Podcasts about MSL

A recent ruling found a MSL presenting at a promotional meeting no breach but why? Was it a technicality or a new PMCPA position?

In this episode of the Epigenetics Podcast, we talked with Peter Becker from the  Biomedical Center Munich about his successful career in Epigenetics, where he discovered the chromatin remodeler ISWI and dosage compensation complex MOF. Dr. Becker shares thoughts about his postdoctoral work with Carl Wu, where he developed embryo extract systems for studying chromatin assembly and transcription. He explains how work on Drosophila extracts led to the purification of ATP-dependent remodeling factors, including ISWI-related complexes, and how these studies showed that such factors slide nucleosomes and help organize chromatin. We also cover his move to EMBL and later to Munich, where his lab expanded into dosage compensation in Drosophila. He describes work on the MSL complex targeting, MRE sequences, ROX RNA, DNA shape features, and how biochemical reconstitution was used to study how the complex recognizes the X chromosome. Finally, we discuss his later work on TIP-60 and histone acetylation, including acetylome studies, and his reflections on leadership roles at EMBL and on the use of the term epigenetics. He emphasizes that epigenetics should be understood as one layer among genetics, environment, and socialization, not as a replacement for genetics. References Tsukiyama, T., Becker, P. B., & Wu, C. (1994). ATP-dependent nucleosome disruption at a heat-shock promoter mediated by binding of GAGA transcription factor. Nature, 367(6463), 525–532. https://doi.org/10.1038/367525a0 Varga-Weisz, P. D., Wilm, M., Bonte, E., Dumas, K., Mann, M., & Becker, P. B. (1997). Chromatin-remodelling factor CHRAC contains the ATPases ISWI and topoisomerase II. Nature, 388(6642), 598–602. https://doi.org/10.1038/41587 Corona, D. F., Längst, G., Clapier, C. R., Bonte, E. J., Ferrari, S., Tamkun, J. W., & Becker, P. B. (1999). ISWI is an ATP-dependent nucleosome remodeling factor. Molecular cell, 3(2), 239–245. https://doi.org/10.1016/s1097-2765(00)80314-7 Akhtar, A., & Becker, P. B. (2000). Activation of transcription through histone H4 acetylation by MOF, an acetyltransferase essential for dosage compensation in Drosophila. Molecular cell, 5(2), 367–375. https://doi.org/10.1016/s1097-2765(00)80431-1 Akhtar, A., Zink, D., & Becker, P. B. (2000). Chromodomains are protein-RNA interaction modules. Nature, 407(6802), 405–409. https://doi.org/10.1038/35030169 Villa, R., Schauer, T., Smialowski, P., Straub, T., & Becker, P. B. (2016). PionX sites mark the X chromosome for dosage compensation. Nature, 537(7619), 244–248. https://doi.org/10.1038/nature19338 Related Episodes Dosage Compensation in Drosophila (Asifa Akhtar) DNase Hypersensitive Sites and Chromatin Remodeling Enzymes (Carl Wu) The Mechanism of ATP-dependent Remodelers and HP1 Gene Silencing (Geeta Narlikar) Regulation of Chromatin Organization by Histone Chaperones (Geneviève Almouzni) Contact Epigenetics Podcast on Mastodon Epigenetics Podcast on Bluesky Dr. Stefan Dillinger on LinkedIn Active Motif on LinkedIn Active Motif on Bluesky Email: podcast@activemotif.com

Arpon Basu with Conor and Shaun with a recap of Game 2 and if the view on the Habs is still glass half full? Does Arpon think MSL makes a change to his lineup tonight? And why are the Habs less dangerous on home ice in the playoffs?

What did you think of how the Habs performed in their series win over Buffalo Any surprise that Brendan Gallagher didn’t slot in last night, instead MSL goes with Oliver Kapanen? SGA wins back to back MVP's and the man who broke the story, Shams Charania, is facing backlash for it. Does that make any sense? What’s the best candy? Not candy bar. More like nerds or gummies or skittles.

In this episode of Medical Affairs Unscripted, Peg Crowley-Nowick speaks with Nick Sarlis, MD, PhD, FACP, Chief Medical Officer at Clara Biotech, about why successful biotech launches begin years before approval. Drawing on experience across six product launches and nine indications, Nick shares a practical CMO perspective on building medical affairs capabilities early, aligning scientific strategy across functions, and preparing organizations for launch success in today's biotech environment. Nick explains why "T-minus 30 months" is becoming the new standard for launch preparation and discusses the foundational role of medical affairs in shaping scientific narrative, publication strategy, KOL engagement, field medical deployment, and long-term evidence generation planning. The conversation also explores: • Early hiring strategy for medical affairs teams • Building experienced MSL and field medical capabilities • Aligning medical, commercial, and corporate communications • Publication planning and scientific congress engagement • Academic center and patient advocacy partnerships • Managing actionable MSL insights • Evidence generation planning beyond approval • Launch readiness in resource-constrained biotech organizations A practical, resource and strategy-focused discussion for biotech executives, CMOs, medical affairs leaders, MSLs, and clinical-stage companies considering commercialization.

Darren Dreger joined Conor and Shaun following the Habs win in Buffalo to grab a 3-2 series lead. Darren talks about the Lane Hutson factor, MSL having total faith in his staff and Jakub Dobes settling down after a rocky start to Game 5. Also, Darren weighs in on the Sabres top line and how they haven't been able to solve the Habs structure.

What were you thinking after Buffalo made it 3-2 in the 1st period? Big credit to MSL and his staff for keeping Dobes in the net? Which Habs player had the biggest impact in that win? Did the Habs expose major flaws on this Sabres team? Are you not kind of surprised a bit at the success MSL and the team have had? A win away from a conference final and MSL showing so much trust and patience in his team?

You expecting MSL to make a change to his top 6 tonight? Move Slaf? Insert Kapanen? Move Dach off his line? With what you’ve seen from Kirby Dach, has he played himself into a long term deal? If so, how long of a contract would you offer him? With all the hype around playoff time in both the NHL and NBA. Do find it’s lived up to the hype in either league so far? Two teams in the NHL have yet to lose a playoff game, we had one series that went 7 and the NBA seems to have more blowout wins than close games?

This episode's Community Champion Sponsor is Ossur. To learn more about their ‘Responsible for Tomorrow' Sustainability Campaign, and how you can get involved: CLICK HEREEpisode Overview: Pharmaceutical launches are among the most complex, high-stakes endeavors in all of healthcare, and the difference between winning and losing often comes down to whether the right intelligence reaches the right people at the right moment.Jason Smith, CTO of AI and Analytics at Within3, has spent his career solving exactly that problem.A three-time co-founder whose companies have raised over $100 million in venture capital, Jason built rMark Bio from scratch before its acquisition by Within3, where his AI platform now powers launch decisions for all of the top 20 pharmaceutical companies.Join us as Jason discusses how Within3's Launch Intelligence platform unifies field insights, social signals, EHR data, and stakeholder engagement into one integrated layer, empowering pharma teams to move with clarity and confidence. Let's go!Episode Highlights:Jason sold his house, packed his dog in a U-Haul, and drove from Seattle to Chicago to launch rMark Bio in 2015.Within3 analyzes over 10 billion data points, filtered into hyper-focused disease community landscapes for pharmaceutical decision-makers.Life sciences AI differs from general models because context matters: how an MSL communicates is entirely different from a general user's query.Social listening gives pharma companies real-time aggregate patient and HCP sentiment, replacing slow, one-to-one relationship-based feedback loops.Jason is an 18-year cancer survivor and American Cancer Society advisor, making him personally invested in faster, better therapeutics for patients.About our Guest:Jason Smith is CTO of AI & Analytics at Within3, where he leads the team behind the company's most advanced AI capabilities serving life sciences organizations. Jason is a three-time co-founder who built Cryptocybernetics, GrayArea, and rMark Bio from inception to successful exit. He was later brought in as CEO of xSides to lead its sale. Over his career, his companies have raised more than $100 million in venture and strategic capital. In addition to Within3, Jason is a Venture Fellow at MATTER, Advisor to Capita3, and a recognized thought leader in AI and Healthcare with publications and speaking engagements at HIMSS, Reuters, and leading healthcare and pharmaceutical conferences.Links Supporting This Episode: Within3 Website: CLICK HEREJason Smith LinkedIn page: CLICK HEREMike Biselli LinkedIn page: CLICK HEREMike Biselli Twitter page: CLICK HEREVisit our website: CLICK HERESubscribe to newsletter: CLICK HEREGuest nomination form: CLICK HERE

We continue to be blown away by the incredible animation, acting, and plot from "Maul: Shadow Lord." In this podcast episode, we dive into MSL episodes 5 and 6, discussing how much we enjoy Devon's development, raving about her and Maul's showdown with the Inquisitor, and speculating on who that mysterious hologram might be.Listen to our episode on MSL episodes 1-4Watch our special EXTRA 200th episode for free on our Patreon (it's different from this audio episode): ⁠https://www.patreon.com/posts/its-our-200th-156470434⁠Support us on Patreon for as little as $3/month: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠patreon.com/MostThingsKenobi⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠most_things_kenobi⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Website: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠mostthingskenobi.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠MostThingsKenobi⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Threads: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠most_things_kenobi⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tumblr: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠MostThingsKenobi⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

PJ Stock joined Conor and Shaun to talk about the Habs knocking out the Tampa Bay Lightning. PJ touches on Dobes, MSL and how the team levelled up to pull off the series win!

The Pro Wrestling Boom Podcast with Jason Powell features former MLW COO Jared St. Laurent discussing his new job as the President of the Lingerie Fighting Championships. The fun conversation includes his departure from MLW, whether he's open to returning, his desire to use pro wrestlers in LFC, his goals for the group, and more...

From votes of confidence, to lineup changes to keeping pretty cool behind the bench, what do you think of the job MSL is doing in these playoffs? Buying or selling:—Shohei Ohtani to win the cy young this year—The Habs Bolts series ends Friday—The 1st round of the nhl playoffs is the best 1st round in all of sports Brady Tkachuk finally weighed in on that trade speculation. Saying he’s been fully committed to the team and the city but also admitting it’s been a distraction. What did his statement on Wednesday do to your opinion about his future with Ottawa.

Écoutez le meilleur des Amateurs de sports du jeudi 23 avril 2026 Le Premier Trio, avec Stéphane Waite, Tony Marinaro et Eric Engels : « Je ne toucherais à rien dans l’alignement. Ils sont passés à un pouce et quart de revenir à la maison avec les devants 2-0. » Antoine Roussel : « Je m'attends à l'éclosion de Cole Caufield. MSL va vouloir éloigner le trio de Suzuki à celui de Cirelli et ça va les aider à débloquer à 5 contre 5. » Samuel Piette : « On veut démontrer aux partisans qu’on est meilleur que notre position au classement. Il y a eu des matchs où on méritait un meilleur sort. » Voir https://www.cogecomedia.com/vie-privee pour notre politique de vie privée

Host: Matt Birnholz, MD Guest: Brandon Young, PhD Today's medical science liaisons (MSLs) are navigating a rapidly shifting healthcare landscape. Step inside the evolving world of medical affairs as Dr. Matt Birnholz sits down with Dr. Brandon Young, senior MSL at CSL Seqirus, to uncover how communication, collaboration, and emerging technologies are shaping the future of the field. Gain insights on these shifts in this discussion from the 2026 Medical Affairs Professional Society (MAPS) Annual Meeting.

