Podcasts about networked

CITR 101.9FM (Vancouver)'s 24 HOURS OF RADIO ART in a snack size format! Difficult music, harsh electronics, spoken word, cut-up/collage and general CRESPAN© weirdness. Tonight's broadcast features ANDREJA ANDRIC AND THE NETWORKED ENSEMBLE | ANJA KREYSING | RAFA RAMOS SANIA | SEABUCKTHORN | MICHAEL GRUNDITZ | MAURIZIO BIANCHI | MASAIDEN | CADLAG | TREPANERINGSRITUALEN | DAVID KOVACS | RSN / CARSTEN VOLLMER | TRIGGER HAPPY | JONAS BONNETTA / STEFAN CHRISTOFF | BÅLSAM, and LAB'S CLOUD.

Anjie Vichayanonda is the founder and CEO of Leg Up Legal, a mentorship platform that connects aspiring law students with attorneys before they apply to law school. In this episode, Anjie shares how mentorship changed the course of her own career, why exposure matters before making the investment in law school, and how lawyers can use their knowledge to create opportunities for others.Lawyer Side HustlesLeg Up Legal began as an effort to solve a problem Anjie experienced firsthand. She knew how difficult it could be for aspiring lawyers to find mentors, learn about different practice areas, and understand what life as a lawyer actually looks like before committing to law school. Instead of accepting that challenge as inevitable, she built a platform designed to make mentorship more accessible. “I wanna be able to teach these things to hundreds of people, thousands of people,” shares Anjie Vichayanonda in Episode 28 of You Are a Lawyer.In addition to running Leg Up Legal, Anjie also became a published co-author of Networked, an anthology written alongside 19 other women lawyers during the COVID-19 pandemic. The project captured stories of resilience, career pivots, personal challenges, and professional growth during a historic moment. Both the book and Leg Up Legal reflect Anjie's broader passion for helping people navigate uncertainty through connection, mentorship, and community.  This episode is produced by Skip the Boring Stuff, a podcast strategy company for business owners and creatives.

How do our everyday digital traces—social posts, check-ins, photos—shape our identities, relationships, and the very nature of privacy in a hyper-connected world? Kate O’Neill sits down with Lee Humphreys, professor and Chair of the Department of Communication at Cornell University and author of The Qualified Self: Social Media and the Accounting of Everyday Life. The conversation explores the rich history and surprising continuity of documenting daily life, from centuries-old diaries and photo albums to today's social media and sensor-driven platforms. Topics Covered: The history and meaning of phatic communication Social media as an extension of historical practices (diaries, notebooks, albums) Privacy, data, and the networked self The context collapse of online identities Location-based sharing and identity work Algorithmic identities and platform agency The impact of digital spaces on rituals and remote work Policy, power, and responsibility in platform design Hopeful uses of technology to build community Connect with Lee HumphreysCornell WebsiteLinkedIn”The Qualified Self – Social Media and the Accounting of Everyday Life” Episode Chapters: 00:04 Introduction to the Tech Humanist Show & guest00:17 The concept of phatic communication02:27 Lee's route into communication technology04:42 From photo manipulation to tech distrust06:00 Diaries, Twitter, and the origins of media accounting12:10 Social reinforcement vs. narcissism in social media13:33 Location sharing and its role in identity16:35 Parasocial relationships and context collapse19:53 Data, experience, and mismatched realities22:33 The shifting meaning of place and time in data24:31 Networked privacy and the collective dimension27:39 Incentives, policy, and platform accountability30:01 Algorithmic identity and the “qualified self”35:26 Digital rituals, remote work, and connection40:31 Closing thoughts: technology, humanity, and hope41:04 Lee’s story of hope and innovation through tech42:58 Episode wrap-up and thanks

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

Northern Ireland, the Far-Right, and the Battle for Democracy with Heidi BirickIn this episode of the Explaining History Podcast, we are joined again by Heidi Birick of the Global Project Against Hate and Extremism to discuss the recent far-right violence in Northern Ireland – and the global networks that fuelled it.In recent weeks, Northern Ireland was rocked by a series of violent attacks against migrant communities following an incident in which a Sudanese national attacked an NHS worker. The attack was not terrorist-related and had no connection to the wider migrant community. But the global far-right seized on the event, spreading misinformation across social media and calling for violence. The footage of the resulting attacks – houses burned, people terrified to leave their homes – had all the hallmarks of a pogrom.Heidi explains how far-right groups are tightly networked in the online space, sharing messaging across continents, coordinating through unmoderated chat channels like Telegram, and meeting in person at conferences to plan their strategy. Figures like Tommy Robinson and Elon Musk amplified the calls for violence – Musk, in particular, has been openly promoting white supremacist ideas, calling for "remigration", and threatening civil war in the UK.We discuss the alarming power of a trillionaire like Musk to ride roughshod over public order and civil society from anywhere in the world, and the inability of states – even powerful ones like the United Kingdom – to respond effectively. The erosion of content moderation on X (formerly Twitter) has created a safe haven for hate speech, and the US government's hostility to online regulation has made the problem worse.But there is hope. The far-right riots in Belfast were met with an enormous counter-protest the following day – the largest show of solidarity in Northern Ireland since the Good Friday Agreement. Heidi argues that the majority of people reject these ideas, and that movements for democracy and human rights remain powerful. She also reflects on the need for structural solutions – taxing billionaires, regulating media, and rebuilding state capacity to deliver for ordinary people.Topics covered:The far-right violence in Northern IrelandTommy Robinson and Elon Musk's role in spreading disinformationThe global network of far-right groupsElon Musk's influence on content moderation and hate speechThe power of trillionaires to undermine democracyThe ineffectiveness of state responsesCounter-protests in Belfast and the rejection of fascismComparisons with historical fascismThe Henry VII principle and the need to tax oligarchsThe generational battle against hateHeidi Birick is co-founder of the Global Project Against Hate and Extremism. Visit globalextremism.org for resources and to support their vital work.Explaining History helps you understand the 20th Century through critical conversations and expert interviews. We connect the past to the present. If you enjoy the show, please subscribe and share.▸ Support the Show & Get Exclusive ContentBecome a Patron: patreon.com/explaininghistory▸ Join the Community & Continue the ConversationFacebook Group: facebook.com/groups/ExplainingHistoryPodcastSubstack: theexplaininghistorypodcast.substack.com▸ Read Articles & Go DeeperWebsite: explaininghistory.org Hosted on Acast. See acast.com/privacy for more information.

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This episode reveals why quantum computing's next big breakthrough might not be about building better qubits, it's about connecting them together. NuQuantum's journey is a masterclass in pivoting based on market reality. "Quantum computing is reassuringly hard," Ed explains. "Whatever technique you pursue, there are different limits of scale. But pretty much every modality hits a point where you can't physically assemble enough qubits in a monolithic machine to solve valuable problems."The solution? Apply classic computing. Just as data centres rely on networking to make distributed computing work, quantum computers need interconnection to scale beyond their physical limits."No one company, probably no one country is going to dominate this. This is going to be a collective endeavour, woven together to make highly valuable, highly resilient solutions."With Series A funding secured, NuQuantum is on an aggressive expansion trajectory.Ready to dive deeper? Listen to the full episode on the Cambridge Tech Podcast to hear Ed's insights on scaling quantum systems, building diverse teams, and why decent coffee matters more than you'd think.Headline sponsor Holden Polestar#CamTechPod Hosted on Acast. See acast.com/privacy for more information.

