Podcasts about periodic

Last 4 days before regular tickets sell out at AI Engineer World's Fair - this is the single biggest gathering of AI Engineers, Founders, Leaders, and Researchers in the world. Attendees get >$5000 worth of sponsor credits and talk tracks are looking FANTASTIC. Join us!The AI scaling debate always focuses on the question of “how do we get more GPUs?” but the better question may be: how do we make the most of ones we already have.The fact that a frontier lab like xAI could be running at sub-10% MFU (Model FLOPs Utilization) is just a hint at what the real problem may be.For context, older frontier-scale training runs were already much higher than 10%. GPT-3 was around 21% MFU. Gopher was around 32%. Megatron-Turing NLG was around 30%. PaLM reached around 46%. And our guest Anjney says best-in-class MFU today is closer to 60–70%.It's not necessarily that xAI is uniquely incompetent (it's clear they have talented folks) but rather the priorities may be flipped in the GPU arms race.While GPU access is a bottleneck, simply increasing CapEx won't automatically translate to better models as frontier AI is increasingly a systems problem: scheduling, utilization, networking, kernels, frameworks, data pipelines, parallelism, cluster reliability, and the thousand small decisions that determine whether your theoretical FLOPs become real training progress.From building Discord's developer platform and backing frontier AI companies like Anthropic, Mistral, Black Forest Labs, and Periodic Labs to now building AMP's independent compute grid, Anjney Midha has spent years close to the real bottlenecks of AI scaling. In this episode, Anjney joins swyx at Periodic Labs to unpack why the AI race is not just about buying more GPUs, why 95% utilization would have been considered an outage at Google, and why the next era of AI infrastructure has to be more aligned, more efficient, and more responsible.We go deep on AMP's vision for a compute grid that makes FLOPs flow like megawatts, the difference between full-stack AI labs and horizontal pooling, why AI data centers need community buy-in, and how compute markets could evolve into something closer to an independent system operator. Anjney also explains why DeepMind's unpublished research points to a market failure, why end-of-life prediction remains one of the most important AI applications he has thought about for fourteen years, and why “output maxing” may become a new discipline for frontier systems.We also discuss Anthropic's culture, why “luck favors the prepared mind” in coding models, how Claude cracked coding, why too much capital too early can make AI labs fragile, what Periodic Labs is trying to do with science and superconductors, why great researchers can become great CEOs, and why Silicon Valley is both deeply missionary and deeply mercenary.We discuss:* Why 95% utilization was considered an outage at Google* Why AI infrastructure waste compounds at frontier-lab scale* Why “move fast and break things” does not work for AI data centers* How data center backlash, power grids, and community incentives shape AI scaling* AMP's vision for making FLOPs flow like megawatts* Why compute needs an independent system operator* How interruptible demand and dynamic prioritization worked inside Google* Why DeepMind research hoarding creates negative externalities* AMP's 1.2GW base-load ambition and the need for 6GW of spike capacity* Why end-of-life prediction could become one of AI's most important healthcare applications* Frontier Systems, output maxing, and full-stack alignment* Why APIs and abstraction layers become lossy as organizations scale* Superconductors, standards, and the dream of lossless systems* SF Compute, open protocols, and the future of compute marketplaces* Why non-NVIDIA chips can still benefit from NVIDIA's reference architecture* Trust boundaries and why chip startups need visibility into future model architectures* Why VCs often underestimate researchers as CEOs* Scientists as star athletes of the mind* Why great CEOs need to be confrontational up and down the stack* Why leading the frontier matters more than “winning”* How Anthropic cracked coding* Why culture is fragile, not a permanent moat* Why hardship was a feature, not a bug, for Anthropic* Why Anthropic's P0 was coding from day one* Periodic Labs, physics as the constraint, and technical reality* Silicon Valley mercenaries, missionary teams, and what happens after a breakthroughAnjney Midha* LinkedIn: https://www.linkedin.com/in/anjney* X: https://x.com/AnjneyMidhaAMP PBC* Website: https://amppublic.com/* X: https://x.com/amppublicTimestamps00:00:00 Introduction00:00:09 Why AI Compute Is Being Wasted00:03:17 Responsible Infrastructure and Data Center Backlash00:06:07 AMP Grid: Making FLOPs Flow Like Megawatts00:12:41 Foundry, Frontier Labs, and Research Hoarding00:14:42 Gigawatt-Scale Compute and End-of-Life Prediction00:24:08 Frontier Systems, Output Maxing, and Alignment00:27:38 Compute Markets, SF Compute, and Non-NVIDIA Chips00:32:57 Trust Boundaries, Co-Design, and Researcher CEOs00:38:17 AI Coachella and First-Principles Thinking00:42:43 Leading vs Winning in Frontier AI00:45:54 How Anthropic Cracked Coding00:48:25 Culture, Hardship, and Anthropic's P000:54:03 Periodic Labs, Physics, and Silicon Valley Mercenaries00:56:26 Rishi Valley, Singapore, and Money as a Measure00:58:47 Closing ThoughtsTranscriptIntroduction: Anjney Midha, AMP, and Compute WasteSwyx [00:00:00]: We're in Periodic Labs with Anjney Midha, CEO, founder of AMP. Welcome.Compute Utilization: Node Allocation, MFU, and AlignmentAnjney [00:00:09]: Thanks for having me. At Google, there are two types of utilization usually, right? That you're measuring in these clusters. One is node allocation, and then the other's MFU. Node utilization is usually like what percentage of cards in the data center are just, used, and that, if it's not at, 95%-Swyx [00:00:29]: There is no excuseAnjney [00:00:29]: There's no excuse, right? I think 95% at Google, which is where my co-founder, Seb, came from, he built the Borg, PBorg/GQM scheduler at Google, and there I think 95% was considered an outage, so 96% node utilization is, should be standard. And most single-tenant clusters are not running at that. So that's one. And then MFU should be, I would say the best in class today is somewhere between 60 and 70%. I think this is a leadership question, right? Fundamentally it's an alignment question, which is are the people who are funding the cluster and then deploying the cluster actually aligned? And sometimes theoretically they are, but in practice the number of people in the chain, the supply chain between, the capital and all the way to whoever's managing the cluster and then whoever's measuring what the output is, are just so many, degrees of separation away that, the, The Have you ever heard the radian metaphor, which is at the beginning of an arc, if you have two arcs that are two lines that are just off by a few degrees, that-Swyx [00:01:33]: It spreads outAnjney [00:01:34]: It spreads out, right? Or at scale. And I think what's happening is a lot of cluster implementations and infrastructure, a lot of frontier labs and other teams, that's what's happening, is they're, they initialize the plan, which is kind of like North Star with a team that wants to do good, but then they're, required to scale so fast instead of iteratively that the wastage just compounds really fast at scale. And so I think we know the answer, which is just do iterative bring ups. If you spend time with people who've been in the semiconductor industry or the DSN industry for a long time, this is not new, and I don't think AI should be an excuse. Sure. Something What is new? Okay. We have a lot of new capabilities, but that doesn't mean just abandon common sense. Common sense should always be in fashion. ? AI scaling doesn't change the in fact, if anything, AI scaling should be putting a premium on the value of common sense and infrastructure because the margin of error now is so much lower and the costs of wastage are so much higher. And the cost of wastage, by the way, is not just economic. I'm, obviously I'm, I'm an investor, or I'm an investor by background. Over the last few years now we're running an AI infrastructure business called, AMP. And I think that it's okay to say this time is different on the capabilities front. We are genuinely getting capabilities at, of the, of a kind we haven't had before. That doesn't give you an excuse to say this time is different for everything, especially infrastructure. So look, I love the hacker mindset and the hustler mindset. Now, that's great for the startup mindset, but you remember this moment where Zuck went from saying, “Move fast, break things” to, move-Responsible Infrastructure and Data Center BacklashSwyx [00:03:10]: Fast and stable infrastructureAnjney [00:03:11]: Move fast with stable infrastructure. I think now we need to move fast with, responsible infrastructure. People are going to ask where the impact is. There was a really In our class yesterday, Scott Nolan, who's the founder of General Matter, came by at Stanford to speak about energy bottlenecks. And he had a phenomenal idea. He said, “if you look at the marginal unit economics of compute per hour,” he goes, “let's call it, $4 an hour. If you're having to bring up a new data center in a new community, why not just say we're going to charge 4.50 an hour, and that marginal impact or that marginal increase, we just literally take that and give it to the local community as cash?” I can tell you as a customer of that compute, I would love that. I'd be happy to pay an additional 50 cents per hour at scale.Swyx [00:03:57]: Wow. Yeah.Anjney [00:03:58]: Because if that means the public benefit is so clear to the communities that the data centers are coming up in, I'm going to feel like that compute is much more reliable. Up to 20% of all data centers this year in the US, my understanding is are at risk.Swyx [00:04:13]: Of community backlash?Anjney [00:04:14]: Correct. Of not getting the community support they need to get brought up.Swyx [00:04:19]: Wow. That's a huge number.Anjney [00:04:20]: Yeah. Now, we, I think we should dig into what that number is. I think it's a little bit of overstated. These things can get over-reported, but it-Swyx [00:04:27]: They don't just care about jobs. They care about all the other stuff around it, right? They care about power grid, they care about environments-Anjney [00:04:33]: Power grid, permitting, and so on. And imagine I think if you said there's a new AI deal. If we're bringing up a data center in your community, we're actually going to reduce the cost of your electricity bill. Okay, now we're talking. Right? The community's going, “Okay. Now this is a deal. I feel like a partner in this.” Right now that's not happening. There will be audits, there will be investigations, and when the, when the regulators come, I don't know when it's going to be, the folks who are moving fast and breaking things in the name of AI progress better be prepared. That's certainly not how we're procuring compute. Or we're, we're trying as much as we can to work with partners who have long-term track records. Many of whom, by the way, are not, AI providers. I think this whole idea of neoclouds being somehow this new category is a lot of marketing speak. There are really good, reliable, trusted data center providers in America who've been around 20 plus years. I love those folks. They know how to Sure. Are they sponsoring happy hours at NeurIPS? No. Are they legibly listed in Build? No. Are they hanging out in my, in, situational awareness parties? No. But they're adults. I trust them.Swyx [00:05:44]: They can run LAN. They can run power.Anjney [00:05:45]: They can run LAN, power, and shell. They have credit histories. We sit down, we have a conversations. Many of them live in Silicon Valley. They've, they've had to deal with the boom and bust cycles of the internet, and I love those folks. They are stable infrastructure partners and thinkers. And I think there's a lot of short-term thinking going on in the compute layer, and it's going to catch up to us. It's not going to be good.AMP Grid: Making FLOPs Flow Like MegawattsSwyx [00:06:07]: You talk about aligning incentives, and, I would think that aligning incentives means you have the full stack in one company, which is xAI and OpenAI, right? So you as a standalone infrastructure layer, why are you somehow more aligned to your portfolio companies than people who just own the whole thing?Anjney [00:06:28]: In systems design, right, there's, there's two regimes of, architecture, right? You have integration, and then you have pooling and utilization, right? So the Or rather, the way to increase utilization often is you can do systems integration where you collapse a lot of process into one node, or you can pull out a process from a node and share that amongst various That resource amongst several different nodes. And so we see the AMP grid, which is, the, what, the system we're building here, which is basically a compute grid. We're trying to do for compute what the electric grid-Swyx [00:07:02]: PowerAnjney [00:07:02]: Yeah, what the power grid did for electricity. It-- this is a pooling and utilization layer across clouds, And so we're actually the opposite of a full stack integration like approach.Swyx [00:07:12]: Super horizontal.Anjney [00:07:13]: Where it's much more horizontal and it's, it's multi-cloud, it's multi-silicon. The goal is to try to make FLOPs flow like megawatts, and that is very hard to do today for many reasons. There's stranded pools of compute all over the place and there's no fungibility. And so right now we do it at the level of scheduling, and we often do it at the economic layer. But as we start to announce what we're working on, it's extraordinary like how many folks are coming out of the woodworks and saying, “Hey, I'm actually working on a way to make compute fungible at this part of the stack and that part of the stack.” And as a grid, we'd like all of these folks to participate on the grid. There's, people often ask me, “Andra, are you a new cloud?” And I go, “No, actually neoclouds are suppliers.” sometimes they'll ask, “Are you a venture capital firm?” I go, “No, actually they are, they are demand like sort of off-takers of the grid.” We see ourselves as what's called an independent system operator. So if you study the history of the electric grid, once it became legible to a lot of factories and industrial sort of participants that, hey, actually it turns out pooling is a good idea. We should pool our generators instead of all having a generator running at half capacity in our backyard. There was a need for an independent entity who could coordinate all these parties. Transmission line, power generation, facilities, transmission lines, factories, and that neutral coordination mechanism is very critical. In order-- If you study like the history of grids, the most enduring ones were those that never owned their own assets. They were ones that had, or often started with long-term anchors who are uncorrelated sources of demand, a steel factory, a shoe mill or whatever in a particular town who weren't competitive, where the steel factory want to spike up at night, the shoe mill wanted to spike up during the day. So then you pool and you share, right? So each of you is guaranteed some base load, but then you kind of schedule your spikes to drive a peak utilization across the town. The gold standard, so to speak, historically, has been these utility companies like PJM Interconnect in the northeast of America, where they, over many years became this what's called an ISO, an independent system operator of the grid. So that's how we see ourselves. Economically, that's what we are. From a technical perspective, we started at the scheduling layer because Seb and Mihai, who, run engineering here, built that at-Swyx [00:09:28]: Did your schedulingAnjney [00:09:28]: They did that at Google. And, -Swyx [00:09:32]: And you have infra shops from Discord as well.Anjney [00:09:35]: I have some.Swyx [00:09:35]: I don't know, I don't know if Discord is like the primary identity, but what-whatever, I'm just kind of-Anjney [00:09:39]: No, D-Discord was-Swyx [00:09:40]: Choosing a well-known name.Anjney [00:09:42]: Well, I So I was running the developer platform there. The internal infrastructure I was not responsible for. That was actually a guy by the name of Mark Smith, who was extraordinary. And yes, Discord did pool So Discord is actually a counter example. I had the chance to learn a lot about fully, full stack infra there because-Swyx [00:09:56]: It's the same thing, yeahAnjney [00:09:57]: It's the, it's the other architecture which is, Discord built its own WebRTC vo-voice and video infra. So like Discord did not use-Swyx [00:10:08]: For the calls, yeah.Anjney [00:10:09]: Yeah, did not For communication, Discord did not use third party infra. It was all built in-house. And then the way you maximize utilization was you pool demand from the world's 200 million plus monthly active gamers, right? And so that's, that's how those stacks were constructed. Again, in systems design, the two concepts that keep coming up over and over again are abstraction and composition, right? And-Swyx [00:10:31]: Bundling and unbundlingAnjney [00:10:33]: Bundling and unbundling, abstraction, composition, like verticalization and-Swyx [00:10:36]: HorizontalAnjney [00:10:36]: Horizontalization. So in that sense, AMP is an independent system operator of the grid. We pool demand, we pool supply from a number of partners we trust At about 1.3 gigawatt scale over four years. And then we pool demand from some of the world's best, research labs and so on. We're sitting at one, periodic labs who need extraordinary long-term demand. And the idea is that, each of them is guaranteed base load on the grid, but they can spike up and down flexibly on, for compute, with much shorter timelines as needed. That was roughly the design of the program I came up with at a16z called Oxygen. The same-- That was the same design of the GQM, BorgX, Borg GQM implementation at Google that Mihai and Seb had built. Which was that how do you allow, teams inside of Google, on the internal infrastructure to be guaranteed capacity, for their base workloads? But when they need to spike up on research, how could they ensure that was sufficiently there? And of course, the big innovation that was not discovered, but kind of implemented in the space, this infra space maybe three, four years ago at Google was the idea of interruptible demand, right? Where you just queue up a bunch of jobs and through this like sort of credit system, there can be a bidding mechanism.Swyx [00:11:53]: Like priorities.Anjney [00:11:54]: It's a dynamic prioritization Basically. And jobs can get interrupted based on somebody else who's saying, “what? I have 10 tokens, 10 credits I want to spend on this job.” Another like team lead, research lead is “Genie 3 or whatever is only worth five, credits, and NanoBanana2 is worth 10 credits,” and so the NanoBanana job gets priority. That's a, that's a made up example.Swyx [00:12:15]: It's very real. Brain Marketplace was real. And, we've, we've covered this on the pod with David Luan, who was-Anjney [00:12:20]: Oh, great. OkaySwyx [00:12:20]: Was there. And the criticism is that, well, actually sometimes you need central command to go all in on a thing. And actually sometimes capitalism via credits doesn't work. Not, this is not a criticism of AMP. I'm just saying, this is a thing that has been tried, internally within Google, and it led to Google missing GPT.Foundry, Frontier Labs, and Research HoardingAnjney [00:12:41]: Like, we structured ourself essentially very similarly to Google. We are structured as a holdings company. So, Alphabet holdings is Alphabet holdings, and then they've got these subsidiaries called Google and-Swyx [00:12:51]: Other betsAnjney [00:12:52]: Other bets and so on. We've got, AMP holdings, and we've got our infrastructure business, and then we've got a capital business called Foundry that incubates new frontier AI labs or invests in them as venture capital, like Periodic. We put a few hundred million dollars into Anthropic from our fund earlier this year. So wherever we feel like teams are making progress, especially researchers and so on who've pushed the frontier inside of existing labs like DeepMind, I find, there comes a point where they feel misaligned with the dictatorship of Alphabet holdings. And at that point, sometimes the dictatorship doesn't want them anymore. And they're “Thank you. You've done your job here. You've kind of helped us through the zero to one phase, and for whatever reason, we're going to deprioritize your amazing, omni model or whatever it is, and instead we're going to prioritize coding.” And, I think that's a tragedy, but I get it. They're Sergey and team are running their own business there. But that doesn't mean we the rest of us should sit around waiting for that progress to get unlocked for the rest of the world and humanity. If you think about how much extraordinary research has happened inside of DeepMind over the last 10 years, I, Demis and Sergey and those guys did such a great job. But at the end of the day, so much of that has never seen the light of day?Swyx [00:14:00]: Or they're like papers only, but they never actually shipped it to production or-Anjney [00:14:03]: What's worse is the paper is actually not even being published anymore ‘cause there's a six-month embargo inside of DeepMind, right? We've heard about this where a paper comes out, and then I think there's a six-month embargo window where if anybody on the business team says, “This could be interesting” It's embargoed for life.Swyx [00:14:18]: Exactly. So the stuff that gets published is the stuff that's not good enough.Anjney [00:14:21]: There's an adverse selection problem, basically. Yeah. At this point-Swyx [00:14:25]: It's, it's a common complaint at NeurIPS, by the way, that's “Well, why would I look at the papers that are the trash of GDM?”Anjney [00:14:31]: Again, I think it's a tragedy. I get it. They're running their business, but the rest of the I think there's negative externalities of research being hoarded, and so that'there's a market failure. And somebody needs to unlock that research, and we can't do it on our own. We only have 1.2 gigawatts of compute. That's nothing. That's about $40 billion of cloud spend. We're going to need a lot-Gigawatt-Scale Compute and End-of-Life PredictionSwyx [00:14:51]: By the way, is that's a new number. I haven't, haven't come across that gigawatt number. That's huge.Anjney [00:14:56]: Yeah. And to be clear, we haven't secured all of it. That's how much demand we have started to secure. I think publicly we haven't actually confirmed how much we have for this year. In order-Swyx [00:15:04]: Where do you want to get to?Anjney [00:15:06]: I think the steady state would be that we have a base load pool Of 1.2 gigawatts at all times Of base load capacity. For spike capacity, right now my estimate is we need roughly six gigawatts over the next four years for all our teams to feel like they were able to keep moving the frontier, whatever they're working on, whether it's, like superconductor discovery over here. There's a new investment we're working on right now, which is in the end of life prediction space in healthcare. It's extraordinary how much you can, you can give this was actually my graduate school work. I went to grad school for bioinformatics at Stanford Med. And I know we-Swyx [00:15:40]: Econ, MCS, bio.Anjney [00:15:41]: So my-- I was this really weird cat where, I was never satisfied with my major options. So at one point I was an econ major, then I was a CS major, then I was a MCS major called mathematical computational science, and they decided they were going to end that major. So I took all that coursework, and I applied it to grad school, my graduate degree in bioinformatics, which was the master's program, and then I thought I was going to do a PhD. I never ended up doing it. I dropped out and went to work at Kleiner. But I was lucky enough to apprentice with this professor at, Stanford Med. His name is Nigam Shah, and he was working on end of life prediction. Stanford is one of the only research facilities in America that has a longitudinal patient data set that's larger at scale. I think it's at least 12 million patient lives. The only larger data set is at the VA, the Veterans Affairs, of America. And to do research, like do any deep learning and so on that data set, it was called the STRIDE data set at that time, you had to be a Stanford Med School affiliate, which is why I went and enrolled in the bioinformatics department. End of deep learning was early. Nigam Shah had the visibility-- the vision to see that, you could do end of life prediction to help palliative care. In America, the, over 30% of all Medicare, Medicaid spend, at least at that time, was spent on end of life care. And what's we grew up in Asia, so we all-- Yeah, at least I won't speak for you, but I have A very different relationship with death than I find folks who grew up in America do. In America, spiritually and culturally, especially in Western societies where Christianity, the Christian tradition sort of frames death as this terminal point, there's often a judgment day and so on. The way we view death is with a finality. In Indian culture, in Hindu culture, death is one-Swyx [00:17:35]: Also, he's Buddhist as well.Anjney [00:17:36]: You're Buddhist, yeah. So it's one, it's one step in a journey of many lives, right? And so, I grew up in this city called Chennai in the south of India, and when people die, you dance on the street. There's like a procession where your body is carried to be cremated and your family, like celebrates and there's drums and so on. It's this huge thing. And, It's because the idea is that you're going to be reincarnated. You've been liberated from the responsibilities of this life, and now you're onto your next. It's a new It's like going off to a new college or whatever, right? And so it was so alien to me when I got here as an undergrad- That the medical system works backwards from that assumption that we have to view death as this terminal thing and delay it, postpone it's a bad thing. And so at the time, clinical decision support in the United States was this very primitive field. Even to this day, physicians in the United States often will tell you when you have a terminal disease, this is your, we've diagnosed you, which is great. Our ability to diagnose you is extraordinary. You have somewhere between six months to six years to live. What do you do with that information? The error bars are so high that then you In times of uncertainty, we default to culture, and when the culture is let's-- this is a bad thing, I've got to prolong my life, then you start doing things like And just to, just sort of from a systems perspective, what's going on there is Physicians often feel like they need to provide such high error bars because there's always some uncertainty in end of life diagnosis, and if you provide the wrong Diagnosis or recommendation to your patient, you can be sued for medical malpractice. And then your license can be taken away. It can be catastrophic for your career. In contrast, if in countries where that's not the case, what you often observe is that patients, physicians are quite prescriptive with their recommendation. They say, “Hey, this is your condition. The literature says that you probably have this much time on Earth left. My expert opinion is that you are an outlier or whatever.” And they try to be more prescriptive, and that empowers a patient, right? ‘Cause then a patient can say, “I trust my doctor. They said on average, I have six months to live, but if I do these things, I may have a shot because of my particular predispositions or my genetic history or whatever.” And that empowers you to go about your life in a actually more scientific way than leaning on religion, culture, spirituality, and so on. In contrast, here, because of that medical malpractice sort of thing looming over your head, a physician never gives you a clear recommendation. So instead you say, “Okay, Doc, well, let's try it all.” And then you start a whole regime of drugs and therapies, and then you often spend weeks and weeks in the hospital, and that deteriorates your quality of life. And when that deteriorates your quality of life, you instead of spending your last few days doing the things you love with your family, you're spending it on a hospital bed. And that ends up being thirty percent of Medicare and Medicaid. So it's worse for the patients. The doctors feel terrible. The American taxpayer is paying a huge amount of money. And so this is why Nigam Shah, who was this professor at Stanford, said, “Anjney, if there's “ I kind of sat down with him. I was this young, I'd, I was twenty-one, and I was “I want to work on a big problem.” He's “The big problem is end of life care.” And so we tried to do deep learning to say, to-- So we started trying to run deep learning on these tried patient data sets to say, “Could you have an AI system make a recommendation that is orders of magnitude more precise about how much time you have left once you've been diagnosed with a terminal condition than a human?” And then if we can get that precision to be high enough, then you can empower the patient. And it turns out the tech works. Like it's-- Once you get the data set, like RL works. Honestly, even regression models work. You don't need to get that fancy. At the time, we were just trying, doing like very simple neural nets.Swyx [00:21:54]: Simple solutions, yeah.Anjney [00:21:54]: Today, what we can do with RL is extraordinary. The problem remains then and now is regulatory, because you actually can't shift the burden of the wrong clinical diagnoses from the physician to the AI system. And so at that time, I got quite disillusioned ten years ago for, twelve years ago where, ‘cause I felt I just didn't have the resources to influence regulation. Today, I'm very lucky. I'm in a different place. I've, I'm a lot older, and so I've been spending a lot of time on my next incubation, which is how can we unlock the, patient empowerment by training AI models to do end of life prediction much, with much more precision and ac-Swyx [00:22:37]: Oh, wow. You're still focused on this the whole time.Anjney [00:22:40]: The-- I haven't been able to get, this out of my mind a single day for the last fourteen years. This is the hill I want, I would like to die on. There's two, I would say. What? I actually, I'd prefer not to die.Swyx [00:22:51]: Yeah, exactly.Anjney [00:22:52]: But I think two bipartisan issues, I think two issues that should be bipartisan in America are how do we empower patients to make the right clinical decisions at the end of their life, such that we're reducing the taxpayer burden with science? It's just good old science, and AI can help here. And the second is, net positive data centers, ‘cause I think that's the biggest critical bottleneck on training and good enough AI models to help people at the end of their life. So there's sort of two sides of the, of the same scaling bottleneck curve, but those two, we formed AMP as a public benefit corporation. My wife and I, who you've met, you've met Viv. Her passion is education. Her family is a long line of educators and so on, and, of physicists. And so this class is my attempt to stop being the black sheep of the family and be a, an educator. But if I'm not educating, the thing I would be doing is working, on these two problems, whether on the political spectrum or as a researcher back at, in some lab. And my hope is if anyone's listening to this podcast, if they're passionate about either of those two topics, I'd love to hear from them. We'll, we'll we can share the contact in the show notes, but, we're looking for people to join both of those missions on the, on the political side as well as on the medical side, on the research side.Frontier Systems, Output Maxing, and AlignmentSwyx [00:24:08]: You said, this is a discipline that you want to form. You call it's called variously called Frontier System. It's variously called One Person Frontier Lab. What