Podcasts about Locality

I personally subscribe to The Economist. TOE listeners get 35% off the annual subscription. No other podcast has this! https://economist.com/TOE This is a careful lecture that can be followed with zero background knowledge. Einstein thought he'd caught quantum mechanics in an act of spookiness — this podcast asks whether he was even worried about the right thing. Tim Maudlin, professor of philosophy at NYU and a leading philosopher of physics, delivers a rare full lecture tracing Einstein, EPR, and the road to Bell's theorem. The central claim: Einstein's real objection was never determinism — "God does not play dice" is a red herring — but non-locality, which he inferred rather than assumed. Maudlin traces the argument from Einstein's overlooked 1927 Solvay objection through the EPR paper's criterion of reality, showing why Bohr's famous reply never actually answered it. FOLLOW: - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Substack: https://curtjaimungal.substack.com/subscribe - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - Crypto: https://nowpayments.io/donation/TOE - PayPal: https://www.paypal.com/donate?hosted_button_id=XUBHNMFXUX5S4 TIMESTAMPS: - 00:00:00 - Einstein's Quantization Hypothesis - 00:07:20 - Photoelectric Effect Implications - 00:12:30 - Wave-Particle Duality Myths - 00:20:40 - De Broglie's Matter Waves - 00:26:40 - Copenhagen's Completeness Doctrine - 00:34:10 - Solvay 1927: Two Conceptions - 00:41:20 - Pinhole Diffraction Problem - 00:48:00 - Collapse and Relativity Violations - 00:56:00 - Epistemic vs. Ontic Collapse - 01:05:00 - Ontological vs. Dynamical Locality - 01:14:00 - Configuration Space Objections - 01:25:00 - EPR's Criterion of Reality - 01:32:40 - Analyzing the Reality Criterion - 01:40:50 - Causal Isolation and Locality - 01:48:45 - Entangled Momentum Eigenstates - 01:56:45 - Logical Core of EPR - 02:04:40 - Position-Momentum Simultaneous Reality - 02:14:00 - Inferring Determinism from Locality - 02:26:30 - Conservation Laws and Information - 02:37:40 - Counterfactual Definiteness Debunked - 02:44:00 - Bohr's Incoherent Response - 02:52:00 - Schrödinger's Entanglement Confession LINKS MENTIONED: - Quantum Non-Locality and Relativity [Book]: https://amazon.com/dp/1444331272?tag=toe08-20 - On a Heuristic Point of View About the Creation and Conversion of Light [Paper]: https://sites.pitt.edu/~jdnorton/lectures/Rotman_Summer_School_2013/Einstein_1905_docs/Einstein_Light_Quantum_WikiSource.pdf - The Ghost in the Atom [Paper]: https://vdoc.pub/download/the-ghost-in-the-atom-a-discussion-of-the-mysteries-of-quantum-physics-1guq071e2ukg - Collected Papers on Wave Mechanics [Paper]: https://mwolf.pracownicy.uksw.edu.pl/MK/Schrodinger_Collected_Papers_on_Wave_Mechanics.pdf - Quantum Theory at the Crossroads [Book]: https://amazon.com/dp/0521814219?tag=toe08-20 - Can Quantum-Mechanical Description of Physical Reality Be Considered Complete? [Paper]: https://journals.aps.org/pr/pdf/10.1103/PhysRev.47.777 - Bohr's EPR Critique [Paper]: https://journals.aps.org/pr/pdf/10.1103/PhysRev.48.696 - The Present Situation in Quantum Mechanics [Paper]: https://personal.lse.ac.uk/robert49/teaching/partiii/pdf/SchroedingerPresentSituation1935(1980trans).pdf - Bertlmann's Socks and the Nature of Reality [Paper]: https://cds.cern.ch/record/142461/files/198009299.pdf - On the Einstein Podolsky Rosen Paradox [Paper]: https://journals.aps.org/ppf/pdf/10.1103/PhysicsPhysiqueFizika.1.195 - Quantum Theory and Measurement [Book]: https://amazon.com/dp/0691613168?tag=toe08-20 - Tim Maudlin [TOE]: https://youtu.be/fU1bs5o3nss - Sean Carroll [TOE]: https://youtu.be/9AoRxtYZrZo - Robert Sapolsky [TOE]: https://youtu.be/z0IqA1hYKY8 - Jenann Ismael [TOE]: https://youtu.be/7kvXihDAOi0 - John Norton [TOE]: https://youtu.be/Tghl6aS5A3M Guests do not pay to appear. #science Learn more about your ad choices. Visit megaphone.fm/adchoices