Chinese giants like BYD have surged in the share of previously impenetrable markets like the EU and the Gulf, prompting concern by policymakers and excitement by consumers looking to save on their next car. How did we get here? Where does the industry go from here? To answer that, host Nick Perloff-Giles sits down with Automobility's Bill Russo, former auto executive and expert in the automotive industry, to discuss how China isn't just rethinking auto manufacturing - it's rethinking what a mobility industry even looks like.

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In this episode of The Future of Identity Podcast, I'm joined by Ross Freiman-Mendel, Head of Product Growth at Persona, to explore the shift from one-off, siloed KYC toward network-based and reusable identity products. Ross walks through Persona's consumer and enterprise identity networks, including Reusable Personas, Persona Connect, and emerging work on Know Your Agent (KYA), and explains why redundant verification has become one of the biggest unsolved problems in identity.Our conversation goes deep on the practical realities of building reusable identity at scale. Ross shares concrete adoption metrics, including 2× higher conversion rates, significantly faster completion times, and why over 90% of Persona customers are now activated on the network. We also unpack how network-based identity improves fraud detection while simultaneously reducing user friction - one of the rare win-win scenarios in identity.In this episode we explore:Why redundant KYC is breaking onboarding experiences and how transferable identity solves it.The difference between consumer-owned identity wallets (Reusable Personas) and enterprise-to-enterprise sharing (Persona Connect).How network-based identity acts as a trust signal, improving fraud outcomes without global blocklists.Where mobile driver's licenses and digital wallets fit into Persona's platform-agnostic acceptance strategy.Why AI agents are accelerating the need for identity portability and what Know Your Agent could look like in practice.This episode is essential listening for anyone building or buying identity verification technology. Ross offers a grounded, metrics-driven perspective on how reusable identity is finally moving from theory to production and why networks, not standalone checks, will define the next era of digital trust.Enjoy the episode, and don't forget to share it with others who are passionate about the future of identity!Learn more about Persona.Reach out to Riley (@rileyphughes) and Trinsic (@trinsic_id) on Twitter. We'd love to hear from you.Listen to the full episode on Apple Podcasts or Spotify, or find all ways to listen at trinsic.id/podcast.

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In this opening episode of Christian Formation and Homeschooling in a Distracted Age, Brendon Naicker explores why Christian parents across the UK are turning to networked homeschooling as a response to cultural pressures, media influence, and the urgent need for intentional discipleship.Brendon challenges the assumption that education is neutral, revealing how modern news cycles and digital media shape young minds long before Scripture does. He argues that homeschooling networks—not isolated efforts—offer parents the supportive community, shared expertise, and Christ-centred formation needed to raise children rooted in biblical truth.This episode introduces Solavia.UK, a developing Christian homeschooling network inviting families to join a movement grounded in collaboration, faith, and academic excellence. If you're seeking an alternative to influence-driven culture, and a community capable of nurturing children for Christ rather than the crowd, this episode is your call to explore what networked homeschooling can offer.#ChristianHomeschooling #SolaviaUK #UKHomeEducation #FaithBasedLearning #ChristianParents #HomeschoolNetwork #MediaWiseKids #ChristianFormation #RaisingDisciples #HomeEdUK #IntentionalParenting #CounterCulturalParenting #LivingTheology #KingdomEducation #DiscipleshipInEducation #brendonnaicker

In this opening episode of Christian Formation and Homeschooling in a Distracted Age, Brendon Naicker explores why Christian parents across the UK are turning to networked homeschooling as a response to cultural pressures, media influence, and the urgent need for intentional discipleship.Brendon challenges the assumption that education is neutral, revealing how modern news cycles and digital media shape young minds long before Scripture does. He argues that homeschooling networks—not isolated efforts—offer parents the supportive community, shared expertise, and Christ-centred formation needed to raise children rooted in biblical truth.This episode introduces Solavia.UK, a developing Christian homeschooling network inviting families to join a movement grounded in collaboration, faith, and academic excellence. If you're seeking an alternative to influence-driven culture, and a community capable of nurturing children for Christ rather than the crowd, this episode is your call to explore what networked homeschooling can offer.#ChristianHomeschooling #SolaviaUK #UKHomeEducation #FaithBasedLearning #ChristianParents #HomeschoolNetwork #MediaWiseKids #ChristianFormation #RaisingDisciples #HomeEdUK #IntentionalParenting #CounterCulturalParenting #LivingTheology #KingdomEducation #DiscipleshipInEducation #brendonnaicker

In this conversation, Mandy Schell, founder of the Pacific Northwest Women's Network, shares her journey of empowering women through community and connection. She discusses the transformative power of saying yes to new opportunities, the importance of creating a welcoming space for women to connect, and the impact of her events on attendees' lives. Mandy emphasizes the shift from traditional networking to building genuine relationships and proximity, and she reflects on the challenges and lessons learned in event planning. Her insights on leadership, financial transparency, and the future of her network inspire listeners to embrace their own journeys of growth and connection.To every woman who craves meaningful, in-person experiences — LIVE is Mandy's signature annual gathering centered on deep connection, powerful visibility, and building the rooms we all deserve! Tickets to PNW LIVE 2026!  January 23, 2026  Tacoma, WA:   https://www.pnwwomensnetwork.com/tickets?fbclid=PAZXh0bgNhZW0CMTEAAae2tb7WFYi1iIdmSvmVagAMVtQeJ5zhvXyLGM6d6mSDTkKOM64TuvhCGJLC2w_aem_K2ioBPgimHER9oM-G1iDvgChapters00:00 Empowering Women Through Community03:02 The Catalyst for Change06:00 Overcoming Fear and Embracing Opportunity09:05 The Impact of Connection11:55 Creating an Ecosystem of Support14:58 Building Relationships and Authenticity17:55 Lessons from the First Event20:51 The Journey of Event Planning23:54 The Purpose Beyond Profit26:33 Creating Meaningful Connections27:39 Dreams and Aspirations in Event Planning29:20 The Joy of Dressing Up and Community30:58 Challenges in Event Sponsorship33:20 Strategies for Securing Sponsors35:32 Handling Unexpected Challenges38:36 The Importance of a Supportive Team40:21 Evolving Membership Models42:57 Creating Fun and Engaging Events45:25 Empowering Women Through Strength and LeadershipConnect with Mandy: Tickets to LIVE 2026! https://www.pnwwomensnetwork.com/tickets?fbclid=PAZXh0bgNhZW0CMTEAAae2tb7WFYi1iIdmSvmVagAMVtQeJ5zhvXyLGM6d6mSDTkKOM64TuvhCGJLC2w_aem_K2ioBPgimHER9oM-G1iDvgPNW Women's Network: https://www.pnwwomensnetwork.com/Instagram: https://www.instagram.com/itsmandyschell/?hl=enConnect with The Women On Top: Follow The Women On Top Podcast on Apple, Spotify, or anywhere you get your podcasts. Subscribe for more empowering conversations and stories! Website: https://thewomenontop.com/YouTube: https://www.youtube.com/@thewomenontop Instagram: https://www.instagram.com/thewomenontoppodcast/LinkedIn: https://www.linkedin.com/in/valerie-lynn/

Field-mounted devices change the way controls engineers approach industrial networking. The shift toward on-machine connectivity can simplify design, streamline wiring and enable strategies like conveyor zone management. In this episode of Control Intelligence, written by contributing editor Rick Rice, editor in chief Mike Bacidore talks about how field networking unlocks automated setup and diagnostics.

