Podcasts about Runway

Most founders think their business determines its valuation. The 1 hidden valuation driver costing founders millions is often the founder themselves. By the time a buyer expresses interest, much of your valuation has already been established. Systems, leadership, and operational independence aren't built during due diligence—they're revealed by it. Waiting until an offer arrives often means negotiating from a position that took years to create, but only weeks to evaluate. The bigger risk isn't always EBITDA or revenue growth. Buyers are also assessing whether the business can thrive without the founder, whether transition expectations are aligned, and whether hidden dependencies will create pressure on valuation after the deal begins. Those conversations can quietly reshape enterprise value long before the purchase agreement is signed. Cece Lung from Rich & Sassy Wealth Strategies shares why founders often become the biggest hidden valuation driver in their own business—and why waiting until buyer interest appears can quietly cost millions before negotiations even begin. Learn more about your ad choices. Visit megaphone.fm/adchoices

This week Ben, Brian, and Ted get into IFR currency: what it actually takes to stay instrument current and ready. Six approaches, holds, tracking and intercepting nav aids, and the clock that never stops running. Foggles versus a safety pilot versus the real thing, why the foggles are "the worst approximation of the instrument experience," and whether an IPC is the smarter move than chasing six approaches every six months. Plus a full tape machine of your voice memos and a whole lot of Oshkosh anticipation.From the tape machine: Ash (flying_wheelies) on flying as a wheelchair pilot and sport pilot in his Paradise P1, and more of your feedback.Mentioned on the show:Brian's THE LONG WAY: https://www.makesmallcorrections.com/Frequency Change Aviation, Nashville: https://frequencychangeaviation.com/EP36 with CFI & flight school owner Jeff Ramsey: https://podcasts.apple.com/us/podcast/ep36-cfi-flight-school-owner-jeff-ramsey-on-how-to/id1591463789?i=1000615289723Ash's Flying Wheelies: https://www.instagram.com/flying_wheeliesParadise P1: https://en.wikipedia.org/wiki/Paradise_P1_LSAICP Savannah: https://en.wikipedia.org/wiki/ICP_SavannahWhen Do You Need An IPC (Boldmethod): https://www.boldmethod.com/learn-to-fly/regulations/when-do-you-need-an-ipc-instrument-proficiency-check/1DullGeek's "I Can't See the Runway!!": https://www.youtube.com/watch?v=ZoIQv7IsfCw

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AI is making creative production faster while increasing the value of human craft, imperfection, and hands-on creative control.Drew and Rory start with Netflix's 300 AI-assisted programs and somehow end up defending Blockbuster, boxy cars, greasy roommates, and the radical act of making creative work harder on purpose. Between the usual intellectual potholes, they uncover why invisible AI succeeds, why perfect outputs are becoming exhausting, and why human-made work may become the premium signal.Covered in this episode:Netflix generative AI workflows span concept development, pre-visualization, visual effects, post-production, and release. Suno, Udio, Strudel, Foley artistry, AI music licensing, Runway visual storytelling, Claude, ChatGPT, Figma shaders, Photoshop retouching, creative consistency, nostalgic design, imperfect aesthetics, and hybrid human-AI production define the broader creative shift.---⏱️ Fast Hour00:00 Why are guests returning to Fast Hours?03:45 Why does summer trigger nostalgia?10:49 How is Netflix using generative AI?20:39 Could Blockbuster have become Netflix?24:04 What AI tools has Netflix open-sourced?28:36 What did the Suno breach reveal?32:21 Should AI be used to make music?43:31 Breaking down Runway's lamp film—hy does it work?51:43 How many movie story arcs exist?53:32 Does AI increase the value of human craft?57:53 Why are creators rejecting AI perfection?01:06:16 Why is nostalgic design returning?01:17:09 Why do simple stories feel better?01:23:09 How do AI projects maintain consistency?01:25:43 Who should Fast Hours interview next?#GenerativeAI #AIFilmmaking #AIMusic #CreativeProcess #FastHours