We've been running a bit of an Agent Cloud series surveying all the top inference/compute/cloud providers, from Databricks to Daytona to Railway and, even further back, E2B, but we're excited to conclude this series returning to Modal, which has just raised a monster $355M Series C.The cloud was built for developers. But agents are now changing that.The old infra stack was designed for a human who could read docs, reason through YAML, and understand dashboards to figure out what they need when something broke. While this was painful for developers, it worked since they could fill in missing context in their heads.However, agents don't have that luxury. Now in this new era of agents, everything has to be tighter.They need a place to write code, run it, inspect the output, change the environment, debug failures, and try again. Fast iteration and feedback loops with all the necessary context are crucial for agents to operate properly. Furthermore, sandboxes are a clear representation of this shift as agents can easily spin up isolated environments. This programmatic infra even extends to research:Two years ago, we were one of the first to cover Modal with CEO Erik Bernhardsson and Alessio designed our favorite LS thumbnail of all time:At the time, Modal was just a teeny little company with a $17M Series A.Today, fresh off their $355M Series C, Modal is one of the clearest examples of the agent cloud future being built in real time: a cloud platform moving past traditional web app assumptions toward the workloads AI actually creates such as elastic inference, sandboxes, GPU burst, post-training, background agents, and infrastructure that agents themselves can operate.In this episode, Modal CTO Akshat Bubna joins swyx and Vibhu to unpack why AI applications don't fit traditional cloud assumptions, why Kubernetes was never designed for bursty compute-heavy workloads, and why Modal is now shifting from developer experience to agent experience.We go deep on Modal's AI infra stack: serverless functions, decorator-based infrastructure, elastic inference for custom models, GPU snapshotting, DeFlash, speculative decoding, Auto Endpoints, sandboxes, persistent storage, networked containers, private IPv6, RDMA, multi-node training, and Modal's capacity pool across 17 cloud providers. Akshat also explains why RL rollouts can require 100,000 sandboxes, why production agents need hard guardrails, why observability may matter more than reading code, and why AI has made infrastructure exciting again.We discuss:* Why Kubernetes wasn't built for bursty AI workloads* How Modal started as a better runtime before becoming an AI cloud* Why Modal added GPUs before ChatGPT* The shift from developer experience to agent experience* Why observability matters when agents are writing the code* Elastic inference for custom models across audio, video, robotics, and comp bio* GPU snapshotting, cold starts, and why inference workloads are so bursty* Why RL rollouts can require 100,000 sandboxes* DeFlash, speculative decoding, and frontier-level inference performance* Auto Endpoints and making optimized inference easier to deploy* What Modal adds beyond vLLM, SGLang, and raw GPU rental* Modal's 17-cloud capacity pool and supercloud strategy* Networked sandboxes, sidecars, private IPv6, and RDMA* Serverless multi-node training for post-training and research workloads* Auto-research, model-guided sweeps, and agents launching GPU experiments* Compute strategy, capacity planning, and batch tiers* Why production agents need specialized sandboxes and hard guardrails* Modal's take on managed agents, CI, Gitpod/Ona, Python, TypeScript, and Modal BenchAkshat Bubna* LinkedIn: https://www.linkedin.com/in/akshat-bubna-188885103* X: https://x.com/akshat_bModal* Website: https://modal.comTimestamps00:00:00 Introduction00:00:39 Modal's origin and why Kubernetes wasn't enough00:04:32 Developer Experience → Agent Experience00:06:21 Modal's AI cloud primitives00:09:14 Sandboxes, agent loops, and proto-Cognition00:12:12 Elastic inference, GPU snapshotting, and 100,000 sandboxes00:15:24 DeFlash, speculative decoding, and Auto Endpoints00:19:59 Production-grade inference beyond raw GPUs00:22:00 Background agents, Ramp Inspect, and the agent lifecycle00:24:08 Modal's 17-cloud supercloud strategy00:26:40 Networked sandboxes, private IPv6, and RDMA00:32:48 Multi-node training, post-training, and auto research00:37:36 Compute strategy, capacity planning, and batch tiers00:40:55 Open models, real-time AI, and production agent infra00:43:06 Hard guardrails, managed agents, and specialized sandboxes00:46:06 Why AI made infrastructure exciting again00:48:30 Model APIs, differentiated products, and agentic video00:51:50 CI, coding-agent infra, SDKs, and Modal Bench00:57:28 Closing ThoughtsTranscriptIntroduction: Modal, Series C, and the Art PartySwyx [00:00:00]: We're here with Akshat, CTO of Modal, together with Vibhu. Congrats on your Series C.Akshat [00:00:10]: Thank you.Swyx [00:00:11]: Your party yesterday was amazing.Akshat [00:00:15]: Yeah.Swyx [00:00:15]: From all the photos and all the swag.Akshat [00:00:17]: We had a bunch of art installations, which was fun, seeing, like, our products on pedestals next to, like, Rodin.Swyx [00:00:25]: Very nice. Very nice. When you started, it was not the GPU inference company. Maybe it was in your mind. Take us back to the origin story.Modal's Origin: A New Runtime Beyond KubernetesAkshat [00:00:39]: I first met Eric, who's the CEO, through an investor. Back then Eric was already thinking about building, a new runtime, and he got there thinking through why are workflow orchestration products so hard to use. It's because you have to run them on Kubernetes. Kubernetes is hard to manage. It's not built for burstiness and, custom images,Swyx [00:01:03]: YeahAkshat [00:01:03]: It has a terrible developer experience.Swyx [00:01:05]: And I'll, I'll interjectAkshat [00:01:06]: YeahSwyx [00:01:07]: For listeners, who are new, we interviewed Eric two years ago, and there's a bit more of the story there from Spotify and all those things.Swyx [00:01:14]: And I came across Eric through Data Council because he did that talk on the serverless container stack that you guys did, which was like, that was my first like, “Okay, I need to take Modal very seriously” moment.Akshat [00:01:26]: Yeah.Swyx [00:01:26]: But it was still very unclear, like, do I need all this for just my data pipelines?Akshat [00:01:33]: Yeah. initially what we were thinking about was if we build a better runtime, it's a very useful primitive in itself. It's There's a lot of things that, get solved by serverless functions, like you can do, ETL stuff, you can do job queues, you can do all this, like, bursty processing, which it turns out every company had needs for. but then we also were thinking about this as like, this is a primitive that we can build a whole collection of products on, which are very verticalized. So perhaps data engineering would've been the first one, but we were thinking about inference. Back then it was more classical inference, like computer vision stuff and running XGBoosts and whatnot. But we added GPUs to the product a year before ChatGPT came out.From Serverless Containers to GPU WorkloadsSwyx [00:02:19]: Nice.Akshat [00:02:19]: We just didn't think it would be that big of a deal.Swyx [00:02:22]: Yeah, just like add A100.Vibhu [00:02:23]: Was there any, like, early key problem that really sparked off why you built it?Akshat [00:02:28]: Yeah. Primarily it's just, none of the tooling that was out there was built for, one, a really great developer experience, and also there's a general trend of, a lot of the workloads that we were seeing were very. I wish there was a better word for it, but compute-heavy. Like, they need, one, like, need a lot more resources, so you need to burst up and down a lot, versus like Kubernetes designed for, like, slow scaling and, more for, like, web server use cases. And also there's just a lot more specialization in, like, what kinds of environments these workloads run in. Like, we had sometimes they need accelerators, sometimes they need different kinds of images, and this is just like a consistent thing that we saw across a lot of companies. That would be the next step.Software-Defined Infrastructure and Decorator-Based DXSwyx [00:03:13]: Yeah. Yeah. Be nice. I don't know how much this factored into the early story, but I wrote a post when I was at Temporal about infrastructure, software-defined infrastructure or something like that.Akshat [00:03:22]: Yeah, the self-provisioningSwyx [00:03:23]: Self-provisioning.Akshat [00:03:24]: Yeah.Swyx [00:03:24]: Yeah. I can't even remember my own post.Swyx [00:03:26]: And then you put me on the landing page.Akshat [00:03:28]: Yeah. We really like, the term and so we stole it.Swyx [00:03:32]: Because you had the insight that everything can just be in decorators co-located with the code, right?Akshat [00:03:37]: Yeah.Swyx [00:03:37]: Was that a big part of the originalAkshat [00:03:39]: YesSwyx [00:03:39]: Story or it was just like a DX layer?Akshat [00:03:41]: That was, really important because we really didn't want people to spend, so much time, writing YAML, and it seemed like you could really condense the surface area of what you're doing, put it in code so you can operate on it just like you operate on other code, and like build stuff that's more expressive and dynamic. and so yeah, that was always a very important part.Swyx [00:04:04]: Then the pushback is this is a DSL.Akshat [00:04:07]: Yeah.Swyx [00:04:07]: It's you're closed source. I am locked into Modal.Akshat [00:04:11]: Yeah. We never really got pushback for that because the nice thing about Modal is you can bring whatever code you have, and sure, the DSL is at the configuration layer for, what hardware you're using, how you're scaling things up, but you still own the code.Akshat [00:04:27]: And that's, that's been an important, part of our story, even as we do inference now.Swyx [00:04:32]: Yeah.Vibhu [00:04:32]: How much of do you think still stays the same today? Like if you were to build something today, DevX very important, but I feel like, a lot of this has been changed with just hook it up to an agent, have Claude Code, have Codex implement a tool. there's very agent native primitives that are different than if I'm doing this myself, right?Developer Experience → Agent ExperienceAkshat [00:04:54]: We've changed our SDK team to think about agent experience instead of, developer experience and we think that the same benefits that apply for DX also apply for AX, which is why would you have an agent read through hundreds of Kubernetes files and like write YAML that's not even typed when it can make a couple of changes in a decorator and it gets this self-provisioning runtime of, being able to see its changes live in action? yeah, it just seems from the customers we talk to, they find Modal is much faster for agents to use versus operating on a different substrate.Swyx [00:05:34]: Yeah, because like you, again, you co-locate the infrastructure requirements to the code that runs it.Akshat [00:05:38]: Yeah.Swyx [00:05:38]: Well, the negative thesis now is that nobody's looking at their code anymore, so there's no point.Akshat [00:05:44]: Yeah, people aren't looking at code. one thing we still see is really important is observability.Swyx [00:05:51]: Yeah.Akshat [00:05:51]: Like how good is your dashboard? And of course, like we have, we push a lot of it to the CLI so the agents can do their own investigation, but you still need humans to go interpret what's going on and, make judgment calls and whatnot. and that's I feel like, Maybe more important now than looking at the code itself.Swyx [00:06:11]: Yes, because like, you can try to treat the code as a black box and then use, see the observable action that comes out of it, and then just prompt a change.What Modal Is For: AI Cloud PrimitivesAkshat [00:06:21]: Yeah.Swyx [00:06:22]: So I think it takes a bit of restraint to not specialize, to say, “I want to ship a new primitive,” and then just be general purpose.Swyx [00:06:31]: People ask you, “What are you for?” You're like, “ I don't know. We can do this, we can do that.”Vibhu [00:06:36]: Well, I'd be curious to see, like, okay, if we were to ask you, like, what is Modal for even at a high level? There's a lot you guys do, sandboxes, GPUs, everything. How do you answer?Akshat [00:06:46]: Modal is a cloud platform that's built for, where we've built the primitives from scratch for AI applications. and right now it covers, inference, training, batch processing, and sandbox workloads.Akshat [00:07:00]: But we're building a lot moreSwyx [00:07:02]: I noticed you didn't say web server, so there is still a role for, like, the always-on large-scale Kubernetes type things.Akshat [00:07:09]: Yeah, absolutely. We're, we're not trying to compete with the renders of the world, because yeah, we think the differentiator for us is the, are the workloads that need specialized compute, need to scale up and down a lot. yeah, they're, they're, they're just shaped differently.Working Alongside Frontier StartupsVibhu [00:07:26]: I think you're building a lot of it alongside the startups, right? They're innovating quite a bit, even in your, like, latest blog post. Like, even in the series C, the customers that you mention here, the cognitions, technical ones, ramps and whatnot, they're, they're innovating with you, right? And that's not something AWS is doing directly with.Akshat [00:07:45]: Yeah, absolutely. I think, this is again classic. We're a small team. We can move really fast. our engineers are working with our customers and figuring it out. Yeah.Swyx [00:07:54]: So my first week at Cognition, I walked in, there was someone wearing a Modal shirt. I was like, “What are you doing here?” They're like, “Yeah, I just. I am embedded inside of Cog.”Akshat [00:08:05]: Yeah, I think that was Peyton. We sent him overSwyx [00:08:07]: Yeah.Akshat [00:08:07]: Because, the latency of communication was too high otherwise.Swyx [00:08:12]: Yeah, distributed node, you have to - you have to place one and collocate.Vibhu [00:08:16]: Yeah.Swyx [00:08:16]: So I had a, I had direct personal experience, right? So I worked on smol developer three years ago. it was inspired by Claude 1. I think you onboarded me at some point, like, just before, and I was like, “Oh, like, I need some bursty compute. Like, I was just gonna try using Modal.” And it was a, it was a pretty pleasant experience. apparently, I showed up in the board meeting, like the analytics.smol developer, Sandboxes, and Proto-CognitionAkshat [00:08:39]: Yeah, you blew up on Hacker News and,Swyx [00:08:41]: YeahAkshat [00:08:41]: We got a big traffic spike. I. I think the way you used smol developer was Modal functions for running stuff, which was. Like, the, that was a good use case. but then, yeah.Swyx [00:08:53]: Yeah. That - So to me, that was proto-cognition.Akshat [00:08:55]: Right.Swyx [00:08:56]: If only I had, like, stuck to it.Swyx [00:08:58]: Like, that was like, if - did you say draw the tech treeAkshat [00:09:00]: AbsolutelySwyx [00:09:00]: You're just like, “Yeah, like, probably this will happen.”Akshat [00:09:02]: Yeah. Like, he was so close. You were just rebuilding upon usSwyx [00:09:04]: I just didn't realize.Akshat [00:09:05]: But the funny story there is at the same time, we were talking to a bunch of customers who needed something like sandboxing.Swyx [00:09:14]: Yeah.Akshat [00:09:14]: This is like twenty-three.Swyx [00:09:15]: Yeah.Akshat [00:09:16]: So we builtSwyx [00:09:17]: You introduced a new API right after that.Akshat [00:09:18]: Yeah.Swyx [00:09:19]: Yes.Akshat [00:09:19]: Like, we built sandboxes in May of twenty-three before anyone was even knew this was gonna be a thing. And the first example we published was, we took smol developerSwyx [00:09:28]: Smol developerAkshat [00:09:28]: And put it in a loop, so the agent can iterate on itself.Swyx [00:09:33]: Loops are hot these days.Vibhu [00:09:34]: It's the looper.Akshat [00:09:34]: Yeah.Vibhu [00:09:35]: Loops in. When was this, twenty-three?Akshat [00:09:38]: Yeah.Vibhu [00:09:39]: A small check.Akshat [00:09:39]: Yeah.Swyx [00:09:39]: It's like twenty-three. so the. the, those for listeners, like, the problem was the models are not built for any of this, right?Swyx [00:09:46]: Like, you're just trying to like. They're not post-training to understand, like, looping and, like, self-correction and tool calling was there, but, like, also not that great.Akshat [00:09:55]: Yeah.Akshat [00:09:55]: I don't remember if you used tool calling in this one, but yeah, the models would just diverge after like ten iterations and not produce anything meaningful.Swyx [00:10:03]: Yeah. But like, then. So okay, like now talking to myself three years ago, the answerVibhu [00:10:08]: Of course they will get betterSwyx [00:10:09]: Collect all the failures, build benchmark, and then collect all the, examples, build the RL environmentAkshat [00:10:15]: RightSwyx [00:10:15]: Sell it for like ten billion dollars to Meta.Swyx [00:10:17]: And then also train a model and then sell that for sixty billion dollars to Elon. And this isAkshat [00:10:23]: Yeah, of courseSwyx [00:10:23]: The funny machine. Like, it's like, it's about the hardware.Akshat [00:10:28]: It's hard to have that inherent conviction that the stuff will get that much better.Swyx [00:10:33]: In retrospect, it's so f*****g obvious.Akshat [00:10:36]: Fair enough.Swyx [00:10:37]: Like, what else were we doing back then? I don't know. anyway. Yeah. So this. That was the start of your sandboxing journey, right? I feel like it didn't blow up until, like, last year.Akshat [00:10:49]: Yeah.Swyx [00:10:50]: So there was like a couple years of quietness.Akshat [00:10:52]: Exactly, yeah. We wereVibhu [00:10:53]: I think very underrated product value. Like, my experience with Modal, Charles, before he had joined Modal, met this guy at a hackathon, and he really insisted we wanted to run some small model, not hosted anywhere, and he's like, “ there's this cool company, Modal. They'll like spin up a GPU sandbox, we can throw it on there. They'll take a Hugging Face link.” And like there's so much value just right there, right? Like instant hosting, spin it up, spin it down. It'll stay cold, but we run the demo a few days later, it'll come back up and like all this stuff in retrospect, like it's still what we needed like today.Akshat [00:11:27]: Yeah, it's still needed today. workload shapes have changed a lot as, we run stuff for people with really massive production scale and, there it's it's not about scaling from zero to one, but it's how do we scale really elastically, from like thousand to fifteen hundred GPUs very quickly in a given region. It's the same shape problem.Elastic Inference, GPU Autoscaling, and Custom ModelsVibhu [00:11:50]: Okay. So you look at, say, Cursor Composer, right?Akshat [00:11:53]: Yeah.Vibhu [00:11:53]: They had a. “We'll do RL on a model every couple hours.” you guys have a whole version of RL inference gym and whatnot.Vibhu [00:12:01]: When you look at workloads like that, you're doing train runs where you need to scale up, scale down every hour thousands of GPUs, right? That's the example for we do need it, right?Akshat [00:12:12]: Yeah. Well, so I'll, I'll take a step back and, maybe talk about like how people use Modal today. because our biggest use case is, elastic inference. And the thing we first found product market fit, with was inference for custom models. So we stayed away from the LLM space, and we were serving companies like Suno for audio, Runway for video, robotics, comp bio companies that train their own model elsewhere. But Modal is the best black box that for deployment, scaling to however many GPUs you need as your traffic pattern changes. And we saw all of them like have a very unpredict- predict- predictable, traffic pattern. it's like diurnal. It's Some days, like the company will do a launch and, they'll need like, way more. And it's not just one model that they deploy. They-- all these companies deploy, lots of different models in different regions, and so the autoscaling problem becomes even harder because then you have to scale within a certain region, and those cycles are offset. So different times you scale up in different regions.Akshat [00:13:20]: So that's like our sortVibhu [00:13:22]: And thatAkshat [00:13:22]: YeahVibhu [00:13:22]: That in and of itself is a huge category. There's a bunch of inference providers which, provide this fireworks, does this as a service together, whatnot, Base10. that's carved into its own niche for language models, at least right now.Akshat [00:13:36]: Yeah. the thing that we have specialized in is the autoscaling aspect.Vibhu [00:13:41]: Yeah.Akshat [00:13:41]: Because we found that it's not universally true that everyone else can autoscale, and we've gone deeper into it on the tech side by, we've incorporated GPU snapshotting into the product so we can take the GPU state, like your torch.compile model, snapshot it, and the next cold start is way faster. And so going back to your question, it's That's why you need a lot of burstiness for inference. But then people also do a lot of demand training, like for RL stuff, your rollouts are bursty, as you said. People also do a lot of batch jobs. So we'll see, a lot of companies, before they have a training run, they'll need thousands of GPUs to run encoding or something like that. And I think those things are much more bursty than. I agree that agents are not that bursty. sandboxes are, except when you're doing RL. RL is justRL, Batch Jobs, and 100,000 SandboxesVibhu [00:14:28]: Or commerceAkshat [00:14:28]: Insanely bursty.Vibhu [00:14:29]: Yeah.Akshat [00:14:30]: Yeah. Like when you're doing, rollouts, you sometimes need a hundred thousand sandboxes in your sandboxes.Vibhu [00:14:37]: Yeah. I'm curious if you've seen early sparks of continual learning. There are some people, like our friends, ngram, recently announced thisAkshat [00:14:45]: YeahVibhu [00:14:45]: They're, they're trying to do training. That also seems like a different workload, right? If you're doing training twenty-four/seven per se, there's a very weird dynamic of how you're using GPUs between people and whatnot, but seems like something you guys would work for.Akshat [00:15:00]: As you said, we're, we're fortunate to work with a number of, customers at the frontier and grab some of our customers. and they are taking the primitives we have, and trying to use them in very interesting ways, like continual learning. It's possible as the stuff gets better, some of that will be part of, our offering as well if, more people need it. but we're, we're just waiting to seeVibhu [00:15:23]: YeahAkshat [00:15:23]: How it shakes out.Vibhu [00:15:24]: Is there a primitive that you added after sandboxing that was the next step in the story?LLM Inference, DeFlash, and Speculative DecodingAkshat [00:15:32]: I guess we've been going much deeper into LLM inferenceVibhu [00:15:35]: YeahAkshat [00:15:35]: Because we realized that some of the advantages we have with like autoscaling, again, especially in different regions and whatnot, are, not present elsewhere. and the place where we had a gap was we weren't, working on the model layer itself. Like we were a black box. And, we realized that, we can get to frontier-level model performance, with, by having great people who work on this. And, we've been open sourcing a lot of our work, in terms of, Recently, we, shared our work on DeFlash, which is a block-based, speculator, and we've open sourced, all of it. So, you can - By using open source DeFlash, you can get the same performance as you would with one of the proprietary providers. And the next thing we're thinking about hereVibhu [00:16:23]: I thought this wasAkshat [00:16:24]: YeahVibhu [00:16:24]: An interesting blog post as well, right? Like, I think in here you make a claim that. Not a claim, just that how effective speculative deco-decoding really just get to.Akshat [00:16:33]: Yeah.Vibhu [00:16:33]: Anything you wanna point out from this around, what people should know?Akshat [00:16:39]: Yeah, absolutely. the high-level summary is, it would help to describe what speculative decoding is.Vibhu [00:16:44]: Yes.Akshat [00:16:44]: I will, yes.Vibhu [00:16:45]: I think, likeAkshat [00:16:46]: YeahVibhu [00:16:46]: So we've covered like Eagle and all thisAkshat [00:16:47]: YeahVibhu [00:16:47]: Like Hydra and all those things, but it was like two years ago.Akshat [00:16:51]: Yeah.Vibhu [00:16:51]: I think it doesn't hurt, right?Akshat [00:16:52]: Yeah. Speculative decoding is you have a smaller model, called a draft model, predict tokens ahead of the bigger model, and then you have the bigger model, verify all of this, all the tokens are predicted. And the reason it's faster is if you're predicting, one token at once, you're bound by memory bandwidth. But if you can batch the verification of, the draft model, then you're much more efficient using compute, and it's faster, and as long as your draft model is producing a lot of tokens that can get accepted, which is called the accept length, you can get a speed up that's, multiple times of, the original model speed. and well, that's what we highlight here. It's Like people talk a lot about we made these kernels faster and whatnot, but improving kernel will only give you like few percentage points of improvement, and, increasing accept length, literally is a multiplicative decreaseVibhu [00:17:47]: Like two to four X.Akshat [00:17:48]: Yeah, exactly.Vibhu [00:17:48]: Without much head-on performance.Akshat [00:17:50]: Yeah. I think it may - you are running a second model, right? So it may be something more expensive in the compute,Vibhu [00:17:57]: I meant quality performanceAkshat [00:17:58]: Probably not by muchVibhu [00:17:58]: But yeah. I thinkAkshat [00:17:59]: So there's no drop in quality performanceVibhu [00:18:01]: YeahAkshat [00:18:01]: Because you're always. You're never accepting a token that the big modelVibhu [00:18:04]: It's strictly betterAkshat [00:18:05]: YeahVibhu [00:18:05]: Or it's same.Akshat [00:18:06]: Exactly.Vibhu [00:18:07]: Right. Yeah.Akshat [00:18:08]: And so we've been working a bunch on DeFlash, which is a block-based speculator. so it's instead of predicting, one token at a time, it's predicting a block. And we've been open sourcing our work with it. The next thing for us here is for helping people train speculators and custom models. it's it's something that traditionally is very forward-deployed engineering driven, support deployed, engineer driven, like you work with customers and help them do that. And our vision for. This is why we launched Auto Endpoints, is we want to make frontier-level performance available to everyone. And so, we mentioned this in the announcement, we teased it. The next thing we're, we're launching is, as you run an auto endpoint, we shadow trafficAuto Endpoints and Frontier-Level PerformanceVibhu [00:18:54]: Do you want to explain what auto endpoints are?Akshat [00:18:57]: Yeah.Vibhu [00:18:57]: I lovely, yeah.Akshat [00:18:58]: Yeah. So, this is, I guess, going back to your Modal is you touch the code, but, sometimes people don't wanna touch the code, and they wanna get started with an endpoint that works and has all the great performance and, scalability that Modal has. So we've made that easier with, a way to create an endpoint from our UI, from the CLI, that has all of our optimizations that we talked about, like the DeFlash stuff already baked in, and there's full transparency. So we give you the code, you can go run it yourself, and if you want, you can eject out into the full Modal experience, which we see as people get sophisticated, they do wanna tweak the models, they wanna, fine-tune stuff. You can still do all of that. It's it's not a black box. And yeah, the next thing, as we teased later in the post, is how do we give you value even beyond this in terms of having your draft models evolve as your data distribution evolves, again, without having to talk to a person and, yeah.Vibhu [00:19:59]: I guess just to understand it directly, you have the GPUs, you have an endpoint that's compatible, you serve open model. If someone was to do this themselves, what's the delta that you guys provide? So you do a lot of open source great work on effective inference. how does it compare to, say, I take the same model, 5.2 FP8, take shelf inference engine, vLLM, SGLang, get compute of similar capacity, similar cost. What's the delta that plugging into something this, like this offers outside of the benefit of, scaling?Production Inference Beyond Raw GPUsAkshat [00:20:34]: It's interesting because we've taken the approach of open sourcing our contributions and upstreaming them. we work closely with the SGLang team. We want the improvements that our team, comes up with to be, there in open source for others to use, even outside of Modal. The benefit to us is we have a team that has significant expertise in terms of if you do have something that is not there, our team can help you get that performance, first. the other thing is with these endpoints, we are way more elastic, as you said, than, anyone else, and you have true scaling to zero. you have true, burstiness, and in practice, that matters a lot more to people than just finding, the GPU and, running Modal code on something.Vibhu [00:21:20]: Yeah. And I will say it's not that straightforward to just. like what I said is easier said than done, right?Akshat [00:21:26]: Yeah.Vibhu [00:21:27]: It's I think still for the average person, still hard to just gut check using different. There's, there's quite a bit of combinations you can make there. the trade-offs aren't really known at face value.Akshat [00:21:40]: Yeah. it's it's not just that. I think it's it's that running production-grade inference is a hard infer problem.Vibhu [00:21:49]: YeahAkshat [00:21:49]: Even if you subtract out the autoscalingVibhu [00:21:50]: YeahAkshat [00:21:51]: Is controlling things like tail latency and, making sure every, request is delivered at least once and whatnot.The Model and Agent LifecycleVibhu [00:22:00]: There's a lot of innovation that you can do here. I think, it's very interesting that you're starting to encroach on, like as you become a full cloud, you're starting to encroach on other people's turf.Vibhu [00:22:09]: What will you not do?Akshat [00:22:13]: Well, we wanna follow our users and, make sure they get like a platform that has everything that works well together. so right now we're focused on the model lifecycle and the agent, lifecycle. so both like going from data prep to training to inference, and then also if I want to deploy a background agent, let's say, sandbox, do persistent storage, a whole bunch of other stuff.Vibhu [00:22:38]: We talked to Cole, who did, OpenInspect. Yeah.Akshat [00:22:42]: Yeah.Vibhu [00:22:42]: And RealInspect also is on Modal.Akshat [00:22:44]: Yeah. So Ramp Inspect was a great example of a background agent that was really successful because they, were able to use some of the primitives like snapshotting and fast scaling to just have something that feels really reactive and works well.Ramp Inspect and Background AgentsVibhu [00:23:02]: Yeah. That's the new CTO of, Ramp right there.Akshat [00:23:05]: Yeah, Rahul.Vibhu [00:23:08]: It was really fun. yeah, okay, I think, all very bullish. Like, one of my reflections was also I did not originally. So when I met you guysThe Inference Inflection: CPU, GPU, and Co-LocationVibhu [00:23:19]: You weren't that much in the GPU game, and now you're all about, inference. And one of the points that I hinged on for Jensen's keynote at GTC this year was, what we're calling like the inference inflection, right? That let's say in AI workloads or machine learning workloads, it used to be like, let's call it eight to one GPU to CPU, and now it's more like one to one, which is like a interesting. Like, - because of how much agents are blocked or call out to this, to CPU heavy stuff the actual, like, limiting factor, like, swings back and forth from GPU to CPU a lot more than it used to be all GPU and then occasional CPU.Akshat [00:24:01]: Yeah.Vibhu [00:24:02]: GPU, CPU. And now it's like just constantly, and you just have to locate everything.Seventeen Clouds and the Supercloud StrategyAkshat [00:24:08]: Yeah. And that's one of the things that, again, we see as, something appealing about Modal, which is we've built this capacity pool that spans, 17 cloud providers, so we're, we're very good at Running on various kinds of cloud capacity across the worldSwyx [00:24:24]: You don't have your own data centers?Akshat [00:24:25]: We don't have our own data centers. We just run across a lot of neo cloudsSwyx [00:24:29]: Yeah. AreAkshat [00:24:30]: Metal providers.Swyx [00:24:30]: Yeah. Question mark.Swyx [00:24:31]: Yeah. You're, you're running the math, and you're like, “What's the cutover point where you're like.”Akshat [00:24:36]: Yeah, it's a good question. part of it is we see our differentiator in the software layer, and, being capital light and focusing on the software helps us move really fast. so far it's worked out well because there are so many other people building data centers that we're able to work effectively with them, and again, focus on what makes us, special.Swyx [00:24:55]: Yeah.Swyx [00:24:56]: 17 gets you into, like, the local providers sometimes. LikeAkshat [00:25:00]: The,Swyx [00:25:01]: Which was the most interesting one?Akshat [00:25:02]: There are a lot more neo clouds than you expect, and they all have various degrees of, various levels of reliability. And, that's why it's something we've invested a lot of time in, is building our own reliability layer on top. so if the GPU falls off the bus or something happens, we user workloads are not affected, and that lets us use a lot more capacity than,Swyx [00:25:30]: YeahAkshat [00:25:30]: You as a user would be able to.Swyx [00:25:32]: It's a useful thing to have because like now everyone knows, like, what layer you are and, like, you optimize for being the super cloud of all clouds.Akshat [00:25:41]: Yeah. That's, that's, that's the idea. and so I guess when you mentioned colocation, that's, that's another interesting thing where, one thing we've seen is people come to us when they want, very specifically located, CPUs or GPUs, like they wantSwyx [00:25:57]: Oh, they pin it in likeAkshat [00:25:58]: YeahSwyx [00:25:58]: EU?Akshat [00:25:59]: Exactly. Or EU, US.Swyx [00:26:01]: Right. Data resiliencyAkshat [00:26:02]: AustraliaSwyx [00:26:02]: Locality thing or performance or what?Akshat [00:26:04]: It's either data locality or latency, yeah.Swyx [00:26:07]: Yeah.Akshat [00:26:07]: Like, you want your. They're running sandboxes and model. They want them to be right next to aSwyx [00:26:10]: Yeah, it's easy thenAkshat [00:26:11]: YeahSwyx [00:26:12]: To. That is important in all those things. and so, like, you've accidentally, I don't know if it's accident, but, like, you've built the perfect primitive for agents to express themselves. And then, like, it's almost very funny how every extra development just involves more file system, just involves more CPU.Akshat [00:26:30]: Yeah.Swyx [00:26:31]: Just like the things that you already have. I don't know much about, if there's any, like, networking usages that are interesting, but you've also done some good work on networking.Networking, Sidecars, Private IPv6, and SandboxesAkshat [00:26:40]: Yeah, that's exactly right. Like, we're just taking compute storage and networking and building stuff on that layer, for, again, the stuff people need.Swyx [00:26:49]: YeahAkshat [00:26:50]: We see a few interesting networking things coming up. one is people want networked sandboxes. so we haveSwyx [00:26:57]: For like a Docker cluster type thing.Akshat [00:26:59]: Yeah.Swyx [00:26:59]: Sorry, Docker Swarm. Oh, f**k. What is it called?Akshat [00:27:02]: Compose.Swyx [00:27:03]: Compose type thing.Akshat [00:27:04]: Yeah. So if you want Docker Compose, our sandboxes now support, this thing called sidecars. So you can. A sandbox is a pod of containers, and you can run multiple containers in, a sandbox. also useful because, going back to networking, people want a lot of control over, outbound networking from a sandbox.Swyx [00:27:23]: Yeah.Akshat [00:27:23]: Like, they might wanna run a middle proxy for, like, maybe logging stuff for RL or, controlling how egress can happen to a domain, injecting credentials. and yeah. So we've, we've had to build a lot of that stuff ourselves.Swyx [00:27:38]: Yeah.Akshat [00:27:39]: But then also sometimes people want, sandboxes spanning multiple nodes to talk to each other, which is an emerging thing we're seeing. We have support for that for a different reason, and yeah, we'll see if that becomes stable.Swyx [00:27:52]: Like, just an open socket. It's a. This is directly like mTLS.Akshat [00:27:56]: We do support that, which is you can, expose a tunnel inside a sandbox.Swyx [00:28:01]: Yeah.Akshat [00:28:01]: And then you can either expose it to public internet or it can be, you can add like a HTTP, auth layer above it. But we have this thing called I6PN, which we haven't talked about, which is this, like, overlay network using IPv6 addresses. so if Modal containers, within the same workspace, when this is enabled, can address each other using this private IPv6 address, and no one else can.Akshat [00:28:28]: So it's like private networking, for containers. We built it because we needed it as a primitive for our distributed training product. so we have this other feature, which is you can add a decorator to a function, and you get a cluster of GPUs. and they have RDMA networking. so you can run a distributed training job, that's truly serverless. and we did the overlay network for that. But then we've seen that people are using it for other reasons, and, I'm intrigued to yeah, what would people do with it.Swyx [00:28:59]: Build primitives and let people figure it out, right?Akshat [00:29:01]: Yeah, exactly.Swyx [00:29:02]: You put out a pretty interestingAkshat [00:29:03]: They're like, they read the docs webpage. Let me use thatSwyx [00:29:06]: YeahAkshat [00:29:06]: Something they never intended to work. This is literally not even in our docs page. People somehow found it, and they're using it.RDMA, Memory Movement, and Distributed TrainingSwyx [00:29:12]: Huh.Swyx [00:29:14]: The way you portrayed it with, like, RDMA versus TCP, like, very well laid out, but just the transfer speed change at scale for RL, like yeah, you have it, you have it built in. I'm sure someone found it. It's found it to be a lot more efficient before you made a thing out of it, right?Akshat [00:29:32]: Yeah. And not to split hairs, I guess the overlay network is the TCP overlay network.Akshat [00:29:39]: The reason we have that is you need that to do the key exchange for RDMA before you set up the RDMA network on top of that. but then people found the TCP part.Swyx [00:29:48]: Can I tell you, this is like a big aha moment for me becauseAkshat [00:29:51]: YeahSwyx [00:29:51]: So I review 2,200 submissions for the World's Fair.Akshat [00:29:56]: Yeah.Swyx [00:29:57]: And then I got this from John OsterhoutAkshat [00:29:58]: HuhSwyx [00:29:59]: Who I don't know if. Do John Osterhout by name?Akshat [00:30:01]: The name sounds familiar.Swyx [00:30:02]: He published a. He's a well-known professor, published a lot of interesting software design books, and this is the talk he chose to submit, is on RDMA at Inference. And I'm like, you wouldn't think that this guy, who is like operating systems guy, would care about RDMA.Akshat [00:30:20]: I, it makes sense to me because I,Swyx [00:30:24]: This is the cloud, right? YeahAkshat [00:30:25]: Like, the way you move around your KV cache and how efficiently you can do it, how efficiently you move, your weights from your training GPUs to your inference GPUs in RL is there's a lot of degrees of freedom, and it is a systems problemSwyx [00:30:41]: YeahAkshat [00:30:41]: Moving memory aroundSwyx [00:30:42]: YeahAkshat [00:30:43]: Scheduling.Swyx [00:30:44]: This shows you how primitive my understanding of networking stuff is.Swyx [00:30:46]: Is this like the domain of WireGuard as well?Akshat [00:30:50]: Not quite.Swyx [00:30:51]: It's adjacent?Swyx [00:30:53]: Explain everything.Akshat [00:30:54]: Sure.Swyx [00:30:56]: How do we move memory around GPUs?Akshat [00:30:58]: Well, so sorry. Yeah, that is memory. Sorry, I was talking more, and maybe I was talking like five minutes back, about the private IPv6, addressing that you've set up.Swyx [00:31:09]: Yeah.Akshat [00:31:09]: Is it like it's a VPN?Swyx [00:31:10]: Yeah, it is like a VPN, and yeah, WireGuard is, yeah, you're right. It is,Akshat [00:31:16]: Right. Yeah, you already moved on to new topicsSwyx [00:31:17]: A similarAkshat [00:31:18]: OkaySwyx [00:31:19]: In the same space, WireGuard is, encrypted and this is,Akshat [00:31:23]: And you don't need encryption.Swyx [00:31:23]: Yeah.Akshat [00:31:24]: Yeah.Swyx [00:31:24]: This is not encrypted. that's the main difference. This is TCP and we have eBPF programs that will reject or allow the TCP connection based on whether you're allowed to do it.Akshat [00:31:35]: Used to involve a full sidecar, but now you have eBPF in the Linux kernel.Swyx [00:31:39]: Yeah.Akshat [00:31:40]: Yeah. I don't know if this is a natural follow-on to the topic of like my skepticism on distributed training is that while, like, people spend a lot of money on, like, cables to hook up GPUs, and even that is not, like, fast enough, and that's the bottleneck, is your networking fast enough?Swyx [00:31:59]: Yeah. So I guess you're talking about fully distributed training like, Dialog or something which is like cross data centerAkshat [00:32:06]: That would be, yes.Swyx [00:32:07]: That's the extreme.Akshat [00:32:08]: Yeah.Swyx [00:32:08]: You're in the middle, and then other people would have like the Mellanox cables up in, like, their actual data center.Akshat [00:32:14]: When you run multi-node training on Modal, RDMA, I think Mellanox, is, or InfiniBand is like a, is all seen as RDMA. but it's a way to bypass the TCP networking stack and, transfer, stuff much faster, between one node, to the other. And we have I think like 3 terabit per second, internal networkingSwyx [00:32:40]: OkayAkshat [00:32:40]: Which is the standard that's needed.Swyx [00:32:42]: Okay. So I misunderstood whatAkshat [00:32:43]: 50Swyx [00:32:43]: What part of the stack you wereAkshat [00:32:44]: 50 gigs overSwyx [00:32:45]: YeahAkshat [00:32:45]: If you wentSwyx [00:32:45]: YeahAkshat [00:32:46]: RDMA.Swyx [00:32:46]: Okay.Swyx [00:32:48]: Yeah. I, very impressive work.Multi-Node Training, Post-Training, and Auto ResearchSwyx [00:32:52]: So effectively you're extending like the model philosophy to the training cluster, like, yeah.Akshat [00:32:59]: Yeah. And we're, we're not going for like large scale training runs. the thing that we've built multi-node training for is, we see a lot of, smaller scale post-training. like, people are post-training like medium sized fund models, so they can, get higher quality on inference. this is a perfect fit, for something like that.Swyx [00:33:21]: Yeah. That is my impression of how a lot of these labs explore branches in post-training and then eventually merge whatever they find in.Akshat [00:33:31]: Yeah. The other use case we've seen for multi-node training is even if you have a big cluster, your researchers are still doing small runsSwyx [00:33:38]: YesAkshat [00:33:39]: Having elasticity thereSwyx [00:33:40]: Right, sureAkshat [00:33:40]: Matters a lot more.Swyx [00:33:41]: Yeah. the, like, this is like the current limiting factor for auto research, which is like you need to give your model some GPUs in order for it to completely run.Akshat [00:33:51]: We have a blog post on auto resource and model is,Swyx [00:33:55]: YeahAkshat [00:33:56]: Yeah, like, turns out to be pretty good substrate for that.Swyx [00:33:59]: So my impression is auto research means many things, likeAkshat [00:34:01]: YeahSwyx [00:34:01]: Anything that Andrej coins. Right now it's still science fair, right? Like not like, I don't know how many people are doing this.Akshat [00:34:08]: We're having a golf.Swyx [00:34:08]: Yeah.Akshat [00:34:09]: I thought the same thing.Swyx [00:34:11]: Yeah, you would know.Akshat [00:34:12]: We, like, our internal both training and inference teams use this the general shape of this quite a bit. like we have this one internal repo called auto inference, which essentially we've automated our own forward-deployed engineering efforts using, this harness, which is, the agent will just spin up a sweep of different things. It'll even run like, NVIDIA inside profiler and it'll like tweak configs and it'll arrive the right thing. it'll change your GPUs both from H200 to B200, and works really well.Swyx [00:34:47]: Nice.Akshat [00:34:47]: So yeah.Swyx [00:34:48]: By the way, I enjoy that your forward-deployed engineering is so technical that you have to do these things.Swyx [00:34:52]: It's very different from forward-deployed engineering from other people.Akshat [00:34:54]: Yeah. For our forward-deployed engineering team is, essentially they're like applied inference researchers or applied training researchers.Swyx [00:35:02]: Someone told me like they have to be able to build, but they also have to be able to sell. do they have to sell or are they like they're good, they're just like post-sale type of thing?Akshat [00:35:09]: It does, being able to talk to a customer and engage effectively with themSwyx [00:35:13]: YeahAkshat [00:35:13]: Matters a lot.Swyx [00:35:14]: They want the same thing.Akshat [00:35:15]: Yeah.Swyx [00:35:15]: ?Akshat [00:35:15]: But it's it's not really a sales, thing. We pair them with-- We have solution architects as well that are more on the sales side.Swyx [00:35:23]: Okay. Let's spend a bit more time on auto research. This is a big focus for for this year. Where does this go? like, have people explored enough? Like, there's all these beautiful charts of like improve and then level off a bit and then you find the next thing. Is this one abstraction up from normal training? Is that how we think about it, or do you think about it differently? Like model level training versus high, like driven hyperparameter search.Auto Inference and Modal BenchAkshat [00:35:51]: Yeah, like,Swyx [00:35:51]: Someone, some people call it like neural architecture search or whatever, right? Like.Akshat [00:35:54]: Yeah, - So the stuff I've seen people do with it is nowhere on the architecture level. It's pretty much tweaking parameters, but it's it's a hyperparameter sweep that's guided by some model intuition, so it's like much more efficient than, whatever other, sweep you would have.Swyx [00:36:12]: Yeah, it's just, it's just a question of where you want to spend your compute?Akshat [00:36:16]: Right.Swyx [00:36:16]: ‘Cause yeah, you can just throw infinite amounts of money on this and somehow you'll bang out Shakespeare?Akshat [00:36:22]: Yeah, infinite monkey.Swyx [00:36:24]: Yeah, so like the very good for model. and I think it's also very important that agents can spin up other agents, can spin up their infrastructure. Like very good for you. how good is our LLMs at generating model code? Like the benefit of existing LLMs is that you are in the data.Akshat [00:36:42]: Yeah. They're, they're surprisingly good. I think like pre Cloud 4 they were not, and then now they're able to shot, stuff out of the box. But we're playing around with releasing like a Modal Bench for like the harderSwyx [00:36:55]: YeahAkshat [00:36:55]: Things, that the LLMs cannot do yet and maybeSwyx [00:36:59]: What's an example of that?Akshat [00:37:01]: I think the things that- Sometimes agents struggle with, without right guidance and a skill is, how to, use the rest of our observability. Like how to. Something is failing, like how do you look at the logs and then update the right thing? It's reasoning about that. But they're able to shot, likeSwyx [00:37:23]: Yeah. You can just add a skill to it?Compute Strategy and Capacity PlanningAkshat [00:37:26]: Yeah. So we have a Modal skill now that. Which is why we built this Modal Bench. It's to find things like that, so we can address them in our tool.Swyx [00:37:35]: Tune a skill. Yeah.Akshat [00:37:36]: Yeah.Swyx [00:37:36]: No. it's it's good. are you facing any shortages? like we talk a lot about GPU shortages, but also CPU, also memory.Swyx [00:37:44]: Yeah.Akshat [00:37:45]: We have had a lot of growth, which means that, there's - we've had to be much better aboutSwyx [00:37:53]: PlanningAkshat [00:37:54]: Proactive capacity planning.Swyx [00:37:55]: Yeah.Akshat [00:37:55]: So we have,Swyx [00:37:57]: Which by the way, like it's like a MBA's like dreamAkshat [00:38:00]: YesSwyx [00:38:00]: Is like just planning this stuff. I think last time you and I talked about something maybe about this.Akshat [00:38:03]: Yeah. we have a really competent team of people that we call, The role is called compute strategy. so yeah, if anyone listening here or wants to work on thatSwyx [00:38:13]: Compute strategy?Akshat [00:38:13]: Yeah.Swyx [00:38:14]: I think,Akshat [00:38:14]: I feel like,Swyx [00:38:15]: I think the normies call it FP&A or something.Akshat [00:38:18]: Well, it's more It's it's not FP&A. It's it's There's a lot of interesting financial questions of like what is the blend between one year and three-year reservations? how do we forecast our own capacity? how do we. especially since our capacity is very fungible across different GPU types and different regions, like you have to model a lot of it. and you also have to have an opinion on how the supply chain is gonna evolve, and then you have to like, take bets,Swyx [00:38:49]: YeahAkshat [00:38:49]: Based on that.Swyx [00:38:50]: Tokenomics.Akshat [00:38:50]: Yeah.Swyx [00:38:51]: This is like probably a not a real point, but, I was trying to think about like what other industries. I was trying to think about like, we cannot be first to like these kinds of problems.Akshat [00:38:59]: Yeah.Swyx [00:39:00]: And what other industries have had this? And I was like, airlines with fuel and like they have to hedge their fuel and like, I think for a long time Southwest because they made like a hero fuel bet, they like were like super low cost becauseAkshat [00:39:12]: OhSwyx [00:39:12]: Compared to everyone else.Akshat [00:39:14]: Yeah. I hadn't thought about that.Vibhu [00:39:16]: We're at a fun time too?Akshat [00:39:18]: Yeah. It's. A lot of the compute business in general, for us is also about being very good about capacity management. That is how you have great unit, economics. but also over time it's how you can unlock more value for customers. Like, one of the things we're building now is like a way for customers to get, If they don't care about latency, like get much cheaper pricing and they'll get results back in like next 24 hours or something, like a batch tier essentially.Batch Tiers and Latency-Insensitive WorkloadsSwyx [00:39:47]: Yeah.Akshat [00:39:47]: And those are levers we have because we control the whole stack and scheduling and whatnot to give people a sufficientSwyx [00:39:53]: Yeah. I feel like they're not as popular. Like those, like the Frontier Labs have all those APIs. They're not as popular as they should be.Akshat [00:40:00]: The demand that we see for something like that is not for LLMs. although sometimes people wanna run evals andSwyx [00:40:08]: OkayAkshat [00:40:08]: Synthetic data prep and there it makes sense.Swyx [00:40:10]: Okay.Akshat [00:40:11]: But it's from a lot of LLM companies, like people who are doing computational bio, like they have to run really big batch jobs and they don't care about when they get it back.Swyx [00:40:22]: Yeah. And like they have a reasonable. It's it's also like a cousin to the stopping problem of like, will this finish in time?Akshat [00:40:30]: Yeah. You can bound it.Swyx [00:40:33]: Yeah.Akshat [00:40:33]: Like you can give peopleSwyx [00:40:34]: YeahAkshat [00:40:34]: SLAs on it.Swyx [00:40:35]: Yeah. I think what's, what's interesting is like the next phase of model.Swyx [00:40:38]: Like what, do people expect from you, now that you're established and you're like well-known compute player among all these leading companies. You had an inference launch week, and we talked a little bit about the launches. like what else? Like what else should people know?What Modal Builds NextAkshat [00:40:55]: We are building primitives that make our users' lives much easier. So, I think for example, with LLM inference, thousands more companies are gonna post-train their own models and, deploy open source models for inference. so we're thinking a lot about what is the best product shape for that. And, that involves everything from our training gym to, then, endpoints that get frontier-level performance. again, but I haven't talked to anyone. It looks somewhat different on other verticals. Like, we're also seeing a lot of real-time, audio-video stuff in there, which is why like, we're working on things like regional routing, with fallbacks. So you can get GPUs that are as close to users as possible. so you get like low latency for video streaming and whatnot. And then on the agent side, it's,Akshat [00:41:52]: We're still working very closely with our customers because stuff is changing so fast in terms of what they need. And, I think beyond sandboxes and persistent file systems, there's a lot of other things people will need from this agent stack as they build production agents. So yeah, we're thinking about those other things that fit in there.Swyx [00:42:13]: I want to ask what the other things are.Akshat [00:42:15]: Yeah. I probably should share right now.Swyx [00:42:17]: I think-- I think, okay, so, I do think a lot about the principal components of cloud, and you do talk about compute storage networking.Akshat [00:42:25]: Yeah.Swyx [00:42:25]: Because so far for me, it's fine. so far for the. the first couple generations of cloud, it's fine. What's different, qualitatively different about agents that you need some new permission level? Like a lot of people, okay, and I'll just kinda spew tokens at you until it like hopefully sparks something.Akshat [00:42:43]: Yeah.Swyx [00:42:44]: Like the new level now is whatever Claude Code does, which is dangerously scope permissions or like allow list by command or like whatever, right? And sometimes they're like, “Well, okay, we have like this adaptive thinking mode where like, just trust me, bro. I will make the calls for you.” Is that it? like mediated permissions.Hard Guardrails vs. LLM-Mediated PermissionsVibhu [00:43:03]: Now you're looping it with a goal and letting it roll.Akshat [00:43:06]: Yeah, I'm, I'm skeptical of LLM media permission for stuff that is at the sandbox level because you do want hard boundaries.Swyx [00:43:16]: Yeah.Akshat [00:43:16]: Otherwise, someone can exfiltrate stuff.Swyx [00:43:20]: But likeAkshat [00:43:20]: YeahSwyx [00:43:20]: Maybe that's old school thinking. Maybe we're the dinosaurs.Swyx [00:43:23]: Maybe the AI OS or the LLM OS is really the kernel is a goddamn LLM.Swyx [00:43:30]: Like it makes you feel uncomfortable.Akshat [00:43:31]: Yeah, I'm, I'm toldSwyx [00:43:32]: But that's what trusting the LLM is. Like imagine a spherical cow perfect LLM.Akshat [00:43:36]: Right.Swyx [00:43:37]: That it.Akshat [00:43:39]: Maybe.Swyx [00:43:41]: I wanna test the boundaries, right?Akshat [00:43:42]: Yeah.Swyx [00:43:42]: Like, and I don't believe that, but I wanna see where I'm wrong ‘cause that's, that's the consensus.Akshat [00:43:49]: Yeah. I think you always need hard guardrails when you want, And you can pair those with softer guardrails, right? And that's gonna be a lot of mediated.Managed Agents and Specialized SandboxesSwyx [00:44:00]: There. I'll also get you a end with a couple of your commentary on like the ecosystem outside of Modal. Manage agents. Everyone has one. Gemini, OpenAI, Claude, very useful for you, but also like it is their way of starting to edge into your space.Akshat [00:44:17]: Yeah.Swyx [00:44:17]: What's going on?Akshat [00:44:19]: Yeah, we're, very excited to partner with Anthropic and some of the other foundation labs, will not name who we're also working with. the way we see it is the manage agent thing is a great place to start if you're starting out building an agent and, But then when you get to, building something more production grade, like you're a company that's like Ramp that's building their own, Ramp also runs their accounting agent on us, so their external-facing agent. You need a lot more control over, your compute primitive on things like, what sort - how do you persist different files that the agent has access to, and how do you snapshot and restore? How do you control the networking? maybe you want GPUs. When you get to that point, you kinda want, a specialized sandbox provider, that gives you those things, and that's the role that we are trying to play.Swyx [00:45:15]: YeahAkshat [00:45:16]: We don't really have an opinion on the harness, whether it runs - it's a cloud-managed agent, and you hook it up to Model Sandbox, or you run the harness in Model Sandbox. We'll see where people converge with that.Swyx [00:45:26]: Yeah. Do you any opinions on like the meta harnesses, or just another layer on top of these things?Akshat [00:45:31]: You mean like the OpenPipeSwyx [00:45:33]: OpenPipe is one. I think Vercel had one, which I can't remember the name of right now. Fredshot had one. and then, to me, most recently was Data Databricks that had Omnigen. All these are meta harness. Like it's kinda pseudo agent cloud type things.Akshat [00:45:50]: I personally have not played around with them.Swyx [00:45:53]: Yeah.Akshat [00:45:53]: Build agents with them.Swyx [00:45:54]: Everything's bullish Modal, as long as it consumes more infra.Akshat [00:45:57]: That's why we're focusing on the infra layer. It's somewhere where our, relative competence is and, also it's a hard problem to solve.Swyx [00:46:06]: Yeah. I will say like just generally reflecting on that, I don't know if - if there's other topics on Modal, but like just generally reflecting as an infra person, not as intense as you, but in that field, this has like been the most exciting time in infra. Like it was boring for a while, and you couldn't really get people excited about data infrastructure. Like Eric would get on Data Console, everyone just watched the video and like say, “Look at how many sandboxes I can spin up,” and no one gave a crap.Why Infrastructure Became Exciting AgainAkshat [00:46:39]: Yeah.Swyx [00:46:40]: And like now everyone gives a crap.Akshat [00:46:42]: That's true. It is a very exciting time, and I think a lot of that's driven by just the amount of scale all of this stuff needs.Swyx [00:46:50]: I think the, like a lot of your initiatives or a lot of your like product directions make sense in retrospect, which is like the best kind, but I wouldn't necessarily have thought about it myself, which.Akshat [00:47:00]: We need the predictions.Swyx [00:47:02]: I think there's a lot that you just don't even see, right? Like you have the batch, you have the voice, you have the multimodal, but what else?Akshat [00:47:10]: What else is coming up for usSwyx [00:47:11]: Yeah. Where do you see things going?Akshat [00:47:13]: Yeah. I, in generalBiotech, Robotics, and Non-LLM AI WorkloadsAkshat [00:47:15]: It's it's clear that there's there's a huge shift happening. I think one thing that's not as obvious to people because LLM inference gets talked about so much and is also we work a lot of companies that are, doing things like drug discovery and computational bio, like the Chai Discoveries of the world. Big things are probably gonna happen there. we work a lot of robotics companies that are putting robots in like active deployments and getting good results out of them.Swyx [00:47:45]: Is there Air Gap Modal? Is there a version that is like prem air gapped whatever?Akshat [00:47:50]: No. We,Swyx [00:47:51]: You should cloud only.Akshat [00:47:51]: Yeah.Swyx [00:47:52]: Yeah. Okay. But yeah, so what you're saying is like because you're focused on primitives and they're good primitives, you find use cases in all these kinds of things.Akshat [00:48:01]: Yeah.Swyx [00:48:01]: Probably diversifies you a little bit away from LMS all the time.Akshat [00:48:05]: Yeah, absolutely. We're, we'- our goal isn't to only serve the LLM inference market.Swyx [00:48:10]: There are a lot just on the website, the audio,Akshat [00:48:12]: Yeah. We said both onSwyx [00:48:14]: Computational bio images. Yeah, there's a lot here. There's QTA TTS, customizing. Oh, Chatterbox. there was customizing Whisper.Akshat [00:48:24]: Okay. Yeah.Swyx [00:48:25]: This screen reminds me of a fallen competitor, which Replicate.Model APIs vs. Differentiated AI ProductsSwyx [00:48:31]: What's your postmortem on what happened?Akshat [00:48:34]: This is one thing we've stayed away from is providing an API for models because I think providing model APIs is some of it ends up serving like a really hobbyist market, which is much less sticky.Swyx [00:48:50]: Yeah.Akshat [00:48:50]: And we've always wanted to build for companies that are building products and need more flexibility that's not just an API.Swyx [00:48:57]: Which you can build an API for a model and this is clearly what it is. But you - but what you're saying, you can wrap it into a more fully functioning back end that you run.Akshat [00:49:06]: Yeah. So all of our examples, it's not that spin up this model, here's an API token, use it. They're all code.Swyx [00:49:13]: Okay.Akshat [00:49:13]: And so the point is that this is just an example.Swyx [00:49:16]: Starter code.Akshat [00:49:17]: Yeah. But you can tweak it however you want.Swyx [00:49:20]: Yeah.Akshat [00:49:21]: And if you're like a company building a product, like, computational bio whatnot, yeah.Swyx [00:49:26]: I guess I'm trying to tease out for listenersAkshat [00:49:28]: YeahSwyx [00:49:28]: When does it stop becoming, oh, you're just an API call and you're just a wrapper on API to becoming what you call a product, right?Swyx [00:49:36]: Like, what is that layer? Like what-- Like, more lines of code, but like beyond that, what is the substance that people add that qualifies it to be something more?Akshat [00:49:46]: I think there's a little bit of like a selection effect of like a lot of the companies who do wanna get deeper into that level are probably building something that's more differentiated. And, I think, an example is like - with LLM inference, originally we, worked with companies that were building their own post-training frameworks or they were, - Ramp early in the day was training their own tokenizer and like swapping out the tokenizer in Llama and whatnot. I'm not saying that's, that successful, in that case. But a better example is like, let's say Suno. because Suno, does not use Modal for training.Swyx [00:50:26]: Mikey on the pod. Yeah.Akshat [00:50:27]: But they use Modal for all their inference and that's because they have like a custom-- They have completely custom model architecture and that means that they have to be at the code level and tweak things that are not, just an API.Swyx [00:50:41]: It's interesting as well, like we had, Ethan, most recently on the xAI Groq team make a prediction that like the next tier in video gen is not a better video model, it's a better model or agent that orchestrates video models.Video Agents and Production WorkflowsAkshat [00:50:56]: Oh, interesting.Vibhu [00:50:56]: Language model backbone that can use toolsAkshat [00:50:58]: RightVibhu [00:50:59]: And write code.Akshat [00:51:00]: Like, yes, I can make my second video or my second video from Groq, but I want my minute video.Akshat [00:51:06]: And I'm not going there through normal video gen.Swyx [00:51:10]: Yeah, that's interesting. I - So we have GPU sandboxes and recently have seen a few companies doing agents that do video manipulation or,Akshat [00:51:22]: Yeah. Give it FFmpeg and just do it.Swyx [00:51:23]: Run FFmpeg. But likeAkshat [00:51:25]: That's not enough.Swyx [00:51:25]: Yeah.Akshat [00:51:26]: You need to give it Adobe.Swyx [00:51:27]: Yeah, I hadn't put it together with like it would be a video production thing. in my mind these things were going more towards editingAkshat [00:51:36]: Yeah.Vibhu [00:51:36]: Well, shout out Mantis.Akshat [00:51:37]: I think about this a lot.Swyx [00:51:38]: .Akshat [00:51:41]: Yeah. Sorry.Vibhu [00:51:41]: Luma. Luma Agent is a version of this for video production, but it's a off.Swyx [00:51:46]: I was gonna get your quick takes, on some other stuff that happensGitpod/Ona, CI, and Runtime SandboxesSwyx [00:51:50]: In recent news and just-just see if you have anything interesting. Gitpod, very li