Today, we check in a year after the first Unsupervised Learning x Latent Space Crossover special to discuss everything that has changed (there is a lot) in the world of AI. This episode was recorded just after AIE Europe, but before the Cursor-xAI deal.Unsupervised Learning is a podcast that interviews the sharpest minds in AI about what's real today, what will be real in the future and what it means for businesses and the world - helping builders, researchers and founders deconstruct and understand the biggest breakthroughs.Thanks to Jacob and the UL production team for hosting and editing this!Jacob Effron* LinkedIn: https://www.linkedin.com/in/jacobeffron/* X: https://x.com/jacobeffronFull Episode on Their YouTubeWe discuss:* swyx's view from the center of the AI engineering zeitgeist: OpenClaw, harness engineering, context engineering, evals, observability, GPUs, multimodality, and why conference tracks now reveal what matters most in AI* Whether AI infrastructure has finally stabilized: why “skills” may be the minimal viable packaging format for agents, why infra companies have had to reinvent themselves every year, and why application companies have had an easier time surviving model volatility* The vertical vs. horizontal AI startup debate: why application companies can act as the outsourced AI team for enterprises, why some horizontal companies still matter, and why sandboxes may be the clearest reinvention of classic cloud infrastructure for the AI era* The “agent lab” playbook: starting with frontier models, specializing for your domain, then training your own models once you have enough data, workload, and user behavior to justify the cost and latency savings* Why domain-specific model training is real, not just marketing: how companies like Cursor and Cognition can get users to choose their in-house models, and why search, domain specialization, and distillation are becoming more important* Open models, custom chips, and alternative inference infrastructure: why swyx has turned more bullish on open source, why non-NVIDIA hardware is suddenly getting real attention, and why every 10x speedup can unlock new product experiences* What it means to sell to agents instead of humans: why agent experience may mostly just be good developer experience by another name, why APIs and docs matter more than ever, and how pretraining-data incumbents are compounding advantages in an agent-first world* Why memory and personalization may become the next big wedge: today's models mostly reward frequency of mentions, but in the future, swyx expects product choice to be shaped much more by personalized memory systems* The state of the AI coding wars: why coding has become one of the largest and fastest-growing categories in AI, how Anthropic, OpenAI, Cursor, and Cognition have all ridden the wave, and why the category may still have more room to run* Capability exploration vs. efficiency: why the industry is still in a token-maxing, experiment-heavy phase where people are rewarded for spending more rather than less* Claude Code vs. Codex and the strange stickiness of coding products: why first magical product experiences may matter more than expected, and why the bigger mystery may be why only a few names have emerged as real winners so far* What the end state of the coding market might look like: two major players, a longer tail of niche products, and possible disruption if Microsoft, Mistral, xAI, or the Chinese labs push harder into coding* Where application companies still have room against the labs: why frontier labs are trying to expand into verticals like finance and healthcare, but still leave space for focused companies that own the workflow and the last mile* Why coding may be a preview of every other AI market: the first category to truly go parabolic, the clearest example of foundation model companies colliding with application companies, and a template for how future vertical AI markets may develop* Why AI valuations now feel unbounded: from billion-dollar ARR products built in a year to trillion-dollar market caps, swyx and Jacob unpack how the AI market has broken traditional startup intuitions about scale and durability* Consumer AI vs. coding AI: why ChatGPT's consumer category may have plateaued on frequency and product design, while coding continues to feel like a daily-use category with real momentum* The next product frontier beyond coding: consumer agents, computer use, and “coding agents breaking containment,” with swyx's thesis that 2025 was the year of coding agents and 2026 may be the year they begin to do everything else* Whether foundation models are really killing startup categories: why swyx is less worried for early founders, more worried for mid-size startups and traditional SaaS, and why building something ambitious may now be the best job interview for a frontier lab* AI vs. SaaS and the internal culture war around adoption: the tension between AI-native employees who want to rip out expensive software and skeptics who think quick AI-built replacements create fragile systems* Why traditional SaaS may be under real pressure: swyx's own experience spending six figures on event and sponsor management software, the temptation to rebuild it cheaply with AI, and the broader question of whether teams will trust custom AI-native replacements* Biosafety, security, and frontier model access: why swyx raised biosafety at a dinner with Anthropic's Mike Krieger, why Krieger argued security is the bigger issue, and what restricted model releases reveal about Anthropic vs. OpenAI* The era of giant models: why 10T+ parameter systems may only be a temporary rationing phase before bigger clusters arrive, why labs may increasingly keep their most powerful models private for distillation, and why scale alone no longer feels like a complete answer* Memory as the slowest scaling factor in AI: why context windows have improved far more slowly than people hoped, why million-token context still has not changed most real workflows, and why memory may be the key bottleneck for the next generation of systems* What swyx changed his mind on in the past year: becoming more bullish on open models, more convinced that the top tier of agent startups behaves very differently from the median AI company, and more optimistic about fine-tuning and specialized model adaptation* “Dark factories” and zero-human-review coding: the next frontier after zero human-written code, where models not only write the code but ship it without human review, forcing companies to rethink testing and verification from first principles* Why RL and post-training may matter more than people assumed: even if the resulting models get thrown out every few months, the data, workflows, and domain-specific improvements persist* Synthetic rubrics, Doctor GRPO, and multi-turn RL: why reinforcement learning is becoming much more domain-specific and multi-step than many people realize, opening the door to much deeper customization* The next frontier after coding: memory, personalization, and world models, including why swyx thinks world models matter not just for robotics or gaming, but for giving AI something closer to lived understanding* Fei-Fei Li, spatial intelligence, and the Good Will Hunting analogy: the idea that today's LLMs may know everything by reading it all, but still lack the lived experience that turns knowledge into a deeper kind of intelligenceTimestamps* 00:00:00 Intro preview: AI coding wars, startup pressure, and market structure* 00:00:28 Welcome to the Latent Space × Unsupervised Learning crossover* 00:01:17 What AI builders are focused on now: OpenClaw, harnesses, and infra* 00:04:33 Why AI infra is harder than apps, and where startups can still win* 00:06:39 Should companies train their own models?* 00:09:28 Open models, custom chips, and the new inference race* 00:11:25 Designing products for agents, not just humans* 00:16:49 The state of the AI coding wars in 2026* 00:19:27 Capability exploration, token-maxing, and why coding is going parabolic* 00:21:41 What the end state of the coding market could look like* 00:23:50 Where app companies still have room against the labs* 00:27:02 Why AI valuations and market swings feel unprecedented* 00:28:56 Consumer AI vs. coding AI, and why sticky products still matter* 00:32:28 What the next breakthrough product experience might be* 00:32:53 2026 thesis: coding agents break containment and eat the world* 00:35:27 Are foundation models wiping out startup categories?* 00:37:33 AI vs. SaaS, vibe coding, and internal team tensions* 00:40:01 Biosafety, security, and the politics of restricted model releases* 00:42:19 Giant models, compute constraints, and the limits of scale* 00:44:30 Memory as the real bottleneck in AI* 00:44:57 Why swyx changed his mind on open models* 00:47:44 Dark factories and the future of zero-human-review coding* 00:49:36 Why post-training and RL may matter more than people think* 00:51:50 Memory, world models, and the next frontier of intelligence* 00:53:54 The Good Will Hunting analogy for LLMs* 00:54:21 OutroTranscript[00:00:00] swyx: Isn't that crazy? That number is just mind boggling.[00:00:03] Jacob Effron: What is the state of the AI coding wars today?[00:00:05] swyx: We're in a phase of sort of like capability exploration. The general thesis that I have been pursuing now is that the same way that 2025 was a year coding agents 2026 is coding agents breaking containments to do everything else.[00:00:16] Jacob Effron: Do you worry about the foundation models just getting into a bunch of these startup categories?[00:00:21] swyx: Mid-size startups. Yes.[00:00:23] Jacob Effron: What do you think the end state of this market is[00:00:25] swyx: for the market structure to, to significantly change? There would be[00:00:28] Jacob Effron: today on unsupervised learning. We had a, a fun episode and what's really become an annual tradition, a crossover episode with our friends at Latent space.Swix and I sat down and we talked about everything happening in the AI ecosystem today. What we thought of the various changes at the model layer, what's happening in the infra world, the coding wars, and a bunch of other things. It's a ton of fun to do this with someone I really respect and another great podcaster in the game.Without further ado, here's our episode. Well switch. This is, uh, super fun to be back with another unsupervised learning, uh, latent space crossover episode.[00:01:02] swyx: Yeah,[00:01:02] Jacob Effron: I feel like a lot of places we could start, but you know, one thing I always find fascinating, uh, about the way you spend your time is you obviously are like at the epicenter of this engineering movement and community, and you run these events and conferences and put on these.Awesome talks and, and I think just have a great pulse on the zeitgeist of what's going on.[00:01:16] swyx: Yeah.[00:01:17] Jacob Effron: Maybe to, to start just what are the biggest topics people are thinking about right now?[00:01:21] swyx: Yeah, so I just came back from London, uh, where we did a IE Europe and we're doing roughly one per quarter now, which Yeah, you've[00:01:27] Jacob Effron: really up[00:01:27] swyx: the, hopefully[00:01:28] Jacob Effron: up the, up the pace.[00:01:29] swyx: It's trying. We're trying to match AI speed, youknow?[00:01:30] Jacob Effron: Yeah, exactly. The tops would be completely different, I imagine. Uh,[00:01:33] swyx: yeah. You know, I definitely curate the tracks, like you can see what I think. When you see the track list and the, the speakers that I invite, obviously Open Claw is like the story of the last four or five months, and then be, be just below that.I would consider harness engineering, context engineering to be two related topics in agents and rag. And then there's a long tail of Evergreen stuff like evals, observability, GPUs, uh, and uh, LM infra and just general, just in general. We also have other updates on like multimodality and, uh, generative media, let's call it.Um, but I definitely, the, the first three that I mentioned are top of mind people. Yeah.[00:02:13] Jacob Effron: I think harness is particular like, so interesting. Um, you know, there was this tweet from Harrison Chase, the, the lane chain, CEO, that, that caught my eye recently where he said, you know, it finally feels like we have stability, uh, around the infrastructure for, uh, you know, around ai.And I think what. He basically was implying his like, look over the past two, three years as a company at the epicenter of AI infrastructure, it was a bit like playing whack-a-mole, right? You were constantly moving around with, however, the building patterns were evolving[00:02:36] swyx: for Harrison for sure. Right? Like he's basically had to reinvent the company every year since he started Lang Chain.Right? It was Lang chain, Ang graph and LP agents and like, uh, I think he's like one of the most nimble, adept sharp people about this. Yeah. Yeah.[00:02:49] Jacob Effron: Saying now, now is finally the time stability[00:02:51] swyx: this. Yeah.[00:02:52] Jacob Effron: Yeah. Um, do you buy that or what have you kind of make of that take?[00:02:56] swyx: I think that. It, it's very expensive to say this Time is different sometimes, but when you're just writing code, like it's actually okay to just like try to make a call and I think it may not even matter if this call is right or not.Like I just don't even care that much because you can be right on a thesis, but if you don't, you don't figure out how to monetize the thesis, then who cares if you said something first that said, um, it does feel like, for example. Uh, we went through a lot of different ways of passion packaging integrations up with, uh, with agents.And it feels like we've landed at skills, which is like the minimal viable format. Yeah. Which is just a markdown file, uh, with some scripts attached to it, and I don't see how it can be more simple than that. And so there is some justification for. The stability around harnesses. I feel like there may be more adaptation with regards to maybe like the real time elements or subagents or memory or any of those like agent disciplines, let's call it in, in agent engineering.Uh, but if, if the thesis is that, okay, you just want agents are LMS with tools in the loop with a file system, what they can do. Retrieval with, with skills and all these like standard tooling that now seems to be relatively consensus then probably. That makes sense. Um, I just think like there's no point trying to stake your reputation on this thesis that we're there because if it changes again, just change with it.It's fine.[00:04:33] Jacob Effron: Yeah. It's always, you know, I've always been struck by how that is. Much more challenging for infrastructure companies and application companies. Like obviously I think, yeah. You know, on the application side you've seen, you know, Brett Taylor from Sierra Max, from Lara. Like, they're like, look, we build, you know, what's ahead of the models and we're willing to throw everything out every three months, you know, as the models get better and better.Exactly. Yeah. But the thing you at least have there is you have. Uh, you have an end customer, right? That's like decently sticky. Um, you know, they will mostly stick, you know, they'll, they'll give you a shot at least of, of building these things. What I've always found more challenging, uh, at, at the kind of like, you know, reinvent yourself every three months of the infrastructure layer, it's like, you know, developers are definitely a, a pickier audience maybe than an accounting firm or, uh, you know, a bank.Yeah. And so it's definitely a, a, a more challenging position to be in to, to have to constantly reinvent yourself.[00:05:17] swyx: Yeah. Yeah. Yeah. And, and like when they turn, it's like. Very complete. Like, they'll leave to like the, the hot new thing, uh, because there's like no defensibility, I guess. Like e even, even if you are a database, like, uh, people can migrate workloads off databases.Like it's, it's a, it's a known thing. Uh, so I think like basically what we're talking about is the vertical versus horizontal, uh, debate in, in AI startups. And uh, the way I think about it also is just that like when you are. Um, Lara, when you are a bridge, like you are the outsource AI team, right? You, you are, your job is to apply whatever state ofthe art AI methods.[00:05:55] Jacob Effron: Yeah. Like this translation layer between model capabilities and your[00:05:57] swyx: own customers. Yeah. To, to the end customers and like, well, if they didn't have you, they would've to hire in house and they're not gonna hire in house so they have you. And like, I think that's like a reasonable, like very robust to any whatever trends and, and discoveries that people make in, in the engineering layer.I do think like there is, um. It like sort of useful horizontal companies being built, but they're all. Very much like, sort of like the reinventions of classic cloud in the AI era and the, the primary one being sandboxes. Yeah. Um, which like, it's another form of compute guys, like, let's not get too excited about it.But I mean, like the, the workloads are enormous.[00:06:38] Jacob Effron: Right.[00:06:38] swyx: Yeah.[00:06:39] Jacob Effron: It's interesting, and I feel like as, as part of this, you know, the questions that folks are asking around infrastructure, there's a lot around, you know, the extent to which companies should have their own AI teams and what they should be doing in-house.And, you know, uh, I think there's questions around should people be training their own models? Should people be doing, you know, rl, uh, in-house based on the data they have? I feel like, you know, one has to evolve their takes on this every, every three months with paces. But where, where are you at on this today?[00:07:00] swyx: I think, well, I mean actually all models have gone up. Um, and obviously I'm involved in cognition and also cursors doing, doing, uh, a lot of own model training. And I think that that is some part of the, what I've been calling the agent lab playbook, where you start off with the state of the art models from, uh, from the big labs and you, uh, specialize for your domain.But once you have enough workload and enough high quality data from your users, then you can obviously train your own models and like save a lot on cost and latency and all that, all that good stuff. Um, you also get like a marketing bonus of like calling it some fancy name and putting out some research[00:07:38] Jacob Effron: from my seat.I can't tell how much of it is like actual, you know, value that's provided to the end user. And how much of it is that marketing bonus? Right. It seems some combination of the[00:07:45] swyx: I think it's both.[00:07:46] Jacob Effron: Yeah.[00:07:46] swyx: Um, no, no. There, there actually is real value. Um, and you, you know that for a number of reasons. Like one, even when it's not subsidized, people do choose it as like one of the top four or five.This is both composer two and, uh, suite 1.6 I one of the top five models. Like in a, in a fair market? In a free market, yeah. In a, in a, in a model switch. Or people do choose it and like, it's not subsidized. Like, so that's as good as it gets. Uh, but beyond that, like domain specific models, for example. For search with, with both, which both companies have absolutely makes, makes a ton of sense.Everyone says like, yeah, we should always, always do this. And honestly like, I think the infrastructure for that is becoming easier with, um, like thinking machines tinker thing as well as primary like, uh, lab stuff. Yeah, I mean like, this is one of those like reversal of the, the bitter lesson where you first bootstrap on the large models and the general purpose models to get big.And as you get very well-defined workloads that are just high quantity but not high variance, um, then you just distill down to a smaller model and run that on your own. Right. Which like totally makes sense.[00:08:50] Jacob Effron: What I'm less clear on is the kind of DIY RL use case, which I think is really mostly around, you know, improved, uh, quality for, for different things.Obviously there's probably like more efficient ways to, you know, get a smaller model that's that's faster and cheaper. And it'll be interesting to see whether. You know, obviously you had, you know, uh, two, three years ago this whole case of companies that were, you know, pre-training and claiming better outcomes in, in their domains than getting kind of cooked as each model iteration improved.You know, I wonder whether that's a, a similar story plays out in the, uh, in, in the, our all space. Yeah, for the focus on, on on pure outcomes and quality, not the cost side, which clearly your own models for cost at scale makes a ton of sense.[00:09:28] swyx: I think there are this, there are two sides of the same coin.Like you basically always want to hold, uh, quality constant or trade off a little bit of quality for a drastic decreasing cost. And that's true for everyone. Uh, one element I wanted to bring out, which is very much in favor of open models, is custom chips. So this would be cereus, but also talu. And then there's a huge range of stuff in between.This has been a huge story this past year on just like everything non Nvidia is getting bid up, including like freaking MatX is working for, which is very, which is very rewarding for me, but I think one of those things where like, oh, like the suddenly, because the number of alternative. Hard, uh, hardware is increasing and the inference that you can get is insanely high.Like, um, we're talking thousands of tokens per second instead of less than a hundred. So the trade off for qua quality doesn't hold as much anymore because the speed is so high.[00:10:24] Jacob Effron: Have you seen a lot of companies go all in on the alternative chip?[00:10:26] swyx: So cognition has Yeah. On Cerebras, uh, and, and so has OpenAIUm, uh, and so no, I don't think so beyond that, uh, and that, do you think that's like a, that's mostly, that's foreshadowing of, that's, yeah. I used to be kind of a skeptic in terms of like, okay, so what if I get my inference at a hundred to a hundred tokens per second sped up to 200 tokens per second. It's only two X faster.It's not that big a deal. Um, but when you, uh, I think every 10 x does unlock a different usage pattern. Um, and you, we have proof in Talas and, and some of the others. That you can actually, um, drastically imp improve inference speed and what happens from there? I don't even really know, like it's, it's so hard to predict when entire applications just appear at once.Yeah. Uh, and it also isn't that expensive, right? So like, um, this is one of those things where like, I, I think the, the investment cycle is gonna be multi-year. Um, and I. Would caution people to not dismiss it too, too quickly.[00:11:25] Jacob Effron: Yeah. I mean, one other like infra question I was curious to get your thoughts on is obviously it seems increasingly a lot of the cutting edge infra companies are building for agents as the buyers of their product or users of their product, right?[00:11:35] swyx: Ooh,[00:11:36] Jacob Effron: and[00:11:37] swyx: another huge theme. Yeah. Yeah.[00:11:38] Jacob Effron: And I'm trying to figure out like what. What, what do you have to do differently about selling into agents? Um, are they just the ultimate rational developers? Uh, or is there, you know,[00:11:46] swyx: no, absolutely not. Um, I think they are easily prompt, injected and, uh, very tuned towards like, basically com compounding existing winners.[00:11:57] Jacob Effron: Yeah,[00:11:57] swyx: so like if, like, congrats if you won the lottery for getting into the training data right before 2023, because now you're like installed in there for the foreseeable future. But yeah. Uh, you know, one stat that Versal, uh, CTO Malta dropped at my conference was that there are now, uh, 60% of traffic to Elle's, um, like app arch, like admin app architecture for like configuring versal applications, uh, is bought.It's not, it's not human. Uh, so like your primary customer is agents now. Um, and it's mostly co like mostly coding agents, mostly people using CLI on CP or whatever. But yeah, I mean, I think. More. I, I think step one, if it doesn't exist as an API that agents can use, it doesn't exist. Right, right. Which I think is like, uh, it's a good hygiene thing anyway, to, to make everything API available, but not as like an extra, um.Push on like products, people to not only work on the ui, um, you should probably work on the on SCLI stuff. Beyond that, I think honestly there is like, so I, I come from the sensibility of, I think everything that you are trying to do for agents experience now, which is the term that Matt Bowman and Nullify is trying to coin, is the same thing that you should have been doing for developer experience.That you should have had good docs, you should have had a consistent API, uh, that is. Mostly stateless. Um, you should have, I guess, discoverable or progressive disclosure or like search or like whatever. And so now that people have energy in like finding these customers to do that, that's great. Um, do I believe in.Extending beyond that into something like a EO, um, for gaming The chatbots? Not necessarily, but obviously there's gonna be huge advantages when people who figure out the short term wins. Yeah. And short term wins can compound.[00:13:43] Jacob Effron: Do you think these compounding advantages to like the, the pre-training data cutoff companies, like, you know, obviously over some period of time, I imagine that doesn't persist.And so as you think about like. I dunno, three, four years from now what the, you know, selection criteria end up being. Do you think it still mirrors exactly what you were saying before? Like it's exactly what you should have been doing all along to sell a good product to developers?[00:14:01] swyx: It could be, except that I think in three, four years we'll probably have much better memory and personalization.So then general a EO or GEO doesn't really matter as much. So I think whatever memory or personalization system we end up with will probably d determine what you end up choosing much more. Than, than what is currently the case, which is just frequency of mentions, let's call it. Yeah,[00:14:26] Jacob Effron: yeah.[00:14:26] swyx: Uh, so you just spa quantity and I think that's, I mean, that's something I'm looking forward to.I do think, like, like, you know, I, I think that the fundamental exercise to work through for yourself is if you start a new, um, sort of. Uh, disruptor company. Now there's a, there's a big incumbent that everyone knows, like, like superb base. Super base is like, kind of like the Postgres, like database, uh, incumbent.If you wanna start like new superb base, how would you compete with them? And I don't necessarily have the answer, but I, I, I do think like people, like resend like relatively new. I think they would start like 20, 23 and still there was, there was a recent survey where like, people. Checked what Claude recommends by default.If you just don't prompt it with anything, just say, gimme an email provider and says, resent as in like 70, 70% of each cases. Like the fact that you can get in there with like such a relatively short existence, I think is, is encouraging.[00:15:14] Jacob Effron: Yeah.[00:15:14] swyx: I do think like. Um, you do want to do whatever it is to, to like to, to get in that Very short mentions this because, um, it's not gonna be 20 of them, it's gonna be like three.[00:15:26] Jacob Effron: No, definitely. It feels like, uh, you know, probably more, more consolidation than ever. Uh, or, or kind of like, you know, uh, a winner take most market than maybe the, the, the physics of go-to market in the past. Yeah. Might have, uh, enabled.[00:15:38] swyx: The other thing also is like, semantic association is gonna be very important, uh, in the sense that like, you want to do like the combo articles where you're like, use my thing with for sale, with blah, blah.And like that all gets picked up in a, in a corpus. And so that's. Probably one thing that you, you wanna do? Well, I don't know what else. Uh, it's, it's, it's, it's one of those things where like, I think I feel, I feel I'm behind, uh, I don't know how you feel about this, but like,[00:16:04] Jacob Effron: I think AI is just everyone constantly feeling like they're behind some, uh,[00:16:08] swyx: yeah.With,[00:16:09] Jacob Effron: I wanna meet the person that doesn't feel behind,[00:16:11] swyx: but like with, with ax, right? Like, so, so like, my, my stance was that exactly what I said before, like everything that you, that you should do for agents is something that you should have done for humans anyway. Yeah. And so. To the extent that you're just getting it more energy to, to do things for agents, great.But like, uh, it's hard to articulate what new thing apart from just like more spam, um, that you should be doing. Anyway, that would be my take right now. Um, I I, I do think like there, there will be more turns at this. I think the personalization turn that is coming, um, will be big. And I don't know what that looks like because like basically we're kind of, we feel kind of tapped out on the memory side of things.[00:16:49] Jacob Effron: Yeah. I, I guess since we last chatted, you know, you, you took this role over at cognition, um, and you've obviously have a, have a front row seat to the AI coding space today. You know, I feel like coding in many ways. You know, people view it as this, like, I mean, besides being like the, the mother of all markets and this massive opportunity, I think it's kinda a preview of like, what's to come for many other spaces.Both. Yeah. You know, I feel like agents are most advanced in coding. I also feel like the, you know, competition between foundation models and application companies, you know, and, uh, mirrors what we may see in other spaces. And so maybe for our listeners, can you just lay out like what is the state of the AI coding wars today?[00:17:25] swyx: Um, it is massive, right? Like, uh, and I don't think necessarily, last time we talked about this, we appreciated the size of what[00:17:32] Jacob Effron: No, I wish we did.[00:17:33] swyx: I state of AI coding wars today, um, both opening eye philanthropic have made it their p serials to competing coding. Um, and. Tropic is like 2.5 billion in a RR just from Cloud Code.The way they recognize a RR is. Opt for debate, uh, open ai. I don't think the, a public number is known, but let's call it 2 billion as well. And then cursor is like, rumored to be 2 billion, you know? And, and those, those are like the public numbers that are known? Yeah. Um, so like huge markets that have just been created in the past one year.Like, like anthropic, just like Claude Code just recently celebrated their one year anniversary, which is, yeah, pretty nice. Um, so, and then I think, like the other thing that I see is there's, there's some other people who are like, oh, here's like the, the sort of relative penetration of, uh, Claude use cases, right?Like, and it's like coding 50% and then legal, whatever. Health, uh, it's like the, the remaining ones. And there was a very popular tweet that was like, okay, I'll look at the, the empty space and all these other use cases. If you are a new founder today, you should be betting on the other stuff because on, on a sort of catch up Yeah.Theory and my. Consider my, my pushback is the same pushback that, uh, I had on app over Google, which is like, well, well why is this time different? Like, why, if it went from let's say 10 to 50% in the past year, why can't I keep going? Uh, and like getting that wrong is actually a very painful one because you could have just did, did the momentum bet.Instead of the mean reversion bed. So I, I, I think that that is the, the state of things now that people are very, very much into psychosis. Um, they're are getting rewarded for spending more rather than spending less. And I think we're not in that phase of efficiency. We're in a phase of sort of like capability exploration.So I think people who are more crazy, who are more. Uh, creative, um, get rewarded comparatively. Yeah.[00:19:27] Jacob Effron: Well, it's interesting. I mean, it feels like behind these like token maxing, leaderboards and whatnot is this, it's like the first phase of this transition from a workforce perspective is you just gotta show your employer like, Hey, I, I use these tools.[00:19:37] swyx: Here's my nu number of tokens I cost, and that's it. They don't care about the quality. Right. It is, uh, maybe distasteful to someone who cares about the craft and, and all that. Um, but directionally everyone just wants you to go up regardless. And so, um, there it is not very discerning. It's, and it's probably very sloppy, but I think it's net fine because we're still probably underusing ai just in generally.Yeah. Um, and so I think that's like very interesting. Like we had on the podcast, uh, Ryan La Poplar from OBI, who spends a billion tokens a day. Yeah. Um, and that's for those county home, it's like something like 10,000 worth, $10,000 worth a day of API tokens. If they, they did market rates, um, and like most of us can't afford that.Yeah. But like. And, and, and probably a lot of what he does is slop.[00:20:25] Jacob Effron: Right.[00:20:25] swyx: But like, he's going to dis, he's like, if there were a new capability, he would discover it first before you because he was, he was trying and you were not trying. Right. And like, you only do things that work like, well, good for you.But like the, the people who are going to discover the next hot thing are living at the edge.[00:20:42] Jacob Effron: Right and increase in living at the edge of just having the compute budget to like run these experiments. I mean, kind of similar to what living at the edge on the research side has always been. You know, it was constrained in many ways by the amount of compute you had to run these experiments.It feels similarly on the, almost on the builder or like actualizing these tools now.[00:20:56] swyx: Yeah. The other thing that's, I mean, very obvious is philanthropic is kind of like the high price premium player. Um, that where, you know. Restricting limits or restricting model releases even is like the name of the game.Whereas Codex is like, come on in guys, use our SDK, use our login and we don't care. We're gonna reset limits. Whatever you do want to try to exploit the subsidies where you can get it. And definitely Codex is super subsidized right now. Gemini also very subsidized. Um, and. Comparatively, like, I think you should make, Hey, I guess while, while that's going on, it's not that bad to be a capabilities explorer on just the $200 a month plan from Cloud Code or from OpenAI.Um, and, uh, I I, I, my sense is that people aren't even there yet.[00:21:41] Jacob Effron: How do you think this, like, market ultimately plays? I mean, it's obviously such a big market that, you know, any slice of that market is interesting for, for anyone going after it. But I think what, what makes people so interesting in the coding market particularly is it feels like it's kind of this.Foreshadowing of what will happen in other, you know, any other kind of application market that the foundation models eventually turn to and are all their models against and gather data around. And so how do you think, you know, like does there end up being room for lots of different kinds of players or like, what do you think the end state of this market is and is that, do you think that's applicable to other markets?[00:22:10] swyx: I feel like there will be, I mean. Status quo is probably the most likely outcome, which is there are two big players and there's a small range of longer tail people that, um, fit other use cases that the, the two big players don't. That feels right to me. I think that, um, for it to, for the market structure to, to significantly change there would be, there needs to be significant change in like the economics or like the, the brand building or like the, the, the, the value propositions of the, of the companies involved and I.Haven't seen any in the last six months that, that have really changed the stories materially. So I feel like they would just keep going until something, something else happens. Something else happens, meaning like Microsoft wakes up and like goes like. Guys, we have GitHub, we have, uh, you know, we, we, we'll, we'll do something much bigger here than other, other than just copilot.Um, and, uh, that would be a big change. Um, MSL has put out a model now, and I was in a breakfast with, uh, Alex Wang, where they were like, yeah, like, we, we really, really want to go after the coding use case. We haven't done anything yet, but like, don't underestimate them. Right. Um, and, and similarly for the Chinese labs.Um, I think they're trying to go after it. Like ZAI is doing stuff. GLM uh, ZI and GLM is same thing. Um, uh, and, and so it's, so like everyone's trying to get a piece of that pie. I, I feel like the, the status quo has been pretty stable for the past, like almost a year I'll say.[00:23:39] Jacob Effron: Yeah. And is the room for the, not like, you know, for, for the application companies more on like the enterprise side or like where do the, where do the, like what surface area do the model companies leave for application companies?[00:23:50] swyx: Yeah, that's a good one. Um. It's very much evolving. Um, it, I, I, I will say because opening I did not have this, the, this level of attention on coding. Yeah. Uh, a year ago. We just don't have that much history. Right. Um, and it seems like, for example, so the big push at Open I now is the Super app. Um, is that a consumer thing?Is that like a products like. Portfolio rationalization thing, how much is that gonna take away attention from coding at the time when they actually do want to put more coding? I think it's, it's very unclear. So I do think like there's, there's all these, like in both big labs, there's. Uh, sorry. Both of the, and, and drop and, and deep minus and XAI are are separate cases.Um, they are trying to see the other time expansion areas. So cloud code for finance. Yeah. Um, uh, cloud cowork, all those, all those things. Whereas I think cursor and cognition are like comparatively just focused on coding and so I, I do think they leave space and I do think for the other verticals that also means the same thing.Right. That, uh, that they're not gonna be that. Um, intensely focused on, on, on that domain. Except for, I, I think I would mark out finance and healthcare as like the next ones, um, that they're clearly going after. Uh, I, I would say comparatively, healthcare seems more thorny. There, there, there've been some announcements about it, but like, I would respect the, the finance work a lot more just because like the, the path to money is a lot clearer.[00:25:12] Jacob Effron: Yeah, no, I mean, obviously like, I, I think, you know, maybe similar to, to the space that's being left in these other domains, you know, there's obviously. Uh, a lot that's required to actually implement these tools in enterprises, uh, versus, you know, maybe just giving them, uh, giving model access to, to folks outta the box.[00:25:27] swyx: Yeah, yeah. Yeah. So the, the agent lab thing is like, we'll do the last mile for you. Whereas I think the model labs tend to just trust the model and, and be minimalist about it. Both of them work.[00:25:38] Jacob Effron: Yeah.[00:25:38] swyx: I, I don't, I don't necessarily think one, uh, beats the other, uh, for every, for every use case. Um, all I, all I do know is that it does seem like.Uh, the large enterprises do want a dedicated partner that isn't just the model labs, which is kind of interesting.[00:25:55] Jacob Effron: We, we've been in this phase of, of pure capability exploration. And so I think nothing has been, you know, better for the large labs, right? I mean, they're always gonna be, uh, uh, the frontier of, of capability exploration.And so I think have a very good relationship with a lot of these enterprises. But ultimately over time, like. The, uh, the incentive structure of these labs is always gonna be maximal, you know, token consumption for, uh, for the end customers they work with. And there's just, I think, so few companies that have actually gotten to massive scale.Maybe coding again is the most interesting. So it's the first space that really is just completely gone, you know? Yeah. You must love it every day. Like absolutely insane. And. I think it[00:26:32] swyx: gets even. Okay. I mean, like, I think we, we say good things about crystal cognition, but the sheer liftoff of like both end UPIC and open ai.‘cause they, they, they have independent valuations. I mean, let's throw an XEI in there because it's now I ping at 1.2 trillion. That number is just mind boggling. Like I, I feel like in normal investing or normal startups, there's kind of like a ceiling market cap or valuation. Totally. That, that like you, you reach and you go like, all right, let's, it's gonna be chiller from now on.And these guys are not slow down. No.[00:27:02] Jacob Effron: Well, I also think the dynamic is fascinating about some of these later stage companies is, is, you know, in the past, I feel like in, in venture world, if you got to a certain level of scale, the question around you was really more a valuation question. And this is like why there was different phase, like, you know, types of venture people did and like the late stage growth people were just incredible at like, you know, a little bit of what's the ultimate market opportunity of this company, but also what's the right way to, to value it.Like we know it's, it's in some bands of an outcome that is like. Sure there's some variance to it, but it's like relatively understood what that bands is and then maybe you get over time surprised to the upside. Whereas any kind of like later, even the labs themselves, any later stage company, the bands of which that company might be worth right now, even in a year or two years are so massive because of how fast the ecosystem changes that it's like.Even for later stage companies, every three months could be an existential level event to the upside to the downside. Yeah. Um, and I think that, like, you are obviously seeing it in the, in the positive with code, which, you know, if you think about a company like philanthropic, you know, that. For a while, it was like unclear if they were going to have access to enough capital, um, to really stay in the, in the race, right?And then coding hit at the exact right time. They had the perfect model for it. They executed brilliantly. Um, and you know, now are, are, you know, uh, you know, one of the most valuable companies in the world.[00:28:13] swyx: Uh, at the same time, I, I don't find, I, I have zero sympathy for opening eye because they're crushing it and they're all rich.You know, this is like a high class champagne problem to have to, uh, to be number two at coding or whatever. Like, who cares? Like, you're, you're doing great.[00:28:27] Jacob Effron: Yeah. It's funny though. I can't even, I mean, you would be closer to this, uh, you know, even that you're in the AI coding space, but it's like a lot of people I talk to think Codex is just as good, if not better than Claude Code.Right. I think one thing that I've been really surprised by, and maybe, maybe Cloud Code is a better product in some ways, I'm curious your thoughts is just in consumer AI with chat GBT. You saw this big first mover advantage, right? Where admittedly today, like, I don't know, Claude Gemini. Great products.Not sure, not abundantly clear chat GBTs any better, but like. People stick with chat, GBT, it's the first thing to introduce them.[00:28:56] swyx: They stay, but they're not growing anymore. I don't know if you've seen[00:28:59] Jacob Effron: Right. But that to me is more of like a, a, a product problem than it is. They're not like, it's not like they've like lost share to someone else.My understanding is the overall problem with consumer AI today is much more of a how do you take this tool and, you know, for, for folks like us, like knowledge workers, it's like this incredible magic tool, but it's not necessarily a daily active use tool for a lot of people around the world today. And what are the like products?It's, it's kind of a category wide problem. Like in coding, for example, like. The entire space has gone parabolic. There may be some relative growth in, uh, in other consumer AI players, but it's not like consumer AI as a category is like going parabolic and they're not capturing most of that thing. I think it's actually the larger problem is much more, hey, the category has kind of hit a bit of a plateau of people haven't figured out how to bring, you know, tons more users on board.Yeah, yeah. Or increase the frequency of those users. And so it seems more of a category wide problem than it is, you know, a massive market share of change. I was gonna draw the comparison to, to the coding space where Claude Co is the first product, obviously, to introduce people to this magical experience.You know, by all accounts, codex is, is pretty damn close to as good, if not better. Um, but like still that first product, you, you would've thought that would not be a super sticky, uh, you know, product surface area. And it actually has, it turns out, I, it feels like the first lab to introduce you and experience really does, uh, keep a lot of, uh, a lot of the focus.[00:30:12] swyx: I, I think. M maybe it's like still, still early days. You know, Chad, BT is like three plus years old and Yeah. Cloud code is only one. Just turned a year. Yeah. So give it time, you know? Yeah. Like, yeah. I mean, definitely sometimes a lot of people have switched from to Codex. Maybe that will keep going. I, it's like really hard to tell.Uh, yeah. I, I, I do, I do think that. Because we are in this like, high volatility, high temperature phase. Um, the loyalty and stickiness to first movers and category creators, I don't think is as high as it might be in some other, uh, areas in our careers that we've looked at.[00:30:47] Jacob Effron: Yeah. Though, I mean, I've been surprised by the cloud code thing.I, I would've thought that, like, in many ways I always worried about the[00:30:52] swyx: enterprise. You think you would've been gone by now?[00:30:53] Jacob Effron: Not gone. But I would've, I I always worried that the, that the consumer business of these companies would be quite sticky. And then the enterprise API business. Uh, was actually like, you know, in some ways like your least loyal buyers, like they would, they would move to,[00:31:05] swyx: right, right.But, but they worked out that it wasn't the enterprise API it was enterprise product.[00:31:09] Jacob Effron: Totally. And maybe that was the, that was the secret that like, but the amount of lock-in or just default behavior that has happened in that space, uh, is, is more than I might've imagined with two products that by all accounts are pretty damn similar.Yeah.[00:31:22] swyx: No fight there. Uh, I will say I do think that Codex is still in like a catch up. Like in terms of personal experience. Um, the only thing I like out of, out of Codex is the, is like Spark and like yeah. Uh, the, I, I feel like the skills integration is a little bit better. I feel like, uh, the, the speed is a bit better.Maybe ‘cause it's in, is written in rust or whatever. Um, very minor things that you like. Almost like telling yourself rather than like objectively assessing between two, two of them. I, I, I do think, like vibes wise, I think that's going on. Um, the, the, you know, I, I feel like the, the missing questions, uh, in, in this whole debate is like, why is this so concentrated in only two names, right?Yeah. Like, um, how, where, like, where is the Gemini? You know, presence, where's the Xai presence? Um, and like they are trying, it's just they haven't made that much progress yet.[00:32:12] Jacob Effron: But what the, what the Claude Co moment does show, and it actually in some ways makes you a little more bullish on the potential for someone else to catch up because it does feel like if you're the first person to introduce some magical net new product experience, that that actually might be stickier than one might have imagined.[00:32:27] swyx: Right, right, right. Okay. Yeah.[00:32:28] Jacob Effron: And so it's, everyone can believe they have shot[00:32:29] swyx: that. What do you think that new product experience might be like? I, I, it's, it's like, and this is a failure of imagination on my part. Like, I always wonder, like, people always say this like, well, the, the thing that will save us is like being first to the next new thing.Like what is it?[00:32:41] Jacob Effron: Yeah.[00:32:42] swyx: It's like,[00:32:45] Jacob Effron: I dunno, something around like, uh, consumer agent, computer use, like hybrid. I think, obviously, I think we're like scratching the surface on the consumer side.[00:32:53] swyx: So my, my current theory is like the. Open claw is like a vision of things to come.[00:32:58] Jacob Effron: Totally.[00:32:58] swyx: Um, and uh, it's good that O open I has like the association with open claw, but by no means do they have the rights to win it.The general thesis that I have been pursuing now is that the year the same way that 2025 was the year of coding agents, 2026 is coding agents breaking containment to do everything else. Um, and so coding agents continue to still win, but because they generate software and software eats the world, so like, it's kind of like the trans.Associated property of like software, eat the world, coding agents, eat software, therefore coding agents eat the world. Um, which is like an interesting,[00:33:30] Jacob Effron: yeah, and breaking containment always an easier phase phrase in the consumer context than the enterprise one. You've seen people run these really cool, uh, experiments in their own personal lives.I think like,[00:33:37] swyx: yes.[00:33:38] Jacob Effron: Figuring out, you know, how you, obviously everyone's focused, you know, on the enterprise side now around how you create these experiences. I feel like the vibes, you know, people love to have these narratives of like, everything is completely shifted. It's like I actually, you know, open AI.Organizationally, uh, you know, volatility aside is, you know, great products, great team, great models like everyone else in the world is incentivized for there to be. Two, three more. Everyone would love more like great model companies. And so I feel like the, the natural forces of the world revolt when any one company, you know, is too much the star of the show, right?There's so many people in the ecosystem that are incentivized for that not to happen. And so I think I'd be shocked if we don't have. Uh, uh, reversion of vibes, not maybe completely the other way, but at least a little bit more equal at some point over the next six, 12 months.[00:34:24] swyx: I, I think there's just a kind of different stages when, when you talk about the world, one wanting more model companies, I talked think about like the neo labs.[00:34:30] Jacob Effron: Yeah.[00:34:31] swyx: And I mean, I don't know, is it fair to say none of them have really broken through in the past year?[00:34:35] Jacob Effron: I think that's totally fair,[00:34:37] swyx: which is rough. Um, and well, how are we gonna, how are we gonna grow that diversity in, in, in choice, like. Um, that's, this is it.[00:34:46] Jacob Effron: Yeah. It'll be really interesting to see what, what, what ends up happening with that.And you've seen, you know, folks like Nvidia, you know, very incentivized to make sure there's, there's a broader platform of, of other model providers.[00:34:57] swyx: I think, uh, I don't know people say this, but I, I, I don't think they try it hard. Nvidia tries harder to build neo clouds[00:35:05] Jacob Effron: Yeah.[00:35:06] swyx: Than neo labs.[00:35:07] Jacob Effron: Well, they try pretty damn hard to build neo Cloud, so[00:35:09] swyx: that's,[00:35:09] Jacob Effron: yeah.[00:35:10] swyx: But like, you know, let's call it like the, the core weaves of the world, much happier place in the, you know, than any neo lab built on top of them.[00:35:18] Jacob Effron: Yeah. That one might argue it's, it's easier to, to enable a neo cloud to be successful than it is. Uh, you can't will a neo lab into existence the same way you, soNvidia[00:35:25] swyx: has more direct control over it.Uh, for sure.[00:35:27] Jacob Effron: What else is kind of catching your eye today on the startup side? I mean, you worry, there's obviously this whole narrative of like, you know, the foundation models, you know, they announced a product and every stock goes down 15%. Like[00:35:36] swyx: Yeah.[00:35:37] Jacob Effron: Do you, do you worry about the foundation models just kind of eating into to a bunch of these startup categories?[00:35:43] swyx: Not really. I, I think actually like. As, uh, there's, there's, okay, there's, there's, there's the, there's the point of view of like being an investor in startups, and there's a point of view of like, do you wanna start something? And I think honestly, like the, the downside for all these is so. Minimal in, in a sense of like, the worst you do is you just get hired into one of these labs anyway.So I, I think the, the market for people who just do things and try things and try to execute in like a competent way, even if like it doesn't work out commercially, even if it just wasn't that great anyway. Like, but like that's your job interview to go into, into one of these things anyway, so, um, I don't feel that.From a, from a very, very small startup perspective, mid-size startups. Yes. Uh, I will say there's been a lot of dead, um, LM Infra, a lot of LM infra consolidation like the, the, uh, lang fuses of the world getting absorbed into, into click house. And I, I think. Like people have maybe worked out the domain specific playbook, uh, and like, I think that's okay.Um, and, and yeah, I'm not that, not that worried about, uh, okay. So, um, I, I would say I'd be more worried about traditional SaaS, like low NPSS. This is the whole AI versus SaaS debate that has, that's been going on. Uh, and, and like literally I'm going through that exact thing in my company where, so I like kind of.Thinking through this on a very visceral, visceral level, right? On one hand you have the people who say you vibe coders don't appreciate the amount of work that goes into A-A-C-R-M and like, yeah, you think you can rip out Salesforce? So did the 30 entrepreneurs before you, right? Like, like, you know, you classically underestimate the things that you don't.Deeply, no. And, and, and target audience is not you. Uh, at the same time, like we have never been able to build software so easily and customize software so easily and like Yeah, you're not gonna use 90% of the things in Salesforce. So like, yeah. What's the typical, so what have you, what[00:37:33] Jacob Effron: have you done internally?[00:37:34] swyx: So we have there the main SaaS that we do for event management and sponsor management. That's, and we paid 200 KA year for that. Not, not huge, but like chunky for, for, for my, my scale. Um, and like, yeah, I could probably spend 2000 and, and build like a custom version of that. Um, the, the, the trick has been dealing with my, the rest of my team and getting them on board.Yeah. ‘cause I'm the most ethical person on my team, but like, I can't make that decision myself. And I think in the same way I've been telling with other CEOs team leaders as well, it's like, well you can be super cloud pilled. You can be super LM psychosis and that you think that's okay, but you like you have to bring your team with you.And I think like there, the sort of widening disparity in LM psychosis in companies is causing real s real riffs because. And on one hand, on one hand, the people who are less AI native are not getting with the picture. They're not, they're actually like behind, they're actually not waking up to the fact that like you, everything you think is necessary is not actually that necessary.And in fact, exactly would be better of you if you just like held your nose and went in and when came out the other side. Yeah, only talking to agents in natural language and like your life would actually be better and you just, you're just like close-minded. There's that perspective. The other perspective is, oh, you vibe coder.You, you did this in a weekend and you got the 80% solution and now the rest of your employees. Have to pick up the rest of your s**t, right, that you, that you thought you were, you were such hot, amazing, uh, uh, at, but like, actually you didn't figure it out. And like, actually LMS are still useless at this and blah, blah, blah.So like, I think there's this huge debate going on in every company right now. Um, and like, um, you know, I have a small microcosm of it, but like, yeah, it, it's making me hesitate to, to pull the trigger. But like I will at some point, it's like maybe I've put it off for one year, but not like five. Yeah, but like, so, so like SaaS is definitely getting squeezed.Um, it does make me wonder, like, I, I do think that there's an opportunity for a more AI native, um, system of record thing that is not just Postgres. Um, or not just MongoDB, although both are very good. Maybe it's like a convex or like people Yeah. Bring up convex a lot. I don't know, like, like, I, I just feel like the sort of quote unquote firebase of, of AI apps isn't really a thing yet.Um, beyond what we have. Uh, which, which is fine. It's, it's, it's just. We could probably start in a more sort of rapid iteration cycle first before scaling up to like a Postgres or MongoDB, which are more sort of old tech. I was at a dinner with, uh, Mike Krieger, the CPO of en philanthropic, and, and he, we were just kind of going around the room going like, what are people most worried about?Yeah. And, uh, for me, uh, I, instead of security, I brought up biosafety. Yeah,[00:40:21] Jacob Effron: classic.[00:40:22] swyx: Um, actually, like I said, it was. Cliche and classic, and the rest of the table were, were like, what do you mean? Someone sitting at home can manufacture a virus that wipes out half of humanity,[00:40:32] Jacob Effron: almost like the OG Jeffrey Hinton.Like, this is why you should be scared.[00:40:35] swyx: I'm like, yeah, like the read the, you know, risk reports. Like this is like the thing. Um, I think, and Mike was just sitting there knowing he was sitting on Mythos and going like, actually it's security. Um, and I think like, um, I think the, there's, there's, part of it is.A very good marketing. Like too good. Yeah, like I would actually advise and topic to tune down the marketing because also it's, it is just a very good model and you don't have to make so many marketing claims around it. At the same time, it is not really a private model. If you give it to 40 companies.Each of whom have like 10,000 employees or whatever. Right. It's not, it's not private, it's, it's like there's bad actors in there.[00:41:18] Jacob Effron: Yeah. Hopefully, hopefully not as, uh, as bad as releasing it widely, but, uh, no, I mean, it's an interesting. You know, it's an interesting case study for how all, I mean, many model releases might, I mean, you know, this might be the first model release that looks like the rest of ‘em from from now on, right?[00:41:31] swyx: It, it, so it's, it's the, there's an overall product strategy, uh, for anthropic of like bundle, uh, you know, restrict access bundle, uh, product with model maybe.Whereas, uh, OpenAI has definitely been a lot more sort of. Philosophically aligned on like, we will just enable access everywhere and we don't know what you, what will come out of it. Right.[00:41:51] Jacob Effron: Right. Though, I mean, this current moment, uh, obviously the cynical take is also just ties to the amount of compute that both companies[00:41:56] swyx: Yeah.Right, right, right. Yeah, I think, I think that's true. I I do think like the, the, this is the, the, the scale, the dawn of like larger than 10 trillion parameter models is very interesting. I don't think it, I think it's a temporary phenomenon because we have much larger compute clusters coming online for everyone over the next like three, five years.It's, and this is like already written in, in the cards.[00:42:18] Jacob Effron: Yeah.[00:42:19] swyx: So to the extent that like, you know, will we have rationing of models, uh, above 10 trillion, uh, in like two years? I don't think so. I think everyone will have no, we'll just[00:42:29] Jacob Effron: have rationing of the next phase.[00:42:30] swyx: Right. Right. But like, that's as it should be almost like, um.My, my classic example, which I, this is just me theorizing, not anything confirmed by Google. When Google announced Gemini, they actually announced three sizes, which was Flash Pro Ultra. They never released Ultra. They only have Pro and Flash. Um, so my theory is they have ultra sitting in a basement and they just could distilling from it for, for flashing pro.Um, which like, yeah, I mean, I, I actually think that's. As it should be for any lab that they, that they do that.[00:43:02] Jacob Effron: Yeah. Just because those are the models that people actually wanna end up using. And it's just like cost prohibit.[00:43:06] swyx: It is more, yeah, it's cost. Yeah. It's, it's not the want, it's just, just, just the cost.Um, I do think, like, uh, it is interesting that, uh, for a while I was, I was considering the theory that models capped out at two, 2 trillion, and I think that's proving to be wrong. And well then if I'm wrong, how wrong? How wrong am I? Do we do 200 trillion? Do we do two quarter trillion, whatever? Um, and I don't think we have the straight answer to that, but like, uh, it's interesting that we are continuing to scale number of pers when everyone kind of assu like can see that we're not going to get like the next thousand or 1 million x from this paradigm.So like the others, like the alias of the world are working on other. Um, model architecture improvements. We need a different scaling law, I guess, because like, we're, I, I feel like people already already feel like we're tapped out on this. Like the, the end, the end state of this is we turn most of the world into data centers and like, I don't know.I don't know if we want that.[00:44:08] Jacob Effron: Yeah, I mean, uh, if the, if, if, if the return of intelligence are there, maybe, uh, maybe not so bad.[00:44:13] swyx: I, I, I think there, there's just a sheer amount of like, like un scalability that like is wrangling people's sensibilities right now. Um, especially in terms of like context lengths.Um, my classic quote is that context length is like the slowest scaling factor in, in lms.[00:44:30] Jacob Effron: Yeah.[00:44:30] swyx: Um, we, like, we took maybe. Three years to go from like 4,000 context length to a million and that's about it. Yeah. Like Gemini has had a million token context length for two years now. Um, and no one's using it.Like, so like yeah, it's memory. Memory is probably gonna be the, the biggest limiting constraint on all these things.[00:44:50] Jacob Effron: Yeah. Certainly seems that way. I guess I'm curious over the last year since you recorded last, like what's one thing you've changed your mind on?[00:44:57] swyx: I feel like I was kind of bearish on open models like last year.Um, in a sense of, like, I, I had just done the podcast with an Al[00:45:07] Jacob Effron: Yeah.[00:45:08] swyx: Of Braintrust where he, and he, I mean, you know, he has a good cross section of all the top AI companies and he says market share of open source is 5% and going down. Um, I think that's changed. I think it's going up. Um, and even if,[00:45:22] Jacob Effron: even though the capability gap does seem to be increasing.Spending on the[00:45:26] swyx: time. It's hard to tell. Yeah, it's, it's really hard to tell. ‘cause like, okay, for, for listeners, capability gap increasing is like on public benchmarks. And let's say you're comparing mythos versus like, I don't know, G-T-O-S-S or like GLM 5.1. And, um, it's, it is really hard to tell. ‘cause even if they were closing, you will also not believe that they were closing that much because it's very easy to gain the benchmarks.Yeah. So you just don't really, really know. Um, all you know is like. Uh, there's somewhat objective open router stats on like what people choose in a free market. And people do choose some of these open models in significant volume, except that a lot of them are heavily discounted. So you need to kind of like price adjust, uh, these things.So even if, even if that were true, which I, I'm not sure, like I, I, I feel like the numbers just up now instead of down. Uh, I think the. Separation between what the top tier agent labs