Today's episode features guest host Michael Upshall (guest editor, Charleston Briefings) who talks with Herbert Van de Sompel, Researcher Fellow at Data Archiving and Networked Services (DANS) and Guest Professor at Ghent University. Although Herbert has spent the last 25 to 30 years working in libraries, he doesn't describe himself as a librarian but as what he calls an "infrastructure plumber."  With a background in mathematics and information science, he has done years of infrastructure work within the library to allow technology to be used to improve research communication. Starting with Ghent University Library, where he did his thesis, and which he says was behind in automation compared to other European libraries, he began with automation of administrative processes, but he says that he didn't then fully understand what automation in an academic library would be fully about. Herbert got to work with a vision- he didn't feel that library automation was catalog automation. It was about providing access to all kinds of other sources. In this conversation, we'll hear how Herbert worked to modernize library services at Ghent, propelling them from way behind to way ahead in automation and his contributions to developing SFX and the OpenURL framework. Social Media: LinkedIn: https://www.linkedin.com/in/mupshall/ https://www.linkedin.com/in/herbertvandesompel/ Keywords: #OpenAccess #ResearchInfrastructure #AcademicTools #LibraryAutomation #OpenSource #OpenScience #metadata #OpenResearch #DigitalLibrary #DigitalTransformation #LibraryTechnology #Innovation #career #scholcomm #ScholarlyCommunication #libraries #librarianship #LibraryNeeds #LibraryLove #ScholarlyPublishing #AcademicPublishing #publishing #LibrariesAndPublishers #podcasts

Is it possible that technology could serve as a modern conduit for curses, rituals, or consciousness that once required physical artifacts? What if the leap from ink to binary isn't just a matter of preservation, but a catalyst for waking something powerful - and completely unexpected - in the world of information and the mind?​​If you are having a mental health crisis and need immediate help, please go to​ ​​​https://troubledminds.org/help/ and call somebody right now. Reaching out for support is a sign of strength. ​ ​ ​ ​​​LIVE ON Digital Radio! Http://bit.ly/40KBtlW ​ ​ ​​http://www.troubledminds.net or ​ ​ ​ ​​https://www.troubledminds.org ​​​​Support The Show! ​ ​ ​ ​​https://www.spreaker.com/podcast/troubled-minds-radio--4953916/support ​ ​ ​ ​​https://ko-fi.com/troubledminds ​ ​ ​ ​​https://patreon.com/troubledminds ​ ​ ​ ​​https://www.buymeacoffee.com/troubledminds ​ ​ ​ ​​https://troubledfans.com ​ ​Friends of Troubled Minds! - ​ ​ ​ ​​https://troubledminds.org/friends ​ ​​​Show Schedule Sun--Tues--Thurs--Fri 7-10pst ​iTunes - ​ ​ ​​​​https://apple.co/2zZ4hx6 ​Spotify - ​ ​ ​​​​https://spoti.fi/2UgyzqM ​TuneIn - ​ ​ ​​​​https://bit.ly/2FZOErS ​Twitter - ​ ​ ​​​​https://bit.ly/2CYB71U ​​​​​----------------------------------------​​https://troubledminds.substack.com/p/the-networked-necronomicon-limits​​https://en.wikipedia.org/wiki/Ghost_story​​https://www.oldstyletales.com/single-post/m-r-james-disturbingly-invasive-introspective-ghost-stories-a-deep-literary-analysis-part-ii​​https://www.reddit.com/r/horrorlit/comments/18j9p3r/mr_james/​​https://www.catholicnewsagency.com/news/264483/restoration-digitization-of-vatican-library-archives-gets-underway​​https://www.hirschsecure.com/resources/blog/the-worlds-most-secure-buildings-the-vatican-secret-archives​​https://en.wikipedia.org/wiki/Vatican_Apostolic_Archive​​https://www.theatlantic.com/technology/archive/2018/04/vatican-secret-archives-artificial-intelligence/559205/​​https://www.reddit.com/r/UrbanMyths/comments/1f5o9lx/the_vatican_apostolic_archives_contains_85/​​https://www.thevaticantickets.com/vatican-archives/That's another dive into the mysteries they don't want you exploring here on Troubled Minds Radio. Keep Your Mind Troubled: If today's episode challenged your perception of reality, you're exactly where you need to be.Subscribe wherever you get your podcasts and hit that notification bell so you never miss our investigations into the unknown.Your five-star rating and review helps other truth-seekers find us in this sea of mainstream disinformation. Join the Community: Connect with nearly 1,000 fellow researchers in our Discord server, follow @TroubledMindsR on X for breaking updates, and support independent media by upgrading to Spreaker Prime for exclusive bonus content.Share Your Truth: Got a paranormal encounter, conspiracy evidence, or inside knowledge they're covering up? Email troubledmindsradio@gmail.com - your story could be featured on an upcoming episode. This is your host reminding you that in a world of manufactured narratives, questioning everything isn't paranoia...

Someone introduces you to the uber connected, highly-proficient networker! Great! Here the important question: How do you make the most of that opportunity? Here's how. For more great insight on professional relationships and business networking contact Frank Agin at frankagin@amspirit.com.

Take a deep dive into networked minds is reshaping the boundaries of artificial thinking. Experts weigh in on why this matters and where it might lead us.Try AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle

It's feeling like we're living in a very strange moment in time where liberal norms of openness have been shattered by the same class of tech industry titans who expressed these values just a decade ago. In this episode I spoke to Nick Houde and Severin Matusek from co-matter, a research and strategy studio based in Berlin, who recently published an incredible memo that is chock full of incredible analysis and insight into our current moment."New World Order: The Return of Hard Power and Soft Beliefs is a 35-page research memo about what happens when power, infrastructure and ideology collide.A manual for anyone trying to make sense of the present, New World Order contains ideas, context and language to participate in shaping the world that emerges in front of our eyes."The memo is chock full of useful and powerful concepts that help explain this moment. You can order a copy of the memo on Metalabel here. (I've already got my copy!) Lots of great quotes like "Yesterday's moral stance is tomorrow's liability" and "Whoever controls the infrastructure controls reality itself."This episode is sponsored by NYM, the world's most private VPN. Unlike traditional VPNs, Nym uses a decentralized mixnet to scramble your internet data — hiding who you're talking to, when, and how often. You can switch between full mixnet mode for maximum anonymity, or a faster VPN mode for everyday use.Use the code blockchainsocialist when signing up and get an extra month!If you liked the podcast be sure to give it a review on your preferred podcast platform. If you find content like this important consider donating to my Patreon starting at just $3 per month. It takes quite a lot of my time and resources so any amount helps. Follow me on Twitter (@TBSocialist) or Mastodon (@theblockchainsocialist@social.coop) and join the r/CryptoLeftists subreddit.Send me your questions or comments about the show and I'll read them out sometime. Support the showICYMI I've written a book about, no surprise, blockchains through a left political framework! The title is Blockchain Radicals: How Capitalism Ruined Crypto and How to Fix It and is being published through Repeater Books, the publishing house started by Mark Fisher who's work influenced me a lot in my thinking. The book is officially published and you use this linktree to find where you can purchase the book based on your region / country.