is the ideal name or shape of this? Like the, what is the mission?Anjney [00:24:24]: Of the class?Swyx [00:24:26]: Of the discipline that you're, exploring, right? I The class is called Frontier Systems. But like for me, maybe one phrase is you're, you're just anti-waste, right? Which is wasting GPUs, wasting in human and Medicare. But is there, is there a broader theme that I'm, that maybe you can encapsulate more succinctly?Anjney [00:24:45]: Yeah. The, from an engineering perspective, it's very simple. It's output maxing. It's the, it's the department of output maxing.Swyx [00:24:51]: Making the most of what we have.Anjney [00:24:52]: Exactly. I'm a huge believer in optimal outcomes. I think both in America and other countries, we are losing our appreciation for nuance, and this is the thing of And AI is the same case, right? Oh, the bitter lesson holds. Okay, fine. But that doesn't mean you just like throw 500 GB300, 500,000 GB300s at your suboptimal model scaling and you waste a bunch of compute. It also doesn't mean that, the most optimal is to have like 50 different architectures where there isn't enough standardization. One of the reasons Anthropic has had extraordinary sort of velocity is ‘cause they picked the transform architecture and said, “This is simple. Let's double down on it,” right? And now luckily there's enough investment going to the space that we can afford other architectures, but at the time, investment was just too fragmented into other architectures, so that arguably unlocked scaling. So I think there's a philosophy. I think we all owe it to ourselves to do output maxing with a new capability called AI on a global level. I think if I was starting a new department at Stanford, depending on how fuzzy or technical I wanted to be, I'd probably call it the Department of Alignment. Like-Swyx [00:25:59]: It's an overloaded termAnjney [00:26:01]: But it is, But alignment really Is a hard problem. And I think when you unlock it, full stack alignment is super hard in any organization and in any system. Like in a, in a venture capital firm, if you can have full stack alignment between your limited partners and your, the founders who are creating the value and ultimately the public that owns the IPO stock, that is a gift that keeps giving. And when you study the history of these systems, when they start off, they usually start out small scale where the feedback loop is actually so tight that there's alignment. And then the more you try to scale, the more division of labor happens, the more specialization happens, and at each step you add abstractions. And wherever there's an API interface, there's like loss. There's communication loss. And so I think a really cool thing would be for us to figure out is there a way for us to have our cake and eat it too as an engineering discipline? Is there a way to actually scale up and scale out Without losing any alignment, without lossy transmission?Swyx [00:27:01]: You mean standards?Anjney [00:27:02]: So standards is one way. The other way is you just have net new capabilities. So like what we're trying to do here is discover new superconductors. A room temperature superconductor would be a lossless transmission mechanism for energy. We would have flying cars. We are right within a few years of having a new room temperature superconductor. So I think those are the two. You either have to standardize On protocols or API specs that allow lossless communication, or you can come up with a whole new capability that unlocks so much abundance, the standardization doesn't matter ‘cause you just unlock net new capacity. This, the, so this is what I spend my days thinking about these days.Compute Markets, SF Compute, and Non-NVIDIA ChipsSwyx [00:27:38]: No, I think every infra person at, who wants scale and wants to output max does eventually end up thinking about this. We don't have time to go into it, but we have done an episode with SF Compute-Anjney [00:27:50]: Oh, coolSwyx [00:27:50]: That is trying to standardize The futures contract for compute. I don't, I don't know how that's going by the way, but like at some point this will be public.Anjney [00:27:57]: Oh, I think Evan is awesome and SF Compute is the kind of effort that I hope we can accelerate because what often happens is these exchanges are very hard to get, they, it's hard to bootstrap them, right? Because they often require-- There's many inefficiencies between parties. There's trust boundary inefficiencies in infrastructure because you don't trust, one part of the stack doesn't trust another part of the stack to give them visibility. There's capital markets inefficiencies, there's operational efficiencies. So if you can inject like a single shock to the system of a ton of compute demand or supply, then you can accelerate, these new flywheels. And so my hope is one day, or soon, if SF Compute needs extra like has excess capacity, they just hook it up to the grid and they get flooded with demand from us. And on the other side, if they have a ton of demand but they don't have supply, they just again hook up to the grid and it's a two-way protocol where they can just hook up to our capacity. And I don't think we're too far from that. Today our working implementation of it is mostly through a group of labs, universities, and a few sort of trusted parties who are, who all feel like they're in alignment to borrow an over sort of used word. But our hope is to just have it be an open protocol that anyone can hook up to on-Swyx [00:29:20]: Hook up for demand or hook up for supply? In primarily demand, it sounds like. Like you-Anjney [00:29:25]: No, bothSwyx [00:29:26]: You would want to offer demand.Anjney [00:29:27]: Both. Yeah. Unfortunately, what's happened in the last six weeks is, we thought we'd have a bunch of excess capacity by the end of this year. It's all gone.Swyx [00:29:37]: It's exploding.Anjney [00:29:38]: It, yeah. It's all gone. And so I have, my text messages are full of friends, we know many of these people, these are founders who've raised billions of dollars in San Francisco going, “Oh, any chance you have like 50 nodes in the next few weeks?”Swyx [00:29:51]: What is the scope for, non-Nvidia, right? You have Lisa Su coming and, Rainer Pope as well. And so There is a lot of demand for, more performance Alternative architectures and all that. At the same time, this hurts your standardization.Anjney [00:30:11]: I don't think so. So actually Rainer's a great example, right? Rainer is a CEO and founder of, MatX. I actually had him by for office hours in the class earlier today, and there was an insight he brought up that I hadn't considered before, which is when they decided to pick the standard For their data center, they picked the NVIDIA reference architecture. So the MatX chips Just plug in to any site that has an NVIDIA bring up planned. And, the-Swyx [00:30:42]: It's just software then. It's, it's not the-Anjney [00:30:44]: A-Swyx [00:30:44]: Hardware.Anjney [00:30:46]: Well, from an input and IO perspective It's the same footprint as an NVIDIA rack.Swyx [00:30:52]: That makes sense.Anjney [00:30:53]: Where they have done, innovated a bunch from what I can tell is on systems co-design. Which is where a lot of the gains are to be had. And so he picked He was “Anjney, we, there's just so much work to do when you're building a new chip company.”Swyx [00:31:08]: Can't fight every front.Anjney [00:31:08]: You just can't fight on every front. So my question to him was, “Well, you're working on this new chip. Their tape-out is next year. What, who are you going to partner with to host the chips?” And he said, “Whoever will host them. That's just not, that's not my focus.” And I said, “But how did you “ you decided back to our earlier systems design question, he decided that, he didn't want to be a full, fully integrated chip provider. The bottleneck they're focused on is the logic die, and they, he feels they can crank out a ton of performance gains through co-design there. But then that means you delegate, to our question earlier, it, you he's the data center provider is a different part of the stack, and so then he's dependent on that part of the ecosystem to host his chips to get the performance gains to the customer. So now you have another abstraction, and you might have loss. So I asked him, “How do you prevent loss?” And back to your point, he said, “I just picked the NVIDIA standard ‘cause I didn't want to Like I wanted to piggyback off of an existing protocol.” And that, what's great about NVIDIA is that reference architecture is known.Swyx [00:32:15]: Open.Anjney [00:32:15]: It's open. They've published it. So Jensen's actually enabled someone like Rainer to build a chip company like MatX, and I don't see them as competitive. The compute demand is so high. Like, I don't I think NVIDIA's not able to meet the demands of production, so we just need more chips. And I think it's very smart what MatX has done, which is say, “We're just going to we're not going to innovate on the data center design ‘cause actually, thank you, Jensen, you've done all the hard work. Where we can innovate is somewhere else.” And I think that's, that's very healthy. I think that's how we unblock new bottlenecks. And my view is these, the, chip teams like MatX, who have arrived at the insight that co-design is the way, The primary bottleneck for them is trust boundary. To do co-design well, you need visibility into the next model generation as soon as possible ‘cause it takes two years to tape out. So if by the time I bring my chip to market, your model architecture's changed, I'm host. Now, when he was inside Google, he was sitting next to the Gemini team. He was on Palm or whatever.Trust Boundaries, Co-Design, and Researcher CEOsSwyx [00:33:19]: His co-founder was the, was one, was one of the Palm guys, I think.Anjney [00:33:23]: Yes. Yes, exactly. So when you're inside the trust boundary of Google, then your systems co-design loop is super tight. When you leave as a founder, one of the biggest risks you take is now you're outside the trust boundary. And so what I love doing is helping chip teams who can help us unlock more capacity for the independent ecosystem access to trust. Because when I If I've been, involved with a lab from day one, and I was lucky enough to work with Anthropic, and then I'm on the board of Mistral and helped Black Forest Labs get started. I think at this point I'm on six or seven different teams.Swyx [00:33:57]: Only six? I feel like my mental number was going to be 13, but yeah, it's-Anjney [00:34:02]: No, I go deep with one at a time.Swyx [00:34:04]: You're founding CEO of Arena.Anjney [00:34:07]: Nah, that was an, that was an-Swyx [00:34:08]: Administrative CEOAnjney [00:34:09]: It was an administrative five-month gig where Whalen and Anastasios were graduating from their PhDs, and they didn't need a product team. So I helped recruit the head of engineering product and design. But Anastasios has always been the CEO of that company. I played a pinch-hitting I'm an intern. I was CEO intern For five months. -Swyx [00:34:33]: I interviewed him, and he's he's very well-spoken. I think he's a debate, former debate, champion. But also very quantitative and mathematical, which is-Anjney [00:34:41]: He-Swyx [00:34:41]: Such a unicorn.Anjney [00:34:43]: See, what's amazing about him? If you look at his output, he's an output maxer. By the time he was graduating from his PhD, which he only graduated last year, he had published more work with a citation count than, people twice his age. But at the same time, he'd already started a project called LLM Arena that was being used by millions of people As a side project. And time and time again, what I've realized is venture capitalists suck at seeing human beings as, dynamic agents where-Swyx [00:35:14]: They want to put you in a boxAnjney [00:35:15]: They want to put you in a box.Swyx [00:35:15]: This is your thing.Anjney [00:35:16]: So the first time I got introduced to Anastasios, somebody had told me “Oh, he's amazing, but he's a researcher.” I was “what? What do you mean he's a researcher?” That's what-Swyx [00:35:28]: Like he's not a CEO, not a founder.Anjney [00:35:29]: Not a CEO, exactly. I was “Are you crazy? Do you Have you met Dario?” Dario's a scientist. He's gone from zero to, what will soon be a trillion-dollar company in four years. Being a CEO, nominally speaking, is not that hard. Being a good CEO is hard. Being a great CEO actually requires a level of performance that scientists who have already published at the top of their field have accomplished. It is super hard to be a competitive scientist. To publish in academia over the last 20, 30 years, to make it to the top of your discipline at a place like Berkeley, you are a star athlete. Like, you are an athlete of the mind, and you perform at the highest levels. And to get there, whether you're, Anastasios or Whalen at Berkeley, or you are Robin, who-Swyx [00:36:23]: BFL, yeahAnjney [00:36:24]: With Black Forest, who created Stable Diffusion, or if you're, like Guillaume at Meta, who created Llama before he started Mistral. The amount of human leadership you have to demonstrate to get the resources, like get the trust of the organization, publish it, put it up. I would just fund researchers all day Right? If who have contributed already to the field. If they've, if they've put SOTA out there, they're, they're star athletes already. If they haven't done SOTA Look, they can still be good CEOs, but then I find the failure mode is that they just don't want to be CEOs, they primarily want to publish, and that's okay, too. One of the things we do with the AMP Grid is we donate excess compute. We have two nonprofits, like university labs. We carved out like a couple thousand H100s. But I do think there's extraordinary research being done on university campuses. My father-in-law's a physicist. He's a professor. Extraordinary work in physics, and we need that. But if you want to be a CEO, what you need to be willing To do is be super confrontational, outside of science. Like within the scientific community, some of the best researchers are very confrontational about their convictions, right? This architecture is right. To be a great CEO, you basically have to be willing to be confrontational up and down the stack.Swyx [00:37:41]: To your own team.Anjney [00:37:42]: To your own team-Swyx [00:37:43]: To customersAnjney [00:37:43]: Hiring, recruiting customers. Well, I would say, Yeah, pretty much to everyone Everybody. Of course-Swyx [00:37:50]: I see, I feel a little bit of that in my own work, but yeah, I can't imagine the stakes that Dario has had to go through. It's, it's pretty insane.Anjney [00:37:56]: No, I don't think the stakes are that different From how you're feeling it, right? Stakes are personal scaling vectors, right? The stakes that seem so low to you, like having this podcast where you can talk to somebody and just have a you're an extraordinary communicator, right? Like already in this conversation, you've pulled more out of me than most people, and I've been on 12 podcasts in the last two weeks.AI Coachella and First-Principles ThinkingSwyx [00:38:17]: I think I, we've just seen each other enough that there's some base trust.Anjney [00:38:20]: There's base trust.Swyx [00:38:20]: And I think, and I know that you, that I've done my homework and like I know that trust is a big deal for you, so.Anjney [00:38:27]: I think trust is about consistency, and you and I have seen each other In the community for years, right? Like, I remember the first time we met was at NeurIPS in New Orleans. I don't know if you remember that, luncheon.Swyx [00:38:38]: Oh my God.Anjney [00:38:39]: Reiko had set up this Reiko's amazing, and he set up this luncheon and-Swyx [00:38:43]: Yeah, I was “Who's this Discord guy?” I'm “Okay.” But-Anjney [00:38:45]: No, you weren't-Swyx [00:38:46]: You were just “You made some investments.”Anjney [00:38:47]: You were much less polite. You were “Who's this VC?” You're like-Swyx [00:38:51]: No, I Was I? Oh my God.Anjney [00:38:53]: It was-Swyx [00:38:53]: I'm so sorryAnjney [00:38:53]: It was visible on your face.Swyx [00:38:54]: I'm so sorry. But you weren't, you weren't The introduction was bad. I was I didn't know who you were.Anjney [00:39:00]: The, see, this is the thing about context, right? Like, but then I think I heard your accent. And I was “Are you-”Swyx [00:39:06]: Singapore, yeahAnjney [00:39:06]: “Are you Singaporean?” And you're “Yeah.” And I said, “I went to high school, JC, in Singapore.” And then the ice broke. But This is the there are in the scientific community, sometimes the stakes are very high for people who haven't had the emotional, what is called EQ Coaching and mentorship, right? Which is like to have scientific impact, you often need to be a extraordinary emotional, like emotionally in tune person with the folks you're trying to influence. And so what comes so naturally to you is actually a super high stakes thing to other people. And so I wouldn't assume that Dario's more stressed out than you. These things are you'd be surprised how similar and small sometimes the problems are to you That some of the world's biggest, leaders are facing. And that's what I've learned from this class. The guest speakers are Sam, Satya, Jensen.Swyx [00:40:01]: AI Coachella.Anjney [00:40:02]: Yeah. It's AI Coachella, right? So we got to get all the headliners, and they're I'm very lucky that some of these people have either mentored me over the years or I've done business with them. And when you, take the performative stuff out and any assumptions you may have about these people that you read in the press or on Twitter, We're all just humans. We're all trying to get along. And what's so special about this moment is AI is forcing, like scaling, the bitter lesson is forcing a lot of people to revise their assumptions for how the world works and go back to first principles or go and educate themselves. So the kind of people I was, I won't name who this person is, but I was at an event last week in Texas and, ran to somebody who said, “Anjney, I came across the class. What do you think about real time action prediction models?” And I was, don't know how happy it made me feel when they asked me that question. I know they've done the work. They've challenged themselves. I'm, they didn't ask me, “What do you think of world models?” They said, “What do you think of n-”Swyx [00:41:04]: Real time action predictionAnjney [00:41:05]: “action, real time action prediction models?” World models, don't get me wrong, are cool and everything, but you and I both know that is a layer of abstraction that is sometimes not usefully precise enough. Right? Ours-Swyx [00:41:16]: There's like four different kinds of world models.Anjney [00:41:17]: Yes, exactly.Swyx [00:41:18]: We've done the part with general intuition, by the way, which is very focused on, -Anjney [00:41:22]: Oh, cool. Yes. I love Pim. Pim is great. And this is what I love about people who've done that level of work. They realize they're not in competition with people who the rest of the world thinks they're in competition with.Swyx [00:41:34]: Because they're not in the category, they're in the specific thing they're trying to do.Anjney [00:41:37]: They're focused on their mission, and they have a systems understanding of the bottleneck they're trying to solve. And when somebody else says, “I'm working on real time, action prediction models too,” Pim goes, “Oh, I love that person. I want, I can learn from them.” But the minute they're “Oh, that person's a world model person,” it's “like which type of world model person?” But mostly they're just trying to figure out if it's a waste of their time, because we don't have enough time. So, Pim, for example, is super, loves this other company I work with we've talked about called Black Forest Labs. And he's mentioned to me multiple times that he's so, He thinks what Flux is doing is really cool. Andy Blattman came by and spoke in the class. And what I find over and over again is for people who do the work, who can be usefully precise enough about like what is actually going on in the world of frontier research, The sense of camaraderie is still well and alive, but it gets lost sometimes when you have to like abstract The technical complexities in, business terms And then the VCs are “How are you different from that world model?” I'm going to say Where do I even start to explain this stuff? And then the misalignment creeps in.Leading vs. Winning in Frontier AISwyx [00:42:43]: This is good. Yeah, I think, people listening get a sense of, what it is like to operate at a real level, like yourself, rather than at, the journalist level, where you have to sort of put everyone in, a rough category and create a narrative of competition, and who's winning today, who's behind.Anjney [00:42:58]: It-- this idea of winning is so Weird to me.Swyx [00:43:03]: You do want to win. You want you want competitiveness.Anjney [00:43:06]: No, I think you want to lead.Swyx [00:43:07]: You want SOTA.Anjney [00:43:07]: No, I think you want to lead. Yes, so you want to push the frontier. You want to push the SOTA. You want to do something that hasn't been done before. You want to capture value, but you don't want to capture so much value that, people think you're unaligned with your mission or trying to do what's best for the world. You want to capture enough value that you can keep innovating, right? And I think that people want to lead, they don't really This idea of winning and losing, again, I love Jensen. He's a, he's a leader. The mindset that he talked about on Dwarkesh's podcast, right? He's “I didn't wake up with a loser mindset.” I think that was awesome, right? Because he's, he's an engineer. Dwarkesh has done the work. So there's at least-- even though the, to me, it was very obvious they're talking about the same thing, they just passed each other. They just had to basically, Jensen has this, five-layer cake abstraction of how the industry works. And Dwarkesh had, I think from that podcast, had more of, a pre-training, mid-training, post-training systems loop concept.Swyx [00:44:04]: It's just a factor of who he talks to, right? Again, it's very clear.Anjney [00:44:06]: It's the systems It's the abstraction, the mental models, the It's the whole-- Dude, so much of the problem in the world is reasoning by analogy. And then the assumptions that are held invisibly.Swyx [00:44:19]: Yeah, I've, I've said, this is actually the best time in human history for first principles thinkers. Because everything you think will happen is actually now coming true.Anjney [00:44:28]: Correct. And the venture capital community is, notorious for this, where people look-- In times of uncertainty, they, cling to axioms that ended up being true from the previous era, and they kind of like proclaim them with confidence as if they're truths, but they're not. And it's very important to see the distinction between a heuristic and an axiom. An axiom can be proven-Swyx [00:44:55]: Like from internal consistency point of viewAnjney [00:44:56]: With internal consistency. A heuristic is a way you kind of a shortcut. And my God, the number of people I have had to put up with over the last few years who proclaim-- use heuristics As axioms to judge people, to judge which companies are going to succeed or the number of people who are “Oh, yeah, Anthropic, they're just training models right now,” but this one continue.Swyx [00:45:22]: Because that's a B2B SaaS?Anjney [00:45:23]: Yeah, the, like Which over the fullness of time, if you squint at it, maybe. But the way you arrive there is so important that you can-- you just, you can dismiss people. Here's what happened, right? What happened is Anthropic basically achieved takeoff in October of last year. That training run-Swyx [00:45:41]: Whatever, three seven?Anjney [00:45:42]: I forget the numbers now, but whatever that checkpoint was-Swyx [00:45:45]: We saw the cognition.Anjney [00:45:46]: Yeah. Right? You probably-- The, to those of us in the community, especially once post-training was done and it was released in December-Swyx [00:45:52]: Yeah. Can I sneak a sneaky question in there? I don't know if you have a perspective, maybe you don't, I just The number one question is how did Anthropic crack coding, right? Because Claude One, Claude Two, okay, like it was part of it, but it wasn't a big deal. And the leading hypothesis, it's a lucky dice roll that was then compounded, right? Like it was like Mildly better, but then they saw it and they were “Okay, let's really invest.”How Anthropic Cracked CodingAnjney [00:46:17]: I had this very annoying teacher. I went to this boarding school called Rishi Valley in India, which is like this, bird preserve. It's like three hundred and fifty acres of bird preserve in rural India, and there was no technology for seven years. There was this teacher, I won't name them, but they would have this-- I hated it every time he said this to me. He was “Luck fa-favors the prepared mind,” which is like a common saying, but the way he delivered it, always grated me, ‘cause he was always I was always one of those kids who got, a good grade without trying very hard. ‘Cause like high middle school is not that hard if you, if you're generally, paying attention and so on. And there was this one time where I-- But then I would get an eighty percent grade, and he would keep pushing me to say “The reason you didn't get the ninety-five plus percent is because you're not that lucky.” And I would say, “What do you mean?” ‘Cause I would think that I deserved that grade, and I would sometimes argue with him. And he'd say, “You didn't have a prepared mind. If you want to get lucky again “ There was basically one time where I got like ninety-five or ninety-six on this, on this subject, and I, now that I felt entitled. I was “Okay, I'm going to keep doing this,” and I didn't. And then he was “Luck favors a prepared mind. You got lucky last time, but you got to stay prepared.” And I didn't understand what he meant. Now, as I'm older, I'm okay, these adults actually knew a thing or two. Anthropic has been the most prepared company for four years. And so then when the right, context data comes in, the right developers start sending in, the right context diffs, Sure, you could say you got lucky, but if you ask me, they're pr-pretty damn prepared with paranoia for like four years. And you have to remember, it was so hard for them to get going early on that they had to do so much more with so much less that you just have to be prepared to be so efficient.Swyx [00:48:06]: Yes. There's numbers on their burn compared to OpenAI. I've, I've written about it, but they are so much more efficient in their, in their tech stack.Anjney [00:48:14]: It's not even It's not funny.Swyx [00:48:14]: Not even close.Anjney [00:48:15]: Yeah. But it's so clear, right? Like how to output max for the world. They have been prepared, and you could call that luck, but Luck favors the prepared mind.Culture, Hardship, and Anthropic's P0Swyx [00:48:25]: This is one of those things that I was going over some of your old lectures and, you were data, people think it's a moat and actually it's culture and actually it's team Actually. And I, it's-- there's different levels of moats, and this is the ultimate one that determines everything else. Which you can then compoundAnjney [00:48:43]: You're saying culture is the ultimate moat? Yeah. But the thing about culture is it's very fragile. So moats, I don't think they're-- there's very few moats I found that are actually moats. They're-- It's, it's a nice concept, but in reality, you have to replenish your culture. Ben Horowitz was, the speaker in CS153 on Tuesday, and I asked him this question about the culture bottleneck in teams because, there are several AI teams-Swyx [00:49:09]: His book, Hard Things About Hard ThingsAnjney [00:49:11]: Hard Thing About Hard Things. But more concretely, there are so many AI labs today that have all the cash they need, they have all the compute they need, and they're still not able to ship anything SOTA. And then you start seeing people leave and so on, and my diagnosis, it's, is it's the culture. And so I asked him, Ben, they're-- He's been one of the most aggressive investors in AI labs. He goes back to this thing which resonates in my mind a lot. It-- When I used to work at a16z, I would, book a conference room, and right outside the conference room, which is closest to the toilet ‘cause it was the fastest way for me to go use the bathroom between Zoom meetings-Swyx [00:49:45]: Oh my God, I'll put maxing my toilet optimization. Okay, never mind.Anjney [00:49:48]: It was not healthy in hindsight, but maybe this is TMI. But anyway, outside that conference on the wall was this quote that was printed that said, “Culture is not a set of beliefs, it's a set of actions.” And it's by Bushido, is this, Japanese philosopher. And if you stop taking the actions that demonstrate the mission alignment to what you've said to your team and to your-- the world matters to you, then your culture starts to fray. So it's not actually a moat, I would say. It's a very brittle, fragile thing that requires daily tending to like a garden. But if you figure out the system to keep that garden tended, which I think ultimately comes down to knowing yourself ‘cause you most naturally, if you're authentic and so on, you'll naturally make trade-offs that seem effortless to you, but that reinforce your culture. And then That becomes this very hard thing for other people to catch up to. And at Anthropic, from day one, there was this mission like-- missionary like zeal and belief that, hey, these capabilities will scale. These systems are stochastic, not deterministic. There will be error bars, and until we crack interpretability, there's risk. And at some point, people will go-- stop using Claude just for coding. They'll use it in some mission-critical context where there's-- it'll throw off a bug, and then people are going to come blame them, and they want to be on the right side of history where they said, “Yes, this is a powerful technology. We think it's going to change the world, And we want to be very measured and scientific about the fact that, ‘Hey, guys, these are stats models, statistical models.' That's how statistics works.” ultimately, when you're training neural nets, it is just a statistical system. And I think that Belief that safety is important and that it might seem toy-like in the early days, and sometimes, you could say, “Anjney, they totally over-exaggerated the risk,” like two years ago when they said, “Let's not launch Claude One,” or whatever. Well, okay, maybe in hindsight, but hindsight is twenty/twenty. And at the time, they didn't know how that model would be used, and to them it felt existential if somebody came and said, “You weren't responsible. It-- This wrote a bug.” The liability associated with that is massive. So how do you prevent against that? Well, day in, day out, you say safety. And when you start deviating from that, you have the team hold you accountable, you have the world hold you accountable, and I think that becomes a moat over time. At some point, that moat will get challenged and so on, and then it become fragile. I hope it endures because that's the beauty of having founders run the show, ‘cause they can make really hard trade-offs to do mission alignment. The hardest part is in the earliest days when you don't have a group of people who are going through difficulty, stress, crisis together, then your culture doesn't get defined sharply enough, and that's what I'm worried about right now, is there's so much money going to these labs. There's no hardship. There's no-Swyx [00:52:50]: To anyone who knowsAnjney [00:52:51]: There's no to anyone who knows. And that, in hindsight, was a feature, not a bug for Anthropic. The number of people who said no, the number of people who said, “Sorry, we're all doing investors in OpenAI,” that is competitive difference. It forces you to really understand, what is the hill you want to die on at the expense of everything else. What's the P zero? And there, P zero from day one was coding. The reason, the mechanism system there was if we crack coding, Then we will crack AGI. Our mission is AGI. We want to get there safely. If we focus on codin