Movie of the Year: 2006The Devil Wears Prada (feat. Katie Walsh!)The Devil Wears Prada Podcast Episode: Fashion, Power, and the Best of 2006Welcome to The Devil Wears Prada podcast episode from Movie of the Year: 2006. This week, the Taste Buds enter the gleaming offices of Runway magazine. Furthermore, they bring backup. Film critic Katie Walsh joins Mike, Greg, and Ryan to decide whether David Frankel's fashion-world comedy can survive the 2006 bracket. Along the way, the panel debates feminism in the workplace, the myth of the suffering artist, and the eternal question of Andy's terrible friends. Additionally, the episode features a full Anne Hathaway Career Retrospective bracket. Consequently, this one runs deep on both style and substance.About the FilmThe Devil Wears Prada arrived in the summer of 2006 and promptly stole it. Director David Frankel adapted Lauren Weisberger's bestselling novel about a young journalist grinding through an impossible job. Anne Hathaway stars as Andy Sachs, an aspiring writer who lands a position at Runway magazine. Her boss is Miranda Priestly, the most feared editor in fashion, played by Meryl Streep in an Oscar-nominated performance. Moreover, Emily Blunt and Stanley Tucci deliver career-launching supporting turns. The film earned over $300 million worldwide and near-universal acclaim. Notably, Roger Ebert praised Streep's icy, understated Miranda as the engine of the whole picture. For more background, the Wikipedia entry on The Devil Wears Prada covers its production and legacy in detail. The film now faces its toughest challenge yet: the Movie of the Year 2006 bracket.Guest Panelist: Katie WalshThe Devil Wears Prada 2006 podcast episode welcomes a genuine authority to the panel. Katie Walsh is a Los Angeles-based film critic who reviews weekly releases for the Tribune News Service and the Los Angeles Times. Additionally, she serves as Vice President of the Los Angeles Film Critics Association. Her writing has appeared in GQ, Vanity Fair, Rolling Stone, Vulture, Slate, and The Playlist. She co-hosted the podcast Miami Nice and has guest-hosted Switchblade Sisters. Furthermore, she frequently appears on KCRW's Press Play and has taught film criticism at Chapman University's Dodge College of Film and Media Arts. In practice, that means the Taste Buds must actually defend their takes this week. Someone in the room knows what she is talking about.Feminism and the WorkplaceIs Miranda Priestly a feminist icon or a cautionary tale? The panel digs into how the film frames women, power, and ambition. Miranda runs an empire, yet the film punishes her with a collapsing marriage. Meanwhile, Andy gets scolded by nearly everyone for taking her job seriously. The episode asks whether the movie critiques workplace sexism or accidentally reproduces it. Notably, Katie Walsh brings a critic's perspective to how 2006 audiences read Miranda versus how we read her now. Two decades of think pieces have flipped the film's villain into its hero. Ultimately, the panel debates whether that reversal says more about the movie or about us.Can Art Only Come from Suffering?Andy suffers for a job she claims to hate, all in service of her writing dreams. Consequently, the Taste Buds tackle a bigger question: does great art require misery? The film suggests that paying dues at Runway makes Andy a better journalist. However, it also shows the cost. She loses friends, a boyfriend, and nearly herself. The panel weighs the romantic myth of the starving artist against the reality of creative work. By contrast, some of the best art comes from stability, support, and cerulean-blue sweaters chosen by someone else. Above all, this segment asks what we actually owe our ambitions.Andy's Friends: The Worst People in FashionEvery rewatch of The Devil Wears Prada produces the same realization: Andy's friends are monsters. They mock her job, demand free designer swag, and play keep-away with her work phone. Meanwhile, her boyfriend Nate pouts because she missed his birthday party for her career. Therefore, the panel litigates the great question of the film's second act. Are these people grounding Andy in reality, or are they sabotaging her? Specifically, the group ranks the friends from least to most insufferable. Nevertheless, at least one Taste Bud attempts a defense of Nate. It does not go well.Anne Hathaway Career Retrospective: The BracketSpecial segment time. The Devil Wears Prada podcast crew builds a full bracket to determine Anne Hathaway's most iconic role. The field spans her entire career. The Princess Diaries, Brokeback Mountain, Rachel Getting Married, Les Misérables, The Dark Knight Rises, and Interstellar all enter the arena. Additionally, deep cuts and dark horses make surprise appearances. Seeding arguments get heated. Upsets happen. As a result, friendships within the panel are tested. Does Andy Sachs herself take the crown, or does an Oscar-winning turn steal it? You will have to listen to find out. Check Anne Hathaway's full filmography on IMDb and play along at home.Why The Devil Wears Prada Still MattersTwenty years later, The Devil Wears Prada refuses to fade. The film remains a Rosetta Stone for conversations about work, ambition, and the price of excellence. Miranda's cerulean monologue is still the definitive speech about how culture actually functions. Moreover, the movie launched Emily Blunt, redefined Anne Hathaway, and gave Meryl Streep one of her signature roles. A 2026 sequel proved the appetite never left. In addition, the film's questions have only grown sharper in the era of hustle culture and quiet quitting. Is Miranda a monster or simply held to a different standard? Ultimately, that debate keeps the film alive, and it makes for a fierce competitor in the Movie of the Year 2006 tournament.Related Episodes from Movie of the Year: 2006Catch up on the season so far, from the 2006 season introduction to the music that defined the year:Movie of the Year 2006: Intro Part 1The 2006 Bracket Reveal: Meet the Sweet 16Tristram Shandy: A Cock and Bull StoryThe 2006 Mixtape, Part IAll Movie of the Year episodesFAQ: The Devil Wears Prada Podcast and FilmWhat is this episode of The Devil Wears Prada podcast about?The Taste Buds and critic Katie Walsh debate whether The Devil Wears Prada deserves to advance in the Movie of the Year 2006 bracket. Topics include workplace feminism, art and suffering, Andy's awful friends, and a full Anne Hathaway career bracket.What is The Devil Wears Prada about?Aspiring journalist Andy Sachs takes a job assisting Miranda Priestly, the tyrannical editor of Runway magazine. Consequently, Andy must decide how much of herself she will trade for success.Who directed The Devil Wears Prada?David Frankel directed the film. He later directed Marley & Me and worked extensively on Sex and the City. Aline Brosh McKenna wrote the screenplay from Lauren Weisberger's novel.Who stars in The Devil Wears Prada?Meryl Streep, Anne Hathaway, Emily Blunt, and Stanley Tucci lead the cast. Streep earned an Academy Award nomination for playing Miranda Priestly.More Questions About The Devil Wears PradaIs Miranda Priestly based on Anna Wintour?Widely, yes. Author Lauren Weisberger worked as an assistant to Vogue editor Anna Wintour, and Miranda is broadly understood as her fictional counterpart. However, Streep has said she modeled the performance on powerful men she knew rather than on Wintour.Who is the guest on this episode?Film critic Katie Walsh joins the panel. She reviews films for the Tribune News Service and the Los Angeles Times and serves as Vice President of the Los Angeles Film Critics Association.What is the Anne Hathaway Career Retrospective?It is a bracket-style special segment. The panel seeds Anne Hathaway's most famous roles against each other and votes round by round until one iconic performance remains.Why does The Devil Wears Prada still matter?The film remains the defining movie about ambition, mentorship, and toxic workplaces. Moreover, its cultural conversation keeps evolving, as the 2026 sequel proved.