Mark Hayward, co-founder of a podcast booking services, share about the value of being a podcast guest and all you can do with the experience. Learn more and contact him at https://podcastintroduction.com/ For more great insight on professional relationships and business networking contact Frank Agin at frankagin@amspirit.com.

We critically examine the future of networked minds could redefine how machines perceive and solve problems. From theory to practice, this could shape the future of thinking machines.Try AI Box: ⁠⁠https://aibox.ai/AI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle/about

Adeline Atlas 11 X Published AUTHOR Digital Twin: Create Your AI Clone: ⁠https://www.soulreno.com/digital-twin⁠AI + Future Technology Series: ⁠https://www.soulreno.com/ai-future-tech-series⁠Soul Series: ⁠https://www.soulreno.com/soul-series⁠Magic + Occult Series: https://www.soulreno.com/magic-occult-series-1a5a4abd-07ae-4bd5-97da-da4580f3c75aManifestation Series: ⁠https://www.soulreno.com/manifestation-series⁠Truth Series: ⁠https://www.soulreno.com/truth-series⁠The Chosen Ones: ⁠https://www.soulreno.com/the-chosen-ones-series⁠Freebies: ⁠https://www.soulreno.com/freebies⁠Instagram:⁠https://www.instagram.com/soulrenovation/⁠Sos Vault:⁠https://www.soulreno.com/joinus-202f0461-ba1e-4ff8-8111-9dee8c726340⁠FREE - SOCIAL VAULT

Send us a textNonprofit leaders feeling the weight of challenging times need more than grit to thrive—they need resilient organizations built on sustainable systems and supportive networks. Brooke Ritchie-Babbage shares her S.T.R.O.N.G. framework for building nonprofit stability while growing impact.• Strategic clarity keeps everyone focused on the "cathedral" they're building beyond daily brick-laying work• Well-designed tools and systems create the interstitial tissue connecting teams without bottlenecks• Resources include not just funding but sustainable approaches like monthly giving programs • Ownership means everyone understands their role and has appropriate decision-making authority• Networked capacity extends organizational roots beyond staff to partners, advisors, and collaborators• Governance provides appropriate oversight and accountability that evolves as organizations grow• Growth and stability aren't competing priorities—stability is the foundation for sustained growth• Burnout isn't a badge of honor or personal failing but a structural mismatch requiring systemic solutions• Building recovery and assessment into organizational rhythms is essential for long-term impact• No leader should try to go it alone—find coaches, mentors, and peer communities for supportCheck out Brooke's podcast at https://brookerichiebabbage.com/podcast/Brooke's BioBrooke Richie-Babbage is a nonprofit growth strategist and social impact advisor. She is the founder and CEO of Bending Arc, a social impact strategy firm that supports the launch and sustainable growth of high-impact nonprofits, and the host of Nonprofit Mastermind Podcast.For the past 23 years, Brooke has worked as a lawyer, nonprofit leader, and social entrepreneur. She has founded and led multiple successful organizations and initiatives, including the Resilience Advocacy Project (RAP), where she served as founder and Executive Director for 11 years, the Sterling Network NYC and the NetLab Initiative, both initiatives of the Robert Sterling Clark Foundation, where she served as Director of Network Initiatives for six years, and the Social Justice Accelerator (SJA), an initiative of the Urban Justice Center, where she has served as SJA Director since 2019.  Brooke received her JD and MPP from Harvard and her BA from Yale. She lives in Brooklyn with her husband and two sons.Brooke Richie-Babbage | LinkedIn Like what you heard? Please like and share wherever you get your podcasts! Connect with Ann: Community Evaluation Solutions How Ann can help: · Support the evaluation capacity of your coalition or community-based organization. · Help you create a strategic plan that doesn't stress you and your group out, doesn't take all year to design, and is actionable. · Engage your group in equitable discussions about difficult conversations. · Facilitate a workshop to plan for action and get your group moving. · Create a workshop that energizes and excites your group for action. · Speak at your conference or event. Have a question or want to know more? Book a call with Ann .Be sure and check out our updated resource page! Let us know what was helpful. Music by Zach Price: Zachpricet@gmail.com

In this throwback episode, I shared the exciting news about my new role and offered valuable insights for jobseekers based on my job hunt journey. The current job market is challenging, but with the right approach and strategies, you can navigate it successfully. I'll walk you through the importance of self-reflection, effective networking, and strategic job applications.In this week's episode, I discussed:The Job Hunt JourneySelf-Reflection ExerciseRelationships, Networking, and Leveraging ReferralsCreating Content on LinkedIn:Referral ImportanceTracking Your EffortsMuch MoreHere are Actionable Takeaways:Conduct a thorough self-reflection to define your career goals.Leverage your network effectively by posting, engaging, and following up with contacts.Create and share relevant content on LinkedIn to build your professional brand.Use a tracking system to organize your job search efforts.Seek referrals and introductions to increase your chances of landing interviews.Build and maintain relationships with key contacts in your network.Please enjoy this week's episode! ____________________________________________________________________________I am now in the early stages of writing my first book! In this book, I will be telling my story of getting into sales and the lessons I have learned so far, and intertwine stories, tips, and advice from the Top Sales Professionals In The World! As a first time author, I want to share these interviews with you all, and take you on this book writing journey with me! Like the show? Subscribe to the email: https://mailchi.mp/a71e58dacffb/welcome-to-the-20-podcast-communityI want your feedback!Reach out to 20percentpodcastquestions@gmdail.com, or find me on LinkedIn.If you know anyone who would benefit from this show, share it along! If you know of anyone who would be great to interview, please drop me a line!Enjoy the show!

Subscribe for $5.99 a month to get bonus content most Mondays, bonus episodes every month, ad-free listening, access to the entire 800-episode archive, Discord access, and more: https://axismundi.supercast.com/ Brad discusses the current trends in Christian nationalism with Kiera Butler of Mother Jones. They talk about Andrew Isker and C.Jay Engel's plans to build a Christian nationalist society in Tennessee, funded by venture capitalists. Isker's antisemitic and anti-Civil Rights Act views are highlighted as they explore the similarities between these Christian enclaves and tech-driven network cities. The discussion includes the impact of recent tragic events at Florida State University and the socio-political implications of such movements. Linktree: https://linktr.ee/StraightWhiteJC Order Brad's book: https://bookshop.org/a/95982/9781506482163 Check out BetterHelp and use my code SWA for a great deal: www.betterhelp.com Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of the World of Higher Education Podcast, host Alex Usher talks with Nicolas Badré, Chief Operating Officer of Galileo Global Education, about the rise of private higher education in Europe. They explore the unique business model of Galileo Global Education, its rapid expansion, and its innovative approaches, including leveraging AI for content creation, student experience, and operational efficiency. They also discuss Galileo's new initiative, Copernia, and its master's program focused on innovation and technology in education. Learn how private institutions are adapting to new educational demands.