Borough Park Morning Briefing — Thursday, June 11, 2026 | Zmanim, NWS New York and MoreBorough Park, Brooklyn, New York | Weather With Enthusiasm — Kol Simcha Productions===========================================HEBREW DATE & PARSHA===========================================Hebrew Date: 26 Sivan 5786Parsha: Sh'lachShabbos Mevarchim Chodesh Tamuz: June 13, 2026Molad Tamuz: Monday, 6:46 AM and 16 chalakimRosh Chodesh Tamuz: June 15–16, 2026===========================================TODAY'S ZMANIM — Borough Park, Brooklyn (ZIP 11219)40.633°N 73.997°W | Elevation: 58m===========================================Alot HaShachar: 3:36:40 AMMisheyakir: 4:13:01 AMMisheyakir Machmir: 4:22:29 AMSunrise (Netz HaChama): 5:24:37 AMSof Zman Shma (GRA): 9:10:13 AMSof Zman Tefila (GRA): 10:25:24 AMChatzos: 12:55:48 PMMincha Gedola: 1:33:24 PMShkiah (Sunset): 8:26:59 PM===========================================WEATHER SUMMARY — NWS UPTON (OKX)===========================================Issued: 3:13 AM EDT, Thursday June 11, 2026Forecasters: DW / MWToday: Hot and humid. Highs upper 80s to lower 90s. Heat Index mid-90s to lower 100s.Heat Advisory in effect: Noon today through 8 PM Friday for NYC metro.Air Quality Alert: 11 AM–11 PM today for NYC area.Thunderstorm Risk: Isolated to scattered severe thunderstorms late afternoon/evening (approximately 4–9 PM). Main threats: damaging wind gusts, large hail, localized flash flooding. SPC: Slight Risk for severe storms.Weekend: Still hot (lower 90s), less humid after cold front. Periodic shower chances next week.Key Technical Notes:- 850 mb (~25.10 inHg) temps near 20°C → surface upper 80s/lower 90s- Dew points upper 60s–lower 70s → heat index mid-90s to 100+- High CAPE + marginal shear → pulse severe possible- PW ~2" → heavy downpours, max hourly rainfall up to 2"/hr- Record high June 11 at KNYC: 95°F (1973)===========================================WEATHER HISTORY — JUNE 11===========================================June 11, 2008 — EF3 Tornado Strikes Boy Scout Camp, Little Sioux, IowaAn EF3 tornado with 145 mph winds struck a Boy Scout camp near Little Sioux, Iowa, killing 4 teenage Scouts and injuring 48 others. Campers had sought shelter in a cabin when the tornado collapsed the chimney, sending concrete blocks onto them. The 1,800-acre camp had no in-ground shelter. It was the deadliest of dozens of severe weather reports across the northern Plains that day.Source: NWS, verified===========================================FAMILY ACTIVITIES — BROOKLYN/NYC, JUNE 11===========================================1. Lincoln Center's Summer for the City — Starts today, runs June 11–Aug 9 | FREE/pay-what-you-can | Lincoln Center, Upper West Side | 200+ events including kids musical storytimes, jazz, dance2. Photoville Photography Festival — Through June 22 | FREE | Brooklyn Bridge Park, Emily Warren Roebling Plaza | 80+ exhibits, free kid activity packs at info tent3. FIFA World Cup Watch Party — Today 2–7 PM | FREE | Brooklyn Army Terminal, Sunset Park4. Shakespeare in the Park: Julius Caesar — Through July 5 | FREE | Delacorte Theater, Central Park5. Prospect Park Carousel — Open daily | Small fee | Prospect Park, Brooklyn | The beloved 1912 carouselNOTE: Brooklyn Children's Museum is CLOSED Thursday June 11.===========================================TOMORROW'S ZMANIM — Friday June 12 (Erev Shabbos)===========================================Alot HaShachar: 3:36:23 AMMisheyakir: 4:12:49 AMMisheyakir Machmir: 4:22:19 AMSunrise (Netz HaChama): 5:24:32 AMSof Zman Shma (GRA): 9:10:16 AMSof Zman Tefila (GRA): 10:25:31 AMChatzos: 12:56:00 PMMincha Gedola: 1:33:37 PMShkiah (Sunset): 8:27:27 PM===========================================SHABBOS TIMES — Shabbos Sh'lach / Mevarchim Chodesh TamuzFri June 12 – Sat June 13, 2026 | 27–28 Sivan 5786===========================================Hadlakas Neiros (Candle Lighting): 8:09 PM Friday, June 12 (18 minutes before Shkiah — Borough Park minhag)Havdalah: 9:18 PM Saturday, June 13 (50 minutes after sunset — local custom)Gut Shabbos and Gut Chodesh!===========================================Weather With Enthusiasm is produced by Kol Simcha Productions.New episodes drop daily — morning forecasts at 7 AM every day on Spreaker, plus a historical weather deep-dive every Tuesday and Thursday at 7 AM CDT. Most podcast platforms (Apple, Spotify, Amazon Music) typically receive new episodes within 1–3 hours of release.Contact: kolsimchaproductions@outlook.comHistorical content is thoroughly researched and factually verified. Should you find any mistakes, please email kolsimchaproductions@outlook.com so we can correct it as quickly as possible.Not affiliated with any government agency or academic institution. Presented for educational and entertainment purposes — with meaning.Support the show — exclusive bonus episodes available to subscribers for just $5/month at spreaker.com/organization/kol-simcha.===========================================#weather #zmanim #BoroughPark #Brooklyn #NWS #morningbriefing #Shlach #Shabbos #MevarchimTamuz #NewYork #WeatherWithEnthusiasm #KolSimchaProductionsBecome a supporter of this podcast: https://www.spreaker.com/podcast/weather-with-enthusiasm--4911017/support.Weather with Enthusiasm is produced by Kol Simcha Productions.New episodes drop daily (B'N)— a morning forecast at 7 AM and historical deep dives Tuesdays and Thursdays. Contact: kolsimchaproductions@outlook.comHistorical content is thoroughly researched and factually verified. After it has been factually verified it often will say so in the description. Should you find any mistakes, please email kolsimchaproductions@outlook.com so we can look into it and correct it. Not affiliated with any government agency or academic institution. Presented for educational and entertainment purposes — with meaning.Support the show — exclusive bonus episodes available to subscribers for just $2/month at spreaker.com/organization/kol-simcha

