data centers, and compute expansion.The episode also covers how AI is affecting software development, lowering the barrier to coding without eliminating the need for experienced engineers, and how agent-driven tools may shift infrastructure decision-making away from humans.Watch more from Six Five Media: https://www.youtube.com/@SixFiveMedia Resources:Follow Martin Casado on X: https://twitter.com/martin_casado  Follow Patrick Moorhead on X:  https://twitter.com/PatrickMoorheadFollow Daniel Newman on X: https://twitter.com/danielnewmanUV Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The marketing teams winning with AI today are not the ones chasing every new model release. They are the ones who found the boring, repetitive tasks their teams hate and automated those first.Nir Pochter, Co-Founder and CMO at Lightricks, joins Stephanie Postles on Marketing Trends to break down what AI actually means for creative workflows and why most teams are still using it wrong.You'll learn:- The "algebra problem" of AI adoption- How to save your design team 80% of their time- Why the gap between marketers who use AI well and those who don't is widening fast.- How to use an LLM scoring system to pre-review documents for you- The dangerous trend of "AI Marketer" job titles- What's really in store for the future of video+AI Key Moments:00:00 — Why AI Hasn't Improved Creative Output Yet02:06 — The Algebra Problem: Tools vs. Knowing How to Use Them07:27 — Nir's Background: AI PhD to Lightricks and FaceTune09:46 — What Used to Take Weeks Now Takes Minutes13:35 — Why Automating Everything Failed Miserably16:38 — Start with What People Hate Doing20:08 — The LLM Scoring System: Nothing Gets Reviewed Without an 8521:43 — Train Your LLM to Be Mean, Not Nice23:32 — Building Custom GPTs with Company Guidelines26:30 — The Pitfall: Using AI to Please Leadership28:47 — From Toys to Tools: Why Text-to-Video Isn't Enough31:05 — Coca-Cola's 70,000 Prompts (Was It Worth It?)34:41 — AI Won't Replace Creatives, But This Will37:04 — The Two Critical Skills: Prompting and Curation37:55 — How AI Multiplies the Skills Gap (7 vs 10 Example)42:47 — What CMOs Should Be Asking Their Teams46:20 — Why "AI Marketer" Is LinkedIn Fluff This episode is brought to you by Lightricks. LTX is the all-in-one creative suite for AI-driven video production; built by Lightricks to take you from idea to final 4K render in one streamlined workspace.Powered by LTX-2, our next-generation creative engine, LTX lets you move faster, collaborate seamlessly, and deliver studio-quality results without compromise. Try it today at ltx.studio Mission.org is a media studio producing content alongside world-class clients. Learn more at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Most AI pilots fail—at least, that's the headline. But today's guest is proving that doesn't have to be true.In this Watson Weekly interview, Rick Watson goes behind the scenes with Chris Kellner, CEO of DigitalGenius, to discuss how a decade-old AI pioneer is navigating the modern LLM explosion. We move past the hype to explore how AI is actually rewriting the playbooks for sales, marketing, and customer support.In this episode, you'll learn:* The "Locomotive" Metaphor: Why DigitalGenius didn't have to reinvent itself, but rather accelerated on existing tracks.* Sales & Marketing Rewired: How Chris's team uses AI for call coaching, MEDPIC scorecards, and CRM automation to let humans focus on high-value closing.* UK vs. US Market Mismatch: Why traditional outbound playbooks failed when crossing the Atlantic and what they did to fix it.*The Competition for Culture: How an internal "Agent-Building" competition spurred unexpected creativity across the company.3 Hard Lessons in AI Support: The essential checklist for any leader deploying AI in customer service today.Chapters00:00 – Intro: Turning AI buzz into customer wins 03:15 – Chris Kellner's journey from Banking to SaaS CEO 07:40 – Acceleration vs. Reinvention: Building the AI train line 14:20 – Rewiring GTM: AI call coaching and MEDPIC scorecards 22:10 – Market Mismatches: Lessons from scaling from the UK to the US 30:45 – Culture & Internal Adoption: The AI Agent competition 38:30 – Why most AI pilots fail (and how to make yours succeed) 45:15 – Build vs. Buy: When to go in-house and when to use a vendor 52:00 – Closing thoughts and key takeaways#watsonweekly #ai #customersupportThis podcast uses the following third-party services for analysis: Podtrac - https://analytics.podtrac.com/privacy-policy-gdrp