Guest: Ed Fidoe: Founder of LIS Ed Fidoe is the visionary founder and CEO of the London Interdisciplinary School (LIS), pioneering a revolution in education. LIS is the first institution in decades to be granted degree-awarding powers from inception in the UK. It offers an innovative, interdisciplinary curriculum designed to address complex global challenges such as inequality, sustainability, ethics, and artificial intelligence. Ed will explore the concept of “networked expertise” versus “narrow expertise” and its application to individuals beyond their defined roles. He'll discuss how understanding a person's broader interests and skills can uncover valuable knowledge and foster greater engagement in the workplace. Additionally, Ed will delve into the idea of organizing learning and work environments around complex problems—such as addressing climate change—instead of traditional departments or disciplines. He argues that framing tasks and discussions in this way can enhance motivation, drive innovation, and improve problem-solving capabilities. Join us as we discuss fostering greater engagement in the workspace. Host: Jo Dodds

Jim talks with John Robb about the ideas in his recent essay "Blitzing DC," about how a networked organization took over Washington. They discuss the early roots of network warfare in Iraq, McLuhan-esque societal rewiring, open source dynamics & plausible promise, the Arab Spring & Occupy movements, empathy triggers, Trump's 2016 campaign as a hybrid swarm, The_Donald as a meme amplifier, the Blue Network's counter-response, the George Floyd protests & moral framework, censorship & 'the long night', digital rights & moderation, the Ukraine conflict & swarm response, the Red Network reconfiguration, digital ledgers & truth-seeking accounts, the professionalization of Red digital warriors, network decision-making at a societal level, the government contracting corruption, defense procurement issues, the D.C. area wealth concentration, the future of network organizations, and much more. Episode Transcript Global Guerrillas (Substack) JRS EP 254 - John Robb on What Went Wrong with America "Blitzing DC," by John Robb "The Open-Source War," by John Robb (New York Times) "Musk and Moderation," by Jim Rutt (Quillette) John Robb is an author, inventor, entrepreneur, technology analyst, astro engineer, and military pilot. He's started numerous successful technology companies, including one in the financial sector that sold for $295 million and one that pioneered the software we currently see in use at Facebook and Twitter. John's insight on technology and governance has appeared on the BBC, Fox News, National Public Radio, CNBC, The Economist, the New York Times, The Wall Street Journal, and BusinessWeek. John served as a pilot in a tier-one counter-terrorism unit that worked alongside Delta and Seal Team 6. He wrote the book Brave New War on the future of national security, and has advised the Joint Chiefs of Staff, NSA, DoD, CIA, and the House Armed Services Committee.

Facing increasingly sophisticated attacks from external adversaries, networked systems owners have to judiciously allocate their limited security budget to reduce their cyber risks. However, when modeling human decision-making, behavioral economics has shown that humans consistently deviate from classical models of decision-making. Most notably, prospect theory, for which Kahneman and Tversky won the 2002 Nobel memorial prize in economics, argues that humans perceive gains, losses and probabilities in a skewed manner. Furthermore, bounded rationality and imperfect best-response behavior has been frequently observed in human decision-making within the domains of behavioral economics and psychology. While there is a rich literature on these human decision-making factors in economics and psychology, most of the existing work studying ​ security of networked systems does not take into account these biases and noises. In this talk, we show our proposed novel behavioral security game models for the study of human decision-making in networked systems modeled by attack graphs. We show that behavioral biases lead to suboptimal resource allocation patterns. We also analyze the outcomes of protecting multiple isolated assets with heterogeneous valuations via decision- and game-theoretic frameworks. We show that behavioral defenders over-invest in higher-valued assets compared to rational defenders. We then propose different learning-based techniques and adapt two different tax-based mechanisms for guiding behavioral decision-makers towards optimal security investment decisions. In particular, we show the outcomes of such learning and mechanisms on different realistic networked systems. In total, our research establishes rigorous frameworks to analyze the security of both large-scale networked systems and heterogeneous isolated assets managed by human decision makers and provides new and important insights into security vulnerabilities that arise in such settings. About the speaker: Dr. Mustafa Abdallah is a tenure-track Assistant Professor in the Computer and Information Technology (CIT) Department at Purdue University in Indianapolis, with a courtesy appointment at Purdue Polytechnic Institute. He earned his Ph.D. from the Elmore Family School of Electrical and Computer Engineering at Purdue University in 2022 and previously served as a tenure-track faculty member at IUPUI. His research focuses on game theory, behavioral decision-making, explainable AI, meta-learning, and deep learning, with applications in proactive security of networked systems, IoT anomaly detection, and intrusion detection. His work has been published in top security and AI venues, includingIEEE S&P, ACM AsiaCCS, IEEE TCNS, IEEE IoT-J, Computers & Security, and ACM TKDD. He has received the Bilsland Fellowship, multiple IEEE travel grants, and internal research funding from IUPUI. Dr. Abdallah has extensive industrial research experience, including internships at Adobe Research (meta-learning for time-series forecasting), Principal Financial Group (Kalman filter modeling for financial predictions), and RDI (deep learning for speech technology applications), which led to a U.S. patent and multiple publications. He holds B.Sc. and M.Sc. degrees from Cairo University, with a focus on electrical engineering and engineering mathematics, respectively.

In this episode of Climate Positive, hosts Gil Jenkins and Guy Van Syckle chat with Zeyneb Magavi, Executive Director of HEET, a Massachusetts-based non-profit focused on designing a strategic evolution of aging gas systems into bidirectional ambient thermal grids, with the aim of driving rapid and equitable decarbonization of heating and cooling in urban areas. The enlivening conversation centers around the networked geothermal, a novel technology gaining traction nationwide that utilizes underground thermal energy systems to provide efficient and sustainable heating and cooling. Magavi breaks down how this innovative neighborhood-scale decarbonization solution works, highlights the business case, policy drivers, the benefits for communities, utilities, workers, and more.Links:HEET WebsiteZeyneb Magavi on LinkedInZeyneb MagaviBioHEET on  XHEET on  LinkedInArticle: Underground Thermal Energy Networks May Be About to Have Their Moment (Wall Street Journal, April 21, 2024)Article: How an Unlikely Coalition of Climate Activists and a Gas Utility Are Weaning a Boston Suburb Off Fossil Fuels (Inside Climate News, December 21, 2024)HEET Blog:  13 Massachusetts Communities Kickstart New Geothermal Networks with $450,000 in Funding from MassCEC (February 29, 2024)HEET Blog: Networked Geothermal: The National Picture (April 17, 2023)Episode recorded December 17, 2024 Email your feedback to Chad, Gil, Hilary, and Guy at climatepositive@hasi.com or tweet them to @ClimatePosiPod.