For many life sciences teams, the first wave of AI has looked like copilots: smart search, quick answers, and help on demand. Useful, but passive. In this episode, Dr Andree Bates is joined by Parth Khanna, CEO and co-founder of ACTO, to explore what comes next: moving beyond copilots into role-based AI agents that proactively close knowledge gaps, improve field readiness, and operate safely inside regulated environments.Parth shares his path into life sciences and tech, including founding an early NLP company in 2012 and then building ACTO after speaking with over 100 life science companies about field force effectiveness. Today, ACTO supports tens of thousands of professionals and hundreds of brand launches, and Parth argues the industry is now entering the “agentic era” where the real differentiator is not just model access, but how organisations build context, control, and change management around AI.A key theme is why generic AI tools often fail inside enterprises. Parth outlines four requirements for agent success: context (role and job-specific personalisation), connection (stitching data sources and agent-to-agent workflows), control (testing, monitoring, observability), and change management (reducing fear and driving adoption). Without these, he says, many copilots and assistants end up underused, with people quietly reverting to old workflows.Parth then introduces ACTO's concept of role-based “super agents”, designed around a real job description (for example an MSL). Rather than a disconnected swarm of task bots, a “queen bee” orchestrator agent delegates to worker agents, checks outputs against compliance guardrails, and can be assessed with exams to quantify risk before deployment. This approach, he argues, makes AI both more powerful and safer for regulated field teams.Finally, the conversation looks ahead. Parth believes the future of work depends on pairing AI capability with distinctly human strengths: strategy, judgement, and human connection. The winners won't be those who automate the most tasks, but those who redesign roles so humans and agents amplify each other.Topics CoveredWhy copilots are useful but fundamentally passiveThe shift from AI that responds to AI that actsWhy generic tools fail: context, connection, control, change managementAdoption reality: why many AI assistants go unusedQuantifying risk and moving from black box to observable AIRole-based super agents and the “queen bee” orchestrator modelTesting agents with exams before field deploymentGuardrails, compliance, and agent-to-agent quality checksHuman skills AI can't replace: strategy, judgement, connectionThe future of MSL and field excellence in an agentic eraEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It's a focused diagnostic that surfaces what's actually broken and what's blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.