Setting financial goals is important—but reviewing them regularly can be just as valuable.In this episode, Miguel Gonzalez discusses why financial goals should evolve as life changes. Learn how career shifts, family priorities, changing expenses, market conditions, and personal milestones can all influence your financial direction. Periodic reviews can help ensure your goals remain aligned with what matters most to you.Miguel Gonzalez is a Certified Retirement Counselor (CRC) with over 25 years of experience helping individuals and families design retirement income strategies and long-term financial plans. He is the Managing Partner of Cortburg Retirement Advisors, a boutique firm focused on retirement planning, investment management, and financial clarity.#FinancialGoals #FinancialPlanning #CortburgSpeaksRetirement #MiguelXGonzalez #FinancialWellness #MoneyGoalsWelcome to Cortburg Speaks Retirement Podcast with Miguel Gonzalez, MBA, AIF®, CPFA®, CRC® CLICK HERE TO LISTEN TO MIGUEL'S LATEST PODCAST FOLLOW US ON: YouTube->https://m.youtube.com/c/CORTBURGRETIREMENTADVISORSFacebook-> https://m.facebook.com/CortburgIncTwitter-> https://twitter.com/CortburgIncLinkedIn->https://www.linkedin.com/in/miguelxgonzalez/Website: www.CortburgRetirement.comEmail:     Miguel@CortburgRetirement.com

The airline industry is heading into summer travel season under cloudy conditions. In this episode of J.P. Morgan's Making Sense, Harry Gowers, lead analyst for European Airlines and Travel Retail stocks, and Jamie Baker, U.S. Airline and Aircraft Leasing Equity analyst, break down their expectations for the airline industry. Together, they discuss how geopolitics and fuel prices are affecting supply and demand, why low-cost carriers are finding success in some markets and not in others and what happens to pricing power if fuel prices ease. This episode was recorded on May 29, 2026.  This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. © 2026, JPMorganChase & Co. All rights reserved.

Dave wraps Season 7 of Reboot IT with Gretchen Steenstra, VP, Client Strategy at DelCor, and a discussion on how organizations can get unstuck and find success with their technology initiatives. Gretchen shares insights from her experience working across multiple organizations, exploring the balance between strategy and execution, the importance of adoption and change management, and how CEOs, CIOs, and business leaders each contribute to achieving success. Themes and Topics:The Balance Between Strategy and ExecutionOrganizations often lean too heavily toward either visionary strategy or detailed execution; success requires both.Strategy sets direction, but execution delivers results and the two must continuously inform each other.Periodic “zoom out” moments are essential to ensure execution is still aligned with strategic goals.Alignment Across the OrganizationTechnology is no longer separate. IT plans must align directly with organizational strategy.CIOs play a critical role in connecting leadership vision with operational reality.Alignment requires continuous communication between leadership, staff, and partners.The Role of the CEO and LeadershipCEOs should connect high-level vision to day-to-day operations without getting lost in the details. Leadership can remove blockers, balance priorities, and champion initiatives effectively. Leadership alignment helps teams understand how their work contributes to the organizational mission.The CIO as a Translator and NegotiatorCIOs act as intermediaries between business needs, technology teams, vendors, and security requirements.They must balance usability and security, often negotiating trade-offs between the two.CIOs also serve as escalation points when projects stall or teams hit roadblocks.Adoption and Change ManagementThe real work begins after launch. Long-term adoption determines success.Organizations often underinvest in post-launch behaviors and process changes.Preventing “backslide” requires ongoing reinforcement and attention to how people actually work.Building Tech Literacy and Cross-Functional CollaborationBusiness leaders must develop a baseline understanding of how systems connect and interact.Cross-functional planning (marketing, finance, IT, membership) helps surface risks early.Mapping the full customer journey, from awareness to transaction to delivery, improves outcomes.

Who is the real Kevin Warsh? Having been sworn in as the Fed's 17th chair, the Warsh era at the FOMC has begun. But with inflation proving sticky and Fed independence under the microscope, how will he balance the committee's dual mandate? What might he do differently than his predecessor, Jerome Powell? And how will he handle President Trump? On this episode of Making Sense, Alexa Hanelin talks to Michael Feroli, J.P. Morgan's chief U.S. Economist, to forecast the path of the Fed and examine what may be in store at the June FOMC meeting and beyond. This episode was recorded on May 22, 2026.  This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. © 2026, JPMorganChase & Co. All rights reserved.

Interview with Robert A. Swerlick, MD, author of Skin Cancer Risk Profile of Asymptomatic Patients Seeking Periodic Skin Examinations for Skin Cancer Concerns. Hosted by Adewole S. Adamson, MD, MPP. Related Content: Skin Cancer Risk Profile of Asymptomatic Patients Seeking Periodic Skin Examinations for Skin Cancer Concerns

Interview with Robert A. Swerlick, MD, author of Skin Cancer Risk Profile of Asymptomatic Patients Seeking Periodic Skin Examinations for Skin Cancer Concerns. Hosted by Adewole S. Adamson, MD, MPP. Related Content: Skin Cancer Risk Profile of Asymptomatic Patients Seeking Periodic Skin Examinations for Skin Cancer Concerns

Hey Team! This week, I'm talking with Christine Lane, an accredited financial counselor (AFC) with a master's degree in psychology. Christine has ADHD herself and, luckily for the rest of us, her hyper-fixation happens to be on personal finance. She's the founder of Mind Over Money, where she focuses on the psychological hurdles that make traditional budgeting feel like a personal failure rather than just a glitch in your executive function. In our conversation today, we get into her "Four-Bucket Banking System" and why we need to stop making our money multitask. We also explore the concept of using "friction" as a tool for impulse control and why simulating the physical loss of cash can be a great way to get your limbic system to play ball. We also talk about the specific tools she uses to gamify spending, why detailed categorization is often just a form of productive procrastination, and how to set up "set it and forget it" systems that protect your bills from your worst impulses. If you'd life to follow along on the show notes page you can find that at HackingYourADHD.com/296 YouTube: https://tinyurl.com/y835cnrk Patreon: https://www.patreon.com/HackingYourADHD This Episode's Top Tips Modern digital spending, such as our cards and phones, provides a "gain" without the physical feeling of money leaving. To help bridge this gap, tools like a calculator, where you can subtract the cost at the moment of purchase, can help the limbic system register the loss, balancing the emotional input so you feel protective of your remaining funds. When we let our savings accounts multitask, we can end up imagining that the same $5,000 can cover both an emergency and a vacation. By using something like the Four-Bucket Banking System (Bills, Variable, Periodic, Emergency), you create "object permanence" for your money, ensuring that essential funds are physically separated from your spending urges. Willpower is a finite resource that often fails when we are stressed. Instead of "trying harder," we want to focus on bending external structures (like deleting the Amazon app or removing saved credit card info) to create enough friction to let our executive function outpace some of our more impulsive spending choices.  