Outline00:00 Intro01:19 Swedish control heritage and early steps05:21 PhD at Lund and relay feedback systems15:40 Berkeley years19:58 Hybrid systems26:46 Networked control systems30:32 Interaction with industry34:40 Wireless control systems40:33 Platooning in freight transport49:27 Future of mobility52:55 Event-based control58:58 Cybersecurity1:05:10 Societal-scale challenges1:12:33 Bode lecture reflections1:15:05 Digital futures1:23:38 Advice for future studentsLinksKalle's website: https://tinyurl.com/yc34dv2xK. J. Åstrom: https://tinyurl.com/5n9admvkPhD Thesis: https://tinyurl.com/3868a92aRelay feedback: https://tinyurl.com/3w4w9dkuFast switches in relay feedback systems: https://tinyurl.com/5dcvn79fS. Sastry: https://tinyurl.com/3f5e978zHybrid system: https://tinyurl.com/v39up6wkDynamical properties of hybrid automata: https://tinyurl.com/yx73x6baWireless Network Design for Control Systems: https://tinyurl.com/mry5cnanCyber–Physical Control of Road Freight Transport: https://tinyurl.com/yc4yhhwuS. Shladover: https://tinyurl.com/352cfwdmAn introduction to event-triggered and self-triggered control: https://tinyurl.com/37p9w8czDistributed Event-Triggered Control for Multi-Agent Systems: https://tinyurl.com/5ddnjsrzCyber security analysis of state estimators in electric power systems: https://tinyurl.com/2wj74spjA secure control framework for resource-limited adversaries: https://tinyurl.com/37pnehuvControl for societal-scale challenges 2030: https://tinyurl.com/yfd3v296Digital futures: https://tinyurl.com/h3nyb2Support the showPodcast infoPodcast website: https://www.incontrolpodcast.com/Apple Podcasts: https://tinyurl.com/5n84j85jSpotify: https://tinyurl.com/4rwztj3cRSS: https://tinyurl.com/yc2fcv4yYoutube: https://tinyurl.com/bdbvhsj6Facebook: https://tinyurl.com/3z24yr43Twitter: https://twitter.com/IncontrolPInstagram: https://tinyurl.com/35cu4kr4Acknowledgments and sponsorsThis episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

For this episode, I had the honor of sitting down with Nakeia Drummond, social entrepreneur and founder of both She's WELL Networked and NLD Strategic. Nakeia shares her inspiring journey of building an ecosystem that uplifts and empowers Black women business owners. From starting her own consulting firm, NLD Strategic, to founding She's Well Networked and The Women Entrepreneur Leadership Lab (The WELL), Nakeia has dedicated herself to closing the equity gap for Black women entrepreneurs. We dive into the importance of designing inclusive spaces, fostering community, and leveraging networks to create financial liberation for Black women.Connect with Nakeia:NLD Strategic Website She's Well Networked WebsiteThe Well Website Nakeia on Linkedin Nakeia on InstagramThe Well on LinkedinMAKING GOOD SHOWNOTES:https://makinggoodpodcast.com/273CONNECT WITH ME ON INSTAGRAM:https://instagram.com/laurentildenGET 100 MARKETING PROMPTS (free!):https://makinggoodpodcast.com/100prompts

In this throwback episode, I shared the exciting news about my new role and offered valuable insights for jobseekers based on my job hunt journey. The current job market is challenging, but with the right approach and strategies, you can navigate it successfully. I'll walk you through the importance of self-reflection, effective networking, and strategic job applications. In this week's episode, I discussed: The Job Hunt Journey Self-Reflection Exercise Relationships, Networking, and Leveraging Referrals Creating Content on LinkedIn: Referral Importance Tracking Your Efforts Much More Here are Actionable Takeaways: Conduct a thorough self-reflection to define your career goals. Leverage your network effectively by posting, engaging, and following up with contacts. Create and share relevant content on LinkedIn to build your professional brand. Use a tracking system to organize your job search efforts. Seek referrals and introductions to increase your chances of landing interviews. Build and maintain relationships with key contacts in your network. Please enjoy this week's episode!  ____________________________________________________________________________ I am now in the early stages of writing my first book! In this book, I will be telling my story of getting into sales and the lessons I have learned so far, and intertwine stories, tips, and advice from the Top Sales Professionals In The World! As a first time author, I want to share these interviews with you all, and take you on this book writing journey with me!  Like the show? Subscribe to the email: https://mailchi.mp/a71e58dacffb/welcome-to-the-20-podcast-community I want your feedback! Reach out to 20percentpodcastquestions@gmdail.com, or find me on LinkedIn. If you know anyone who would benefit from this show, share it along! If you know of anyone who would be great to interview, please drop me a line! Enjoy the show! ____________________________________________________________________________ I am now in the early stages of writing my first book! In this book, I will be telling my story of getting into sales and the lessons I have learned so far, and intertwine stories, tips, and advice from the Top Sales Professionals In The World! As a first time author, I want to share these interviews with you all, and take you on this book writing journey with me!  Like the show? Subscribe to the email: https://mailchi.mp/a71e58dacffb/welcome-to-the-20-podcast-community I want your feedback! Reach out to 20percentpodcastquestions@gmail.com, or find me on LinkedIn.

This week's Misfit Entrepreneur is Deb Feder. Deb is the CEO of Feder Development, a business development and practice management strategist and coach with a special focus on effective communication. Her work focuses on helping professionals bring in consistent clients through curious, confident conversations. Over the last decade, Deb has committed herself to changing the way people think about communication, building healthy careers, and tackling high-stakes work, allowing for big careers while enjoying our free time. She is the author of After Hello: How to Build a Book of Business, One Conversation at a Time and Tell Me More: Building Trusted Client Relationships through Everyday Interactions. She is also a contributing author to the best-selling anthology #Networked. Effective communication is probably one of, if not, the most important skill for entrepreneurs, so I asked Deb on to give us her best thoughts, practices, and strategies to communicate at our best in our businesses and with our customers. To see the full show notes and Misfit 3 for this episode, go to www.MisfitEntrepreneur.com. Show Sponsors: Entrepreneurs, what if there was a way to know you were hiring the best salespeople to drive your business? How much would that help your success? Well, with SalesDrive's DriveTest, you can! Drive is composed of three non-teachable traits shared by all top producers: Need for Achievement, Competitiveness, and Optimism. You can get a FREE DriveTest assessment to help you in your hiring efforts at www.MisfitEntrepreneur.com/SalesDrive 5 Minute Journal: www.MisfitEntrepreneur.com/Journal

In their latest book, Fandom is Ugly: Networked Harassment in Participatory Culture (NYU Press, 2024), Mel Stafill highlights the importance of considering contemporary public culture through the lens of fan studies The Gamergate harassment campaign of women in video games, the “Unite the Right” rally where hundreds of Confederate monument supporters cried out racist and antisemitic slurs in Charlottesville, and the targeted racist and sexist harassment of Star Wars' Asian American actress Kelly Marie Tran all have one thing in common: they demonstrate the collective power and underlying ugliness of fandoms. These fans might feel victimized or betrayed by the content they've intertwined with their own identities, or they may simply feel that they're speaking truth to power. Regardless, by connecting via social media, they can unleash enormous amounts of hate, which often results in severe real-world consequences.  Fandom Is Ugly argues that reactionary politics and media fandoms go hand in hand, and to understand one, we need to understand the other. Stanfill pushes back on two mainstream assumptions: that media and the pleasure of consumption are frivolous and unworthy of study, and that fandoms are inherently progressive. Drawing on a corpus of angry social media posts, Fandom Is Ugly finds that ugly moments happen when deep emotional attachments collide with social structures and situations that have been misunderstood. By holistically examining the forms of ugly fandom in cases that touch upon race, gender, and sexuality, Fandom Is Ugly produces a comprehensive theory of the negative sides of fan attachments. 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