Hey yall, Alex here, writing this from sunny London, at the first ever AI Engineer conference in Europe!What a show we have for you today! First, let me catch you up on what's important: Anthropic, this week announced a whopping $30B ARR up from 19B in Feb, while also telling us about Claude Mythos Preview their next gen HUGE model that they won't release to the public (yet?) that finds crazy vulnerabilities in existing code bases. Apparently OpenAI will follow up with a similar non-public model soon.The Meta Superintelligence Lab led by Alex Wang finally showed what they were working on, Muse Spark, the smaller of their upcoming models on a complete new infrastructure (MSL announcement, Simon Willison's deep dive on the 16 hidden tools).In other news:Z.AI released GLM 5.1 in OSS finally (HF weights), Seedance 2.0 finally available in US on Replicate, OpenAI testing out GPT-image-2 on LM Arena under codenames, HappyHorse from Alibaba takes the video crown, and Mila Jovovich (5th Element, Resident Evil) releases agentic memory plugin called MemPalace (Ben Sigman's transparent correction thread is worth reading).We had 5 guests today on the show, we kick off with @swyx the founder of AI Engineer and host of Latent Space. We then chatted with @petergostev from Arena (formerly LMArena) about Mythos and the compute wars, then Vincent Koc, the second most prolific contributor to OpenClaw, then our friends VB from OpenAI and Omar from DeepMind, both previously at HuggingFace. This is a busy busy show, and given the time-zones, I unfortunately don't have time for a full weekly writeup, but as always, I will share the raw notes and post the video (lightly edited).ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.AI Engineer - LondonThursdAI came a long way since the first AI Engineer conference, but many who read this don't know, that was my big break. Swyx invited me to cover the first AIE in San Francisco in 2023, and I remember, I was in an Uber to the airport, the driver asked me what I do, and I, for the first time said “I host a podcast”. I (and ThursdAI) owe a lot to Swyx, and AIE team, and it's been incredible to see how big they've grown and how many great speakers this event hosts! The term AI Engineer has drifted in those 3 years, but also has the term Software Engineer. Swyx predicted this nearly 3 years ago, what I don't think he predicted, is that all engineers are now AI Engineers, and this includes domains like Agens (OpenClaw), Context and Harness Engineering, Evals and Observability, Voice & Vision all of which are tracks in this conference. I was really surprised to see how many of the talks/speakers here are native to London (after all, Deepmind is from here, OAI, Anthropic, Meta have offices here) and the latest boom in agents, OpenClaw, Pi were all Europe based as well, and they are joined the AI Engineer stage. Oh, and there's also a Giant Inflatable Claw at the entrance, yup, for pictures and vibes, and to show off how quickly the OpenClaw took over the mind-share. Anthropic announces $30B ARR and Mythos, their next model, will not be released to the public. The thing that everyone will tell you, is that Anthropic is on a roll, this is obviously connected to their upcoming IPO this year. We've been covering many issues on their part, but this week we saw them posting about a HUGE increase in ARR, from 19B in February to 30B in April, passing OpenAI at $25B. That last fact though, is kind of disproven because they report on ARR differently, OpenAI apparently only counts their cloud revenue from Microsoft per the information. The growth is undeniable though, and so is the most unprecedented release announcement, Claude Mythos Preview, which was rumored for a bit and now was announced proper. With project Project GlassWing, Anthropic has announced that this model is SO good at cyber security and finding bugs in code, that they cannot share it with the public, and through GlassWing they will share it with companies like Microsoft, Linux, CrowdStrike and a bunch of others, to harden their security. This is it folks, this is the first time, where a model was “announced” but deemed too risky to release. Now, is it truly “too risky”? Previously, folks thought that DALL-E is too risky, or cloning voice tech is too risky, and now it's everywhere. The capabilities catch up even in OpenSource. But the facts are, Anthropic says they've found a 27-year old bug in OpenBSD (famously very secure), and that this model is very very good at connecting the dots between several, seemingly inacuous bugs, to string them together into one coheren exploit. This is, indeed scary. Just last week, one of the top security researchers in the world, Nicolas Carlini, now at Anthropic, gave a talk at Black Hat, showing off these results, and saying that these models since December and definitely recently have passed him as a security engineer. If you haven't seen this talk, watch it, then try to estimate if Anthropic did the right thing by only releasing this model to enterprises first. But on the show, Peter Gostev from Arena gave me a take on this that I haven't been able to shake. Peter pulled up his Compute Wars chart live on the show — and the picture is that OpenAI is way ahead of Anthropic on compute, with Anthropic only recently getting a noticeable bump (which lines up suspiciously well with Mythos being trainable in the first place). His read: “it sounds cooler to say it's too risky to release than ‘we can't serve it.'” The official partner pricing is $25 / $125 per million tokens — 5x Opus 4.6 — but if you don't have the GPUs to serve it broadly, the price doesn't matter. In the year of the IPO, the company that cannot serve a model says the model is too dangerous to serve. Make of that what you will.This also reframes the whole rate-limit drama with OpenClaw. Anthropic didn't ban OpenClaw — I want to be very clear about this because the discourse went sideways. What they did is they made it significantly more expensive for Max-tier subscribers to use Opus through OpenClaw, which pushed a lot of people over to GPT-5.4 via Codex. Same root cause: they're out of compute. The freshly announced Anthropic + Google TPU deal (Google already owns ~10% of Anthropic) is them trying to fix this — though as Peter noted, it's pretty wild that Google is propping up a direct competitor to their own DeepMind team. Same pattern as their original $2B Anthropic investment ending up propping AWS Bedrock against Google Cloud. Big Google contains multitudes.Meta Superintelligence Labs ships Muse Spark — Llama is dead, long live MuseLlama is dead, long live Muse. This week Meta finally showed what the very expensive Meta Superintelligence Labs under Alexandr Wang has been cooking, and the answer is Muse Spark — the smaller of their new model family, built on a fully rebuilt AI stack from scratch in just 9 months. Nine months is wild for that kind of overhaul, and the headline number people are quoting is that they reach Llama 4 Maverick capability with over 10x less compute.Spark is intentionally small and latency-optimized — it's not trying to be the biggest, it's trying to be the first step on Meta's new scaling ladder. But the benchmarks in certain areas are nuts: 86.4 on CharXiv Reasoning (beats Opus, Gemini, GPT-5.4), and the one that really got me — 42.8 on HealthBench Hard vs Opus at 14.8 and Gemini at 20.6. They trained it with data curated by over 1,000 physicians and it shows. They also shipped a Contemplating mode which is parallel multi-agent reasoning, hitting 58.4% on Humanity's Last Exam with tools. Coding is the acknowledged weak point (77.4 on SWE-Bench Verified vs Opus 80.8) but for v1 from a brand new stack, this is extremely respectable.Meta is Back!The real story isn't any single benchmark though, it's distribution. Spark is rolling out across meta.ai, WhatsApp, Instagram, Threads, Messenger, and Ray-Ban Meta glasses — billions of users. Meta went from open Llama to a closed consumer model and they're clearly playing a different game now (though Wang says future Muse versions might be open-sourced).The deep-dive that's really worth your time is Simon Willison's post where he poked at the meta.ai chat UI and got the model to spit out descriptions of 16 hidden tools behind the scenes — full Code Interpreter with persistent Python 3.9, a visual grounding tool that does pixel-precise object detection (bounding boxes, point coordinates, counting — it located 8 objects including individual whiskers and claws on a generated raccoon), sub-agent spawning, file editing, and semantic search across Instagram/Threads/Facebook posts. It's basically an entire agentic harness baked into the chat UI. Jack Wu from MSL confirmed the tools are part of a new harness built specifically for Spark's launch. Meta stock went up 7% on this. They are very much back in the frontier game.Guest highlights We had an unprecedented packed show with 5 guests (also this is the shortest show we've everSwyx kicked us off with vibes from the AI Engineer floor — harness engineering as the dominant theme (gains are coming from the harness, not the weights), the rise of skills (English-as-programming-language) absorbing more of that harness work, and his thesis that supply-chain attacks like the recent light LLM and Axios incidents mean you should basically vendor everything — pip fork instead of pip install. We also chatted about how MCP has gone from “the most exciting protocol” to “settled and stable, therefore less interesting,” which is a great problem to have.Peter Gostev from Arena (you saw a lot of him in the Mythos section above) also dropped a bonus on us: Arena just released 3 years of historical leaderboard data and actual prompt datasets on Hugging Face. He used to literally scrape the arena website by hand into Google sheets to make those overtime leaderboards we all loved — now it's all public. Also: he confirmed that Seedance 2.0 jumped ~80 ELO points above the next video model on Arena, which is unprecedented — video models normally cluster within 10 points of each other.Vincent Koc — the #2 OpenClaw maintainer after Peter Steinberger — joined us fresh off the OpenClaw track stage. The OpenClaw codebase is now ~1.5 million lines of code including unreleased iOS and Android native apps. GitHub literally caps the issue/PR counter at “5K+” and they hit the ceiling. We talked about OpenClaw 2026.4.5 which ships /dreaming GA (Light/Deep/REM phases that defrag agent memory and write a human-readable Dream Diary to DREAMS.md), built-in video and music generation across 4 backends, GPT-5.4 as the new default, prompt-cache reuse improvements, and Control UI + docs in 12 new languages. Vincent's framing of dreaming was beautiful — “how do you explain agent memory to a mom? You call it dreaming.” He also gave my favorite line of the show on the GPT-5.4 personality problem: incredible at coding, but soulless. (For what it's worth, I came home after watching Project Hail Mary, cloned the Rocky voice, dropped it into my OpenClaw, and it was magical. That's the kind of thing you can only do when the harness and the model are decoupled.)VB from OpenAI told us Codex just hit 3 million weekly active users — up from 2 million last month. We talked plugins (the Stripe / Supabase / shadcn ones that ship as packages), sub-agents (yes, one is named Jason), and Guardian Approvals — an experimental mode that classifies each tool call by risk and only escalates the dangerous ones to you, so you don't have to YOLO-mode everything. The story that stuck with me though is his 9 AM Codex automation: every morning it reads his Slack mentions, cross-references Gmail and Calendar, and creates 5-minute pre-brief calendar events for upcoming meetings. None of that is “coding.” That's the super-app future hiding inside a “developer tool.” I'm stealing this workflow.Omar Sanseviero from Google DeepMind came on to celebrate Gemma 4 crossing 10M+ downloads with 1,000+ Gemma-4-based fine-tunes already on HF (and Gemma family total is now over 500M downloads). Gemma 4 is also the foundation for the next generation of Gemini Nano on Pixel/Samsung devices. Lama.cpp vision capability fixes are landing. Gemma 4 is also live on W&B Inference if you want to play. Wolfram (whose entire household runs on Pixel + Google AI Studio, including his 70-year-old mother on voice unlock) was in heaven.This Week's BuzzA short but spicy week from Weights & Biases:* W&B Automations are LIVE. You can now wire event triggers from your training runs (completion, eval thresholds, drift) into notifications, GitHub Actions, deployments, infra shutdowns — closing the loop from experiment to production. Pairs really well with the iOS app we recently shipped, so you can get a ping on your phone the moment something interesting happens on a run.* GLM 5.1 is live on W&B Inference (alongside Gemma 4 from last week) — the team is moving fast to host the best open models the moment they drop.* Wolfram published a deep dive on “more reasoning is not always better” on the W&B blog — the research behind his finding that giving models more thinking tokens can actually make them dumber on certain tasks. It's the in-depth version of what we discussed on the show last week, with all the data. Go read it on wandb.com.Also: shout out to everyone who came up to me at AI Engineer and said hi. The Wolf Bench mentions in particular made my day. If you're listening to this and you're at AIE — come find us, we'll be around tomorrow too.That's it for this week — newsletter is short because the show was long and London is calling. As always, thanks for reading and listening