SPONSORS: - Go to https://www.plaud.ai/curt and use the promo code "CURT" to get a Plaud device today - Accelerate your efficiency. Sign up for your one-dollar-per-month trial today at http://shopify.com/theories - I personally subscribe to The Economist. TOE listeners get 35% off the annual subscription. No other podcast has this! https://economist.com/TOE This is a podcast all about time: depending on how you look at it, that's either unnerving or exhilarating. Professor Simon Saunders — Emeritus Fellow at Merton College, Oxford, and one of the most celebrated philosophers of physics alive — goes deep on what time actually is, why special relativity demands a block universe, and what any of this has to do with the Many Worlds Interpretation. Why doesn't space inherit the paradoxes of time? What's really missing from the block universe picture (and is it the same thing missing from quantum probability?) Saunders argues that Bell inequality violations aren't evidence against locality but evidence for Many Worlds, presents a novel derivation of the Born rule from a single physical postulate, and sketches a quantum version of Leibniz's monadology as a possible path through the mind-body problem. I hope you enjoy. FOLLOW: - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Substack: https://curtjaimungal.substack.com/subscribe - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - Crypto: https://nowpayments.io/donation/TOE - PayPal: https://www.paypal.com/donate?hosted_button_id=XUBHNMFXUX5S4 TIMESTAMPS: - 00:00:00 - Defining Temporal Passage - 00:05:03 - Block Universe and Relativity - 00:11:15 - The Timeless Viewpoint - 00:18:07 - CMB and Global Time - 00:23:19 - Persistence and Spatial Revisitability - 00:31:02 - Philosophy of Physics Foundations - 00:38:46 - Relativistic Localization Problems - 00:49:22 - Reeh-Schlieder and Vacuum States - 00:55:23 - Branching and Actuality - 01:05:41 - Interval Probabilities and Frequentism - 01:14:14 - Decoherent Histories Interpretation - 01:25:49 - Ontic Structural Realism - 01:32:15 - Deriving the Born Rule - 01:38:02 - Leibnizian Quantum Monadology LINKS MENTIONED: - Simon's Papers: https://scholar.google.com/citations?user=htEv3XIAAAAJ - Many Worlds? [Book]: https://amazon.com/dp/0199560560?tag=toe08-20 - A Brief History of Time [Book]: https://amazon.com/dp/0553380168?tag=toe08-20 - How Relativity Contradicts Presentism [Paper]: https://users.ox.ac.uk/~lina0174/kansas.pdf - Trouble With Quantum Mechanics [Article]: https://www.nybooks.com/articles/2017/01/19/trouble-with-quantum-mechanics/ - Locality, Complex Numbers, and Relativistic Quantum Theory [Paper]: https://www.jstor.org/stable/192768 - Bohmian Mechanics: https://plato.stanford.edu/entries/qm-bohm/ - Finite Frequentism Explains Quantum Probability [Paper]: https://arxiv.org/abs/2404.12954 - Chance in the Everett Interpretation [Paper]: https://arxiv.org/abs/1609.04720 - Reeh-Schlieder Defeats Newton-Wigner [Paper]: https://arxiv.org/abs/quant-ph/0007060 - Everett's Thesis [Paper]: https://cqi.inf.usi.ch/qic/everett_phd.pdf - Physics and Leibniz's Principles [Paper]: https://philpapers.org/rec/SAUPAL-2 - Critical Exposition of the Philosophy of Leibniz [Book]: https://amazon.com/dp/1605204536?tag=toe08-20 - Avshalom Elitzur [TOE]: https://youtu.be/pWRAaimQT1E - David Wallace [TOE]: https://youtu.be/4MjNuJK5RzM - David Deutsch [TOE]: https://youtu.be/vKeWv-cdWkM - Sean Carroll [TOE]: https://youtu.be/9AoRxtYZrZo - Tim Maudlin [TOE]: https://youtu.be/fU1bs5o3nss - Sechit Madra (Trainer): https://www.instagram.com/sechit_madra More links at https://curtjaimungal.substack.com Guests do not pay to appear. #science Learn more about your ad choices. Visit megaphone.fm/adchoices