Are you ready to take your podcast from a passion project to a monetization-based international business advertising/marketing tool? In this comprehensive episode, host Favour Obasi-ike, MBA, MS delivers an in-depth masterclass on leveraging podcast SEO and monetization strategies for international business growth. This session is the final installment in a series focused on helping podcasters and business owners build sustainable, globally-reaching content strategies.Favour explores the critical intersection of podcasting, search engine optimization, and international business development. The episode covers essential topics including multilingual content localization, performance benchmarks, download metrics, and how to position podcasts for passive monetization through advertising networks.Key highlights include real-world success stories from clients who have transformed their podcasts into powerful SEO assets, including a case study of turning 50 podcast episodes into 50 optimized blog posts that now rank on Google's AI-powered search results. Favour also demonstrates how his own podcast appears in Google's featured snippets and AI mode results, providing concrete proof of the strategies discussed.The episode features interactive discussions with community members Juliana, Celeste, and others who share their own experiences with SEO implementation, AI optimization (AIO), and the tangible business results they've achieved. Juliana shares an exciting success story about landing a major client through Google Gemini recommendations, directly attributable to SEO work completed three years prior with FavourThis episode is essential listening for podcasters, content creators, coaches, consultants, and international business owners who want to understand how to build long-term digital assets, increase discoverability across global markets, and create multiple revenue streams through strategic content optimization.Need to Book An SEO Discovery Call for Advertising or Marketing Services?>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Book a Complimentary SEO Discovery Call with Favour Obasi-Ike⁠>> Visit Work and PLAY Entertainment website to learn about our digital marketing services>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Join our exclusive SEO Marketing community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Read SEO Articles>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to the We Don't PLAY Podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Purchase Flaev Beatz Beats OnlineWhat You'll Learn:International SEO Fundamentals: How to optimize your podcast content for multiple languages, regions, and search engines (Google.com, Google.co.uk, and beyond).Monetization Metrics That Matter: Understanding downloads vs. unique listeners, 7-day and 30-day performance benchmarks, and what advertising networks look for.Multilingual Content Strategy: Leveraging localization and translation features to expand your audience across different cultures and languages.Podcast-to-Blog Conversion: The proven method of turning podcast episodes into SEO-optimized blog posts that rank on Google and drive traffic back to your audio content.AI Optimization (AIO): How to position your content to appear in Google's AI mode, featured snippets, and AI-powered recommendation engines like Google Gemini.Real Results: Case studies including a client whose emotional coaching podcast now ranks on Google, and a CPA who landed a major client through Gemini AI recommendations.Long-Term Asset Building: Why SEO is a marathon, not a sprint, and how work done today pays dividends for years to come.Detailed Episode TimestampsIntroduction & Overview (00:00 - 05:55) 00:00 - 00:13: Episode title: "Podcast SEO Monetization for International Businesses". 00:13 - 00:45: Welcome and call to subscribe to We Don't Play Podcast. 00:45 - 01:27: Overview: International business connections through podcasting. 01:27 - 02:31: Performance benchmarks: Downloads vs. unique listeners, measuring success. 02:31 - 03:33: Building sustainable growth and niche dominance. 03:33 - 04:48: Multilingual content and localization strategies. 