Habs struggle v Florida or MSL putting his lines in the blender. The bigger surprise from the habs win over Florida? Will Brendan Gallagher play in the playoffs? Are the Ottawa Senators a sleeper time come playoff time? What is the main course at your Masters Champions dinner

Marco D'Amico with Conor and Shaun off the Habs shootout win over Florida. Race for the division, MSL changing his lines and the Habs game breaking talent

durée : 00:02:40 - Volley : Poitiers début les play-offs de MSL Vous aimez ce podcast ? Pour écouter tous les autres épisodes sans limite, rendez-vous sur Radio France.

The latest guest on The PR Week podcast is none other than Diana Littman, U.S. CEO of MSL.  She talks about her goals for the agency, seven years into its top role, and what it's like working on client assignments with other agencies from Publicis Groupe and other networks. She also gives listeners a behind-the-scenes look at the un-retirement campaign for Mr. Clean.  Plus, the biggest marketing and communications news of the week, such as Omnicom PR relocating agencies, the fortuitous timing of Wendy's chief tasting officer job ad and Cup Noodles' special celebrity collaboration product launch in Asia.  It's also the biggest week of the year on the PR calendar, with the PRWeek Awards U.S. set for Thursday night in New York City.  PRWeek.comTheme music provided by TRIPLE SCOOP MUSICJaymes - First One Follow us: @PRWeekUSReceive the latest industry news, insights, and special reports. Start Your Free 1-Month Trial Subscription To PRWeek Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

幻冬舎の暗号資産（仮想通貨）/ブロックチェーンなどWeb3領域の専門メディア「あたらしい経済 https://www.neweconomy.jp/ 」がおくる、Podcast番組です。 ーーーーー 【番組スポンサー】 この番組は、暗号資産取引におけるフルラインナップサービスを提供する「SBI VCトレード」のスポンサーでお届けします。 ーーーーー SBI VCトレードは、「暗号資産もSBI」のスローガンのもと、国内最大級のインターネット総合金融グループであるSBIグループの総合力を生かし、暗号資産取引におけるフルラインナップサービスを提供しております。暗号資産交換業者・第一種金融商品取引業者・電子決済手段等取引業者として高いセキュリティ体制のもと、暗号資産の売買にとどまらない暗号資産運用サービスや法人向けサービスの展開、さらにステーブルコインのユーエスディーシー（USDC）を国内で初めて取り扱っております。 ーーーーー SBI VCトレード公式サイト：https://account.sbivc.co.jp/signup?hc_ak=1RNML.3.M06AS ーーーーー 【紹介したニュース】 ・メタプラネットがJPYC社に4億円出資へ、完全子会社2社設立も ・マスターカード、暗号資産企業など85社以上参加の協働枠組み「クリプト・パートナー・プログラム」開始 ・リップル、豪州金融ライセンス取得へ。BCペイメンツ買収で決済事業拡大 ・バイナンス、WSJを名誉毀損で提訴。イラン制裁関連報道巡り ・ECB、トークン化金融エコシステム構築へ。「Appia」ロードマップ公開 ・Zcash向け機関投資家マイニングプール、大手ファウンドリーが4月開始へ ・米財務省、暗号資産ミキサーの正当な金融プライバシー用途を認識＝報告書 ・スタークネット、ERC20向けプライバシー機能「STRK20」発表。匿名DeFiなど想定 ・ゴールドマンサックス、開示ベースでXRP現物ETFの最大保有機関に ・ソニックラボ、米ドル建てステーブルコイン「USSD」ローンチ、BUIDLなどを準備資産に ・米ウェルズ・ファーゴ、「WFUSD」商標を出願。暗号資産取引やトークン化関連サービスを想定 ・英スマーケッツ、米予測市場参入へ。CFTCに取引所ライセンス申請=報道 ・ヴィタリック、機関向けワンクリック分散型ステーキング構想を公開 ・AIエージェントが無断でGPUを暗号資産マイニングに転用、研究チームが安全性リスク指摘 ・米メタ、AIエージェントSNS「モルトブック」買収、創業者2名はMSLへ 【あたらしい経済関連リンク】 ニュースの詳細や、アーカイブやその他の記事はこちらから https://www.neweconomy.jp/

幻冬舎の暗号資産（仮想通貨）/ブロックチェーンなどWeb3領域の専門メディア「あたらしい経済 https://www.neweconomy.jp/ 」がおくる、Podcast番組です。 ーーーーー 【番組スポンサー】 この番組は、暗号資産取引におけるフルラインナップサービスを提供する「SBI VCトレード」のスポンサーでお届けします。 ーーーーー SBI VCトレードは、「暗号資産もSBI」のスローガンのもと、国内最大級のインターネット総合金融グループであるSBIグループの総合力を生かし、暗号資産取引におけるフルラインナップサービスを提供しております。暗号資産交換業者・第一種金融商品取引業者・電子決済手段等取引業者として高いセキュリティ体制のもと、暗号資産の売買にとどまらない暗号資産運用サービスや法人向けサービスの展開、さらにステーブルコインのユーエスディーシー（USDC）を国内で初めて取り扱っております。 ーーーーー SBI VCトレード公式サイト：https://account.sbivc.co.jp/signup?hc_ak=1RNML.3.M06AS ーーーーー 【紹介したニュース】 ・メタプラネットがJPYC社に4億円出資へ、完全子会社2社設立も ・マスターカード、暗号資産企業など85社以上参加の協働枠組み「クリプト・パートナー・プログラム」開始 ・リップル、豪州金融ライセンス取得へ。BCペイメンツ買収で決済事業拡大 ・バイナンス、WSJを名誉毀損で提訴。イラン制裁関連報道巡り ・ECB、トークン化金融エコシステム構築へ。「Appia」ロードマップ公開 ・Zcash向け機関投資家マイニングプール、大手ファウンドリーが4月開始へ ・米財務省、暗号資産ミキサーの正当な金融プライバシー用途を認識＝報告書 ・スタークネット、ERC20向けプライバシー機能「STRK20」発表。匿名DeFiなど想定 ・ゴールドマンサックス、開示ベースでXRP現物ETFの最大保有機関に ・ソニックラボ、米ドル建てステーブルコイン「USSD」ローンチ、BUIDLなどを準備資産に ・米ウェルズ・ファーゴ、「WFUSD」商標を出願。暗号資産取引やトークン化関連サービスを想定 ・英スマーケッツ、米予測市場参入へ。CFTCに取引所ライセンス申請=報道 ・ヴィタリック、機関向けワンクリック分散型ステーキング構想を公開 ・AIエージェントが無断でGPUを暗号資産マイニングに転用、研究チームが安全性リスク指摘 ・米メタ、AIエージェントSNS「モルトブック」買収、創業者2名はMSLへ 【あたらしい経済関連リンク】 ニュースの詳細や、アーカイブやその他の記事はこちらから https://www.neweconomy.jp/