Think annuities mean your money disappears when you die? In this episode, Stan The Annuity Man breaks down lifetime income backstops and shows how to structure annuities so every penny is guaranteed to go to your beneficiaries—not the "evil annuity company."   In this episode, The Annuity Man discussed:  Common misconceptions about lifetime income annuities Life-only annuities vs. annuities with backstops Single premium immediate annuities, deferred income annuities, and QLACs Cash refund, installment refund, and period certain structures Income riders on index and variable annuities as lifetime income solutions   Key Takeaways:  Many people, including financial professionals, misunderstand annuities and wrongly assume the money vanishes at death, when in reality, there are numerous ways to protect beneficiaries. Life-only structures deliver the highest lifetime income but intentionally accept the risk that no money may remain for heirs if death occurs early. Cash refund and installment refund backstops ensure that every unused dollar of premium ultimately goes to beneficiaries rather than being retained by the annuity company. Periodic certain options are generally less efficient, because they simply guarantee a minimum payout period rather than maximizing long-term protection and benefits for heirs. Income riders attached to index or variable annuities focus on the contractual income guarantee, with the underlying annuity acting as the death benefit backstop, often providing strong lifetime income solutions.   "We only look at the contractual guarantees of the policy. We only own it for what it will do, not what it might do." —  Stan The Annuity Man   Connect with The Annuity Man:  Website: http://theannuityman.com/  Email: Stan@TheAnnuityMan.com  Book: Owner's Manuals: https://www.stantheannuityman.com/how-do-annuities-work YouTube: https://www.youtube.com/channel/UCCXKKxvVslbeGAlEc5sra2g  Get a Quote Today: https://www.stantheannuityman.com/annuity-calculator!

Is this a resilient labor market, or a fragile one? In this episode of Making Sense, Mike Feroli, Chief U.S. Economist at J.P. Morgan, joins Lauren Brice from the North America Rates Sales team to break down the April jobs report and discuss what it means for the health of the U.S. economy in 2026. They discuss the data on claims, AI's impact on construction and other sectors, and what this report might suggest about the projected path of Fed rate cuts going forward.   This episode was recorded on April 8, 2026.   This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. © 2026, JPMorganChase & Co. All rights reserved.

ADHD doesn't clock out at bedtime. From delayed sleep phases and racing thoughts to stimulant timing and restless nights, sleep disruption is one of the most common (and most overlooked) challenges of living with ADHD. Plus, poor sleep makes every ADHD symptom worse!  In this episode, Dr. J breaks down why ADHD and sleep don't always get along. And she shares five science-backed strategies to help you finally get some rest. For more on this topic  Watch: ADHD and weed: Why it feels like a fix (but isn't) Read: 13 tips for getting more sleep Listen: ADHD and: Self-medicating For a transcript and more resources, visit MissUnderstood on Understood.org. You can also email us at podcast@understood.org Sources: Cortese, S., Faraone, S. V., Konofal, E., & Lecendreux, M. (2009). Sleep in children with attention-deficit/hyperactivity disorder: Meta-analysis of subjective and objective studies. Journal of the American Academy of Child & Adolescent Psychiatry, 48(9), 894-908. Kooij, J. J., & Bijlenga, D. (2013). The circadian rhythm in adult attention-deficit/hyperactivity disorder: Current state of affairs. Expert Review of Neurotherapeutics, 13(10), 1107-1116. Van Veen, M. M., Kooij, J. J., Boonstra, A. M., Gordijn, M. C., & Van Someren, E. J. (2010). Delayed circadian rhythm in adults with attention-deficit/hyperactivity disorder and chronic sleep-onset insomnia. Biological Psychiatry, 67(11), 1091-1096. Picchietti, D. L., England, S. J., Walters, A. S., Willis, K., & Verrico, T. (1998). Periodic limb movement disorder and restless legs syndrome in children with attention-deficit hyperactivity disorder. Journal of Child Neurology, 13(12), 588-594. Yoon, S. Y., Jain, U., & Shapiro, C. (2012). Sleep in attention-deficit/hyperactivity disorder in children and adults: Past, present, and future. Sleep Medicine Reviews, 16(4), 371-388. Schredl, M., Alm, B., & Sobanski, E. (2007). Sleep quality in adult patients with attention deficit hyperactivity disorder (ADHD). European Archives of Psychiatry and Clinical Neuroscience, 257(3), 164-168. Boonstra, A. M., Kooij, J. J., Oosterlaan, J., Sergeant, J. A., & Buitelaar, J. K. (2010). Does methylphenidate improve inhibition and other cognitive abilities in adults with childhood-onset ADHD? Journal of Clinical and Experimental Neuropsychology, 32(9), 954-969. Gau, S. S., Kessler, R. C., Tseng, W. L., Wu, Y. Y., Chiu, Y. N., Yeh, C. B., & Hwu, H. G. (2007). Association between sleep problems and symptoms of attention-deficit/hyperactivity disorder in young adults. Sleep, 30(2), 195-201. Sobanski, E., Brüggemann, D., Alm, B., Kern, S., Deschner, M., Schubert, T., ... & Rietschel, M. (2007). Psychiatric comorbidity and functional impairment in a clinically referred sample of adults with attention-deficit/hyperactivity disorder (ADHD). European Archives of Psychiatry and Clinical Neuroscience, 257(7), 371-377. Bijlenga, D., Vollebregt, M. A., Kooij, J. J., & Arns, M. (2019). The role of the circadian system in the etiology and pathophysiology of ADHD: Time to redefine ADHD? ADHD Attention Deficit and Hyperactivity Disorders, 11(1), 5-19. . Understood.org is a nonprofit organization dedicated to empowering people with learning and thinking differences, like ADHD and dyslexia. If you want to help us continue this work, donate at understood.org/give Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

fWotD Episode 3283: Crusading movement Welcome to featured Wiki of the Day, your daily dose of knowledge from Wikipedia's finest articles.The featured article for Friday, 1 May 2026, is Crusading movement.The Crusading movement—a major religious, political, and military endeavour of the Middle Ages—is generally dated from the Council of Clermont (1095), at which Pope Urban II proclaimed an armed expedition in support of Eastern Christians under Muslim rule. He framed it as a form of penitential pilgrimage. By this point, papal authority had grown through church reforms, and tensions with secular rulers encouraged the notion of holy war—combining classical just war theory, biblical precedents, and Augustine's teachings on legitimate violence. Armed pilgrimage aligned with the era's Christocentric and militant Catholicism, sparking widespread enthusiasm. Western expansion was further enabled by economic growth, the decline of older Mediterranean powers, and Muslim disunity. These factors allowed crusaders to seize territory and found four Crusader states in the Levant, whose defence inspired successive Crusades. The papacy also launched crusading campaigns against other targets—Muslims in Iberia, Paganism in the Baltic, and other opponents of papal authority.Though aimed primarily at the warrior elite through appeals to chivalric ideals, the movement depended on broad support from clergy, townspeople, and peasants. Women, despite being discouraged, were involved as participants, proxies for absent crusaders, or victims. Although many crusaders were motivated by indulgences (absolution from sins), material gain also played a part. Crusading campaigns were typically initiated through papal bulls, and participants pledged to join by "taking the cross"—sewing a cross onto their garments. Failure to fulfil vows could result in excommunication. Periodic waves of zeal produced unsanctioned "popular crusades".The papal-sanctioned wars fostered distinctive institutions and ideologies. Initially funded through improvised means, later campaigns received more organized support via papal taxes on clergy and the sale of indulgences. Core crusading forces were heavily armed knights, backed by infantry, local troops, and naval aid from maritime cities. Crusaders secured their holdings by building strong castles, and the fusion of chivalric and monastic ideals led to the rise of military orders. The movement extended Western Christendom and created new frontier states, some surviving into the early modern period. Crusading encouraged cultural exchange and left lasting marks on European art and literature. Despite a decline during the Reformation, anti-Ottoman "holy leagues" sustained the tradition into the 18th century.This recording reflects the Wikipedia text as of 00:42 UTC on Friday, 1 May 2026.For the full current version of the article, see Crusading movement on Wikipedia.This podcast uses content from Wikipedia under the Creative Commons Attribution-ShareAlike License.Visit our archives at wikioftheday.com and subscribe to stay updated on new episodes.Follow us on Bluesky at @wikioftheday.com.Also check out Curmudgeon's Corner, a current events podcast.Until next time, I'm generative Ruth.

From geopolitical tensions and energy disruptions to the latest tariff developments, uncertainty was a recurring motif at the IMF–World Bank Spring Meetings 2026. Yet, bullish market sentiment still prevails. What's causing this disconnect? Join Joyce Chang, chair of Global Research, and Derek Chollet, head of the JPMorganChase Center for Geopolitics, as they explore why markets have remained largely resilient despite the uncertain macro backdrop.  This episode was recorded on April 21, 2026.  The views or opinions expressed herein are solely those of the JPMorganChase Center for Geopolitics and may differ from the views and opinions expressed by J.P. Morgan Securities LLC Research Department or other departments or divisions of JPMorgan Chase & Co. or its affiliates.  Information has been obtained from sources believed to be reliable, but JPMorganChase does not warrant its completeness or accuracy. Opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice.  The opinions herein should not be construed as an individual recommendation for any particular client and is not intended as advice or recommendations of particular securities, financial instruments, or strategies for a particular client.  The information contained herein has been provided solely for informational purposes and does not constitute an offer, solicitation, advice or recommendation, to make any investment decisions or purchase any financial instruments, and may not be construed as such. This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. © 2026, JPMorganChase & Co. All rights reserved.

In this episode of J.P. Morgan's Making Sense, global economist Maia Crook is joined by senior U.S. economist Mike Hanson to break down the March CPI report. They discuss the energy-driven jump in headline inflation, why core inflation may remain firm and signs of tariff pass-through. The conversation also explores why CPI and the Fed's preferred Personal Consumption Expenditures (PCE) measure are sending different signals, how that gap could shape Fed policy and how the Iran conflict may influence the global inflation outlook.   This episode was recorded on April 13, 2026.   This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. © 2026, JPMorganChase & Co. All rights reserved.

In this episode of Making Sense, Stephen Dulake, co-head of Global Fundamental Research, is joined by Jake Pollack, head of North American Credit Trading and Global Credit Financing, to take stock of where private credit stands today. They unpack the two forces shaping the narrative — investor liquidity in retail vehicles and underlying credit performance — alongside investor focus areas like PIK (payments in kind), software and services exposure, and early markers of AI-related disruption. The conversation closes with views on marking practices, the 2028–2029 maturity wall and ongoing price discovery, and what increased regulatory scrutiny could look like as the market continues to grow. This episode was recorded on March 31, 2026.    --   This podcast is intended for institutional clients only. The views expressed in this podcast may not necessarily reflect the views of J.P. Morgan Chase & Co, and its affiliates, together J.P. Morgan, and do not constitute research or recommendation advice or an offer or a solicitation to buy or sell any security or financial instrument. Referenced products and services in this podcast may not be suitable for you, and may not be available in all jurisdictions. J.P. Morgan may make markets and trade as principal in securities and other asset classes and financial products that may have been discussed. For additional disclaimers and regulatory disclosures, please visit www.jpmorgan.com/disclosures.  --  This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan.  © 2026, JPMorganChase & Co. All rights reserved. 

What happens when you apply the scaling laws of large language models to the physical work of atoms? Elad Gil sits down with Liam Fedus, co-founder at Periodic Labs, which is pioneering an AI foundation lab for atoms. Liam discusses how he pivoted from dark matter physics research to the front lines of artificial intelligence, including stints at Google Brain and working on ChatGPT at OpenAI. He talks about how Periodic is connecting massive language models to the physical world to overcome data bottlenecks in material science. Liam also shares how they use language models as an orchestration layer operating alongside specialized neural nets to run closed-loop physical experiments. They also explore the future of AGI and ASI, as well as the role of robotics in lab automation. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @LiamFedus | @periodiclabs Chapters: 00:00 – Cold Open 00:05 – Liam Fedus Introduction 00:39 – Liam's Background at Google Brain, OpenAI 05:14 – From ChatGPT to Materials and Atoms 06:34 – Training Data in the Physical World 09:52 – Generalization Across Domains 11:31 – Models as an Orchestration Layer 12:48 – Commercialization and Business Model 16:10 – How Periodic's Success May Shape the Future  17:45 – Multidisciplinary Scaling 19:41 – Capital and Compute 21:12 – Hiring at Periodic 21:44 – Thoughts on AGI and ASI 23:30 – Timeline for Machine-Directed Self-Improvement 25:39 – Automation and Data Generation 27:59 – Why Liam is Excited About the Future of Robotics 29:25 – Conclusion

In this episode of Making Sense, Mike Feroli, Chief U.S. Economist at J.P. Morgan, joins Sam Azzarello, head of Content Strategy, to unpack the March jobs report and what it signals beneath the headline. They discuss the rebound in hiring after February's data, early signs that AI may be reshaping the labor market, and what higher energy prices could mean for consumer momentum. The conversation closes with Feroli's outlook on how the data may shape the Fed's near-term policy stance and his base-case outlook for the U.S. economy.   This episode was recorded on April 3, 2026.  This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. © 2026, JPMorganChase & Co. All rights reserved.

Check out the next episode of our podcast, Under the Surface! In episode 15, Fells' Elements of Success: A Periodic Journey, we immerse ourselves in the world of chemistry and career alchemy with James Fells. From his early days as a curious freshman to his role as an Associate Director, In Silico Discovery at Johnson & Johnson Innovative Medicine, James recounts his journey through the ups and downs of the scientific realm and the importance of guidance along the way. Hear how his childhood curiosity about Gargamel inspired his success, how he moved between academia and industry, and why his story stands out. We think this episode will really connect with you. Listener discretion is advised. 02:12 The story behind the early use of MOE software in 1999 03:36 Childhood obsession with potions and how it sparks real science 07:00 Funding, scholarships, and the importance of independence 08:41 Making the leap from academia to industry: speed and culture shock 12:33 The value of humility, openness, and collaboration in pharma 16:15 Crafting winning fellowship applications and proactive networking 20:19 Transitioning from postdoc to industry: timing and strategy 24:17 How industry teams differ from academia in hierarchy and respect 37:33 The big cultural shifts moving from Merck to Johnson & Johnson 45:18 The importance of company culture, openness, and shared lessons learned 49:12 J&J's evolving approach to science, leadership, and opportunity 57:47 Reflections: What he'd do differently, advice for future scientists 62:03 If not in science, what would James do? Coach? Math teacher? 63:53 Final thoughts: Exploring opportunities, being adaptable, and following your curiosity   Subscribe & listen to all episodes of our podcast: https://sites.libsyn.com/459216/underthesurface  Follow us on LinkedIn & X

Watch the full episode with Robert Edward Grant here: https://youtu.be/GntqR4jQ7_ESupport this show http://supporter.acast.com/inspiredevolution. Hosted on Acast. See acast.com/privacy for more information.

In this episode of Making Sense, Anthony Paolone, co-head of U.S. Real Estate Stock Research, and John Sim, head of Securitized Products Research, offer their take on the U.S. housing market. They examine current supply-demand dynamics, regional price trends and mortgage rates, which have remained elevated since 2022. Where are home prices headed, and how might new reforms alter the wider outlook? Plus, how are rental markets faring amid growing “rent fatigue”?   This episode was recorded on March 2, 2026. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. © 2026, JPMorganChase & Co. All rights reserved.