Trap Talk Reptile Network PresentsKush's Korner Ep.117 Deep dive into locality Water Monitor breeding with Taylor and Nikki JusticeJoin The Kush's Korner/Kush Reptile Patreon: https://www.patreon.com/cw/KushReptile/membershipHOST: Steven Kushhttps://www.instagram.com/scrubshepherd/GUEST: Taylor and Nikki Justice  https://www.instagram.com/obsessedexotics/JOIN TRAP TALK FAM HERE: https://bit.ly/311x4gxSUPPORT USARK: https://usark.org/MORPH MARKET STORE: https://www.morphmarket.com/stores/ex...SUBSCRIBE TO THE TRAP TALK NETWORK: https://bit.ly/39kZBkZSUBSCRIBE TO TRAP TALK CLIPS:   / @traptalkclips  SUBSCRIBE TO THE TRAP VLOGS:https://www.youtube.com/channel/UCKxL...SUPPORT USARK: https://usark.org/memberships/Follow On IG: The Trap Exotics https://bit.ly/3hthAZuTrap Talk Reptile Podcast https://bit.ly/2WLXL7w Listen On Apple:Trap Talk With MJ https://bit.ly/2CVW9Bd Unfiltered Reptiles Podcast https://bit.ly/3jySnhV Listen On Spotify:Trap Talk With MJ https://bit.ly/2WMcKOO Unfiltered Reptiles Podcast https://bit.ly/2ZQ2JCbTrap Talk Reptile Podcast Sponsors:MORPHMARKET SHIPPING:https://shipping.morphmarket.com/MARC BAILEY REPTILES https://www.morphmarket.com/stores/ma...WORKSHOP REPTILLIUM   / workshop_reptilium  PRAGUE MORPHS:  / praguemorphs  SUNDOWN REPTILEShttps://www.sundownreptiles.com/TX CHONDROShttps://www.texaschondros.com/FOCUS CUBED HABITAT:   / focuscubedhabitats  JERSEY GUYS BALLS:  / jerseyguysballs  RARE GENETICS INC:https://www.raregeneticsinc.com/  / raregeneticsinc     / @raregeneticsinc8166   KINOVA REPTILES & CLTCH:https://cltch.io/https://kinovareptiles.com/THE REPTILE SUPER SHOW:https://reptilesupershow.com/SOUTHEAST REPTILE EXPO:  / southeast_reptile_expo  BLAKES EXOTIC FEEDERS  / blakesexoticfeeders  ZOO MED:https://zoomed.com/#fyp #reptiles #coolestreptilepodcastintheworld