O tom, že křesťanství není rodinná tradice, a že je užitečnější vyjít za dětmi na hřiště, než se je snažit zvát do církevních prostor, hovoří Tereza Parks, která je součástí centra Runway Bystrc.Tento podcast můžete podpořit na https://radio7.cz

Welcome back to Behind the Win. We're talking about how a city positions itself for growth, visibility, and long-term impact without losing what makes it special. And a big part of that conversation right now is Ogden, especially with the momentum around the Ogden Airport and new commercial service, including Breeze Airways. Joining us today is Casey Sanders, the Airport Marketing and Business Recruitment Manager for Ogden-Hinckley Airport, where he's leading efforts to bring in new service and drive economic growth through aviation. He also serves as an honorary commander with the Hill Air Force Base, giving him a unique perspective on the connection between the airport, the defense community, and the broader region.

First Phosphate Corp. CEO John Passalacqua joined Steve Darling from Proactive to discuss the successful closing of the final tranche of the company's non-brokered private placement, raising $17.7 million in gross proceeds to support development of its flagship Bégin-Lamarche phosphate project in Québec. Passalacqua said the financing included the issuance of 7.24 million flow-through shares, generating $14.48 million, and 1.61 million hard dollar units, raising an additional $3.22 million. With the completion of this financing, First Phosphate has now raised approximately $82.2 million since June 2022 through 11 management-led non-brokered financings, as well as proceeds from option and warrant exercises. The company plans to use the proceeds to advance its Bégin-Lamarche property in the Saguenay–Lac-Saint-Jean region of Québec, a high-purity igneous phosphate deposit that management believes is well positioned to support the growing North American lithium iron phosphate (LFP) battery supply chain. The company also announced the return of Peter Kent to its Board of Directors. Kent, a former Canadian journalist, federal cabinet minister, and Conservative Member of Parliament, previously served as president, director, and advisor to First Phosphate and played a key role in the company's development. As part of the appointment, the company restructured its Audit Committee, with Kent replacing Passalacqua as a member. The committee is now chaired by Laurence W. Zeifman and includes Peter J. F. Nicholson and Peter Kent. Management said the strengthened balance sheet and board enhancements position First Phosphate to continue advancing its mine-to-market strategy for supplying high-purity phosphate to North America's expanding LFP battery industry. #proactiveinvestors #firstphosphatecorp #cse #phos #otcqx #frspf #frspf #BeginLamarche #LFPBatteries #CriticalMinerals #Phosphate #QuebecMining #EnergyTransition #BatteryMaterials #MiningNews #PrivatePlacement #NorthAmerica #peterkent