When your business runs on data, even a few seconds of downtime can hurt. That's why this episode focuses on what keeps Oracle Database@AWS running when real-world problems strike.   Hosts Lois Houston and Nikita Abraham are joined by Senior Principal Database Instructor Rashmi Panda, who takes us inside the systems that keep databases resilient through failures, maintenance, and growing workloads.   Oracle Database@AWS Architect Professional: https://mylearn.oracle.com/ou/course/oracle-databaseaws-architect-professional/155574 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. --------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption with Customer Success Services, and with me is Nikita Abraham, Team Lead: Editorial Services with Oracle University. Nikita: Hi everyone! In our last episode, we explored the security and migration strengths of Oracle Database@AWS. Today, we're joined once again by Senior Principal Database Instructor Rashmi Panda to look at how the platform keeps your database available and resilient behind the scenes. 01:00 Lois: It's really great to have you with us, Rashmi. As many of you may know, keeping critical business applications running smoothly is essential for success. And that's why it's so important to have deployments that are highly resilient to unexpected failures, whether those failures are hardware-, software-, or network-related. With that in mind, Rashmi, could you tell us about the Oracle technologies that help keep the database available when those kinds of issues occur? Rashmi: Databases deployed in Oracle Database@AWS are built on Oracle's Foundational High Availability Architecture. Oracle Real Application Cluster or Oracle RAC is an Active-Active architecture where multiple database instances are concurrently running on separate servers, all accessing the same physical database stored in a shared storage to simultaneously process various application workloads. Even though each instance runs on a separate server, they collectively appear as a single unified database to the application. As the workload grows and demands additional computing capacity, then new nodes can be added to the cluster to spin up new database instances to support additional computing requirements. This enables you to scale out your database deployments without having to bring down your application and eliminates the need to replace existing servers with high-capacity ones, offering a more cost-effective solution. 02:19 Nikita: That's really interesting, Rashmi. It sounds like Oracle RAC offers both scalability and resilience for mission-critical applications. But of course, even the most robust systems require regular maintenance to keep them running at their best. So, how does planned maintenance affect performance?  Rashmi: Maintenance on databases can take a toll on your application uptime. Database maintenance activities typically include applying of database patches or performing updates. Along with the database updates, there may also be updates to the host operating system. These operations often demand significant downtime for the database, which consequently leads to slightly higher application downtime. Oracle Real Application Cluster provides rolling patching and rolling upgrades feature, enabling patching and upgrades in a rolling fashion without bringing down the entire cluster that significantly reduces the application downtime.  03:10 Lois: And what happens when there's a hardware failure? How does Oracle keep things running smoothly in that situation? Rashmi: In the event of an instance or a hardware failure, Oracle RAC ensures automatic service failover. This means that if one of the instance or node in the cluster goes down, the system transparently failovers the service to an available instance in the cluster, ensuring minimal disruption to your application. This feature enhances the overall availability and resilience of your database.  03:39 Lois: That sounds like a powerful way to handle unexpected issues. But for businesses that need even greater resilience and can't afford any downtime, are there other Oracle solutions designed to address those needs? Rashmi: Oracle Exadata is the maximum availability architecture database platform for Oracle databases. Core design principle of Oracle Exadata is built around redundancy, consisting of networking, power supplies, database, and storage servers and their components. This robust architecture ensures protection against the failure of any individual component, effectively guaranteeing continuous database availability. The scale out architecture of Oracle Exadata allows you to start your deployment with two database servers and three storage servers, having different number of CPU cores and different sizes and types of storage to meet the current business needs. 04:26 Lois: And if a business suddenly finds demand growing, how does the system handle that? Is it able to keep up with increased needs without disruptions? Rashmi: As the demand increases, the system can be easily expanded by adding more servers, ensuring that the performance and capacity grow with your business requirements. Exadata Database Service deployment in Oracle Database@AWS leverages this foundational technologies to provide high availability of database system. This is achieved by provisioning databases using Oracle Real Application Cluster, hosted on the redundant infrastructure provided by Oracle Exadata Infrastructure Platform. This deployment architecture provides the ability to scale compute and storage to growing resource demands without the need for downtime. You can scale up the number of enabled CPUs symmetrically in each node of the cluster when there is a need for higher processing power or you can scale out the infrastructure by adding more database and storage servers up to the Exadata Infrastructure model limit, which in itself is huge enough to support any large workloads. The Exadata Database Service running on Oracle RAC instances enables any maintenance on individual nodes or patching of the database to be performed with zero or negligible downtime. The rolling feature allows patching one instance at a time, while services seamlessly failover to the available instance, ensuring that the application experienced little to no disruption during maintenance. Oracle RAC, coupled with Oracle Exadata redundant infrastructure, protects the Database Service from any single point of failure. This fault-tolerant architecture features redundant networking and mirrored disk, enabling automatic failover in the event of a component failure. Additionally, if any node in the cluster fails, there is zero or negligible disruption to the dependent applications. 06:09 Nikita: That's really impressive, having such strong protection against failures and so little disruption, even during scaling and maintenance. But let's say a company wants those high-availability benefits in a fully managed environment, so they don't have to worry about maintaining the infrastructure themselves. Is there an option for that? Rashmi: Similar to Oracle Exadata Database Service, Oracle Autonomous Database Service on dedicated infrastructure in Oracle Database@AWS also offers the same feature, with the key difference being that it's a fully managed service. This means customers have zero responsibility for maintaining and managing the Database Service. This again, uses the same Oracle RAC technology and Oracle Exadata infrastructure to host the Database Service, where most of the activities of the database are fully automated, providing you a highly available database with extreme performance capability. It provides an elastic database deployment platform that can scale up storage and CPU online or can be enabled to autoscale storage and compute. Maintenance activities on the database like database updates are performed automatically without customer intervention and without the need of downtime, ensuring seamless operation of applications. 07:20 Lois: Can we shift gears a bit, Rashmi? Let's talk about protecting data and recovering from the unexpected. What Oracle technologies help guard against data loss and support disaster recovery for databases? Rashmi: Oracle Database Autonomous Recovery Service is a centralized backup management solution for Oracle Database services in Oracle Cloud Infrastructure. It automatically takes backup of your Oracle databases and securely stores them in the cloud. It ensures seamless data protection and rapid recovery for your database. It is a fully managed solution that eliminates the need for any manual database backup management, freeing you from associated overhead. It implements an incremental forever backup strategy, a highly efficient approach where only the changes since the last backup are identified and backed up. This approach drastically reduces the time and storage space needed for backup, as the size of the incremental changes is significantly lower than the full database backup. 08:17 Nikita: And what's the benefit of using this backup approach? Rashmi: The benefit of this approach is that your backups are completed faster, with much lesser compute and network resources, while still guaranteeing the full recoverability of your database in the event of a failure. You can achieve zero data loss with this backup service by enabling the real-time protection option, while minimizing the data loss by recovering data up to the last subsecond. It is highly recommended to enable this option for mission-critical databases that cannot tolerate any data loss, whether due to a ransomware attack or due to an unplanned outage. The protection policy can retain the protected database backups for a minimum of 14 days to a maximum of 95 days. The recovery service requires and enforces the backups are encrypted. These backups are compressed and encrypted during the backup process. The integrity of the backups is continuously validated without placing a burden on the production database. This ensures that the stored backup data is consistent and recoverable when needed. This protects against malicious user activity or any ransomware attack. With strict policy-based retention strategy, it prevents modification or deletion of backup data by malicious users. 09:30 Lois: Now, let's look at the next layer of protection. Rashmi, can you tell us about Oracle Active Data Guard? Rashmi: Oracle Active Data Guard provides highly available data protection and disaster recovery for Enterprise Oracle Databases. It creates and manages one or more transactionally consistent standby copies of production database, which is the active primary. The standby database is isolated from production environment located miles away in a distance data center, ensuring the standby remains protected and unaffected, even if the primary is impacted by a disaster. In the event of a disaster or data corruption occurring at the primary, the standby can take over the role as new primary, thus allowing business to continue its operations uninterrupted. It keeps the standby database in sync with the production database by continuously applying change logs from production. 10:25 Do you want to stay ahead in today's fast-paced world? Check out our New Features courses for Oracle Fusion Cloud Applications. Each quarter brings new updates and hands-on training to keep your skills sharp and your knowledge current. Head over to mylearn.oracle.com to dive into the latest advancements! 10:45 Nikita: Welcome back! Rashmi, how does Oracle Active Data Guard operate in practice? Rashmi: It uses the knowledge of Oracle Database block format to continuously validate physical blocks or logical intrablock corruption during redo transport and change apply. With automatic block repair feature, whenever any corrupt block is detected in the primary or the standby database, then it is automatically repaired by transferring a good copy of the block from other destination that holds it. This is handled transparently without any error being reported in the application. It enables you to upload the read-only workloads and backup operations to the standby database, reducing the load on the production database. You can achieve zero data loss at any distance by configuring a special synchronization mechanism known as parsing. File systems form the attack surface for ransomware. Since Active Data Guard replicates the data at the memory level, any ransomware attack on the primary database will never be replicated to the standby database. This allows for a safe failover to the standby without any data loss, and shielding the database from effects of the attack. You can enable automatic failover of the primary database to a chosen standby database without any manual intervention by configuring a Data Guard Broker. The Data Guard Broker continuously monitors the primary database and automatically performs a failover to the standby when the predefined failover conditions are met. Active Data Guard enables you to perform database maintenance or database software upgrades with almost zero or minimal downtime. 12:18 Lois: And how does disaster recovery work for Exadata Database Service in Oracle Database@AWS? Rashmi: Exadata Database Service, by design, are already protected against local failures by use of technologies like Oracle RAC and Oracle Exadata. Now, by deploying Exadata Database Service across multiple availability zones in an AWS region, it can ensure that your database services remain resilient to site failures. It leverages Oracle Active Data Guard to create standby in a separate availability zone such that if the primary availability zone is affected, then all application traffic can be routed to the database services in the secondary availability zone, restoring business continuity of the application back to normal. Through continuous validation of the data blocks at both the primary and the standby database, any potential corruption is detected and prevented. This ensures data integrity and protection across the entire database service. By leveraging zero data loss Autonomous Recovery Service, the database ensures that the backup remains secure and unaffected by ransomware. This enables rapid restoration of clean, uncompromised data in the event of an attack. Periodic patching and upgrades are performed online in a rolling fashion with little to no impact on the application uptime using a combination of Oracle RAC and Oracle Active Data Guard technologies. For all resource-intensive workloads like database backup or generating monthly reports, which are read-only in nature, they can be uploaded to the standby, reducing the load on the production database. In the cross-availability zone DR setup, you have the flexibility to configure Active Data Guard to use either the AWS network or the OCI network for keeping database redo logs to the standby database. Choosing which network to use for the traffic is entirely at the enterprise discretion. However, both are Oracle maximum availability–compliant and the setup is pretty simple. If the network traffic being used is OCI network or AWS network, then respective cloud provider is responsible for ensuring the reliability. You have to take into account the different charges that each cloud provider may have. And you can provision multiple standby databases using the console. Optionally, you may set up a broker manually to enable automatic failover capability. 14:30 Nikita: We just covered cross-availability-zone protection. But what if an entire AWS region goes down? Rashmi: This is where we can provide an additional level of protection by provisioning cross-region disaster recovery for your Exadata Database Service in Oracle Database@AWS.  This deployment protects your database against regional disasters. You can provision another DR environment in a different AWS region that supports Oracle Database@AWS. This deployment, together with the cross-availability zone deployment, complements your highly available and protected database service deployment in Oracle Database@AWS. Under the hood, it uses the same Oracle Database technologies that include Oracle Active Data Guard, OCI Autonomous Recovery Service, Oracle Exadata, Oracle RAC to provide the same capabilities as in case of cross-availability zone deployment. Here too, you have the flexibility to configure Oracle Active Data Guard to use either AWS network or OCI network for shipping database redo logs to the standby. And for the network traffic options, the feature remains the same, except a small difference with respect to chargeback. When using OCI Network for cross-region deployment, there is no charge for the first 10 TB of data transfer per month. Beyond that, standard OCI charges would apply. When using AWS network, you may refer to AWS charging sheet for the cross-region traffic. 15:49 Nikita: Thank you so much, Rashmi, for this insightful episode. Lois: Yes, thank you! And if you want to dive deeper into the topics we covered today, go to mylearn.oracle.com and search for the Oracle Database@AWS Architect Professional course. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 16:13 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

In this episode of J.P. Morgan's Making Sense, Phoebe White, a senior U.S. rates strategist and head of U.S. inflation strategy, sits down with senior economist Mike Hanson to unpack the January CPI report and the inflation outlook for 2026. They discuss why inflation may hover near 3% this year, the impact of tariffs, the gradual cooling in rents, and how differences between the CPI and PCE could inform the Fed's path. The conversation also touches on energy and food prices, data quality concerns at the BLS and much more.   This episode was recorded on February 18, 2026.  This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. © 2026, JPMorganChase & Co. All rights reserved.

Ashley & Jacqui Derrick   Ashley Derrick & Jacqui Derrick/Workright, LLC The Drug Lady is an important team member for any business wishing to create or maintain a Drug Free Workplace. Our “Drug Lady” is powered by two  amazing ladies- a mother-daughter team who have been working together for almost 30 years. Jacqui Derrick developed […]

Assyrian Aid Relief–Australia is hosting its periodic afternoon tea to raise funds for heaters in classrooms at Assyrian schools in northern Iraq. President Shushan Tower told SBS this is the first time the event has been held in the afternoon, instead of the traditional morning tea.

Silver has been on a volatile ride since the start of last year. In this episode, host Sam Azzarello, head of content strategy for Global Research, is joined by Greg Shearer, head of Base and Precious Metals Strategy, to break down the dramatic changes in silver prices and what could be next for the market. They cover why silver's price is so volatile compared with gold, policy uncertainty including tariffs, and the evolving role of silver in industrial uses and how that influences demand. What are the key risks and opportunities for the silver market?   This episode was recorded on February 6, 2026.   This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. © 2026, JPMorganChase & Co. All rights reserved.

The January jobs report may be delayed, but there are many other factors shaping the path forward for the U.S. economy. Join Lauren Brice from the North America Rates Sales team and chief U.S. economist Mike Feroli as they unpack recent data including job openings and tech earnings, as well as the latest Fed developments. What do the headline numbers suggest about the economic outlook, and how might the nomination of a new Fed chair influence monetary policy?    This episode was recorded on February 6, 2026.   This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. © 2026, JPMorganChase & Co. All rights reserved.

Manipulating the scattering of waves can allow engineers to achieve numerous goals, like reducing unwanted noise or eliminating potentially destructive vibrations in structures. In this episode, we talk to Vladislav Sorokin (University of Auckland) and Luke Bennetts (University of Melbourne), two guest editors of the recent Special Issue on Wave Phenomena in Periodic, Near-Periodic, and Locally Resonant Systems about recent advances in research regarding vibroacoustic systems. Read all the articles from the special issue here!Read more from The Journal of the Acoustical Society of America (JASA).Learn more about Acoustical Society of America Publications.Music Credit: Min 2019 by minwbu from Pixabay. 

Recent events in Venezuela have so far had limited immediate impact on global commodity markets — but the longer-term implications could be significant, especially if Western investment returns to the country. In this episode, analysts from J.P. Morgan Global Research explore the outlook for oil, natural gas and metals.    Speakers: Natasha Kaneva, Head of Global Commodities Research Greg Shearer, Head of Base & Precious Metals Research Otar Dgebuadze, Natural Gas Research   This podcast was recorded on January 9, 2026. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. Copyright 2026, JPMorganChase & Co. All rights reserved.

Non-farm payrolls increased by just 50,000 in December while the unemployment rate dipped to 4.4%, reinforcing the “low-hire, low-fire” theme of the past few months. Does this point to a Fed pause at the January meeting? And how are consumers holding up against this backdrop? Join chief U.S. economist Mike Feroli and Alexa Hanelin from the North America Rate Sales team as they discuss the latest numbers.    This episode was recorded on January 9, 2026.   This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. Copyright 2026, JPMorganChase & Co. All rights reserved.

Dylan from the City of Yarra and Tex McKenzie speak about the Yarra Queer History Walk, a guided tour that traces Melbourne's queer‑footprints through Fitzroy, Collingwood and Abbotsford. Jack is also joined by Rachel Cook and Chiron Hooson from Thorne Harbour to discuss the Community Periodic Surveys, our presence at Carnival, and more. Check out our other JOY Podcasts for more on LGBTIQ+ health and wellbeing at joy.org.au/wellwellwell. If there's something you'd like us to explore on the show, send through ideas or questions at wellwellwell@joy.org.au Find out more about LGBTIQ+ services and events in Victoria and South Australia at thorneharbour.org and samesh.org.au.  

If you're not losing weight, dangerous diet advice may be the reason. Discover the worst weight loss mistakes and how to lose weight fast with these 13 effective weight loss tips.0:00 Introduction: weight loss lies1:01 The worst weight loss advice 1:49 Low-calorie diets2:30 Weight loss mistakes6:01 13 weight loss tips14:08 Periodic prolonged fasting to lose weight fast Surprisingly, the most common weight loss tips given by mainstream dietitians and medical professionals are the worst diet advice! Calorie counting and portion control will leave you feeling hungry and constantly craving carbs. The body adapts to a low-calorie diet, leading to a slower metabolism. A low-calorie, high-carbohydrate diet raises insulin levels.I'm sure you've heard these other bad weight loss tips: • Eat 6 small meals per day• Count calories• Increase fiber• Drink more water to help you feel full• Chew gum• Take Ozempic These tips will not boost fat loss!Your body can use fat or glucose for fuel. Although stored fat is potential energy, you must lower your insulin to utilize it.Insulin resistance is at the root of many chronic illnesses and can negatively affect the liver, nervous system, immune system, and more. Low-calorie diets that don't lower insulin are not sustainable. You won't be able to achieve your goals if you're hungry, craving carbs, dealing with brain fog, high blood pressure, or other related issues. If you really want to lose weight, stop calorie counting! Try these 13 weight loss tips instead:1 Don't use pre-workout, sugary drinks, or protein bars.2. Keep your carbs at around 10 to 20 grams per day.3. No bright lights at night. 4. Get early morning sun.5. Avoid late-night snacking. 6. Never buy junk food at the grocery store. Don't shop while hungry!7. Be cautious around social situations.8. Walk after meals.9. Don't eat unless you're hungry.10. Prioritize healthy animal protein.11. Consume apple cider vinegar before meals.12. Avoid diets that keep you bloated.13. Do periodic prolonged fasting. Dr. Eric Berg DC Bio:Dr. Berg, age 60, is a chiropractor who specializes in Healthy Ketosis & Intermittent Fasting. He is the Director of Dr. Berg Nutritionals and author of the best-selling book The Healthy Keto Plan. He no longer practices, but focuses on health education through social media.Disclaimer: Dr. Eric Berg received his Doctor of Chiropractic degree from Palmer College of Chiropractic in 1988. His use of “doctor” or “Dr.” in relation to himself solely refers to that degree. Dr. Berg is a licensed chiropractor in Virginia, California, and Louisiana, but he no longer practices chiropractic in any state and does not see patients, so he can focus on educating people as a full-time activity, yet he maintains an active license. This video is for general informational purposes only. It should not be used to self-diagnose, and it is not a substitute for a medical exam, cure, treatment, diagnosis, prescription, or recommendation. It does not create a doctor-patient relationship between Dr. Berg and you. You should not make any change in your health regimen or diet before first consulting a physician and obtaining a medical exam, diagnosis, and recommendation. Always seek the advice of a physician or other qualified health provider with any questions you may have regarding a medical condition.