WORKSHOP REPTILLIUM https://www.instagram.com/workshop_reptilium/PRAGUE MORPHS:https://www.instagram.com/praguemorphs/SUNDOWN REPTILEShttps://www.sundownreptiles.com/TX CHONDROShttps://www.texaschondros.com/FOCUS CUBED HABITAT: https://www.instagram.com/focuscubedhabitats/JERSEY GUYS BALLS:https://www.instagram.com/jerseyguysballs/RARE GENETICS INC:https://www.raregeneticsinc.com/https://www.instagram.com/raregeneticsinc/https://www.youtube.com/@raregeneticsinc8166 KINOVA REPTILES & CLTCH:https://cltch.io/https://kinovareptiles.com/THE REPTILE SUPER SHOW:https://reptilesupershow.com/SOUTHEAST REPTILE EXPO:https://www.instagram.com/southeast_reptile_expo/BLAKES EXOTIC FEEDERShttps://www.instagram.com/blakesexoticfeeders/ZOO MED:https://zoomed.com/#fyp #reptiles #coolestreptilepodcastintheworld

SPONSORS: - Go to https://expressvpn.com/theoriesofeverythingyt to find out how you can get up to 4 extra months thanks to our sponsor, ExpressVPN - Accelerate your efficiency. Sign up for your one-dollar-per-month trial today at http://shopify.com/theories - I subscribe to The Economist for their science and tech coverage. As a TOE listener, get 35% off! No other podcast has this: https://economist.com/TOE This conversation belongs in a category I wish were larger on this channel: the experimentalist who also thinks (deeply) about foundations. Professor Aephraim Steinberg, winner of Physics World's Breakthrough of the Year in 2011, is that species! For basically 30 years, he's been measuring aspects of physics that others wouldn't touch: Bohmian trajectories, Heisenberg's disturbance bound (he showed it was wrong), even where the photon is inside the double slit (which most textbooks will tell you is impossible). His lab measured negative time — and it keeps reappearing across completely different experiments, stubbornly suggesting it means something. FOLLOW: - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Substack: https://curtjaimungal.substack.com/subscribe - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - Crypto: https://commerce.coinbase.com/checkout/de803625-87d3-4300-ab6d-85d4258834a9 - PayPal: https://www.paypal.com/donate?hosted_button_id=XUBHNMFXUX5S4 TIMESTAMPS: - 00:00:00 - Defining Negative Time - 00:06:50 - Quantum Trajectory Theory - 00:12:44 - The Holland Tunnel Analogy - 00:18:40 - Resonant Atomic Interactions - 00:26:05 - Superluminal Energy Propagation - 00:32:00 - Eight Velocities of Light - 00:38:00 - Causality and Retrocausality - 00:44:00 - Dwell Time vs. Delay - 00:50:24 - Time: Operator or Parameter? - 00:58:21 - Bell's Theorem and Realism - 01:04:55 - Heisenberg's Measurement Disturbance - 01:11:26 - Weak Measurement Formalism - 01:17:37 - Time Symmetry and Entropy - 01:27:07 - Bohmian Trajectories Observed - 01:35:56 - Spin-Statistics and Indistinguishability - 01:42:14 - Quantum Computational Advantage - 01:48:15 - Many Worlds vs. Complexity - 01:54:51 - Psi-Ontic vs. Psi-Epistemic - 02:01:37 - Collapsing Tunneling Particles - 02:08:48 - Larmor vs. Atto Clocks - 02:15:24 - Locality and Information LINKS MENTIONED: - Aephraim's Website: https://www.physics.utoronto.ca/~aephraim/ - Aephraim's Papers: https://scholar.google.com/citations?user=PzUyb6IAAAAJ - Photon Negative Time in Atom Cloud [Paper]: https://arxiv.org/pdf/2409.03680 - How Much Time Does a Photon Spend as Atomic Excitation? [Paper]: https://arxiv.org/abs/2310.00432 - Measuring Time Atoms Spend in Excited State [Paper]: https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.3.010314 - Tunneling Atom Time in Barrier [Paper]: https://arxiv.org/abs/1907.13523 - Single-Photon Tunneling Time [Paper]: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.71.708 - Traversal Time for Tunneling [Paper]: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.49.1739 - Propagation of a Gaussian Light Pulse [Paper]: https://journals.aps.org/pra/abstract/10.1103/PhysRevA.1.305 - Linear Pulse Propagation in Absorbing Medium [Paper]: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.48.738 - Eighth Velocity of Light [Paper]: https://pubs.aip.org/aapt/ajp/article-abstract/45/6/538/1045817/Eighth-velocity-of-light - Attosecond Ionization [Paper]: https://www.science.org/doi/10.1126/science.1163439 - Tunneling Optical Pulses Photonic Band Gaps [Paper]: https://attoworld.de/fileadmin/user_upload/tx_attoworld/publications/paper_PhysRevLett_Y1994_M10_D24_V73_P2308.pdf - Evidence of Negative Time [Article]: https://www.scientificamerican.com/article/evidence-of-negative-time-found-in-quantum-physics-experiment/ - Light Speed Reduction [Article]: https://www.nature.com/articles/17561 - On the Theory of Light and Colors [Paper]: https://www.jstor.org/stable/pdf/107113.pdf - Wave Propagation and Group Velocity [Book]: https://amazon.com/dp/1483253937?tag=toe08-20 - EPR Paper [Paper]: https://journals.aps.org/pr/abstract/10.1103/PhysRev.47.777 - Uncertainty Principle: https://en.wikipedia.org/wiki/Uncertainty_principle - QBism [Paper]: https://arxiv.org/abs/1003.5209 More links at https://curtjaimungal.substack.com Guests do not pay to appear. #science Learn more about your ad choices. Visit megaphone.fm/adchoices

Ajahn Amaro read and commented on subchapter 8, “Unsupported and Unsupportive Consciousness" (from the second chapter, “The Terrain”) on March 15, 2025, during the Winter Retreat at Amaravati Buddhist Monastery in the UK. The post Chapter 8 and 9 – Unsupported and Unsupportive Consciousness (part 7) and The Unconditioned and Non-locality (part 1) appeared first on Amaravati Buddhist Monastery.

The episode centers on the process of locality research for Cass County, Georgia, as Diana continues her project to find the father of Cynthia (Dillard) Royston. Diana explains her research objective is to discover a candidate for Cynthia's father residing in the county during the 1830s. Nicole discusses the importance of narrowing the time frame for a locality guide, focusing on the county's earliest years from 1832 to 1860. They then compare their process for utilizing the Deep Research capabilities of large language models (LLMs) to create the guide, sharing their query and noting the varying results from Claude, Perplexity, ChatGPT, and Gemini. Diana and Nicole discuss two crucial findings that impacted their research strategy. They detail the county's name change from Cass to Bartow in 1861 due to General Lewis Cass's Union sympathies and the Confederacy's desire to honor Colonel Francis S. Bartow. They also review the record loss event from the courthouse burning in 1864, explaining that many records like deed and marriage books were saved by the heroic efforts of County Clerk Tom Word. Additionally, they summarize the 1832 Cherokee Land Lottery, which was the method for distributing land and attracting settlers to the area. Listeners learn how to efficiently use AI to create a comprehensive locality guide and gain valuable insight into how events like name changes, record loss, and land distribution fundamentally shape genealogical records. This summary was generated by Google Gemini. Links Revisiting the Father of Cynthia (Dillard) Royston: Part 3 Locality Research - https://familylocket.com/revisiting-the-father-of-cynthia-dillard-royston-part-3-locality-research/ Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Trap Talk Reptile Network Presents Ep.705All In The Tree Tuesday's w/ David Brahms Of The Reptile Perch LiveJOIN TRAP PATRON FAM HERE: https://bi t.ly/311x4gxSUPPORT THE GUEST:  / thereptileperch  TRAP TALK CO-HOST:  / phoenix.reptiles    / redmountainherp  SUPPORT USARK: https://usark.org/MORPH MARKET STORE: https://www.morphmarket.com/stores/ex...SUBSCRIBE TO THE TRAP TALK NETWORK: https://bit.ly/39kZBkZSUBSCRIBE TO TRAP TALK CLIPS:   / @traptalkclips  SUBSCRIBE TO THE TRAP VLOGS:https://www.youtube.com/channel/UCKxL...SUPPORT USARK: https://usark.org/memberships/Follow On IG: The Trap Exotics https://bit.ly/3hthAZuTrap Talk Reptile Podcast

Local advertising is one of the most effective methods for brands of all sizes to reach the audiences that matter most, and platforms like Locality's LocalX are becoming industry leaders by enabling advertisers to plan, buy and measure local broadcast and streaming in one intelligent workflow. LocalX was purpose-built for local advertising, and by using real-time insights and unified data, the platform empowers agencies and partners to maximize impact with confidence." At the end of the day, the reason we're targeting local is to drive a better outcome for our brand in a local community or local space," said Zach Mullins, chief strategy officer at Locality, on a special edition of Ad Age's Marketer's Brief podcast. "By creating unification at scale, we can do that much more effectively in local markets." Tune in to hear more about how LocalX works to combat the increasing complexity and fragmentation within local markets, advance the local ad-buying ecosystem, and the future the company sees for the local media market.