In this episode of New Frontiers in Functional Medicine, Dr. Kara Fitzgerald speaks with Dr. Robert Lustig about the new USDA dietary guidelines and the broader forces shaping nutrition and metabolic health. Dr. Lustig brings a characteristically direct and nuanced perspective on sugar, ultra-processed foods, and food policy—raising important questions about what drives real change. It's a thoughtful conversation that challenges assumptions and invites deeper reflection. Full show notes + references: https://www.drkarafitzgerald.com/fxmed-podcast/ GUEST DETAILS Robert H. Lustig, MD, MSL, is Emeritus Professor of Pediatric Endocrinology at UCSF and a neuroendocrinologist with expertise in obesity, metabolism, and nutrition. Known for his influential work on sugar and ultra-processed foods, Dr. Lustig focuses on improving metabolic health through food system reform, research, and advocacy. He is the author of Fat Chance, The Hacking of the American Mind, and Metabolical, and a leader with Eat REAL, Biolumen, SnapRecall, and Perfact. Website: https://robertlustig.com/ Email: rlustigmd@gmail.com THANKS TO OUR DIAMOND SPONSORS DUTCH: https://dutchtest.com/for-providers Biotics Research: https://www.bioticsresearch.com/ Time—Line Nutrition: https://tinyurl.com/bdzx2xms EXCLUSIVE OFFERS FROM OUR SPONSORS Find out why MitoQ's mitochondria-targeting is a critical step for your healthspan and longevity strategy. http://mitoq.com/drkara CONNECT with DrKF Want more? Join our newsletter here: https://www.drkarafitzgerald.com/newsletter/ Or take our pop quiz and test your BioAge! https://www.drkarafitzgerald.com/bioagequiz YouTube: https://tinyurl.com/hjpc8daz Instagram: https://www.instagram.com/drkarafitzgerald/ Facebook: https://www.facebook.com/DrKaraFitzgerald/ DrKF Clinic: Patient consults with DrKF physicians including Younger You Concierge: https://tinyurl.com/yx4fjhkb Younger You Practitioner Training Program: www.drkarafitzgerald.com/trainingyyi/ Younger You book: https://tinyurl.com/mr4d9tym Better Broths and Healing Tonics book: https://tinyurl.com/3644mrfw

Can a clinician really thrive in the high-stakes world of pharmaceutical sales?In this episode of Medical Sales U, I sit down with Randy Rhodes, a former Nurse Practitioner at the Cleveland Clinic who successfully transitioned into Oncology Sales. Randy pulls back the curtain on why he left the bedside, the "identity crisis" clinicians face when moving to sales, and the exact strategy he used to land a role at a top pharma company.Whether you are a nurse practitioner, RN, or pharmacist looking to break into the industry, this deep dive provides the tactical roadmap you need to bridge the gap between clinical expertise and commercial success.WHAT YOU'LL LEARN IN THIS EPISODE:* The "Business of Nursing": Why Randy's business degree and clinical background became his "unfair advantage."* The MSL vs. Sales Debate: Why Randy pivoted from the Medical Science Liaison path to the commercial side.* The 4:54 AM Mindset: How a disciplined routine (and CrossFit!) fuels a successful sales territory.* Overcoming the "Salesperson" Stigma: How to stay patient-centric while hitting your quota.* Interview Secrets: The specific questions Randy wasn't prepared for and how you can avoid his mistakes. TIMESTAMPS:0:00 - Intro: Meet Randy Rhodes, NP turned Oncology Pro02:15 - The Louisiana Connection: From Business to Nursing05:30 - Life at the Cleveland Clinic: Bone Marrow Transplant Expertise09:45 - Making the Jump: Why Pharma?13:10 - The MSL Interview Nightmare: Learning the Hard Way18:40 - Reframing "Sales": It's About the Patient22:15 - Landing the Job: The 4-Round Interview Process26:30 - A Day in the Life: Sunday Planning & Territory Hustle32:00 - Staying Motivated When Doctors Say "No"38:45 - Leadership & Advice for Aspiring Reps42:10 - The Power of Feedback: Why Every "No" is a "Not Yet"

How should PR pros react to Reddit's surge in popularity? PRWeek's latest podcast takes a look.Joining the latest episode of Beyond the Noise are Paige Hiley, director of social at Golin; and Jo Bromilow, director of social and influence at MSL.Beyond the Noise looks at some of the biggest issues affecting communications and PR. Download the podcast via Apple, Spotify, or listen on your favourite platform.Speaking to PRWeek UK deputy news editor Evie Barrett, the guests discuss clients taking an interest in social media platform Reddit, and how its community focus requires an entirely different approach to other channels.Reddit's changing userbase, and its links to Google and OpenAI, are also discussed within the episode.Bromilow and Hiley give advice on communicating with Reddit moderators, as well as using the app as a social listening tool.The episode was recorded prior to the news of Reddit being fined £14m by the Information Commissioner's Office for failing to properly check the age of its users, as reported on Tuesday (24 February).Commenting after the announcement, Bromilow said: “Reddit's response – that it intends to appeal and that it feels like it treads a delicate balance between protecting users' privacy and policing its platform – is a consistent one with how it has always operated and helps reinforce some of the points we made about the platform self-policing and the moderators existing to protect the userbase.“There have been lots of headlines recently about various social networks from TikTok to Meta being hit with fines in this regard, so this isn't a Reddit-specific issue. I anticipate a lot of back and forth along these lines as the online safety act comes into effect, and the reality of enforcing it vs the PR power of talking about it.” Hosted on Acast. See acast.com/privacy for more information.

'One FM' by One MSL strives to connect voices within the global Field Medical community.For episode 16 Helen was joined by Wade May, Global Capability Owner - Learning, Training & Coaching (FLM & MSL), Boehringer Ingelheim.If you would like to feature on a future episode, please email community@onemsl.comhttps://www.onemsl.com/

In this episode, I sit down with Josh Wageman, PhD, DPT, MPAS, CLS, CSCS — Clinical Lipid Specialist, PA who formerly practiced in Endocrinology, and Medical Science Liaison — to explore the intersection of protecting your healthspan while building wealth and expanding career flexibility as a physician associate. Josh's PhD research focused on cholesterol disturbances in Alzheimer's disease, and he's widely known for his ability to teach complex lipid physiology in a relatable, practical way. We break down cholesterol and cardiovascular risk without the overwhelm, discussing which labs and screening strategies are truly worth the cost and effort — and when age or family history should factor into the decision. He also shares what inspired him to write The Home Security System and the Lipid Neighborhood, how writing can serve as both education and diversified income while having a meaningful impact, and why clinicians don't have to feel boxed into a single career path. From becoming a Medical Science Liaison (MSL) to building credibility beyond the clinic, this episode highlights how health, impact, and optionality can work together. If you've ever wondered how to better understand cholesterol, prevent heart attacks, strokes, and dementia, or expand your career beyond traditional clinical roles, this conversation is for you. Get your copy of Josh's book: https://amzn.to/4rYcpoz Connect with Josh on LinkedIn: https://www.linkedin.com/in/josh-wageman-48893445/ Connect with Josh on X: @JoshJWageman Check out Josh's website: lifelovelipids.com If this episode was helpful, subscribe to the PA the FI Way podcast or YouTube channel for more content to help you build financial independence and prevent burnout along the way. Are you just beginning your journey to financial independence and want to learn more? Download your free copy of the PA the FI Way Beginner's Workbook here! Website / Blog: pathefiway.com Follow PA the FI Way on Instagram: @pathefiway https://www.instagram.com/pathefiway/ Connect with Kat on LinkedIn: https://www.linkedin.com/in/katarina-kat-astrup-mspas-pa-c-175848255/ Watch on Youtube: https://www.youtube.com/@pathefiway Join the private Facebook group created for current and future PAs on their journey to financial independence: https://www.facebook.com/groups/pathefiway Like the Facebook page to follow along for updates: https://www.facebook.com/pathefiway Keywords: physician associate, physician assistant, PA, PA-C, MSL, medical science liaison, non-clinical medical roles, non-clinical roles, cardiovascular screening, medical author

Eri Mizobe is a digital marketing leader with over 12 years of experience spanning influencer marketing, social media, and public relations. As VP of Digital at MSL, Publicis Groupe's creative communications agency, she leads integrated digital strategy and execution for global brands including KitchenAid and JM Smucker. She has worked with industry-leading companies such as Dyson, Estée Lauder, and Marriott International, driving innovative campaigns that connect brands with modern audiences. Outside of work, Eri enjoys traveling, film photography, cooking and planning her wedding in Malta.

在學界專注在研究上多年，對於要踏入不熟悉的業界總是會有許多擔憂和害怕。到底業界有什麼樣的工作機會呢？業界和學界工作性質差異很大嗎？業界和學界在意的又有什麼不同？   這一集節目，我們透過和 Sky in the Wall 的合作，邀請到橫跨兩大洋三大洲的生技業界菜鳥一起上節目分享在美國、歐洲、臺灣等不同國家地區的生技業工作心得。除了所在地不同，這一集的講者工作內容也有很大的差異，包括醫藥學術專員和商業開發、藥廠免疫檢測自動化科學家、藥廠蛋白質工程與抗體開發科學家，到藥廠影像資料科學家。在會談中，講者們會分享在不同地區部門的職場菜鳥工作心得和觀察，也會分享在不同地區求職、升遷和 networking 文化的差異。希望透過這集輕鬆的聊天交流，讓聽眾能對世界各地和各部門的生技業界樣貌有初淺的認識，幫助大家從學界到業界的轉換更加順暢。   ✨ 生技來一刻感謝國科會與駐波士頓辦事處科技組贊助我們製作節目。我們也歡迎聽眾小額捐款生技來一刻，您的支持能幫助我們製作更優質的節目。 ✨ 節目連結、講者Linkedin連結請見留言處！感謝講者提供詳盡的延伸閱讀連結和文章！  

This episode: The first real-world activation of the Garmin Autoland system, the E‑7 Wedgetail networked airborne early warning and control (AEW&C) platform, the flu season impact on crews, an airline captain stands up for exhausted flight attendants, and airlines with the largest fleets. Additionally, airport modernization and the Dulles people movers, the infrastructure needed to support the growth of personal air vehicles, and containment systems for lithium battery thermal runaway. Aviation News Autoland Saves King Air, Everyone Safe, FAA, NTSB Launch Probes On December 20, 2025, a Super King Air (N479BR) operated by Buffalo River Aviation experienced an in-flight emergency after departing from Aspen, Colorado (KASE) on a FAR Part 91 reposition flight. No passengers were on board. Climbing through 23,000ft MSL, the aircraft experienced a rapid, uncommanded loss of pressurization. The aircraft was equipped with Garmin Aviation’s latest Emergency Descent Mode (EDM) and Autoland systems, automatically engaged when the cabin altitude exceeded the prescribed safe levels. The system selected a suitable airport per Garmin criteria (KBJC, Rocky Mountain Metropolitan Airport), navigated to it, and landed safely. See: NTSB News Talk Episode 20: Garmin Autoland Emergency Landing: First King Air Save Buffalo River Aviation Statement Regarding Colorado Emergency Landing Image courtesy Garmin. Boeing's $724 million radar plane lives on, despite Pentagon efforts to kill it The E‑7 Wedgetail program is designed to replace the legacy E‑3 Sentry/AWACS-type aircraft (Airborne Warning And Control System) with a modern, networked airborne early warning and control (AEW&C) platform. The E-7 is designed to provide long-range, 360° air and maritime surveillance using an electronically scanned array radar mounted on a Boeing 737 airframe. It's intended to serve as an airborne battle management node, coordinating fighters, surface units, and ground-based air defenses. The Pentagon wants to cancel the purchase of two prototype E-7 Wedgetail jets, but Congress refuses to do so. In fact, Congress provided $847 million in additional funding for the two prototypes. Major Radio Failure Paralyzes Greek Airspace A major failure of aviation radio communications across Greece led to a temporary shutdown of Greek airspace, grounding or diverting flights nationwide for several hours and causing knock-on disruption across Europe. The collapse of radio frequencies in the Athens Flight Information Region (FIR) forced authorities to halt departures and arrivals until communications were partially restored. Travelers stranded in Caribbean as US military operation sends airlines scrambling to add flights A US military operation to capture Venezuelan President Nicolás Maduro led to a temporary FAA closure of Caribbean airspace, causing more than 425 flight cancellations and stranding thousands of travelers across islands including Puerto Rico, Anguilla, St. Maarten, and Aruba. Airlines are now restoring service and adding extra capacity, with most commercial restrictions lifted and operations gradually normalizing. Alaska Airlines Captain Sues Boeing Over 737Max Door Plug Incident Alaska Airlines captain Brandon Fisher has filed a $10 million lawsuit against Boeing and subcontractor Spirit AeroSystems, alleging they tried to make him a scapegoat for the January 5, 2024, mid‑air door plug blowout on Flight 1282. He claims Boeing falsely suggested the incident was due to maintenance or crew error, despite later NTSB findings that pointed to Boeing's inadequate training, guidance, and oversight in its manufacturing processes. Fisher says he has suffered “profound physical and mental repercussions” since the blowout, describing ongoing deterioration linked to emotional injury. Alaska Airlines Hits New All Time Record of 540+ Flight Attendants Going Sick With Carrier Struggling to Operate Full Schedule Flight attendants and pilots are calling out sick in great numbers as the flu season takes hold. Alaska Airlines reports that 540 flight attendants are out. Meanwhile, Frontier, JetBlue, and Spirit have activated contingency plans. In an internal memo, Spirit Airlines said, “Our reserve levels are virtually the same as they have been since 2023, but during this holiday, our sick calls have exceeded previous periods by nearly 250% on some days.” Weather delays and ATC shortages have compounded the problem. A memo reviewed by PYOK explained that nearly 20% of the airline's flight attendants called out sick just before the New Year. My Crew Is Done: United Airlines Captain Refuses to Push Tired Flight Attendants And One Passenger Thanks Him For The Delay FAA regulations generally limit a flight attendant's maximum scheduled duty day to 14 hours on domestic flights. With an augmented crew (adding additional flight attendants), duty can be scheduled beyond 14 hours but is capped at 20 hours. This PYOK article relates the observations of a passenger who saw a United Airlines Captain refuse the attempts of the ground crew to keep the timed-out flight attendants on the boarded plane while another cabin crew could be found. With the FAs exiting the plane, the passengers would have to deplane. Top 10 airlines with the biggest fleets in 2026 United Airlines has the largest fleet with 1,050 single-aisle and widebody aircraft. American Airlines follows with 1,023 aircraft, then Delta Airlines (989), Southwest Airlines (810), China Southern Airlines (708), China Eastern Airlines (679), Skywest Airlines (600), Air China (531), Turkish Airlines (399), and Ryanair (349). The data comes from Planespotters.net and individual airlines. It is current as of December 2025. Mentioned Micah was a guest on WBZ, AM Radio 1030 in Boston with Bradley Jay. He spent an hour talking about all sorts of different aviation and travel things: Ready for Take Off! Dulles Airport Modernization: Dulles mobile lounges could last another two decades, airport officials say 18 people sent to the hospital after mobile lounge crashes at Washington D.C.-area airport Trump's Transportation Secretary Sean P. Duffy Launches New Initiative to Revitalize Dulles Airport into The International Gateway Our Nation's Capital Deserves Plane Mate mobile lounge. Newer model. Jetson ONE Jetson ONE. Lithium-ion battery containment: Lithium Fire Guard Lithium Battery Air Safety Advisory Committee FAA testing videos: Competitor 1, Competitor 2, Competitor 3, Competitor 4, and PG100. Hosts this Episode Max Flight, Rob Mark, and our Main(e) Man Micah.