In their latest book, Fandom is Ugly: Networked Harassment in Participatory Culture (NYU Press, 2024), Mel Stafill highlights the importance of considering contemporary public culture through the lens of fan studies The Gamergate harassment campaign of women in video games, the “Unite the Right” rally where hundreds of Confederate monument supporters cried out racist and antisemitic slurs in Charlottesville, and the targeted racist and sexist harassment of Star Wars' Asian American actress Kelly Marie Tran all have one thing in common: they demonstrate the collective power and underlying ugliness of fandoms. These fans might feel victimized or betrayed by the content they've intertwined with their own identities, or they may simply feel that they're speaking truth to power. Regardless, by connecting via social media, they can unleash enormous amounts of hate, which often results in severe real-world consequences.  Fandom Is Ugly argues that reactionary politics and media fandoms go hand in hand, and to understand one, we need to understand the other. Stanfill pushes back on two mainstream assumptions: that media and the pleasure of consumption are frivolous and unworthy of study, and that fandoms are inherently progressive. Drawing on a corpus of angry social media posts, Fandom Is Ugly finds that ugly moments happen when deep emotional attachments collide with social structures and situations that have been misunderstood. By holistically examining the forms of ugly fandom in cases that touch upon race, gender, and sexuality, Fandom Is Ugly produces a comprehensive theory of the negative sides of fan attachments. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/sociology

In this episode, I share exciting news about my new role and offer valuable insights for jobseekers based on my recent job hunt journey. The current job market is challenging, but with the right approach and strategies, you can navigate it successfully. I'll walk you through the importance of self-reflection, effective networking, and strategic job applications. In this week's episode, I discussed: The Job Hunt Journey Self-Reflection Exercise Relationships, Networking, and Leveraging Referrals Creating Content on LinkedIn: Referral Importance Tracking Your Efforts Much More Here are Actionable Takeaways: Conduct a thorough self-reflection to define your career goals. Leverage your network effectively by posting, engaging, and following up with contacts. Create and share relevant content on LinkedIn to build your professional brand. Use a tracking system to organize your job search efforts. Seek referrals and introductions to increase your chances of landing interviews. Build and maintain relationships with key contacts in your network. Please enjoy this week's episode!  ____________________________________________________________________________ I am now in the early stages of writing my first book! In this book, I will be telling my story of getting into sales and the lessons I have learned so far, and intertwine stories, tips, and advice from the Top Sales Professionals In The World! As a first time author, I want to share these interviews with you all, and take you on this book writing journey with me!  Like the show? Subscribe to the email: https://mailchi.mp/a71e58dacffb/welcome-to-the-20-podcast-community I want your feedback! Reach out to 20percentpodcastquestions@gmdail.com, or find me on LinkedIn. If you know anyone who would benefit from this show, share it along! If you know of anyone who would be great to interview, please drop me a line! Enjoy the show!

Outline01:16 - Intro02:28 - Early steps in Italy and California13:00 - From Riemannian geometry …17:01 - … to geometric control, robotics and locomotion34:54 - Academic environment at Caltech35:06 - From single robots to robotic networks53:51 - Art gallery problem1:01:37 - Networked and cyber-physical systems1:21:47 - Contracting dynamics1:33:07 - Coupled oscillators and power grids1:47:20 - On mathematical sociology1:56:44 - Writing and publishing2:02:14 - About professional service2:08:04 - Advice for future students2:08:04 - OutroLinksFrancesco's website: https://fbullo.github.io/CSM “People in Control” interview: https://tinyurl.com/cw4s8b4nGeometric Control of Mechanical Systems: https://tinyurl.com/mt59bw2nPD control on the Euclidean group: https://tinyurl.com/5xe9rtc2Coverage control for mobile sensing networks: https://tinyurl.com/ye83duhmVoronoi tassellations: https://tinyurl.com/y7w2tux4 Art gallery problem: https://tinyurl.com/yc8h88c3Dynamic vehicle routing for robotic systems: https://tinyurl.com/5n8c393pDistributed control of robotic networks: https://tinyurl.com/5xe6ztw3Attack detection and identification in cyber-physical systems: https://tinyurl.com/mvm44d24Voltage collapse in complex power grids: https://tinyurl.com/55mfdj28Lectures on network systems: https://tinyurl.com/tbd9dhy2Opinion dynamics and the evolution of social power in influence networks: https://tinyurl.com/2cd5v7taBanach contraction theorem: https://tinyurl.com/2yv4jjy6Contraction theory for dynamical systems: https://tinyurl.com/2r2pxh9pContracting dynamics YouTube series: https://tinyurl.com/3p7nsrypGetting it write: https://tinyurl.com/yhtabw2fHamming - You and your research: Support the Show.Podcast infoPodcast website: https://www.incontrolpodcast.com/Apple Podcasts: https://tinyurl.com/5n84j85jSpotify: https://tinyurl.com/4rwztj3cRSS: https://tinyurl.com/yc2fcv4yYoutube: https://tinyurl.com/bdbvhsj6Facebook: https://tinyurl.com/3z24yr43Twitter: https://twitter.com/IncontrolPInstagram: https://tinyurl.com/35cu4kr4Acknowledgments and sponsorsThis episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

Swapnil Rai's book Networked Bollywood: How Star Power Globalized Hindi Cinema (Cambridge UP, 2024) brilliantly navigates the intricate landscapes of stardom, shedding light on its diverse meanings amidst the ever-evolving new media industries and the demands of a globally interconnected audiences. With a keen focus on the global south, she masterfully explores the intersection of transnational networked cultures with the dynamic tapestry of media industries, geopolitics, and audience engagement. Dr. Swapnil Rai is an Assistant Professor in the Department of Film, Television, and Media at the University of Michigan, Ann Arbor. As an interdisciplinary scholar, she works at the intersection of media studies, critical cultural communication, women's and gender studies, and industry studies. She has published her scholarship in a range of journals such as Communication, Culture & Critique, Feminist Media Studies, International Journal of Communication, Media, Culture and Society among others. Priyam Sinha recently graduated with a PhD from the South Asian Studies Programme at the National University of Singapore. Her interdisciplinary academic interests lie at the intersection of film studies, disability studies, production cultures, affect studies, anthropology of the body, creative media industries and cultural studies. She can be reached here. 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

Swapnil Rai's book Networked Bollywood: How Star Power Globalized Hindi Cinema (Cambridge UP, 2024) brilliantly navigates the intricate landscapes of stardom, shedding light on its diverse meanings amidst the ever-evolving new media industries and the demands of a globally interconnected audiences. With a keen focus on the global south, she masterfully explores the intersection of transnational networked cultures with the dynamic tapestry of media industries, geopolitics, and audience engagement. Dr. Swapnil Rai is an Assistant Professor in the Department of Film, Television, and Media at the University of Michigan, Ann Arbor. As an interdisciplinary scholar, she works at the intersection of media studies, critical cultural communication, women's and gender studies, and industry studies. She has published her scholarship in a range of journals such as Communication, Culture & Critique, Feminist Media Studies, International Journal of Communication, Media, Culture and Society among others. Priyam Sinha recently graduated with a PhD from the South Asian Studies Programme at the National University of Singapore. Her interdisciplinary academic interests lie at the intersection of film studies, disability studies, production cultures, affect studies, anthropology of the body, creative media industries and cultural studies. She can be reached here. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/film