NEW! 2025 NOVEMBER SPEAKER SERIES!WITH A PHENOMENAL LINEUP OF THE BEST OF THE BEST!SIGN UP BEFORE OCT 31ST TO CHOOSE YOUR TUITION RATE! AS LOW AS $5 A CLASS FOR A LIMITED TIME!Learn More & Sign up now at synchronicityuniversity.comScheduleClass 1: Ashli Scott | Esoteric Medicine of Fall & WinterClass 2: Stephen Poplin | Fine Tuning the Birth Chart: RectificationClass 3: Sharri Keller | Cosmic Care: How to Work with Herbs Through the Lens of AstrologyClass 4: Luisa Arboleda | BaZi Astrology Made Simple: Find Your Day Master and Elemental BalanceClass 5: Geoff Gronlund | Rebel Mars Through the Signs and Houses Casting a horoscope, date, place and time. But … is your birth time correct? Even if your birth certificate has a specific time, did the hospital nurse fill out that form after the coffee break? Stephen Poplin, with decades of experience, will teach a simple method, using secondary progressions, that will not only point out amazing details and patterns about one's life and development, but can be used to rectify, or correct the birth time, and also aid in predictions. Every chart should be rectified, and this is especially true if one wishes to calculate and use Locality charts. A few minutes off could mean hundreds of miles/kilometers off.Although this program can be understood even by those new to this ancient art, seasoned astrologers will find this fascinating. Have your charts ready!Stephen Poplin, M.A., CHT, is a transpersonal astrologer and spiritual hypnotherapist, has degrees in philosophy and humanities, and has taught these subjects in several colleges in the US and Germany. A globetrotter, living part time in Europe and the USA, Stephen is also an interfaith minister and “worth-shop” leader. He has studied history and culture, drama therapy, symbology, Tarot and metaphysics, among other interests. He has been the president of two NCGR astrology chapters in the USA and has taught many topics in astrology over the years. He travels frequently – giving talks and leading seminars. Stephen is the author of the two volume series on reincarnation, “Inner Journeys, Cosmic Sojourns”. He is known for his compassion, insight and humor. Stephen's videos collected on his website:https://stephen-poplin.com/videos His YouTube channel - https://www.youtube.com/@stephenpoplin8298Meditations on YouTubehttps://www.youtube.com/playlist?list=PLiyJLhlK6ywpuWsOij0XGh_-cegs46p5vSound cloud  https://soundcloud.com/stephen-poplin

In this episode, we are discussing Locality Kingsnakes with Jerry HartleyFollow:Zac Loughman @https://www.instagram.com/dr_crawdad/On FB https://www.facebook.com/profile.php?id=100011423011423Clint Bartley @IG: MetazoticsLLC FB: MetazoticsWebsite: metazotics.comPatreon:https://www.patreon.com/c/ColubridandColubroidRadio/Discord:http://discord.gg/ccradioExo-terrahttps://exo-terra.comhttps://linktr.ee/exoterrausaMPR NetworkFB: https://www.facebook.com/MoreliaPythonRadioIG: https://www.instagram.com/mpr_network/YouTube: https://www.youtube.com/channel/UCtrEaKcyN8KvC3pqaiYc0RQSwag store: https://teespring.com/stores/mprnetwork ★ Support this podcast on Patreon ★

In our first hour this Wednesday morning, we give you "Five Things" that you need to know today -- and ask: Is any tax as reviled as the car tax??

Trap Talk Reptile Network Presents Varanus Vault Podcast Ep.17 w/ Nick Mutton LiveHOST: Chris Applin of Rare Reptiles   / rarereptiles  FOLLOW & SUPPORT GUEST:JOIN TRAP TALK PATREON HERE: https://bit.ly/311x4gxSUPPORT USARK: https://usark.org/MORPH MARKET STORE: https://www.morphmarket.com/stores/ex...SUBSCRIBE TO THE TRAP TALK PODCAST: https://bit.ly/39kZBkZSUBSCRIBE TO TRAP TALK CLIPS:   / @traptalkclips  SUBSCRIBE TO THE TRAP VLOGS:https://www.youtube.com/channel/UCKxL...SUPPORT USARK: https://usark.org/memberships/Follow On IG: The Trap Exotics https://bit.ly/3hthAZuTrap Talk Reptile Podcast https://bit.ly/2WLXL7w Listen On Apple:Trap Talk With MJ

This week we take a look at Y2K, the poignant historical fiction of our time that accurately encapsulates the fallout of our first robot uprising. We know this is the end of our “bad movie” season before doing a good movie next week, but we (read: Rob) will argue in this movie's favor for being such an explosive exploration of retro-futuristic tech, teen romance, and our lord and savior, Fred Durst. Did you think this movie sucked? Because we (read: Rob) thought QUITE THE OPPOSITE (fuck you, Chris). Let's get into the mayhem. A kinda cringey kid, a cute coder, and a completely cool kiwi combat killer computers who kill kids! Kilobyte catastrophe! The Member Berry grift! Machines have Matrix motives! Locality leaves a lot unlearned! Another episode echoing Eddie character's cranial cooking! Piss-mouth pal goes public! Chris gives himself too much credit! Throbby Robby's ironic layers of abstraction! 10,000 maniacs getting twisted, and much, much more on this week's episode of The Worst Movie Ever Made! www.theworstmovieevermade.com

Trap Talk Reptile Network Presents Ep. 614All In The Tree Tuesday's w/ Mike of MNM Chondros Live  JOIN TRAP PATRON FAM HERE: https://bi t.ly/311x4gxSUPPORT THE GUEST:  / mnm_chondros  TRAP TALK CO-HOST:  / phoenix.reptiles    / redmountainherp  SUPPORT USARK: https://usark.org/MORPH MARKET STORE: https://www.morphmarket.com/stores/ex...SUBSCRIBE TO THE TRAP TALK NETWORK: https://bit.ly/39kZBkZSUBSCRIBE TO TRAP TALK CLIPS:   / @traptalkclips  SUBSCRIBE TO THE TRAP VLOGS:https://www.youtube.com/channel/UCKxL...SUPPORT USARK: https://usark.org/memberships/Follow On IG: The Trap Exotics https://bit.ly/3hthAZuTrap Talk Reptile Podcast https://bit.ly/2WLXL7w Listen On Apple:Trap Talk With MJ https://bit.ly/2CVW9Bd Unfiltered Reptiles Podcast https://bit.ly/3jySnhV Listen On Spotify:Trap Talk With MJ https://bit.ly/2WMcKOO Unfiltered Reptiles Podcast https://bit.ly/2ZQ2JCbTrap Talk Reptile Podcast Sponsors:MARC BAILEY REPTILES https://www.morphmarket.com/stores/ma...THE CHIPPER COCO https://cocodude.com/SUNDOWN REPTILEShttps://www.sundownreptiles.com/BLAKES EXOTIC FEEDERS  / blakesexoticfeeders  TX CHONDROShttps://www.texaschondros.com/FOCUS CUBED HABITAT   / focuscubedhabitats  GS REPTILES   / gs.reptiles     / @gsreptiles5606  JUGGERNAUT REPTILES  / juggernautreptiles     / @juggernautreptiles  RARE GENETICS INChttps://www.raregeneticsinc.com/  / raregeneticsinc     / @raregeneticsinc8166  CLTCHhttps://cltch.io/  / cltch  THE REPTILE SUPER SHOWhttps://reptilesupershow.com/#fyp #reptiles #coolestreptilepodcastintheworld

Federal employees who telework at least once a week would lose locality pay under a new House bill. Under the Federal Employee Return to Work Act, teleworking employees would receive "Rest of U.S." locality pay even if they live and work in a region with a higher cost of living. Rep. Dan Newhouse introduced the bill. He and Sen. Bill Cassidy led the bill during the last session of Congress. Learn more about your ad choices. Visit podcastchoices.com/adchoicesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Federal employees who telework at least once a week would lose locality pay under a new House bill. Under the Federal Employee Return to Work Act, teleworking employees would receive "Rest of U.S." locality pay even if they live and work in a region with a higher cost of living. Rep. Dan Newhouse introduced the bill. He and Sen. Bill Cassidy led the bill during the last session of Congress. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Head over to https://www.masterclass.com/theories for the current offer. MasterClass always has great offers during the holidays, sometimes up to as much as 50% off. In today's episode of Theories of Everything, Curt Jaimungal speaks to Maria Volaris for a gentle introduction to quantum computing, diving into quantum no-go theorems, Schrödinger's cat, the nature of quantum entanglement, and how these concepts lay the foundation for the future of computational science. As a listener of TOE you can get a special 20% off discount to The Economist and all it has to offer! Visit https://www.economist.com/toe LINKS MENTIONED: •⁠ ⁠Maria Violaris's OSV profile: https://www.osv.llc/fellows-grantee/maria-violaris •⁠ ⁠Maria's YouTube channel: https://www.youtube.com/@maria_violaris/videos •⁠ ⁠Maria's series on Qiskit: https://www.youtube.com/watch?v=Pz829XZIxXg •⁠ ⁠Chiara Marletto on TOE: https://www.youtube.com/watch?v=40CB12cj_aM •⁠ ⁠Curt Jaimungal's Substack: https://curtjaimungal.substack.com/ Timestamps: 00:00 - Introduction 00:59 - Maria's Background 04:20 - Quantum No-Go Theorems 09:55 - Schrödinger's Cat 13:41 - Theory Independence & Loopholes 17:21 - Uncertainty Principle (Entanglement) 23:11 - Qubits (Quantum Bit) 31:58 - Bell's Theorem (Quantum Entanglement) 45:12 - Locality & Realism 49:04 - Bell's Theorem Continued… 01:00:06 - GHZ States New Substack! Follow my personal writings and EARLY ACCESS episodes here: https://curtjaimungal.substack.com TOE'S TOP LINKS: - Enjoy TOE on Spotify! https://tinyurl.com/SpotifyTOE - Become a YouTube Member Here: https://www.youtube.com/channel/UCdWIQh9DGG6uhJk8eyIFl1w/join - Support TOE on Patreon: https://patreon.com/curtjaimungal (early access to ad-free audio episodes!) - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - Subreddit r/TheoriesOfEverything: https://reddit.com/r/theoriesofeverything #quantumphysics #science #physics #quantumcomputing #theoreticalphysics Learn more about your ad choices. Visit megaphone.fm/adchoices

Socialist pop music, the control of the clock, the beautiful digital. The Hailuoto, Finland-based artist and poemproducer discusses three important albums.Antye's picks:Silly – Mont KlamottBLACK QUANTUM FUTURISM – Waiting Time​/​Weighting​/​Wading Time: On Juneteenth, Watch Night, Freedom​'​s Eve, and Emancipation DayHelena Gough – With What RemainsHere's a trove of links through which to explore AGF's work and more:Curation: https://rec-on.orgOrganum: https://hailuotoorganum.tumblr.com/Music: https://agf-poemproducer.bandcamp.comWorks: https://antyegreie.com/Locality: https://haiart.org/Gigs: https://poemproducer.com/dates.phpMstdn: https://systerserver.town/@poemproducerDonate to Crucial Listening on Ko-fi: https://ko-fi.com/cruciallistening

Trap Talk Reptile Network Presents Ep. 571 Live All In The Tree Tuesday's Pure Locality  GTP Episode JOIN TRAP PATRON FAM HERE: https://bi t.ly/311x4gxSUPPORT THE GUEST:  / snake.spirit    / molecularreptile    / arboreal_obsession  TRAP TALK CO-HOST:  / phoenix.reptiles    / redmountainherp  SUPPORT USARK: https://usark.org/MORPH MARKET STORE: https://www.morphmarket.com/stores/ex...SUBSCRIBE TO THE TRAP TALK NETWORK: https://bit.ly/39kZBkZSUBSCRIBE TO TRAP TALK CLIPS:   / @traptalkclips  SUBSCRIBE TO THE TRAP VLOGS:https://www.youtube.com/channel/UCKxL...SUPPORT USARK:

Cited sources:Johnson, Allen W. Families of the Forest : The Matsigenka Indians of the Peruvian Amazon. Berkeley, University Of California Press, 2003. Nicholas Q. Emlen. “The Poetics of Recapitulative Linkage in Matsigenka and Mixed Matsigenka-spanish Myth Narrations”. Bridging Constructions, Language Science Press, 2019, pp. 45–77, doi:10.5281/zenodo.2563680. ‌Rosengren, Dan. “Cultivating Spirits: On Matsigenka Notions of Shamanism and Medicine (and the Resilience of an Indigenous System of Knowledge).” Revista Anales, no. 5, 1 Jan. 2002, pp. 85–108. Accessed 18 Nov. 2024.Rosengren, Dan. “Matsigenka Corporeality, a Nonbiological Reality: On Notions of Consciousness and the Constitution of Identity.” Tipití/Tipiti, vol. 4, no. 1, 1 Jan. 2006, p. 5. Accessed 18 Nov. 2024.Rosengren, Dan. “Sharing, Sociality, and Stratification - Exchange and Godparentage in the Amazon.” Anthropos, vol. 109, no. 2, 2014, pp. 485–498, https://doi.org/10.5771/0257-9774-2014-2-485. Accessed 5 May 2022.‌Santos-Granero, Fernando. 2005. “Arawakan Sacred Landscapes. Emplaced Myths, Place Rituals, and the Production of Locality in Western Amazonia.” in Kultur, Raum, Landschaft: Zur Bedeutung Des Raumes in Zeiten Der Globalität, edited by Halbmayer, Ernst and Mader, Elke., 93–122. Frankfurt am Main Verlag: Brandes and Apsel. ‌Shepard, Glenn. (1999). Pharmacognosy and the Senses in Two Amazonian Societies. PhD dissertation.Shepard, Glenn. (1999). Shamanism and diversity: A Matsigenka perspective.