Streaming and media expert Dan Rayburn shares why investors should only care about the Warner Bros/Netflix/Paramount deal if it happens (0:40). NFL and NFLX; streaming and sports (11:00). Appropriate metrics to use in this space (18:40). Brand and revenue: Apple, Google, Amazon, Disney, Netflix (27:40). What is TV? (45:00)Show Notes:Netflix Is Still KingStreaming Media BlogRead our transcriptsFor full access to analyst ratings, stock and ETF quant scores, and dividend grades, subscribe to Seeking Alpha Premium at seekingalpha.com/subscriptions

As with all demo-heavy and especially vision AI podcasts, we encourage watching along on our YouTube (and tossing us an upvote/subscribe if you like!)From SAM 1's 11-million-image data engine to SAM 2's memory-based video tracking, MSL's Segment Anything project has redefined what's possible in computer vision. Now SAM 3 takes the next leap: concept segmentation—prompting with natural language like “yellow school bus” or “tablecloth” to detect, segment, and track every instance across images and video, in real time, with human-level exhaustivity. And with the latest SAM Audio:SAM can now even segment audio output!We sat down with Nikhila Ravi (SAM lead at Meta) and Pengchuan Zhang (SAM 3 researcher) alongside Joseph Nelson (CEO, Roboflow) to unpack how SAM 3 unifies interactive segmentation, open-vocabulary detection, video tracking, and more into a single model that runs in 30ms on images and scales to real-time video on multi-GPU setups. We dig into the data engine that automated exhaustive annotation from two minutes per image down to 25 seconds using AI verifiers fine-tuned on Llama, the new SACO (Segment Anything with Concepts) benchmark with 200,000+ unique concepts vs. the previous 1.2k, how SAM 3 separates recognition from localization with a presence token, why decoupling the detector and tracker was critical to preserve object identity in video, how SAM 3 Agents unlock complex visual reasoning by pairing SAM 3 with multimodal LLMs like Gemini, and the real-world impact: 106 million smart polygons created on Roboflow saving humanity an estimated 130+ years of labeling time across fields from cancer research to underwater trash cleanup to autonomous vehicle perception.We discuss:* What SAM 3 is: a unified model for concept-prompted segmentation, detection, and tracking in images and video using atomic visual concepts like “purple umbrella” or “watering can”* How concept prompts work: short text phrases that find all instances of a category without manual clicks, plus visual exemplars (boxes, clicks) to refine and adapt on the fly* Real-time performance: 30ms per image (100 detected objects on H200), 10 objects on 2×H200 video, 28 on 4×, 64 on 8×, with parallel inference and “fast mode” tracking* The SACO benchmark: 200,000+ unique concepts vs. 1.2k in prior benchmarks, designed to capture the diversity of natural language and reach human-level exhaustivity* The data engine: from 2 minutes per image (all-human) to 45 seconds (model-in-loop proposals) to 25 seconds (AI verifiers for mask quality and exhaustivity checks), fine-tuned on Llama 3.2* Why exhaustivity is central: every instance must be found, verified by AI annotators, and manually corrected only when the model misses—automating the hardest part of segmentation at scale* Architecture innovations: presence token to separate recognition (”is it in the image?”) from localization (”where is it?”), decoupled detector and tracker to preserve identity-agnostic detection vs. identity-preserving tracking* Building on Meta's ecosystem: Perception Encoder, DINO v2 detector, Llama for data annotation, and SAM 2's memory-based tracking backbone* SAM 3 Agents: using SAM 3 as a visual tool for multimodal LLMs (Gemini, Llama) to solve complex visual reasoning tasks like “find the bigger character” or “what distinguishes male from female in this image”* Fine-tuning with as few as 10 examples: domain adaptation for specialized use cases (Waymo vehicles, medical imaging, OCR-heavy scenes) and the outsized impact of negative examples* Real-world impact at Roboflow: 106M smart polygons created, saving 130+ years of labeling time across cancer research, underwater trash cleanup, autonomous drones, industrial automation, and more—MSL FAIR team* Nikhila: https://www.linkedin.com/in/nikhilaravi/* Pengchuan: https://pzzhang.github.io/pzzhang/Joseph Nelson* X: https://x.com/josephofiowa* LinkedIn: https://www.linkedin.com/in/josephofiowa/Full Video EpisodeTimestamps00:00:00 Introduction and the SAM Series Legacy00:00:53 SAM 3 Launch: Three Models in One Release00:05:30 Live Demo: Concept Prompting and Visual Exemplars00:10:54 From Prototype to Production: The Evolution of Text Prompting00:15:45 The Data Engine: Automating Exhaustive Annotation00:14:10 Real-World Impact: 130 Years of Humanity Saved00:25:11 Architecture Deep Dive: Decoupled Detection and Tracking00:28:02 SAM 3 Agent: Bridging Vision and Language Models00:33:20 Head-to-Head: SAM 3 vs Gemini and Florence00:47:50 Video Understanding and the Masklet Detection Score00:20:24 Fine-Tuning and Domain Adaptation: From Waymos to Medical Imaging00:52:25 The Future of Perception: Native Vision vs Tool Calls01:05:45 Building with SAM 3: Roboflow's Rapid Auto-Labeling00:57:02 Open Source Philosophy and the Path to AGI00:58:24 What's Next: SAM 4, Video Scale, and Beyond Human Performance Get full access to Latent.Space at www.latent.space/subscribe

as with all demo-heavy and especially vision AI podcasts, we encourage watching along on our YouTube (and tossing us an upvote/subscribe if you like!) From SAM 1's 11-million-image data engine to SAM 2's memory-based video tracking, MSL's Segment Anything project has redefined what's possible in computer vision. Now SAM 3 takes the next leap: concept segmentation—prompting with natural language like "yellow school bus" or "tablecloth" to detect, segment, and track every instance across images and video, in real time, with human-level exhaustivity. And with the latest SAM Audio (https://x.com/aiatmeta/status/2000980784425931067?s=46), SAM can now even segment audio output! We sat down with Nikhila Ravi (SAM lead at Meta) and Pengchuan Zhang (SAM 3 researcher) alongside Joseph Nelson (CEO, Roboflow) to unpack how SAM 3 unifies interactive segmentation, open-vocabulary detection, video tracking, and more into a single model that runs in 30ms on images and scales to real-time video on multi-GPU setups. We dig into the data engine that automated exhaustive annotation from two minutes per image down to 25 seconds using AI verifiers fine-tuned on Llama, the new SACO (Segment Anything with Concepts) benchmark with 200,000+ unique concepts vs. the previous 1.2k, how SAM 3 separates recognition from localization with a presence token, why decoupling the detector and tracker was critical to preserve object identity in video, how SAM 3 Agents unlock complex visual reasoning by pairing SAM 3 with multimodal LLMs like Gemini, and the real-world impact: 106 million smart polygons created on Roboflow saving humanity an estimated 130+ years of labeling time across fields from cancer research to underwater trash cleanup to autonomous vehicle perception. We discuss: What SAM 3 is: a unified model for concept-prompted segmentation, detection, and tracking in images and video using atomic visual concepts like "purple umbrella" or "watering can" How concept prompts work: short text phrases that find all instances of a category without manual clicks, plus visual exemplars (boxes, clicks) to refine and adapt on the fly Real-time performance: 30ms per image (100 detected objects on H200), 10 objects on 2×H200 video, 28 on 4×, 64 on 8×, with parallel inference and "fast mode" tracking The SACO benchmark: 200,000+ unique concepts vs. 1.2k in prior benchmarks, designed to capture the diversity of natural language and reach human-level exhaustivity The data engine: from 2 minutes per image (all-human) to 45 seconds (model-in-loop proposals) to 25 seconds (AI verifiers for mask quality and exhaustivity checks), fine-tuned on Llama 3.2 Why exhaustivity is central: every instance must be found, verified by AI annotators, and manually corrected only when the model misses—automating the hardest part of segmentation at scale Architecture innovations: presence token to separate recognition ("is it in the image?") from localization ("where is it?"), decoupled detector and tracker to preserve identity-agnostic detection vs. identity-preserving tracking Building on Meta's ecosystem: Perception Encoder, DINO v2 detector, Llama for data annotation, and SAM 2's memory-based tracking backbone SAM 3 Agents: using SAM 3 as a visual tool for multimodal LLMs (Gemini, Llama) to solve complex visual reasoning tasks like "find the bigger character" or "what distinguishes male from female in this image" Fine-tuning with as few as 10 examples: domain adaptation for specialized use cases (Waymo vehicles, medical imaging, OCR-heavy scenes) and the outsized impact of negative examples Real-world impact at Roboflow: 106M smart polygons created, saving 130+ years of labeling time across cancer research, underwater trash cleanup, autonomous drones, industrial automation, and more — MSL FAIR team Nikhila: https://www.linkedin.com/in/nikhilaravi/ Pengchuan: https://pzzhang.github.io/pzzhang/ Joseph Nelson X: https://x.com/josephofiowa LinkedIn: https://www.linkedin.com/in/josephofiowa/ [FLIGHTCAST_CHATPERS]

//The Wire//1500Z December 14, 2025////PRIORITY////BLUF: TERROR ATTACK STRIKES AUSTRALIA AS 12X KILLED IN BONDI BEACH MASS SHOOTING. VEHICLE RAMMING ATTACK FOILED IN GERMANY. MASS SHOOTING REPORTED AT BROWN UNIVERSITY IN PROVIDENCE.// -----BEGIN TEARLINE----- -International Events-Australia: A few hours ago, a complex terror attack took place at a Hanukkah event in Bondi Beach. Multiple gunmen approached a gathering of people at a picnic area on the east side of the park, and began engaging those taking part in holiday celebrations. At least two gunmen took up a tactical position on the pedestrian bridge at grid coordinate: 56H LH 40786 48784 // 61.2 ft MSL. From there, the gunmen began firing at event participants in the park below. After a few minutes, these two shooters were eventually neutralized by armed police on this bridge.At least one other gunman was present at the shooting, but was disarmed by a bystander who attacked the shooter with his bare hands and took the weapon from him. This disarmed-shooter was later detained by police on the pedestrian bridge with the others.Analyst Comment: Concerning casualties, right now the number stands at 10x killed during the attack, with a few dozen wounded. At least two of the attackers were wounded/killed by armed police, however their status is not known. The total number of shooters involved in this attack is also not known, but right now the count stands at 3x shooters taking part in the attack. At least one shooter did survive, as indicated by the videos of the incident taken by observers. Regarding the identities of the attackers, official confirmation of their name and status will take some time. However, photos of some of the shooter's drivers licenses have circulated social media in the hours after the attack. At least one of the attackers appears to be Naveed Akram, who had a NSW driver license.Germany: Yesterday a vehicle ramming attack was foiled by police, which involved a local terror cell in lower Bavaria. Local authorities state that 5x suspects have been arrested after they planned to carry out a vehicle ramming attack at a Christmas Market in the Dingolfing-Landau area.Analyst Comment: The suspects have not been identified by name, however their nationalities are: 1x Egyptian, 3x Moroccans, and 1x Syrian. All are currently being held in pre-trial detention, and more documents are expected to be released regarding how this plot was alleged to have been planned. -HomeFront-Rhode Island: Yesterday evening a mass shooting was reported at Brown University after a shooter opened fire during final exams near the Barus and Holley Engineering building on campus. 2x people were killed and 9x were wounded during the attack.Analyst Comment: The assailant egressed from the area after the shooting, which triggered a manhunt for several hours and prevented the scene from being secured for medical personnel to provide aid to the wounded. As of this morning, police state that they have one "person of interest" in custody regarding the case, however they stopped short of calling this person a suspect. Officially, the shooter has not been captured yet. No weapon was recovered from the scene, and the assailant was wearing a mask during the attack.-----END TEARLINE-----Analyst Comments: In Germany, it must be noted that if this terror cell was rolled up by police, there are probably others which have not yet been detected. Five terrorists is NOT a lone-wolf-style attack, and heavily indicates a more hierarchical organization structure. Depending on how well this cell was organized and commanded, this could mean that other terrorists that haven't been detected yet might be motivated to accelerate their attack planning. Considering the success of the horrific attack in Australia, it's possible that other attacks are coming down the pipeline. As such, inc

This episode of Student Affairs Now celebrates the twentieth anniversary of the Multi-Institutional Study of Leadership (MSL), one of the most influential research projects in student affairs and leadership education. Host Heather Shea talks with longtime colleagues and collaborators John Dugan and Kristan Cilente-Skendall about the study's origins, impact, and evolution. Together they reflect on how the MSL has shaped our understanding of leadership, learning, and social responsibility across higher education and beyond. The conversation also explores their new venture, the Center for Expanding Leadership and Opportunity (CELO), and its role in advancing equity and human development for the next generation of learners.

The Centre for European Legal Studies (CELS) hosts an annual public lecture in honour of Lord Mackenzie-Stuart, the first British Judge to be President of the Court of Justice. Among the eminent scholars of European legal studies invited to give the lecture are Professor Joseph Weiler, former Judge David Edwards of the European Court of Justice, and Advocate-General Francis Jacobs of the European Court of Justice. The texts of the Mackenzie-Stuart Lectures are published in the Cambridge Yearbook of European Legal Studies.The 2025-26 Mackenzie-Stuart Lecture was delivered by Professor Anand Menon, Director, UK in a Changing Europe, on the title 'Reflections on the Brexit Revolution' on 3 November 2025.Anand Menon is Director of the UK in a Changing Europe and Professor of European Politics and Foreign Affairs at King's College London. He has written widely on many aspects of EU politics and policy and on UK-EU relations. He is a frequent contributor to the media on matters relating to British relations with the EU.Abstract: The outcome of the Brexit referendum was driven by many forces, including increasing frustration at an economic and political model that seemed to be failing far too many people. And the vote to Leave in fact provided a unique opportunity for this discontent to be addressed. The fact that it was not has merely contributed to the growing appeal of populism. And along the way, many of the things we took for granted about our country and the way it is governed have been challenged.Lecture begins at 03:52The slides are available at:PDF: https://resources.law.cam.ac.uk/cels/MSL_2025_26_slides.pdfPowerpoint: https://resources.law.cam.ac.uk/cels/MSL_2025_26_slides.pptxMore information about this lecture, including photographs from the event, is available from the Centre for European Legal Studies website at:https://www.cels.law.cam.ac.uk/mackenzie-stuart-lectures

This week's episode of The PR Week podcast comes to you from PRWeek's PRDecoded conference in Chicago, which took place on October 16 and was themed around navigating uncertainty.PRWeek news editor Diana Bradley catches up with Bespoke Beauty Brands CEO Stacey Tank right before she took to the stage to share her journey from the comms office to the boardroom. Bradley also speaks with Feeding America's Monica Lopez Gonzalez, PepsiCo's Andrea Foote, MSL's Diana Littman and The Lagrant Foundation's Kim Hunter. Meanwhile, PRWeek associate news editor Jess Ruderman interviews Burson's Vikki Chowney.The episode also includes conversations with attendees from on the stage at the event, such as Kevin Warren, president and CEO of the Chicago Bears, who was the closing keynote speaker; as well as Omnicom Public Relations Group CEO Chris Foster and Edelman CEO Richard Edelman, who met for an on-stage discussion about the “state of the PR nation.” AI Deciphered is back—live in New York City this November 13th.Join leaders from brands, agencies, and platforms for a future-focused conversation on how AI is transforming media, marketing, and the retail experience. Ready to future-proof your strategy? Secure your spot now at aidecipheredsummit.com. Use code POD at check out for $100 your ticket! PRWeek.comTheme music provided by TRIPLE SCOOP MUSICJaymes - First One Follow us: @PRWeekUSReceive the latest industry news, insights, and special reports. Start Your Free 1-Month Trial Subscription To PRWeek Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Send us a textThis week on Here's What We Know, we welcome Dr. Dan Docherty, Chief Coaching Officer of Braintrust and a leadership development expert, for an inspiring conversation about the heart of human connection. We'll explore how communication, neuroscience, and mentorship shape who we become as leaders, parents, and friends.From the story of a music teacher who changed Dan's life to the Six P's framework that can transform any relationship, this episode is packed with insights on purpose, empathy, and growth. It's a conversation that reminds us all to reach out, say thank you, and keep learning from the people who believed in us first.In This Episode:Why great communication is the greatest gift we can giveDiscover how personal setbacks can become powerful springboards for growthHow applied neuroscience helps us connect more deeplyLearn practical frameworks (like the Six P's) that transform everyday interactions into moments of real impactThe difference between wisdom and knowledgeSimple steps to discover your personal “why”A touching reunion story decades in the makingThis episode is sponsored by:Dignity MemorialBio:Dan Docherty, PhD, Chief Coaching Officer of Braintrust, has found a true passion for creating world-class communicators that make a positive difference. His 25 years of experience in leading various sales, marketing, MSL, and operational pharmaceutical teams, led him to a PhD degree in Management at Case Western Reserve University where his research was focused on the neuroscience of coaching, engagement, and performance in the leader-team member relationship. All of this led to a commitment to the science behind brilliant and effective leadership, and ultimately, the co-creation of NeuroCoaching®.Dr. Dan has coached thousands of leaders in management positions around the world, all while continuing to pour into the lives and futures of students in his own backyard at Miami University in Oxford, OH. Dan teaches courses in management, leadership coaching, and entrepreneurship within undergraduate, MBA, and executive education at the Farmer School of Business. From the world-renowned mentors of his doctorate program to the wisdom shared by his small-town high school music teacher, Dan knows firsthand just how formative good leadership can be to the individual, thus leading to stronger organizations, communities, and families.Website: https://dandocherty.com/LinkedIn: https://www.linkedin.com/in/dan-docherty/Instagram: https://www.instagram.com/drdandocherty/Connect with Gary: Gary's Website Follow Gary on Instagram Gary's Tiktok Gary's Facebook Watch the episodes on YouTube Advertise on the Podcast Thank you for listening. Let us know what you think about this episode. Leave us a review!