04:48 - 05:55: International perspective: Moving beyond regional thinking.International SEO Strategy (05:55 - 10:03) 05:55 - 06:58: Analytics insights: Tracking international audience growth. 06:58 - 08:04: Case study introduction: Client success with emotional coaching podcast. 08:04 - 09:09: Turning 50 podcast episodes into 50 SEO-optimized blogs. 09:09 - 10:03: Podcast-to-blog strategy and long-term asset building.Content Conversion & Client Success Stories (10:03 - 15:00) 10:03 - 11:00: Amazon book-to-podcast conversion strategy. 11:00 - 12:00: Passive vs. active content consumption patterns. 12:00 - 13:00: Multi-platform distribution: Spotify, Apple Podcasts, YouTube. 13:00 - 14:00: Clubhouse as a content creation and community building platform. 14:00 - 15:00: Real-time engagement and relationship building.Technical SEO Implementation (15:00 - 20:00) 15:00 - 16:00: Search engine algorithms and content discoverability. 16:00 - 17:00: Metadata optimization for podcasts. 17:00 - 18:00: Location-specific SEO strategies. 18:00 - 19:00: Building booking systems and conversion pathways. 19:00 - 20:00: Creating "red carpet" experiences for potential clients.Monetization Strategies (20:00 - 25:00) 20:00 - 21:00: Advertising network requirements and download thresholds. 21:00 - 22:00: Passive income through podcast monetization. 22:00 - 23:00: Building credibility through consistent content. 23:00 - 24:00: Long-term revenue stream development. 24:00 - 25:00: International market opportunities.Community Engagement & Live Discussion (25:00 - 30:00) 25:00 - 26:22: Community building on Clubhouse since 2020. 26:22 - 27:40: Prayer and intentionality in content creation. 27:40 - 28:40: Daily room commitment and audience engagement. 28:40 - 29:19: Juliana's Success Story: Landing a major CPA client through Google Gemini. 29:19 - 30:00: AI Optimization (AIO) and its importance.AI-Powered Search Results (30:00 - 35:00) 30:00 - 31:11: SEO as a long-term investment: Results from work done 3 years ago. 31:11 - 32:30: Live Demonstration: Host's podcast appearing in Google AI mode with timestamp references. 32:30 - 33:50: Dual focus: Local search dominance + global revenue streams. 33:50 - 34:30: International markets and currency considerations (Shopify example). 34:30 - 35:00: Technical factors: IP address, API, LLM, search history.Actionable Strategies & Takeaways (35:00 - 39:07) 35:00 - 35:50: Being intentional about topics of interest. 35:50 - 36:20: Importance of independent research and validation. 36:20 - 37:18: Celeste's Reflection: Community value and 2026 goals. 37:18 - 38:00: Top 3 priorities: Booking system, financial management, business structure. 38:00 - 38:46: Encouragement and resources for implementation. 38:46 - 39:07: Closing remarks and invitation to daily rooms.This episode is perfect for:Podcasters looking to monetize their content.International business owners seeking global visibility.Coaches and consultants building authority online.Content creators wanting to maximize their reach.Marketers interested in AI optimization strategies.Episode Tags/KeywordsPodcast SEO, International Business, Podcast Monetization, Multilingual Content, Content Localization, AI Optimization, AIO, Google Gemini, Featured Snippets, Download Metrics, Passive Income, Content Repurposing, Blog Strategy, Digital Marketing, Search Engine Optimization, Global Revenue Streams, Podcast Analytics, Advertising Networks, Authority Building, Long-term Strategy, Clubhouse Marketing, Community Building, Business Growth, Online Visibility, International Markets.Target AudiencePodcasters seeking monetization strategies.International business owners.Digital marketers and SEO professionals.Coaches and consultants.Content creators and influencers.Entrepreneurs building online presence.Small business owners expanding globally.Marketing professionals learning AI optimization.Anyone interested in passive income through content.This episode is part of the We Don't PLAY!™️ Podcast series, hosted by Favour Obasi-Ike, focusing on practical digital marketing strategies for business growth.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Enterprise SEO teams struggle to prove ROI while chasing AI visibility metrics. Eli Schwartz, growth advisor who has driven millions in organic revenue for Tinder, Coinbase, and LinkedIn, challenges the industry's obsession with LLM mention tracking and prompt visibility tools. He reveals why first-click attribution models show SEO driving 67% of conversions at major brands, demonstrates how to position SEO as a revenue driver rather than traffic generator, and explains why sustainable organic growth requires focusing on user intent over algorithmic manipulation.