Met. Luke of the Ukrainian Orthodox Church (UOC) delivered this address on December 4, 2025 at the conference titled: "The Crucifixion of Orthodoxy in the 21st Century: Spiritual Wars, Ecumenical Offensive, and Global Politics" hosted by Center for Geostrategic Studies in Belgrade, Serbia.

The year ahead will likely be driven by three powerful forces: uneven monetary policy, the relentless AI cycle and deepening polarization across markets and economies. What are the key opportunities and risks to watch across equities, commodities, currencies and more? Join analysts from J.P. Morgan Global Research as they explore the outlook for 2026.   In this episode, we hear from: Bruce Kasman, Chief Global Economist - 01:00 Mislav Matejka, Head of Global Equity Strategy - 05:19 Francis Diamond, Head of European Rate Strategy - 11:50 Meera Chandan, Co-Head of Global FX Strategy - 15:58 Stephen Dulake, Co-Head of Global Fundamental Research - 19:43 Jonathan Goulden, Head of EM Fixed Income Strategy - 25:13 Natasha Kaneva, Global Head of Commodities Research - 30:21 Fabio Bassi, head of Cross-Asset Strategy - 35:25   This episode was recoded between December 9 and December 17, 2025.   This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication.  This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan.  Copyright 2025, JPMorganChase & Co. All rights reserved. 

In this episode of J.P. Morgan's Making Sense, Joyce Chang, chair of Global Research, is joined by Sarah Isgur, senior editor at The Dispatch and Supreme Court expert, and Peter Harrell, visiting scholar at Georgetown Law and Fellow at the Carnegie Endowment for International Peace. Together, they unpack the Supreme Court cases challenging President Trump's use of executive power, focusing on trade, tariffs and presidential authority over independent agencies and the Federal Reserve Bank. The discussion explores the legal and economic implications of these cases, the evolving balance between Congress and the executive branch and the potential consequences for markets, businesses and governance.   This episode was recorded on November 19, 2025.   This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. Copyright 2025, JPMorganChase & Co. All rights reserved.

A senior vice-president worries that attention on his people's development will get overwhelmed in the volume of work. He asks his coach for tools to make the process effective and efficient. Download our free tool that maps the Three Conversations Development Plan.Core Concepts Prioritizing professional development is hard.The 3-Conversation model makes development easy for the leader and meaningful for the person.The three conversations in summary: Define ‘what,' ‘why' and give homework;The person reflects on the homework and how they plan to improve;Periodic check-ins about the homework. ‘What are you learning?'The leader's role in these conversations: Clarify the ‘what' and ‘why' Listen and encourageAsk, ‘What are you learning?'You can sign-up for more resources and tools in our monthly email. If you're thinking about coaching for yourself, or for someone on your team, let's talk. tom@essentialcomm.com.This episode is tagged in three categories in our podcast library:FeedbackLeadershipManagement SkillsRELATED EPISODES132  Coaching Your People212  How to Coach Your People258  How to Manage Defensive People83  Leadership and Listening206  Understanding FeedbackThanks, as always, for your reviews!Happy holidays. Until next time, thanks so much for listening.From The Look & Sound of Leadership team  

Welcome to The Eagle's View!This is where you can listen to the students of Emerson School in Ann Arbor, Michigan soar.  Join 4th graders Riaan and Elli as they host this episode. This week you will need all of your brainpower as we explore space, reading, teachers, brains, nuclear fusion, the periodic table of elements and as always, The Joke of the Week!Thank you for listening to The Eagles View. Be sure to like, follow, and share our podcast with your friends and family.And don't just listen—leave us a comment! We'd love to hear your thoughts, your favorite part, or even your own joke of the week.New episodes come out every Wednesday—even during summer break., plus The Eagle's View Presents every Monday and Story Tellers on FridayBe sure to check out our new merchandise on The Emerson School Store website below.https://apparelnow.com/emerson-school-store-apparel/Follow on social media too!https://www.facebook.com/theemersonschool/https://www.instagram.com/emersonschool/Thanks for hanging out with us, and remember—Eagles always soar!

Last week, I talked about building credibility by looking outside your organization for validation. External benchmarking, expert opinions, and industry recognition all help shift internal perception. But validation only works if people understand the actual value you're delivering. That brings us to today's topic: measuring and communicating UX success in ways that resonate with stakeholders.Because, unless you can demonstrate value clearly, the rest of the organization won't recognize it.Fortunately, decision makers across your company have an inherent need to improve the metrics they see. By establishing the right metrics, you'll influence their behavior. It's a weird phenomenon, but if you give people something to measure, they will want to improve that thing.Two ways to quantify successThere are basically two ways to demonstrate the benefit of what you're doing.Qualitative data can be incredibly powerful. A compelling story generates empathy among stakeholders in ways that raw numbers sometimes can't. Testimonials, videos, and user feedback help people understand the human impact of your work.But quantitative data is even more powerful because people believe in hard numbers in a way they don't believe anything else. Ideally, this data should tie to some kind of financial return for the organization.There is something about hard data and having hard numbers you can track that really resonates with people and makes them want to start moving that needle.Deciding on your metricsThe first step is to have metrics based around organizational goals. Right back at the beginning of this course, I talked about getting that company strategy and identifying the organizational goals. Now we need to translate those into something measurable.Depending on what kinds of products and digital services your organization offers will impact how you go about doing this. Essentially, you're taking the company objectives and translating those to the website, app, or digital service that you're running. For example, "increase revenue" might be a company goal for the year, so your website's role might be to generate more leads. Then you need to get specific about key performance indicators. What metric are we going to measure? Maybe we're measuring the number of people completing an online form or visiting a contact page. You need to make those metrics very tangible because otherwise, you can't track them easily.Vary your metricsHowever, be careful. Many organizations end up focusing on a single metric like conversion, which often ends up undermining their long-term success. For example, if you only care about conversion, you end up using pop-up overlays and attention-grabbing things, especially if you're thinking about conversion over the next quarter rather than longer term. You'll do anything to meet that target for that particular month. But what you're also doing is alienating people who won't come back because your website is hard to use or annoying.It's much better to have a variety of metrics that you measure rather than focusing on just one area so that you approach things in a more rounded way.I typically try to have metrics in three broad areas:Engagement metrics assess if users find your design delightful, if the content is interesting, and if it's relevant to their needs. You might put out a quarterly survey on the website or measure dwell time (although sometimes that can be a sign that people are lost on the website) or track how much of a video they watch.Usability metrics answer whether users can find answers to their questions and use features effectively. Periodic usability testing can bring those metrics in. You can measure things like task success rate, time to complete tasks, error rates, and the system usability scale I mentioned earlier.Conversion metrics show whether the right users take action on the site and what the financial value of those actions is. You've got the conversion rate, average order value, average lifetime value, number of repeat customers, and so on.Tie metrics to dollar valueThe most important thing is to try and tie these metrics to a dollar value if possible. Let me give you an example of how powerful this can be.I was at a restaurant called Pizza Express here in the UK. My wife and I were sitting there when the server came over to take our order. However, they took forever to input the order into an iPhone app. I glanced at my wife, who immediately rolled her eyes at me because she knew exactly what I was thinking. That the app had a bad user experience and needed improvement. The server went away, and my poor wife had to listen to me go on about how annoying these apps can be. I then became obsessed and ruined our lunch by starting some calculations.I calculated that if we could save 10 seconds per order, with about 350 orders placed per day in an average restaurant, that would save 58 minutes every day. Pizza Express is open about 364 days a year, meaning we could save 351 hours per year per restaurant. With 450 restaurants worldwide, that equates to nearly 158,000 hours that could be saved by fixing this app. According to ChatGPT, the average server in the UK earns about £9.90 per hour, so fixing the app could save the company over £1.5 million a year.Now, you might think I made up these numbers, and that would be the kind of feedback you'd get if you did something similar. You're right. People will say the numbers are made up, and yes, I did make them up. But it shows the potential. You can use that as a case to run a proof of concept project to work out the real cost savings. It's okay to make educated guesses, and the power of linking a usability or user experience problem to a financial value cannot be overstated. That is where you'll really get people's attention and begin to show the organization the value you can provide.If you want to make similar calculations, I've created a UX ROI calculator on my website that helps you work out the financial impact of UX improvements. Whether you're trying to increase your conversion rate, improve user retention and engagement, or boost productivity and efficiency, it walks you through the math and gives you numbers you can take to stakeholders.Report your successHowever, we can't just calculate these numbers. We also need to report them back. There are several techniques I use for demonstrating this value across the organization.I use storytelling quite a lot. Creating an engaging story that demonstrates how UX enhancements can address issues and achieve measurable business results. That's where your qualitative feedback becomes valuable because you've got all these stories of different users and their experiences. I could have just given you the hard numbers about the Pizza Express example, but by telling you how I ruined our lunch and alienated my wife, I made that story more interesting.I'm also a great fan of dashboards. Providing UX metrics in a dashboard will demonstrate how changes in the user experience help meet business objectives in a very tangible, visual way that people can instantly understand.I also produce impact reports either quarterly, half-yearly, or annually which report back to the organization about the impact that user experience changes have had on the long-term goals of the business.And then there are demos. Host demo days to showcase recent successes, what you changed, what it was like before and after, and the tangible difference that made.Reporting success is really an important part of the equation, and that means you need to be measuring success and tying that back to a financial benefit if you possibly can.Outie's AsideIf you're a freelancer or agency working with clients, demonstrating value becomes even more critical. Your client relationships depend on proving ROI.When you start a project, agree on the metrics you'll track upfront. Don't wait until the end to figure out how you'll demonstrate success. Build measurement into your proposal. If your client says "increase conversions," get specific about which conversions, by how much, and over what timeframe.Document the baseline before you start work. Take screenshots, record the current metrics, and note the user complaints. This gives you a clear before state to compare against.During the project, create a simple dashboard that your client can check anytime. Share wins as they happen. Don't save everything for the final report.When you're calculating potential value, be conservative. Underpromise and overdeliver. If your rough calculation suggests £100,000 in savings, present it as "potentially £50,000 or more." This protects you from overpromising while still showing meaningful impact.Finally, make your impact reports visual. Before-and-after screenshots, simple charts showing metric improvements, and short video clips of users struggling with the old design versus succeeding with the new one. These make your case far more compelling than a spreadsheet full of numbers.So that is it for this time. Next week, I'll wrap up this course with some final thoughts and a summary of everything we've covered. I'll pull together the key lessons and give you a framework for moving forward with confidence.

Inner thigh fat loss isn't just about exercise. Your inner thigh workout should prioritize rest and recovery. Discover the best inner thigh exercises, along with the necessary diet and lifestyle changes, for achieving smooth, toned, and healthy legs. 0:00 Introduction: Inner thigh toning and fat loss1:06 Inner thigh fat loss4:45 How to tone inner thighs7:16 What causes inner thigh fat?7:58 The best inner thigh workout12:29 More inner thigh fat loss tips Subcutaneous fat is the fat stored just under the skin. Visceral fat surrounds the organs. This type of fat is unhealthy and inflammatory, often related to insulin resistance. Liver fat can be eliminated in a matter of days or weeks. Fat on the inner thighs is the most difficult type of fat to get rid of. This fat is not just superficial; it's woven inside the muscle fibers, similar to the marbling in Wagyu beef. Muscle deteriorates and is replaced by fat and scar tissue. Stem cells that make muscle cells are lost, resulting in fewer contractions, less ATP, and more insulin resistance in the muscle.This abnormal accumulation of fat in the muscle is called myosteatosis, or intramuscular fat. This fat must be burned locally! As you begin to address this problem, you may not initially lose weight or notice a visible change, because the change occurs at the cellular level. For inner thigh fat loss, focus on repairing damaged muscle cells, rather than simply losing weight. Strength and decreased appetite will signify that you are improving. The root causes of intramuscular fat are the following:•Inactivity/sedentary life •Insulin resistance •Inflammation •Aging For the most inner thigh fat loss, try the following:1. Eccentric exercises 2. Walking 3. Sprinting/HIIT4. Two meals per day/low-carb diet 5. Increase key nutrients: magnesium, vitamin D, and omega-36. Get plenty of sleep7. Periodic prolonged fasting 8. Cold plunge/shower Learn how to do step-ups and walking lunges here: ▶️ https://youtu.be/wfhXnLILqdk ▶️ https://youtu.be/tQNktxPkSeE Dr. Eric Berg DC Bio:Dr. Berg, age 60, is a chiropractor who specializes in Healthy Ketosis & Intermittent Fasting. He is the Director of Dr. Berg Nutritionals and author of the best-selling book The Healthy Keto Plan. He no longer practices, but focuses on health education through social media.Disclaimer: Dr. Eric Berg received his Doctor of Chiropractic degree from Palmer College of Chiropractic in 1988. His use of “doctor” or “Dr.” in relation to himself solely refers to that degree. Dr. Berg is a licensed chiropractor in Virginia, California, and Louisiana, but he no longer practices chiropractic in any state and does not see patients, so he can focus on educating people as a full-time activity, yet he maintains an active license. This video is for general informational purposes only. It should not be used to self-diagnose, and it is not a substitute for a medical exam, cure, treatment, diagnosis, prescription, or recommendation. It does not create a doctor-patient relationship between Dr. Berg and you. You should not make any change in your health regimen or diet before first consulting a physician and obtaining a medical exam, diagnosis, and recommendation. Always seek the advice of a physician or other qualified health provider with any questions you may have regarding a medical condition.

On today's episode, we're joined by Jeff Keckley and Ron Rosenthal, both Partners at Meridian Compensation Partners, LLC.Jeff and Ron break down the purpose of stock ownership guidelines, how they support alignment with shareholders and why companies should revisit these policies as their compensation programs evolve. They outline how guidelines are typically structured, what counts as ownership, how external stakeholders evaluate them and the growing use of holding requirements as a complement or alternative to traditional ownership timelines.Key Takeaways:00:00 Introduction.02:02 Ownership guidelines encourage executives to think and act like owners.04:17 Tiered ownership levels help clarify expectations across the leadership team.07:11 Pay mix influences how quickly executives can reach ownership requirements.11:16 Ownership guidelines focus on vested value while holding power focuses on unvested awards.13:07 Participation decisions reflect the company's culture and overall pay philosophy.15:58 Companies make judgment calls on which share types to count toward ownership.24:30 Holding requirements help executives build and maintain ownership over time.28:01 Periodic reviews keep guidelines aligned with market practice and business needs.Resources Mentioned:Jeff Keckleyhttps://www.linkedin.com/in/jeffkeckley/Ron Rosenthalhttps://www.linkedin.com/in/ron-rosenthal-a48ab5ab/Meridian Compensation Partners, LLChttps://www.linkedin.com/company/meridian-compensation-partners-llc/This episode is brought to you by Meridian Compensation Partners, LLC. Learn more by visiting MeridianCP.com. #Compensation #Wages #SPAC

As the U.S. government shutdown drags on, uncertainty continues to build for both investors and everyday Americans. In this episode of J.P. Morgan's Making Sense, Samantha Azzarello, head of Content Strategy, sits down with chief U.S. economist Michael Feroli and Jay Barry, head of Global Rates Strategy, to explore the impacts of the prolonged shutdown. How is it weighing on consumer sentiment and economic growth, and how are markets responding? Plus, have expectations for Fed policy changed as a result?    This episode was recorded on November 7, 2025.   This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. Copyright 2025, JPMorganChase & Co. All rights reserved.

In this episode, Kenneth Worthington, a Brokers, Asset Managers and Exchanges equity analyst at J.P. Morgan, is joined by Teresa Ho, head of U.S. Short Duration Strategy, to explore the dynamic world of stablecoins. Together, they break down what stablecoins are, how they work and why they're gaining so much attention in today's financial landscape. The discussion covers how stablecoins differ from deposits and money market funds, the impact of recent legislation such as the GENIUS Act, as well as what all this could mean for the future of finance.   This episode was recorded on October 23, 2025.   This communication is provided for information purposes only. Please visit www.jpmm.com/research/disclosures for important disclosures. JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively, J.P. Morgan) normally make a market and trade as principal in securities, other financial products and other asset classes that may be discussed in this communication. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan. Copyright 2025, JPMorganChase & Co. All rights reserved.