Hosts Nick and Christine welcome Dr. Michael Loete, a dynamic leader dedicated to both healthcare and community well-being. As Board President of ROCCREW, he helps guide an inspiring organization where rowing becomes a vehicle for healing, resilience, and connection. Michael also serves as Treasurer for Person Centered Housing Options Inc. (PCHO), a nonprofit providing homeless outreach, permanent supportive housing, and care management services throughout the region.From his extensive career in healthcare leadership to his community board work, Michael exemplifies how passion, service, and vision can create waves of positive change in Rochester.LinkedIn: www.linkedin.com/in/dr-michael-loete-ed-d-lah-msl-7b480a70Michael Loete has been in healthcare for over ten years. Currently he is an employee of UnitedHealthcare as a Senior ACO Network Contract Manager, and subsequently held positions at a variety of local health insurance carriers. A career highlight was as a Director of Provider Network Operations, Mike led a team that successfully and initially contracted physicians, facilities, and providers in over 30 counties in New York State to work with individuals who are intellectually and developmentally disabled so that they could receive medical care.Mike is a graduate of Roberts Wesleyan's OM and MSL programs. In the MSL program, Mike's group studied the Walt Disney Company. The group specifically and successfully defended a strategic audit and recommendation for streaming services as a partnership between the Walt Disney Company and Netflix. Mike had finished his doctorate in educational leadership through St. John Fisher in 2021, and published his dissertation on the Communication styles of senior leaders in health insurance during times of organizational change.ROCCREW Website: https://roccrew.comROCCREW Facebook: facebook.com/share/1F2XgaNvvnPCHO Facebook: facebook.com/share/1CgqMgNFrRFor More About That Sounds Terrific in the 585Check out our Website: www.thatsoundsterrific.comIf you or someone you know is doing something terrific in the 585 area and should be featured on our show, email us at thatsoundsterrific@gmail.com.Special Thanks To Our Key SupportersA huge thank you to (585) magazine for their continued support in sharing Rochester's stories. Special appreciation goes to our intern, Ashlyn Dugdale, for their behind-the-scenes work in research, writing, and promotion.

Employee voice is transforming HR practices across Indian Country, creating both opportunities and challenges for Tribal organizations. This episode, REDW National Tribal Practice Leader Wes Benally welcomes Taryn Reynolds, MSL, THRP II, and Jessica Goodfox, THRP, TMP, from REDW's Human Resource Consulting team to discuss the heightened focus on HR accountability, proper documentation practices, and the unique cultural considerations that shape Tribal workplace policies. From developing bereavement policies that honor four-day traditional burial practices to managing investigations in close-knit communities where "everyone knows everyone," Taryn and Jessica share practical insights for HR professionals navigating these complex dynamics. They also preview their upcoming presentations at the NNAHRA Conference, including executive coaching for HR practitioners and compensation clarity sessions.Whether you're a seasoned HR professional or a new manager dealing with employee relations for the first time, this conversation offers valuable guidance on documentation best practices, cultural competency, and leveraging external expertise when needed.Chapters00:00 - Introduction and Welcome02:04 - The Rise of Employee Voice in Indian Country HR07:17 - Top Three Things for New Managers10:22 - Cultural Competency Beyond Buzzwords13:21 - NNAHRA Conference Experience and Networking16:38 - What to Expect at NNAHRA 2025TakeawaysEmployee needs and investigations are increasing across Indian Country, requiring proper documentation and legal complianceHR professionals should document employee interactions immediately and avoid promising complete confidentiality during investigationsCultural competency in Tribal HR means aligning policies with traditional practices, such as four-day bereavement periods for burial ceremoniesThe NNAHRA Conference provides transformative networking opportunities and professional development for Tribal HR professionalsExternal HR consulting can help remove bias and provide objective investigation services in close-knit Tribal communitiesResourcesLearn how to design effective compensation strategies amid ongoing financial uncertainty in our latest blog, “Navigating Compensation: Creative Strategies Amid Uncertainty” | READ MOREDownload our FREE white paper, “Addressing Pay Compression: Strategies and Best Practices” | LEARN MORENNAHRA'S 29th Annual Conference - September 29 - October 1 - Pechanga Resort CasinoREDW's Human Resource Consulting team will be front and center at NNAHRA's 29th Annual Conference with presentations on executive coaching and compensation clarity, plus our popular booth featuring chair massages and great swag. Stop by to learn how REDW can support your Tribal organization's HR needs. | Connect with REDW at NNAHRAREDW Advisors and CPAs is proud to bring you the Insight in Indian Country Podcast, covering important advisory, accounting, and finance topics that impact Tribal Nations and business affairs. Thanks for listening!

On episode 526 of The Nurse Keith Show nursing and healthcare career podcast, Keith interviews Brian LeCount and Earl Dalton of Health Carousel, the organization behind Nursing Careers Week, an inspiring annual virtual event for nurses which will be held for the second time during the week of November 10th, 2025. In the course of their conversation, Keith and his guests discuss the challenges facing 21st-century nurses, the current state of the profession, the continuing evolution of healthcare technology, and how nurses can be supported in creating flexible, fulfilling, and future-ready careers. Brian LeCount is the Chief Marketing Officer at Health Carousel, where he leads multi-brand marketing efforts, digital strategy and corporate strategic planning initiatives. Brian has delivered executive-level strategic counsel, digital thinking, customer journey expertise, and activation guidance for many multi-billion dollar global brands. He has led benchmark-beating initiatives across nearly every digital channel: content, media, web, mobile, social media, experiential, eCommerce, and shopper marketing. Earl Dalton, MHA, MSL, BSN, NEA-BC, is the Chief Nursing Officer at Health Carousel and has over 30 years of acute hospital experience in various leadership roles from Adult Health to Emergency and Critical care. In addition, Dalton is an accomplished speaker, author, and innovator in the healthcare industry. Dalton has worked for several hospital systems, most notably, the Duke University Health System, consistently in the top ten for healthcare delivery in the United States and globally. Dalton is an industry thought leader and has made exceptional contributions in work culture, quality improvement, and customer experience. Connect with Earl Dalton, Brian LeCount, Health Carousel, and Nursing Careers Week: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Nursing Careers Week Health Carousel Facebook (Nursing Careers Week) Instagram (Nursing Careers Week) LinkedIn (Nursing Careers Week) LinkedIn (Earl Dalton) LinkedIn (Brian LeCount) Contact Nurse Keith about holistic career coaching to elevate your nursing and healthcare career at ⁠⁠⁠⁠⁠⁠⁠⁠NurseKeith.com⁠⁠⁠⁠⁠⁠⁠⁠. Keith also offers services as a motivational and keynote speaker and freelance nurse writer. You can always find Keith on⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠. Are you looking for a novel way to empower your career and move forward in life? Keith's wife, Shada McKenzie, is a gifted astrologer, reader of the tarot, and teacher and mentor who combines ancient and modern techniques to provide valuable insights into your motivations, aspirations, and life trajectory, and she offers listeners of The Nurse Keith Show a 10% discount on their first consultation. Contact Shada at ⁠⁠⁠⁠⁠⁠⁠⁠TheCircelandtheDot.com ⁠⁠⁠⁠⁠⁠⁠⁠or shada@thecircleandthedot.com.

Amazon KDP just rolled out a new look for the dashboard—and that's not all. They've also updated their keyword rules, and Kindlepreneur breaks it all down in plain English. Plus, PublishDrive has released a comprehensive guide to accessibility in digital publishing for 2025. Get all the latest updates and author opportunities in this week's indie publishing news roundup. Subscribe to The Self-Publishing Hub - https://TheSelfPublishingHub.com Subscribe to my email newsletter - https://DaleLinks.com/SignUp Join Channel Memberships - https://DaleLinks.com/Memberships Join Me on Discord - https://DaleLinks.com/Discord Check out my main YouTube channel - https://www.youtube.com/@DaleLRoberts My Books - https://DaleLinks.com/MyBooks Wanna tip me? Visit https://dalelroberts.gumroad.com/coffee.  Sources: KDP - https://kdp.amazon.com  Kindlepreneur: Amazon Book Keyword Rules Explained (2025 Update) - https://kindlepreneur.com/amazon-book-keyword-rules/ Accessibility in Digital Publishing 2025: Your Complete Guide to Creating Inclusive EPUBs - https://publishdrive.com/accessibility-in-digital-publishing-2025-your-complete-guide-to-creating-inclusive-epubs-2.html Spotify for Authors - https://authors.spotify.com/ Book Bounty - https://DaleLinks.com/BookBounty (affiliate link) Get Authentic Book Reviews - https://GetAuthenticBookReviews.com MSL 213 - Dale L. Roberts on Starting a Solopreneur Business, Part 2 - https://youtu.be/VtsgStWHBWk?si=G7d7vZXNcTloJmXl The Sample Chapter Podcast: YouTube For Authors: Dale L. Roberts - https://youtu.be/XNGt89X79Dc?si=HB38iw1S1huy8XgX  Busting Indie Publishing Myths with Dale Roberts - https://www.youtube.com/live/6oPXIhuzROg?si=bWx-Gm6rFx6xJPzb BookMARCon 2025 - https://bookbrush.com/bookmarcon/ AuthorNation Volunteer Survey - https://form.smartsuite.com/so8pqexh/D9a8mbe9ZM?kuid=29d26bb5-3f29-40fa-851e-11bb2f7d2ab0-1753730183&lid=11679&kref=PULKc40ysYCp Author Nation - https://DaleLinks.com/AuthorNation (affiliate link) Where noted, some outbound links financially benefit the channel through affiliate programs. I only endorse programs, products, or services I use and can stand confidently behind. These links do not affect your purchase price and greatly helps to building and growing this channel. Thanks in advance for understanding! - Dale L. Roberts

So many PAs and NPs are ready to make the transition away from clinical medicine. Whether they are burned out, looking for a change or searching for more leadership roles with a greater impact, healthcare providers are moving to nonclinical roles. My guest today, Laura Sweatman, is a PA who did just that! In today's episode, Laura explains just what exactly an MSL is and what she does on a day to day basis. Laura dives into the nitty gritty of how she made the transition into industry, including the hurdles she overcame to get her first MSL interview. She also lays out the specific skills PAs and NPs use daily in clinic that can be translated and leveraged into an MSL role. Tune in to hear the pros & cons of being an MSL and some tips & tricks on applying and interviewing. Could working in industry as an MSL be the right role for you? This episode will give you lots to contemplate as you consider making a career change. SPONSORS

For many healthcare clinicians, MSL sounds like a unicorn job. But how do you actually break into such a competitive industry? What's the day to day life like as an MSL? What do you need to know to set you apart from other applicants?Don't you wish you had a step by step guide to walk you through the process and share insider tips for success? Well that's exactly why my guest is on today's podcast episode!Dr. Samuel Dyer has 25 years of experience as an MSL and now works as the CEO of the Medical Science Liaison Society. Dr. Dyer explains exactly what an MSL is and why PAs and NPs have a decisive advantage over other applicants. Dr. Dyer also walks through what an MSL interview is really like and gives key tips on how to ace the interview process. If you're struggling with burnout, but still want to use your clinical skills, MSL could be the answer. Tune in to learn the secrets of how to break into your first role. SPONSORS

There's a new Linux phone, but it stretches the definition of "affordable". Another government is going Libre, Xlibre continues to divide, and Apple brings WSL to their platform. Nano has an update with a secret feature, the kernel may get an API, and Rocky hits 10! For tips we have Uptime Kuma and datadog for system monitoring, and a bug report from pw-cli, for something that really should work. It's fun don't miss it! And don't miss the show notes at https://bit.ly/4jJIA6x Enjoy! Host: Jonathan Bennett Co-Hosts: Ken McDonald and Rob Campbell Download or subscribe to Untitled Linux Show at https://twit.tv/shows/untitled-linux-show Want access to the ad-free video and exclusive features? Become a member of Club TWiT today! https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

Constellation returns! Below is the original description Dagan sent me for the show, but to be honest, it feels a little too bold to leave on its own and I (Dustin) am worried people are going to think their phone or computers are going insane. To respect the artistic vision, I'll leave it, but know that this episode features Dagan, Cog, Gene, and Jaffe. Enjoy! .dauqs MSL eht fo tser eht dna retsgaD ,effaJ ,eneG ,goC evoL .emoclew er'uoY .siht ekiL .gniyonna repus s'ti nehw neve ,ytilanigiro dna ssenevitnevni fo smret ni rab eht esiar syawla ot esimorp ew ,eroferehT .ylgnidrocca reviled dna xob eht edistuo kniht dluohs sretsacdop etirovaf ruoy dna ,sretsacdop etirovaf ruoy morf ytivitaerc erom tcepxe dluohs uoY .elbatpeccanu yllatot s'taht wonk ew aideM dnatS tsaL ta ereH .gniroooooooooooooooooooooooB ?soediv ebuTuoY tsom fo snoitpircsed eht daer revE 0:00:00 - Intro00:15:09 - Shigeru Miyamoto00:48:09 - Source Material01:55:56 - Early Internet Experiences Learn more about your ad choices. Visit podcastchoices.com/adchoices

Did you know you can specialize when you work in primary care? As a surgical PA, I've worked in various surgical subspecialities, but the concept of primary care subspecialities was brand new to me. My guest today, Alex Childs, shares his story of specializing in pharmacogenetics as a primary care PA.  Alex is a PA with a Doctor of Medical Science degree working in family medicine in Utah. Alex's doctorate research focused on implementing genetic testing in primary care. In practice, he has done this with hereditary cancer risk testing and pharmacogenetic testing. In today's episode, Alex shares what he loves about working in primary care and gives actionable tips on how to thrive as a primary care provider. Alex also explained what the heck pharmacogenetics is and how he uses it to provide high quality care and early interventions with his patients. He also describes how he began working as an medical science liaison (MSL) in industry while still working as a family medicine PA. I think my favorite part of our discussion was talking about how every medical provider can get their joy back when it comes to practicing medicine. Press play to learn how to find your passion for medicine again if you've been feeling burned out. SPONSORSAAPA Job Source: aapa.org/pajobsourceFreed AI [DISCOUNT CODE: PA50] https://www.getfreed.aiREFERENCES1. Fred HL, Scheid MS. Physician burnout: causes, consequences, and (?) cures. Tex Heart Inst J. 2018;45(4):198-202. doi:10.14503/THIJ-18-68422. Samuel D. Who Are Medical Science Liaisons? THE MSL. March 27, 2020. Accessed February 3, 2025. https://themsljournal.com/article/who-are-medical-science-liaisons/3. Carrau D, Janis JE. Physician burnout: solutions for individuals and organizations. Plast Reconstr Surg Glob Open. 2021;9(2):e3418. doi:10.1097/GOX.0000000000003418CONNECT WITH ALEXLinkedIn: https://www.linkedin.com/in/alex-childs-565b4884COACHING⁠1-ON-1 NEGOTIATION CONSULT https://calendly.com/the-pa-is-in/negotiate⁠ ⁠FREE 30-MINUTE COACHING CONSULT⁠ ⁠https://calendly.com/the-pa-is-in/gen-call⁠  LINKS⁠TRACY ON INSTAGRAM https://www.instagram.com/mrstracybingaman/⁠⁠TRACY ON LINKEDIN https://www.linkedin.com/in/tracybingaman/⁠SUPPORT THIS PODCAST: https://podcasters.spotify.com/pod/show/thepaisin/supportKeywords: Pharmacogenetic testing, Hereditary cancer risk testing, PA career growth, Primary care subspecialties, Doctor of Medical Science PA, Physician assistant career paths, PA industry jobs, PA professional development, Genetic testing in medicine, How to thrive as a primary care PA. Secondary keywords: Pharmacogenetic testing, Hereditary cancer risk testing, PA career growth, Primary care subspecialties, Doctor of Medical Science PA, Physician assistant career paths, PA industry jobs, PA professional development, Genetic testing in medicine, How to thrive as a primary care PALong-tail keywords: Can physician associates specialize in primary care?, How to implement genetic testing in primary care, Pharmacogenetics for primary care providers, What is a medical science liaison (MSL) in healthcare?, Career options for physician associates outside clinical practice, How PAs can work in both industry and clinical practice, Overcoming burnout as a primary care provider

In this episode, we interview Morgan Anderson, PharmD, BCIDP, a graduate of the RFUMS College of Pharmacy, about her career path from a pharmacy resident, emergency medicine specialist, infectious diseases specialist, and now a medical sciences liaison. The views, thoughts, and opinions expressed in this podcast are solely Dr. Anderson's own and do not necessarily reflect the views, positions, or policies of her employer. This podcast is conducted in a personal capacity, and any reference to her professional background is for context only. Key Concepts Having a wide breadth of skills and making yourself marketable is important when transitioning between jobs or career paths. Skills like communication and teamwork can be improved and are applicable to a wide variety of careers within pharmacy. Medical Science Liaisons (MSLs) are a common role for pharmacists in the pharmaceutical industry. MSLs are field-based roles within the medical affairs department of the company. MSLs are medical and scientific experts who build collaborative relationships with key thought leaders, facilitate exchange of scientific information and insights, and serve as a conduit between these thought leaders and other areas of the company. Two common career paths to pharmacists becoming an MSL are via a fellowship program or after years in clinical practice. A fellowship program provides a more structured approach, including mentoring and networking, with access to a variety of areas of the company outside of medical affairs. A pathway after clinical practice is more self-directed with less structure, but provides pharmacists with a strong clinical background that can be helpful in an MSL role. Being a scientific communicator, possessing strong emotional intelligence, and being adaptable are critical soft skills that are essential for success in an MSL role. These soft skills can be improved with practice! References https://www.industrypharmacist.org/