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of the Level Up Claims Podcast, host Galen Hair sits down with Austin Holmes, CEO of Signal Raptor and President of Publicity for Good, to break down how storytelling, earned media, and authentic communication help businesses stand out in an increasingly noisy, AI-driven world. Austin shares how his background in the military shaped his leadership and communication style, why most business owners struggle to build trust at scale, and how PR can be transformed from a vague expense into a predictable growth tool. From scaling a seven-figure PR agency while raising a family on the road to building systems that replace "hope-based PR," this conversation delivers a practical, no-fluff framework business owners can apply every day. Highlights ·       Austin Holmes' journey from military leadership to scaling PR companies ·       Why authenticity and storytelling are essential in modern marketing ·       How AI has increased noise—and why story cuts through it ·       Turning your customer's story into a trust-building asset ·       Why "hope-based PR" doesn't work for growing businesses ·       Earned media vs influencers vs advertising: what actually matters ·       How Austin grew his company more than 50x with mentorship and systems ·       Building a business while traveling full-time with a growing family ·       Why systems—not hustle—create sustainable growth ·       Breaking down the COMPARE framework for business communication ·       The importance of omnipresence across platforms ·       Using earned media as third-party validation ·       How relationships and engagement drive long-term visibility ·       Preparing your brand for AI and LLM-based search ·       Austin's definition of leveling up: never settling and always growing Episode Resources ·       Connect with Austin Holmes ·       https://signalraptor.com ·       https://publicityforgood.com ·       Connect with Galen M. Hair ·       https://insuranceclaimhq.com ·       hair@hairshunnarah.com  ·       https://levelupclaim.com/  

"How many states are there in the United States?" Attackers are actively scanning for LLMs, fingerprinting them using the query How many states are there in the United States? . https://isc.sans.edu/diary/%22How%20many%20states%20are%20there%20in%20the%20United%20States%3F%22/32618 Closing the Door on Net-NTLMv1: Releasing Rainbow Tables to Accelerate Protocol Deprecation Mandiant is publicly releasing a comprehensive dataset of Net-NTLMv1 rainbow tables to underscore the urgency of migrating away from this outdated protocol. https://cloud.google.com/blog/topics/threat-intelligence/net-ntlmv1-deprecation-rainbow-tables Out-of-band update to address issues observed with the January 2026 Windows security update Microsoft has identified issues upon installing the January 2026 Windows security update. To address these issues, an out-of-band (OOB) update was released today, January 17, 2026 https://learn.microsoft.com/en-us/windows/release-health/windows-message-center

As religion bleeds followers, it's looking for a digital transfusion from the high-tech elite. We're dissecting the rise of techno-cults, the Vatican's desperate attempt to regulate AI with its Antiqua et Nova policy, and why tech bros like Peter Thiel are now becoming guest speakers at megachurch revivals. It turns out that when you can't get answers from a burning bush, a large language model that tells you exactly what you want to hear is the next best thing. Silicon Valley is building the new gods of a digital age where faith and profit finally merge.News Source:Tech revival after Peter Thiel's Antichrist talks: There's hope and warinessBy Religion News ServiceJanuary 2, 2026

MANSCAPED, the men's grooming brand that pioneered below-the-belt care, sold out its first product in two weeks and scaled to $300 million in just three years. Founder Paul Tran shares how rapid iteration, customer feedback, and a razor-sharp focus turned a taboo idea into a global brand.For more on MANSCAPED and show notes click here Subscribe and watch Shopify Masters on YouTube!Sign up for your FREE Shopify Trial here.