In this episode, Joyce Chang, chair of Global Research at J.P. Morgan, is joined by Jahangir Aziz, head of Emerging Markets Research, and Jay Barry, head of Global Rates Strategy. Together, they explore how AI is reshaping global economic narratives, why tech innovation trumps tariffs, the evolving U.S.–China relationship and more. They also discuss other topics including stagflation risks, shifting trade dynamics and the outlook for U.S. Treasury markets. What does the global economy's new normal look like?  This episode was recorded on October 21, 2025. This communication has been prepared based upon information from sources believed to be reliable, but J.P. Morgan does not warrant its completeness or accuracy except with respect to any disclosures relative to J.P. Morgan and/or its affiliates and an analyst's involvement with any company (or security, other financial product or other asset class) that may be the subject of this communication. Any opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is not indicative of future results. This communication is not intended as an offer or solicitation for the purchase or sale of any financial instrument. J.P. Morgan Research does not provide individually tailored investment advice. Any opinions and recommendations herein do not take into account individual circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies. You must make your own independent decisions regarding any securities, financial instruments or strategies mentioned or related to the information herein. Periodic updates may be provided on companies, issuers or industries based on specific developments or announcements, market conditions or any other publicly available information. However, J.P. Morgan may be restricted from updating information contained in this communication for regulatory or other reasons. This communication may not be redistributed or retransmitted, in whole or in part, or in any form or manner, without the express written consent of J.P. Morgan. Any unauthorized use or disclosure is prohibited. Receipt and review of this information constitutes your agreement not to redistribute or retransmit the contents and information contained in this communication without first obtaining express permission from an authorized officer of J.P. Morgan.  Copyright 2025, JPMorganChase & Co. All rights reserved. 

Send us a textThe hardest conversations often happen in the quiet minutes between calls. We sat down with clinician and co-response partner Amanda Rizoli to explore how real support for first responders is built—on language, trust, and the discipline to show up when services are thin and the need is loud. Amanda works alongside the Milford Police Department's Family Services Unit and partners with Community Impact, Chris's Corner Recovery Resource Center, and New England Medical Group to create a wraparound model that meets people where they are.We talk through the realities of police and EMS life: constant hypervigilance, the pull toward numbing after shift, and the challenge of switching from fight-or-flight to family dinner. Amanda breaks down how she approaches alcohol as a coping strategy without judgment, how she teaches practical skills like structured decompression and tactical breathing, and why brief, timely check-ins during ride-alongs can open doors that a formal office visit can't. She also shares how a therapy canine lowers defenses on scene, and how clinicians earn credibility by respecting patrol's turf and knowing when to step back.Culture and language shape access. As a trilingual clinician, Amanda navigates the nuances of Portuguese and Spanish dialects across Portugal, Brazil, and Latin America, where stigma can be high and immigration status complicates care. We dig into the shift among younger parents willing to break cycles of silence, and how targeted outreach, transparent pathways, and confidentiality build trust. Families matter here: spouses can act as early warning systems, keeping communication open and knowing when work stress is spilling into home. Periodic joint sessions help couples tune the signal without turning the house into a clinic.If you care about officer wellness, community trust, and practical ways to prevent burnout, this conversation delivers a grounded playbook: co-response done right, multilingual services, stepped care from outpatient to IOP, and the small, repeatable habits that actually make a difference after shift. Subscribe, share with someone who needs it, and leave a review to help more first responders and families find these tools.Freed.ai: We'll Do Your SOAP Notes!Freed AI converts conversations into SOAP note.Use code Steve50 for $50 off the 1st month!Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.Support the showYouTube Channel For The Podcast

AI Assisted Coding: From Deterministic to AI-Driven—The New Paradigm of Software Development, With Markus Hjort In this BONUS episode, we dive deep into the emerging world of AI-assisted coding with Markus Hjort, CTO of Bitmagic. Markus shares his hands-on experience with what's being called "vibe coding" - a paradigm shift where developers work more like technical product owners, guiding AI agents to produce code while focusing on architecture, design patterns, and overall system quality. This conversation explores not just the tools, but the fundamental changes in how we approach software engineering as a team sport. Defining Vibecoding: More Than Just Autocomplete "I'm specifying the features by prompting, using different kinds of agentic tools. And the agent is producing the code. I will check how it works and glance at the code, but I'm a really technical product owner." Vibecoding represents a spectrum of AI-assisted development approaches. Markus positions himself between pure "vibecoding" (where developers don't look at code at all) and traditional coding. He produces about 90% of his code using AI tools, but maintains technical oversight by reviewing architectural patterns and design decisions. The key difference from traditional autocomplete tools is the shift from deterministic programming languages to non-deterministic natural language prompting, which requires an entirely different way of thinking about software development. The Paradigm Shift: When AI Changed Everything "It's a different paradigm! Looking back, it started with autocomplete where Copilot could implement simple functions. But the real change came with agentic coding tools like Cursor and Claude Code." Markus traces his journey through three distinct phases. First came GitHub Copilot's autocomplete features for simple functions - helpful but limited. Next, ChatGPT enabled discussing architectural problems and getting code suggestions for unfamiliar technologies. The breakthrough arrived with agentic tools like Cursor and Claude Code that can autonomously implement entire features. This progression mirrors the historical shift from assembly to high-level languages, but with a crucial difference: the move from deterministic to non-deterministic communication with machines. Where Vibecoding Works Best: Knowing Your Risks "I move between different levels as I go through different tasks. In areas like CSS styling where I'm not very professional, I trust the AI more. But in core architecture where quality matters most, I look more thoroughly." Vibecoding effectiveness varies dramatically by context. Markus applies different levels of scrutiny based on his expertise and the criticality of the code. For frontend work and styling where he has less expertise, he relies more heavily on AI output and visual verification. For backend architecture and core system components, he maintains closer oversight. This risk-aware approach is essential for startup environments where developers must wear multiple hats. The beauty of this flexibility is that AI enables developers to contribute meaningfully across domains while maintaining appropriate caution in critical areas. Teaching Your Tools: Making AI-Assisted Coding Work "You first teach your tool to do the things you value. Setting system prompts with information about patterns you want, testing approaches you prefer, and integration methods you use." Success with AI-assisted coding requires intentional configuration and practice. Key strategies include: System prompts: Configure tools with your preferred patterns, testing approaches, and architectural decisions Context management: Watch context length carefully; when the AI starts making mistakes, reset the conversation Checkpoint discipline: Commit working code frequently to Git - at least every 30 minutes, ideally after every small working feature Dual AI strategy: Use ChatGPT or Claude for architectural discussions, then bring those ideas to coding tools for implementation Iteration limits: Stop and reassess after roughly 5 failed iterations rather than letting AI continue indefinitely Small steps: Split features into minimal increments and commit each piece separately In this segment we refer to the episode with Alan Cyment on AI Assisted Coding, and the Pachinko coding anti-pattern.  Team Dynamics: Bigger Chunks and Faster Coordination "The speed changes a lot of things. If everything goes well, you can produce so much more stuff. So you have to have bigger tasks. Coordination changes - we need bigger chunks because of how much faster coding is." AI-assisted coding fundamentally reshapes team workflows. The dramatic increase in coding speed means developers need larger, more substantial tasks to maintain flow and maximize productivity. Traditional approaches of splitting stories into tiny tasks become counterproductive when implementation speed increases 5-10x. This shift impacts planning, requiring teams to think in terms of complete features rather than granular technical tasks. The coordination challenge becomes managing handoffs and integration points when individuals can ship significant functionality in hours rather than days. The Non-Deterministic Challenge: A New Grammar "When you're moving from low-level language to higher-level language, they are still deterministic. But now with LLMs, it's not deterministic. This changes how we have to think about coding completely." The shift to natural language prompting introduces fundamental uncertainty absent from traditional programming. Unlike the progression from assembly to C to Python - all deterministic - working with LLMs means accepting probabilistic outputs. This requires developers to adopt new mental models: thinking in terms of guidance rather than precise instructions, maintaining checkpoints for rollback, and developing intuition for when AI is "hallucinating" versus producing valid solutions. Some developers struggle with this loss of control, while others find liberation in focusing on what to build rather than how to build it. Code Reviews and Testing: What Changes? "With AI, I spend more time on the actual product doing exploratory testing. The AI is doing the coding, so I can focus on whether it works as intended rather than syntax and patterns." Traditional code review loses relevance when AI generates syntactically correct, pattern-compliant code. The focus shifts to testing actual functionality and user experience. Markus emphasizes: Manual exploratory testing becomes more important as developers can't rely on having written and understood every line Test discipline is critical - AI can write tests that always pass (assert true), so verification is essential Test-first approach helps ensure tests actually verify behavior rather than just existing Periodic test validation: Randomly modify test outputs to verify they fail when they should Loosening review processes to avoid bottlenecks when code generation accelerates dramatically Anti-Patterns and Pitfalls to Avoid Several common mistakes emerge when developers start with AI-assisted coding: Continuing too long: When AI makes 5+ iterations without progress, stop and reset rather than letting it spiral Skipping commits: Without frequent Git checkpoints, recovery from AI mistakes becomes extremely difficult Over-reliance without verification: Trusting AI-generated tests without confirming they actually test something meaningful Ignoring context limits: Continuing to add context until the AI becomes confused and produces poor results Maintaining traditional task sizes: Splitting work too granularly when AI enables completing larger chunks Forgetting exploration: Reading about tools rather than experimenting hands-on with your own projects The Future: Autonomous Agents and Automatic Testing "I hope that these LLMs will become larger context windows and smarter. Tools like Replit are pushing boundaries - they can potentially do automatic testing and verification for you." Markus sees rapid evolution toward more autonomous development agents. Current trends include: Expanded context windows enabling AI to understand entire codebases without manual context curation Automatic testing generation where AI not only writes code but also creates and runs comprehensive test suites Self-verification loops where agents test their own work and iterate without human intervention Design-to-implementation pipelines where UI mockups directly generate working code Agentic tools that can break down complex features autonomously and implement them incrementally The key insight: we're moving from "AI helps me code" to "AI codes while I guide and verify" - a fundamental shift in the developer's role from implementer to architect and quality assurance. Getting Started: Experiment and Learn by Doing "I haven't found a single resource that covers everything. My recommendation is to try Claude Code or Cursor yourself with your own small projects. You don't know the experience until you try it." Rather than pointing to comprehensive guides (which don't yet exist for this rapidly evolving field), Markus advocates hands-on experimentation. Start with personal projects where stakes are low. Try multiple tools to understand their strengths. Build intuition through practice rather than theory. The field changes so rapidly that reading about tools quickly becomes outdated - but developing the mindset and practices for working with AI assistance provides durable value regardless of which specific tools dominate in the future. About Markus Hjort Markus is Co-founder and CTO of Bitmagic, and has over 20 years of software development expertise. Starting with Commodore 64 game programming, his career spans gaming, fintech, and more. As a programmer, consultant, agile coach, and leader, Markus has successfully guided numerous tech startups from concept to launch. You can connect with Markus Hjort on LinkedIn.

Today's special crosspost features a16z General Partner Anjney Midha with Liam Fedus and Ekin Dogus Cubuk of Periodic Labs. They discuss experiments in training frontier AI models on real-world physics lab experiments—rather than digital reward functions—and how coupling language models with automated materials synthesis could accelerate the discovery of room-temperature superconductors and transform R&D in advanced manufacturing. Shownotes brought to you by Notion AI Meeting Notes - try one month for free at: ⁠https://notion.com/lp/nathan Core innovation: Periodic Labs is creating a "physically grounded reward function" by integrating experiments directly with AI systems. Physical lab integration: Unlike traditional AI labs, Periodic includes actual physical experimentation facilities where AI can run tests in the real world. Novel approach to training: Periodic takes pre-trained language models and further trains them on physics and chemistry knowledge to improve performance in scientific domains. Read the full transcript here: https://storage.aipodcast.ing/cache/combinedtranscript-20251002T100327544Z.html Sponsors: Linear: Linear is the system for modern product development. Nearly every AI company you've heard of is using Linear to build products. Get 6 months of Linear Business for free at: https://linear.app/tcr AGNTCY: AGNTCY is dropping code, specs, and services. Visit AGNTCY.org. Visit Outshift Internet of Agents Claude: Claude is the AI collaborator that understands your entire workflow and thinks with you to tackle complex problems like coding and business strategy. Sign up and get 50% off your first 3 months of Claude Pro at https://claude.ai/tcr Shopify: Shopify powers millions of businesses worldwide, handling 10% of U.S. e-commerce. With hundreds of templates, AI tools for product descriptions, and seamless marketing campaign creation, it's like having a design studio and marketing team in one. Start your $1/month trial today at https://shopify.com/cognitive PRODUCED BY: https://aipodcast.ing

Relax with this calm bedtime reading about the periodic table, perfect for sleep and easing insomnia. Drift off as you learn about the history, structure, and significance of this fundamental tool in chemistry. In this gentle episode, we explore how the periodic table organizes elements, the contributions of scientists like Mendeleev, and the properties that define each group. Benjamin's soothing voice guides you through the facts in a peaceful, thoughtful tone—no whispering, no hypnosis, just calm education to help you relax and unwind. This episode is ideal for relieving stress, anxiety, and sleepless nights. Press play, get cozy, and let your mind settle. Happy sleeping! Read with permission from Periodic table, Wikipedia (https://en.wikipedia.org/wiki/Periodic_table), licensed under CC BY-SA 4.0. Learn more about your ad choices. Visit megaphone.fm/adchoices

Scaling laws took us from GPT-1 to GPT-5 Pro. But in order to crack physics, we'll need a different approach. In this episode, a16z General Partner Anjney Midha talks to Liam Fedus, former VP of post-training research and co-creator of ChatGPT at OpenAI, and Ekin Dogus Cubuk, former head of materials science and chemistry research at Google DeepMind, on their new startup Periodic Labs and their plan to automate discovery in the hard sciences.Follow Liam on X: https://x.com/LiamFedusFollow Dogus on X: https://x.com/ekindogusLearn more about Periodic: https://periodic.com/ Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome to PICU Doc on Call, the podcast where we break down real-life cases from the pediatric intensive care unit and share practical insights for clinicians everywhere! I'm Dr. Monica Gray, and I'm joined by my co-host, Dr. Pradip Kamat.Today, we're diving into a fascinating case: a 13-year-old boy who suddenly developed muscle weakness and was found to have severe hypokalemia. After some detective work, he was diagnosed with familial hypokalemic periodic paralysis, a rare but important condition to recognize in the PICU.We'll discuss the genetic underpinnings, classic clinical features, and common triggers associated with this disorder. Additionally, we'll guide you through the differential diagnosis, key management strategies, such as potassium supplementation, and explain why genetic testing is so crucial. We'll also cover essential considerations for anesthesia and cardiac monitoring in these patients.Whether you're a pediatric intensivist or just interested in acute neuromuscular care, stick around for some practical pearls you can use on your next shift!Show Highlights:Clinical case discussion of a 13-year-old male patient with muscle weakness and hypokalemiaDiagnosis and management of familial hypokalemic periodic paralysisGenetic basis and mutations associated with hypokalemic periodic paralysis (CACNA1S and SCN4A)Physiological mechanisms underlying hypokalemic periodic paralysisCommon clinical presentations and triggers for episodes of muscle weaknessDifferential diagnoses for muscle weakness and hypokalemia in pediatric patientsLaboratory investigations to confirm hypokalemic periodic paralysisTreatment options for hypokalemic periodic paralysis, including potassium supplementation and prophylactic medicationsImportance of avoiding triggers and coordinating care with anesthesiaReferences:Fuhrman & Zimmerman - Textbook of Pediatric Critical Care Chapter 68: Weimer M et al. Acute neuromuscular disease and disorders page 840Rogers Textbook of Pediatric Intensive Care Medicine: Management of Sodium and Potassium Disorders. Pages 1876- 1883Reference 1: Weber F, Lehmann-Horn F. Hypokalemic Periodic Paralysis. 2002 Apr 30 [Updated 2018 Jul 26]. In: Adam MP, Feldman J, Mirzaa GM, et al., editors. GeneReviews® [Internet]. Seattle (WA): University of Washington, Seattle; 1993-2025. Available from: https://www.ncbi.nlm.nih.gov/books/NBK1338/Reference 2: Channelopathies. Clin Exp Pediatr. 2014;57(1):1-18. Published online January 31, 2014**DOI: https://doi.org/10.3345/kjp.2014.57.1.1**Reference 3: Statland JM, Fontaine B, Hanna MG, Johnson NE, Kissel JT, Sansone VA, Shieh PB, Tawil RN, Trivedi J, Cannon SC, Griggs RC. Review of the Diagnosis and Treatment of Periodic Paralysis. Muscle Nerve. 2018 Apr;57(4):522-530.