Co-hosts Mark Thompson and Steve Little examine OpenAI's new Canvas feature, demonstrating how this split-screen interface revolutionizes document creation and editing for genealogists. Locality guides and research reports are used as practical examples.They explore how AI platforms like Canvas and Perplexity Spaces are challenging traditional software, suggesting a future where content creation happens primarily within AI environments rather than conventional office applications.This week's Tip of the Week addresses critical privacy considerations when using AI tools, introducing the practical "Water Cooler Rule" for protecting sensitive genealogical data.In RapidFire, they discuss Apple's research on AI reasoning, NotebookLM's enhanced audio overview capabilities for turning historical documents into conversations, and preview Apple's upcoming AI features in iOS 18.1.Whether you're embracing AI tools or just starting to explore them, this episode offers valuable insights into the evolving landscape of AI's and genealogical research.Timestamps:In the News:04:15 OpenAI Canvas: The New Frontier of AI Writing12:40 The Great Shift: AI Platforms vs Traditional Software26:20 Perplexity Spaces: Collaborative AI Research BreakthroughTip of the Week:31:30 Privacy & Protection: Smart Guidelines for AI Use in Family HistoryRapidFire:39:15 Apple's Research on AI Reasoning: What It Means for Users43:40 NotebookLM's Game-Changing Audio Features49:25 Apple Intelligence: iOS 18.1 PreviewResource LinksOpenAIChatGPT: https://chatgpt.com/ Canvas feature: https://openai.com/index/introducing-canvas/AnthropicClaude 3.5 Sonnet: https://www.anthropic.com/claude/sonnet Artifacts feature: https://support.anthropic.com/en/articles/9487310-what-are-artifacts-and-how-do-i-use-themProjects feature: https://www.anthropic.com/news/projects GoogleNotebookLM: https://notebooklm.google.com/ Google Docs: https://docs.google.com/ Google Slides: https://slides.google.com/  Audio Overview feature: https://blog.google/technology/ai/notebooklm-update-october-2024/PerplexitySpaces (collaborative feature): https://www.perplexity.ai/hub/faq/what-are-spacesPages feature: https://www.perplexity.ai/hub/blog/perplexity-pagesMicrosoftMicrosoft Office: https://www.office.com/ Microsoft Word: https://www.microsoft.com/word Microsoft Excel: https://www.microsoft.com/excel Outlook with Copilot: https://www.microsoft.com/outlook AppleApple Intelligence: https://www.apple.com/apple-intelligence/ Siri: https://www.apple.com/siri/ VOICE ASSISTANTS:Siri (Apple): https://www.apple.com/siri/ Alexa (Amazon): https://developer.amazon.com/alexa Google Assistant: https://assistant.google.com/ GENEALOGY RESOURCES:North Carolina Genealogical Society: https://www.ncgenealogy.org/ National Genealogical Society (NGS): https://www.ngsgenealogy.org/ East Coast Genetic Genealogy Seminar: https://ecggc.org/ Internet Archive (archive.org): https://archive.org/ RESEARCH TOOLS:Leeds Method (DNA analysis): https://www.danaleeds.com/the-leeds-method/ Custom GPTs: https://openai.com/index/introducing-gpts/PRESENTERS/EXPERTS MENTIONED:David McCorkle: http://davidmccorkle.com/ Dana Leeds: https://www.danaleeds.com/ Professor Ethan Mullock (author of "Cointelligence"): https://www.oneusefulthing.org/p/i-cyborg-using-co-intelligenceTagsFamily History, Genealogy, Artificial Intelligence, AI, Generative AI, OpenAI Canvas, Canvas, AI Writing, Privacy Tips, Apple AI, Perplexity Spaces, NotebookLM, ChatGPT, Claude, Anthropic, Microsoft Office, Google Notebook, Perplexity, iOS 18, Genealogy Tools, Family Research, DNA Genealogy, Genealogy Research, Family Historian, AI Tools, Content Creation, Digital Writing, Collaboration, Workspaces, Smart Assistants, Document Editing, Research Tools, Writing Tools, Data Privacy, Data Protection, AI Privacy, AI Ethics, Target Audience: Genealogists, Family Historians, Tech Writers, Researchers, Digital Creators.

Connor had the pleasure of sitting down with Omar Ramadan, a former big tech entrepreneur who transitioned into the world of crypto and DePIN. They delved into the concept of Content Delivery Networks (CDNs) and how they play a crucial role in enhancing user experience by caching website data closer to users geographically. Omar shared his background, including his involvement in projects like Magma and OpenCellular, which aimed to provide connectivity to remote communities. They discussed the limitations of traditional CDNs, particularly in live streaming scenarios where multiple users access the same content. Omar highlighted the inefficiencies of unicast-based CDNs and introduced the idea of multicast CDNs, which can significantly reduce bandwidth usage by allowing multiple users to share the same stream. The conversation also touched on the challenges faced by streaming giants in deploying CDN infrastructure in high-demand areas, as well as the potential of decentralized infrastructure and blockchain technology to incentivize individuals to run their own CDN nodes. Omar explained how DePIN's could help overcome the cold start problem and facilitate a more efficient and cost-effective CDN model. Overall, this episode provided valuable insights into the future of content delivery, the role of decentralization, and the exciting possibilities that lie ahead in the intersection of technology and crypto. 00:00 - Introduction 00:38 - Omar's Transition from Big Tech to Crypto 02:54 - Understanding CDNs: A User's Perspective 03:32 - How CDNs Work: Caching and Latency 05:01 - Challenges for Remote Areas and Streaming Giants 06:25 - The Role of Locality in CDN Performance 08:24 - CDNs and the Future of the Metaverse 10:19 - Multicast CDNs: A New Paradigm 10:41 - Incentives and Blockchain in CDN Infrastructure 12:30 - Conclusion  Disclaimer: The hosts and the firms they represent may hold stakes in the companies mentioned in this podcast. None of this is financial advice.

In this episode of The Vint Podcast, Brady and Billy chat with Jon Fine, Editor-in-Chief of The New Wine Review. Jon shares his fascinating journey into the world of wine, discussing how his passion for music and writing shaped his unique perspective. He dives into the inspiration behind The New Wine Review, which aims to demystify wine for enthusiasts of all levels while highlighting lesser-known producers and regions.Jon also talks about what differentiates The New Wine Review from traditional wine publications, emphasizing the focus on community, exploration, and engaging storytelling. He introduces the publication's interactive Slack channel, where subscribers and contributors exchange tips, travel recommendations, and discuss their latest wine discoveries. Throughout the episode, Jon stresses the importance of highlighting under-the-radar and under appreciated wines, bringing attention to producers, regions, and vintages that often go unnoticed aside from those in the know. The Billy, Brady, and Jon touch on topics such as natural wines, hidden gems on wine lists, the significance of intellectual and sensuous enjoyment in wine, and the vibrant conversations happening in the wine world today. This episode offers listeners a fresh, inclusive perspective on wine, blending enthusiasm with knowledge and encouraging open-minded exploration.Chapters:00:51 Weekend Wine Adventures03:37 Exploring Bordeaux's New White Wine07:30 Introducing John Fine and The New Wine Review12:23 John Fine's Wine Journey23:13 The New Wine Review: Vision and Team30:19 Cretan Wine and Legacy Publications32:11 Exploring Wine Regions and Personal Preferences34:21 The Locality and Romance of Wine35:44 Diverse Wine Regions and Producers42:04 The New Wine Review Community44:32 Hidden Gems on Wine ListsThe Vint Podcast is presented by Coravin, the world's leader in wine preservation systems. Listeners of the Vint Podcast can take 15% off their purchase on Coravin.com by using promo code VINT15 at checkout*. Members of the trade can access exclusive discounts at trade.Coravin.com.The Vint Podcast is a production of the Vint Marketplace, your source for the highest quality stock of fine wines and rare whiskies. Visit www.vintmarketplace.com. To learn more about Vint and the Vint Marketplace, visit us at https://vint.co or Vintmarketplace.com or email Brady Weller at brady@vint.co, or Billy Galanko at Billy@vintmarketplace.com.*Terms and Conditions Apply. Offer valid only on Coravin.com while supplies last. Pricing and discount are subject to change at any time. Coravin reserves the right to limit order quantities. No adjustments to prior purchases. Not valid for cash. Cheers!Past Guests Include: William Kelley, Peter Liem, Eric Asimov, Bobby Stuckey, Rajat "Raj" Parr, Erik Segelbaum, André Hueston Mack, Emily Saladino, Konstantin Baum, Landon Patterson, Heather Wibbels, Carlton "CJ" Fowler, Boris Guillome, Christopher Walkey, Danny Jassy, Kristy Wenz, Dan Petroski, Buster Scher, Andrew Nelson, Jane Anson, Tim Irwin, Matt Murphy, Allen Meadows, Altan Insights, Tim Gaiser, Vince Anter, Joel Peterson, Megan O'Connor, Adam Lapierre, Jason Haas, Ken Freeman, Lisa Perrotti-Brown,...

In this episode of the Research Like a Pro Genealogy podcast, Diana and Nicole discuss using AI in locality research, focusing on the Isabella Weatherford project. They emphasize the importance of locality guides in genealogical research, as they provide essential historical context, help researchers understand available records, and shed light on migration patterns and local events that may have impacted ancestors' lives. The hosts explore how AI tools like ChatGPT, Claude, Gemini, and Perplexity can be used to create locality guides more efficiently. Diana shares her experience using AI to create a locality guide for Dallas County, Texas, in the 1870s, demonstrating how AI helped her gather historical and geographical information, create a timeline of major events, and identify relevant record collections. Diana and Nicole also discuss the strengths and limitations of different AI tools and offer tips for effectively using AI in locality research. They emphasize the importance of verifying information from AI sources and using AI as a tool to complement, rather than replace, traditional research methods. This summary was generated by Google Gemini. Links Post-apocalyptic education by Ethan Mollick - https://www.oneusefulthing.org/p/post-apocalyptic-education Using AI in Locality Research: Isabella Weatherford Project Part 3 - https://familylocket.com/using-ai-in-locality-research-isabella-weatherford-project-part-3/ Custom GPT - Diana's Genealogy Locality Guide Builder by Diana Elder - https://chatgpt.com/g/g-Y7oqvFVmP-diana-s-genealogy-locality-guide-builder Custom GPT - Locality Guide for Genealogical Research by Mark Thompson - https://chatgpt.com/g/g-TpLAIvCzD-locality-guide-for-genealogical-research Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code “FamilyLocket” at checkout.   Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series 2024 - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product/research-like-a-pro-webinar-series-2024/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes, Stitcher, Google Podcasts, or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Top 20 Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

CarMax Park coming to the Diamond District, students walked out of classes at VCU, Goochland quarry expansion approved, and other stories.

In this episode of Altitude, Woody is joined by co-host Jason Gervickas and special guest Matt Simpson, EVP of Business Development and Global Channel at Megaport. Matt brings a unique perspective to the show, having transitioned from a background in hospitality and hotels to becoming a leader in the network connectivity industry.The trio dives deep into the concept of the "new edge," focusing on the evolution and future of edge technology and its critical role in cloud transformation. Matt shares his journey from the early days of Megaport, highlighting how private connectivity solutions like Direct Connect and ExpressRoute revolutionized the industry. They discuss the initial challenges enterprises faced with data being on-prem while applications were agilely developed in the cloud, leading to the rise of dedicated and private connectivity. Learn more about Altitude here. Learn how the combined power of Aviatrix and Megaport provides customers with secure, resilient, and high-performance multicloud and hybrid cloud connectivity here.Connect with Matt on LinkedIn here.Timestamped Overview:00:00 Transitioning from hospitality to network connectivity.06:08 Private connectivity essential for serious cloud adoption.07:08 Challenges of data gravity in Matt's previous role.14:34 Locality of LLMs and AI27:23 The Megaport & Aviatrix partnership

If you telework, you lose locality pay. That's the gist of a provision in the Federal Employee Return To Work Act … sponsored in the Senate by Louisiana Republican Bill Cassidy. That's not the only challenge to federal pay Cassidy has proposed. Details now from federal employment attorney Stephanie Rapp-Tully of Tully Rinckey. Learn more about your ad choices. Visit podcastchoices.com/adchoicesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

If you telework, you lose locality pay. That's the gist of a provision in the Federal Employee Return To Work Act … sponsored in the Senate by Louisiana Republican Bill Cassidy. That's not the only challenge to federal pay Cassidy has proposed. Details now from federal employment attorney Stephanie Rapp-Tully of Tully Rinckey. Learn more about your ad choices. Visit megaphone.fm/adchoices

Jay Shek is the VP Consumer Product of Hone Health. Hone is the premier men's optimization clinic that helps men get their spark back and be their best self. Prior to Hone Health, Jay was the Director of Product Management at Noom, a product that helped people live healthier lives by changing their long-term habits. Jay also worked at Facebook, Snapfish, and founded his own startup Locality. Jay has a passion for mastering new life skills like health, fitness, cooking, and fashion. In this episode, he shares his learnings with us.

In this episode, we talk with Jacob Bratz of Long Leaf Reptila, THP, and the Flipping Tin Podcast about Field herping and locality keeping.Follow:Zac Loughman @https://www.instagram.com/dr_crawdad/On FB https://www.facebook.com/profile.php?id=100011423011423Clint Bartley @IG: MetazoticsLLC FB: MetazoticsWebsite: metazotics.comExo-terrahttps://exo-terra.comMPR NetworkFB: https://www.facebook.com/MoreliaPythonRadioIG: https://www.instagram.com/mpr_network/YouTube: https://www.youtube.com/channel/UCtrEaKcyN8KvC3pqaiYc0RQSwag store: https://teespring.com/stores/mprnetworkPatreon: https://www.patreon.com/moreliapythonradio ★ Support this podcast on Patreon ★

Sam tells Ryan about a recent talk he gave at BigSkyDevCon. They chat about how backend frameworks are raising the ceiling of what UIs they're capable of delivering, how frontend frameworks are raising the floor of what backend features they come bundled with, and what each community can learn from the other.Timestamps:0:00 - Intro4:23 - Recap of Ryan Florence's talk6:49 - Overview of "High floor, high ceiling"10:02 - Cohesion is the biggest strength of backend frameworks17:10 - Why doesn't Rails for JavaScript exist?23:48 - Locality of behavior is the biggest strength of frontend frameworks33:14 - The use of lexical scope in React50:27 - Which community is raising both the floor and ceiling the most?Links:"High floor, high ceiling" talk

AdTechGod sits down with Doug Knopper. Doug is the co-founder of Freewheel and serves on the board of several adtech companies, including Magnite, Extreme Reach, and Locality, and has previously been on the boards of TripleLift and WURL.Freewheel, which was acquired by Comcast for $360 million in 2014 remains a major player in the CTV space, offering a comprehensive platform for buyers and sellers working with CTV and video partners globally.Thank you RainBarrel for advertising on this episode.

https://linktr.ee/IntoTheNorthPodcast Patreon: https://www.patreon.com/Intothenorthpodcast

Tim Palmer joins Curt Jaimungal to discuss the progress and persistent challenges in fundamental physics, touching on topics such as the successes of the Standard Model, the unresolved issues of quantum mechanics and general relativity, and the potential implications of quantum entanglement and non-locality for our understanding of the universe. Please consider signing up for TOEmail at https://www.curtjaimungal.org  Support TOE: - Patreon: https://patreon.com/curtjaimungal (early access to ad-free audio episodes!) - Crypto: https://tinyurl.com/cryptoTOE - PayPal: https://tinyurl.com/paypalTOE - TOE Merch: https://tinyurl.com/TOEmerch  Follow TOE: - *NEW* Get my 'Top 10 TOEs' PDF + Weekly Personal Updates: https://www.curtjaimungal.org - Instagram: https://www.instagram.com/theoriesofeverythingpod - TikTok: https://www.tiktok.com/@theoriesofeverything_ - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - iTunes: https://podcasts.apple.com/ca/podcast/better-left-unsaid-with-curt-jaimungal/id1521758802 - Pandora: https://pdora.co/33b9lfP - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Subreddit r/TheoriesOfEverything: https://reddit.com/r/theoriesofeverything  

In episode 150 Steph fields some great questions from our good friend Anonymous (ha!) about naming your biz and choosing a HA based on locality. She also breaks down how to become a travel agent in some handy steps! 1. I am just stepping into starting a travel agency at the very early stages and still working on what it would look like for me. When considering a niche and a business name, I suspect having the niche in the business name can help, but would it cause issues if I wanted to pivot or expand to a different niche at some point in the future and possibly require a business name change and rebranding challenges. Do you have any advice or should I just worry about the future. –Anonymous 2. How important is it to join a local host agency? —Anonymous 3. I know there isn't one set answer for this, but how would you break down the steps on how to become a travel agent? —Anonymous TODAY'S RESOURCES: https://hostagencyreviews.com/blog/find-a-travel-niche (Guide to choosing a travel niche) https://hostagencyreviews.com/blog/tips-for-choosing-travel-agency-names (Tips for choosing travel agency names + examples) https://hostagencyreviews.com/7DS-lite (HAR's 7 Day Setup LITE is a free online course that helps you start your agency. It does not have support and takes you through resources to help you make things happen) https://hostagencyreviews.com/7DS-accelerator (HAR's 7 Day Setup Accelerator course with 70+ easily digestible videos, 48 exclusive resources, monthly live meetups with HAR team and others for support and accountability, priority email support) https://hostagencyreviews.com/hosts (Find a map of host agencies on our host agency list.) https://hostagencyreviews.com/blog/how-to-become-a-travel-agent (All you need to know to become a travel agent) https://hostagencyreviews.com/page/travel-advisor-research-reports/ (Travel agent survey data on employee travel agents and self-employed travel agents.)