Swapnil Rai's book Networked Bollywood: How Star Power Globalized Hindi Cinema (Cambridge UP, 2024) brilliantly navigates the intricate landscapes of stardom, shedding light on its diverse meanings amidst the ever-evolving new media industries and the demands of a globally interconnected audiences. With a keen focus on the global south, she masterfully explores the intersection of transnational networked cultures with the dynamic tapestry of media industries, geopolitics, and audience engagement. Dr. Swapnil Rai is an Assistant Professor in the Department of Film, Television, and Media at the University of Michigan, Ann Arbor. As an interdisciplinary scholar, she works at the intersection of media studies, critical cultural communication, women's and gender studies, and industry studies. She has published her scholarship in a range of journals such as Communication, Culture & Critique, Feminist Media Studies, International Journal of Communication, Media, Culture and Society among others. Priyam Sinha recently graduated with a PhD from the South Asian Studies Programme at the National University of Singapore. Her interdisciplinary academic interests lie at the intersection of film studies, disability studies, production cultures, affect studies, anthropology of the body, creative media industries and cultural studies. She can be reached here. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/performing-arts

It's a modern day reality that large social media platforms deliver political information to many citizens, making these companies' policies for removing and blocking speech critical to politics and culture. Emergencies such as the January 6th attack on the U.S. Capitol and the genocide of the Rohingya people in Myanmar can be traced in part to misinformation and hate speech shared online via large social media platforms. The problem of how social media companies should create policies to govern these spaces makes them uniquely quasi-governmental, a role, still developing today.

Is there such a thing as being in touch with too many people? Whose fault is that?

Welcome to a new episode of Get Creative. In this episode we dive into the inspiring journey of Brenda Villafranco, a real estate enthusiast from Houston, Texas. From overcoming tornadoes to closing her first deal, Brenda's story is a testament to the power of action, community, and resilience in the world of creative finance. Tune in Listen in for invaluable insights, heartwarming stories, and practical advice to inspire your next bold move in real estate investing.   Highlights: "Don't sit on the sidelines. We don't wait for things to happen. We create them." "Networking is key. Deals will always be there, but the right relationships can make all the difference." "Take action, find the right people, and don't be afraid to step out of your comfort zone."   Timestamps: 00:00 - Introduction by Justin Termina. 00:11 - Importance of community in creative finance. 00:54 - ntroduction to Brenda Villafranco. 01:14 - Brenda's Start in real estate and taking action. 02:54 - Networking and attending events despite challenges. 04:36 - First Deal: finding and executing her first deal. 11:39 - Brenda shares her first deal experience. 18:16 - Plans for 2024 and 2025. 21:52 - The importance of working together. 28:37 - Key takeaways for aspiring investors.   ► Join The Subto Community & Learn Creative Finance Directly from Pace:  https://paceapproves.com/subto-gc ► Want to Become a Private Money Lender? Join Us For The Upcoming LIVE Training this Saturday to Learn How to Lend Money on Real Estate Deals: http://joingatortribe.com/yt   ► Join Our Free Facebook Group to Connect with Pace and his Students: https://paceapproves.com/freefb-yt   ► Become a Top Tier Transaction Coordinator and Make Money Doing The Paperwork For Real Estate Transactions: https://paceapproves.com/tttc-gc   ► Listen To Pace and His Students Share Insider Secrets To Real Estate Investor Success: https://getcreativepodcast.com/   PLUG IN & SUBSCRIBE Instagram: https://www.instagram.com/pacemorby/ TikTok: https://www.tiktok.com/@pacemorby

(Aloka Earth Room) Short Reflection & Guided Meditation | Earthworm Practice for the Anthropocene II | Online Wednesday-Mornings

Black Networked Resistance: Strategic Rearticulations in the Digital Age (U California Press, 2024)​ explores the creative range of Black digital users and their responses to varying forms of oppression, utilizing cultural, communicative, political, and technological threads both on and offline.  Raven Maragh-Lloyd demonstrates how Black users strategically rearticulate their responses to oppression in ways that highlight Black publics' historically rich traditions and reveal the shifting nature of both dominance and resistance, particularly in the digital age. Through case studies and interviews, Maragh-Lloyd reveals the malleable ways resistance can take shape and the ways Black users artfully demonstrate such modifications of resistance through strategies of survival, reprieve, and community online. Each chapter grounds itself in a resistance strategy, such as Black humor, care, or archiving, to show the ways that Black publics reshape strategies of resistance over time and across media platforms.  Linking singular digital resistance movements while arguing for Black publics as strategic content creators who connect resistance strategies from our past to suit our present needs, Black Networked Resistance encourages readers to create and cultivate lasting communities necessary for social and political change by imagining a future of joy, community, and agency through their digital media practices. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/african-american-studies

Black Networked Resistance: Strategic Rearticulations in the Digital Age (U California Press, 2024)​ explores the creative range of Black digital users and their responses to varying forms of oppression, utilizing cultural, communicative, political, and technological threads both on and offline.  Raven Maragh-Lloyd demonstrates how Black users strategically rearticulate their responses to oppression in ways that highlight Black publics' historically rich traditions and reveal the shifting nature of both dominance and resistance, particularly in the digital age. Through case studies and interviews, Maragh-Lloyd reveals the malleable ways resistance can take shape and the ways Black users artfully demonstrate such modifications of resistance through strategies of survival, reprieve, and community online. Each chapter grounds itself in a resistance strategy, such as Black humor, care, or archiving, to show the ways that Black publics reshape strategies of resistance over time and across media platforms.  Linking singular digital resistance movements while arguing for Black publics as strategic content creators who connect resistance strategies from our past to suit our present needs, Black Networked Resistance encourages readers to create and cultivate lasting communities necessary for social and political change by imagining a future of joy, community, and agency through their digital media practices. 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

He's the guy pointing to a NASA launch behind him, in the most legendary shot in television history. He's a science historian and Apollo Program correspondent. He's the creator, host, and writer of the long-running program “Connections.” He is a science communication hero to millions and a global treasure. He is James Burke, and he chats about how connected historical events are, and how connection between humans is vital. We also talk about Napoleon's toothpick, dog pee, shipworms, writer's block, TV shoots, and his new Connections season on Curiosity Stream. Also: (surprise!) they gave me a spinoff called “Quick Connections.” Watch Connections with James Burke on Curiosity Stream and Alie's spinoff, Quick Connections with Alie WardBrowse books by James Burke including Connections and American Connections: The Founding Fathers. Networked.A donation went to National Energy ActionMore episode sources and linksSmologies (short, classroom-safe) episodesOther episodes you may enjoy: Pedagogy (SCIENCE COMMUNICATION) with Bill Nye, TikTokology (SCICOMM) with Hank Green, Molecular Biology (PROTEINS & SCICOMM) with Dr. Raven Baxter, Futurology (THE FUTURE), Eudemonology (HAPPINESS), Cosmology (THE UNIVERSE) Encore, Astrobiology (ALIENS), Maritime Archeology (SHIPWRECKS), Classical Archaeology (ANCIENT ROME), Egyptology (ANCIENT EGYPT), Delphinology (DOLPHINS), Mythology (STORYTELLING), Geology (ROCKS), Curiology (EMOJI)Sponsors of OlogiesTranscripts and bleeped episodesBecome a patron of Ologies for as little as a buck a monthOlogiesMerch.com has hats, shirts, hoodies, totes!Follow @Ologies on Twitter and InstagramFollow @AlieWard on Twitter and InstagramEditing by Mercedes Maitland of Maitland Audio ProductionsManaging Director: Susan HaleScheduling Producer: Noel DilworthTranscripts by Emily White of The WordaryWebsite by Kelly R. DwyerTheme song by Nick Thorburn