In the dynamic landscape of today's digital era, communication has become both effortless and fraught with challenges. Social media platforms amplify voices, often leading to hurtful comments and the spread of misinformation. In acknowledging these pitfalls, it becomes imperative to approach conversations with empathy and openness, fostering mutual understanding even in the face of emotionally charged topics. This realization forms the foundation of our journey as we delve into the complexities of consciousness and human connection.   History serves as a sobering reminder of the destructive power of intolerance and ignorance. From the Crusades to modern-day conflicts, the underlying cause remains the same: a failure to learn from past mistakes. Through reflection, we uncover the importance of understanding history to prevent repeating its darkest chapters. It's a call to action, urging us to approach discussions with an open mind and a willingness to learn, striving for better understanding and meaningful connections.   Central to our exploration is the concept of consciousness and its non-local nature. This intriguing idea challenges our understanding of existence and the interconnectedness of all things. As we navigate the complexities of consciousness, we come to realize the importance of understanding our current level of experience for a profound human existence. It's a journey of self-discovery, prompting us to reflect on the nature of reality and our place within it.   Amidst discussions of consciousness lies the age-old debate of predetermination versus free will. We grapple with the notion that our actions may be predetermined by the universe's initial conditions, yet we also cherish the agency to shape our destinies. It's a delicate balance, prompting ethical considerations and introspection into our roles as conscious beings navigating the vast expanse of existence.   At the heart of our exploration lies the quest for personal responsibility and ethical growth. We are challenged to align our actions with universal laws, recognizing the interconnectedness of all things. Through introspection and alignment with these principles, we pave the way for personal and collective evolution, grounded in love and understanding.   Ultimately, our purpose as humans is to evolve and embody the universal love that surrounds us. Each moment presents an opportunity for growth and self-discovery, guiding us towards a deeper understanding of our existence and our interconnectedness with all things. It's a journey of introspection, reflection, and collective evolution—a journey we invite you to embark on with us. Join us Alexander and Jason as they delve into the depths of consciousness and embrace the transformative power of understanding and love.

Razak Khan's Minority Pasts: Locality, Emotions, and Belonging in Princely Rampur (Oxford UP, 2022) explores the diversity of the histories and identities of Muslims in Rampur-the last Muslim-ruled princely state in colonial United Provinces and a city that is pejoratively labelled as the center of "Muslim vote bank" politics in contemporary Uttar Pradesh. The book highlights the importance of locality and emotions in shaping Muslim identities, politics, and belonging in Rampur. The book shows that we need to move beyond such homogeneous categories of nation and region, in order to comprehend local dynamics that allow a better and closer understanding of the historical re-negotiations of politics and identities by Muslims in South Asia. This is the first comprehensive English-language monograph on the local history and politics of Rampur princely state, based on Persian, Pashto, Urdu, Hindi, and English archives and oral histories of Rampuris. The book provides insights into the various facets of the political, economic, religious, literary, socio-cultural, and affective history of Rampur and Rampuris in India and Pakistan. Anindita Ghosh is a doctoral candidate in history at the University of Illinois Chicago. Her dissertation is about the histories of absorption of the eastern native states of South Asia into the nations and their socio- political afterlives in the post- colonial nations. Arighna Gupta is a doctoral candidate in history at the University of Michigan, Ann Arbor. His dissertation attempts to trace early-colonial genealogies of popular sovereignty located at the interstices of monarchical, religious, and colonial sovereignties in India and present-day Bangladesh. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Razak Khan's Minority Pasts: Locality, Emotions, and Belonging in Princely Rampur (Oxford UP, 2022) explores the diversity of the histories and identities of Muslims in Rampur-the last Muslim-ruled princely state in colonial United Provinces and a city that is pejoratively labelled as the center of "Muslim vote bank" politics in contemporary Uttar Pradesh. The book highlights the importance of locality and emotions in shaping Muslim identities, politics, and belonging in Rampur. The book shows that we need to move beyond such homogeneous categories of nation and region, in order to comprehend local dynamics that allow a better and closer understanding of the historical re-negotiations of politics and identities by Muslims in South Asia. This is the first comprehensive English-language monograph on the local history and politics of Rampur princely state, based on Persian, Pashto, Urdu, Hindi, and English archives and oral histories of Rampuris. The book provides insights into the various facets of the political, economic, religious, literary, socio-cultural, and affective history of Rampur and Rampuris in India and Pakistan. Anindita Ghosh is a doctoral candidate in history at the University of Illinois Chicago. Her dissertation is about the histories of absorption of the eastern native states of South Asia into the nations and their socio- political afterlives in the post- colonial nations. Arighna Gupta is a doctoral candidate in history at the University of Michigan, Ann Arbor. His dissertation attempts to trace early-colonial genealogies of popular sovereignty located at the interstices of monarchical, religious, and colonial sovereignties in India and present-day Bangladesh. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/history

Razak Khan's Minority Pasts: Locality, Emotions, and Belonging in Princely Rampur (Oxford UP, 2022) explores the diversity of the histories and identities of Muslims in Rampur-the last Muslim-ruled princely state in colonial United Provinces and a city that is pejoratively labelled as the center of "Muslim vote bank" politics in contemporary Uttar Pradesh. The book highlights the importance of locality and emotions in shaping Muslim identities, politics, and belonging in Rampur. The book shows that we need to move beyond such homogeneous categories of nation and region, in order to comprehend local dynamics that allow a better and closer understanding of the historical re-negotiations of politics and identities by Muslims in South Asia. This is the first comprehensive English-language monograph on the local history and politics of Rampur princely state, based on Persian, Pashto, Urdu, Hindi, and English archives and oral histories of Rampuris. The book provides insights into the various facets of the political, economic, religious, literary, socio-cultural, and affective history of Rampur and Rampuris in India and Pakistan. Anindita Ghosh is a doctoral candidate in history at the University of Illinois Chicago. Her dissertation is about the histories of absorption of the eastern native states of South Asia into the nations and their socio- political afterlives in the post- colonial nations. Arighna Gupta is a doctoral candidate in history at the University of Michigan, Ann Arbor. His dissertation attempts to trace early-colonial genealogies of popular sovereignty located at the interstices of monarchical, religious, and colonial sovereignties in India and present-day Bangladesh. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/islamic-studies

Today we're joined by Ben Prystawski, a PhD student in the Department of Psychology at Stanford University working at the intersection of cognitive science and machine learning. Our conversation centers on Ben's recent paper, “Why think step by step? Reasoning emerges from the locality of experience,” which he recently presented at NeurIPS 2023. In this conversation, we start out exploring basic questions about LLM reasoning, including whether it exists, how we can define it, and how techniques like chain-of-thought reasoning appear to strengthen it. We then dig into the details of Ben's paper, which aims to understand why thinking step-by-step is effective and demonstrates that local structure is the key property of LLM training data that enables it. The complete show notes for this episode can be found at twimlai.com/go/673.

Free Copy of My Book: Building Wealth In the TSP: Your Road Map To Financial Freedom as A Federal Employee: https://app.hawsfederaladvisors.com/free-tsp-e-book FREE WEBINAR: "The 7 Biggest FERS Retirement Mistakes": https://app.hawsfederaladvisors.com/7biggestmistakeswebinar Want to schedule a consultation? Click here: https://hawsfederaladvisors.com/work-with-us/ Submit a question here: https://app.hawsfederaladvisors.com/question-submission I am a practicing financial planner, but I'm not your financial planner. Please consult with your own tax, legal and financial advisors for personalized advice.

David Albert is the Frederick E. Woodbridge Professor of Philosophy at Columbia University and one of the world's most respected philosophers of physics. He is also the director of the Philosophical Foundations of Physics program at Columbia and a faculty member of the John Bell Institute for the Foundations of Physics. This is David's fifth (!) appearance on Robinson's Podcast. He appeared on episode #23 with Justin Clarke-Doane on metaethics and absolute space, episode #30 on the philosophy of time, episode #67 with Tim Maudlin on the foundations of quantum theory, and episode #106 with Sean Carroll on Many-Worlds and fine-tuning. In this episode, Robinson and David discuss his new book, A Guess at the Riddle: Essays on the Physical Underpinnings of Quantum Mechanics (Harvard, 2023), and the metaphysics of quantum mechanics. If you're interested in the foundations of physics—which you absolutely should be—then please check out the JBI, which is devoted to providing a home for research and education in this important area. Any donations are immensely helpful at this early stage in the institute's life. A Guess at the Riddle: https://a.co/d/6qcsidl The John Bell Institute: https://www.johnbellinstitute.org OUTLINE 00:00 In This Episode… 00:56 Introduction 05:12 On The Metaphysics of Quantum Mechanics 30:24 The Complex Origins of Antirealism in Quantum Physics 37:29 Instrumentalism and String Theory  45:31 The Amazing History of Locality in Physics 01:22:38 Quantum Mechanics as Experimental Metaphysics 01:26:27 What Is Wave-Function Realism in the Foundations of Quantum Mechanics? Robinson's Website: http://robinsonerhardt.com Robinson Erhardt researches symbolic logic and the foundations of mathematics at Stanford University. Join him in conversations with philosophers, scientists, weightlifters, artists, and everyone in-between.  --- Support this podcast: https://podcasters.spotify.com/pod/show/robinson-erhardt/support

YouTube link https://youtu.be/rd7a_5M_37I Tim Maudlin, a physicist specializing in quantum mechanics, and Bernardo Kastrup, a philosopher with focus on consciousness studies. Topics include the ontological interpretations of quantum theory ("realism") and Bell's theorem. An attemptolocution. NOTE: The perspectives expressed by guests don't necessarily mirror my own. There's a versicolored arrangement of people on TOE, each harboring distinct viewpoints, as part of my endeavor to understand the perspectives that exist. LINKS MENTIONED: - Go Fund Me for John Bell Institute: https://www.gofundme.com/f/a-permanent-home-for-the-john-bell-institute - John Bell Institute: https://www.johnbellinstitute.org - Essentia Foundation: https://www.essentiafoundation.org OTHER TIM / BERNARDO APPEARENCES: - Tim Maudlin (solo): https://youtu.be/fU1bs5o3nss - Tim Maudlin Λ Tim Palmer: https://youtu.be/883R3JlZHXE - Bernardo Kastrup (solo): https://youtu.be/lAB21FAXCDE - Benardo Λ John Vervaeke: https://youtu.be/UWcTmeAs44I - Bernardo Λ Susan Blackmore: https://youtu.be/jrVnAWP2XEs - Bernardo Λ Donald Hoffman: https://youtu.be/VmQXpKyUh4g - Bernardo Λ Sabine Hossenfelder: https://youtu.be/kJmBmopxc1k - Bernardo Λ Chris Langan: https://youtu.be/HsXxgQy4xLQ - TOE Playlists: https://www.youtube.com/@TheoriesofEverything/playlists - Patreon: https://patreon.com/curtjaimungal (early access to ad-free audio episodes!) - Crypto: https://tinyurl.com/cryptoTOE - PayPal: https://tinyurl.com/paypalTOE - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - iTunes: https://podcasts.apple.com/ca/podcast/better-left-unsaid-with-curt-jaimungal/id1521758802 - Pandora: https://pdora.co/33b9lfP - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Subreddit r/TheoriesOfEverything: https://reddit.com/r/theoriesofeverything - TOE Merch: https://tinyurl.com/TOEmerch TIMESTAMPS: 00:00:00 Introductions to Tim Λ Bernardo 00:01:47 John Bell Institute and non-Locality 00:03:50 Bernardo's latest book and writing process 00:05:58 Local realism and Bell's theorem 00:14:04 Curt's message to audience Learn more about your ad choices. Visit megaphone.fm/adchoices

Have you heard of Django? It's this little web framework that, well, kicked off much of Python's significance in the web space back in 2005. And that makes Django officially an adult. That's right, Django is now 18. And Django continues to lead the way on how community should be done for individual projects such as web frameworks. We have Carlton Gibson and Will Vincent back on the show this episode to discuss a bit of the Django history, Django trends in 2023, a little HTMX + Django, and lots more. Links from the show Guests Will Vincent: wsvincent.com Carlton Gibson: @carlton@fosstodon.org Button.dev: btn.dev Learn Django: learndjango.com Django News: django-news.com Yak-Shaving to Where the Puck is Going to Be Talk: youtube.com Open Source for the Long Haul: fosstodon.org Django 4.2: docs.djangoproject.com Django 5: docs.djangoproject.com Environs: github.com Neapolitan: github.com Django Template Paritals: github.com Jinja Partials: github.com Django Chat Podcast: djangochat.com Locality of Behavior Essay: htmx.org HTMX: htmx.org You're Fullstack Now Meme: twitter.com Deployment Checklist: docs.djangoproject.com Django-HTMX: github.com Django @Instagram DjangoChat: djangochat.com Talk Python HTMX Course: talkpython.fm Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors Sentry Error Monitoring, Code TALKPYTHON Talk Python Training

YouTube link https://youtu.be/883R3JlZHXE Tim Palmer is a Royal Society Research Professor in the Department of Physics at Oxford. Tim Maudlin is a Professor of Philosophy at New York University, specializing in the philosophy of physics. We discuss superdeterminism, chaos theory, and free variables. - Patreon: https://patreon.com/curtjaimungal (early access to ad-free audio episodes!) - Crypto: https://tinyurl.com/cryptoTOE - PayPal: https://tinyurl.com/paypalTOE - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - iTunes: https://podcasts.apple.com/ca/podcast/better-left-unsaid-with-curt-jaimungal/id1521758802 - Pandora: https://pdora.co/33b9lfP - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Subreddit r/TheoriesOfEverything: https://reddit.com/r/theoriesofeverything - TOE Merch: https://tinyurl.com/TOEmerch LINKS MENTIONED: - Tim Maudlin's podcast on TOE: https://youtu.be/fU1bs5o3nss - Primacy of Doubt (Tim Palmer's book): https://amzn.to/3Oo55k7 - Metaphysics Within Physics (Tim Maudlin's book): https://amzn.to/3pXHNcn - Quantum Non-Locality and Relativity (Tim Maudlin's book): https://amzn.to/44QoS2F - Go Fund Me for "The John Bell Institute" initiative: https://www.gofundme.com/f/a-permanent-home-for-the-john-bell-institute - Speakable and Unspeakable in Quantum Mechanics (John Bell's book): https://amzn.to/43RyQ2t TIMESTAMPS: 00:00:00 Introduction 00:02:04 Explaining Superdeterminism & Fractal Cosmology 00:05:06 What is Tim Palmer working on 00:09:24 What is Tim Maudlin working on 00:11:47 Assumptions of Bell's inequality / theorem 00:22:40 Locality and Superdeterminism 00:28:33 Summary of disagreement + why do we care what Bell said? 00:32:54 Counterfactuals & Counterfactual definiteness 00:59:38 Chaos theory, attractors, and fractals 01:26:32 Free variables and ensembles 01:36:30 Invariant set theory 01:48:21 Relevant links and teaser for Part 2 Learn more about your ad choices. Visit megaphone.fm/adchoices

Last year's Nobel Prize for experimental tests of Bell's Theorem was the first Nobel in the foundations of quantum mechanics since Max Born in 1954. Quantum foundations is enjoying a bit of a resurgence, inspired in part by improving quantum technology but also by a realization that understanding quantum mechanics might help with other problems in physics (and be important in its own right). Tim Maudlin is a leading philosopher of physics and also a skeptic of the Everett interpretation. We discuss the logic behind hidden-variable approaches such as Bohmian mechanics, and also the broader question of the importance of the foundations of physics.Support Mindscape on Patreon.Blog post with transcript: https://www.preposterousuniverse.com/podcast/2023/06/26/241-tim-maudlin-on-locality-hidden-variables-and-quantum-foundations/Tim Maudlin received his Ph.D. in philosophy from the University of Pittsburgh. He is currently a professor of philosophy at New York University. He is a member of the Academie Internationale de Philosophie des Sciences and the Foundational Questions Institute (FQXi). He has been a Guggenheim Fellow. He is the founder and director of the John Bell Institute for the Foundations of Physics in Croatia.Web siteNYU web pageGoogle Scholar publicationsPhilPeople profileAmazon author pageWikipediaContribute to the John Bell Institute!See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.