Local fashion designers took high fashion to the streets last month to showcase clothes characterized as "rasquachic."

Episode Description A goal without a launchpad is just a daydream without a deadline. Today we build the structure that makes your Mars mission real before you move a single inch. I think SMART goals are stupid, at least the time-based, realistic part. Ask Elon how long Mars should take. A big goal doesn't fit in a tidy box. What it needs is one thing. A decision to begin, a date on the calendar, and a few visible markers so you can feel yourself moving. Build it to pull you forward, not push you. Let's build your launchpad. Featured Story I'm recording this on Monday the 29th, right before I head out on vacation. I've got a goal that splits the year in two, the first half from the second. So every single thing I'm doing today and tomorrow is cleanup. Clearing stuff out, tying off loose ends, getting it all off my plate. I'm not white-knuckling it. I'm building momentum on purpose. When July 1st hits and I kick into the next stage, the obvious next step is already carrying me there. That's a launchpad. The decision is made, the date is set, and the runway is clear. All I have to do then is light it up. Important Points A goal without a launchpad is a daydream without a deadline. Make it real before you move with a date and a structure. The decision to begin is the one move that fuels everything after it. Decide first, and the motivation shows up next. Lay small visible markers between here and your goal. They prove you're moving so you don't get lost in the dark middle. Memorable Quotes A goal without a launchpad is a daydream that doesn't have a deadline. Your daydream without a deadline is nothing. There is one thing that gives you the motivation to continue your goal, and that is the decision to begin it. Decide. You decide to go, you go. Your commitment is automatic if you're motivated enough to reach the freedom on the far side. Scott's Three-Step Approach Start by making one clear decision to begin, because that single choice is what fuels every step that comes after it. Next, make it real before it's real, naming a date, putting it on the calendar, and saying the goal out loud to someone. Then lay visible markers down the runway, benchmarks that prove your momentum so you never stall in the dark middle. Chapters 1:53 - A goal without a launchpad is just a daydream 2:42 - Why SMART goals are stupid for a big goal 4:15 - The decision to begin is your only motivation 5:31 - Make it real with a date you say out loud 5:58 - Anticipation is the fuel that pulls you forward 6:37 - Designing the next step to be totally obvious 7:29 - Runway markers that prove you are moving Connect With Me Search for the Daily Boost on YouTube, Apple Podcasts, and Spotify If you enjoy the Daily Boost, you might like Notes From Scott. A few mornings each week, I send a short note with something I've been thinking about or noticing lately. Sometimes those ideas turn into podcast episodes later. You can sign up at https://notesfromscott.com. Email: support@motivationtomove.com Main Website: https://motivationtomove.com YouTube: https://youtube.com/dailyboostpodcast Instagram: https://instagram.com/heyscottsmith Facebook Page: https://facebook.com/motivationtomove Facebook Group: https://dailyboostpodcast.com/facebook Learn more about your ad choices. Visit megaphone.fm/adchoices

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

Brady goes on an aerobatic stunt flight - and Tim is annoyed by the theme tune from Roger Ramjet. Plus loads of other stuff.A few snippets from the flight can be seen on the YouTube video for this episode - https://youtu.be/YQeBXNE868MAn extended video of the flight with multiple camera angles and all the audio can be seen on our Patreon - https://www.patreon.com/unmadeFM/posts/163054917With the thanks to Cabaero Aviation and pilot Mark Hooton - https://cabaeroaviation.com/Today's Request Room - https://www.patreon.com/unmadeFM/posts/163143083Support us on Patreon - https://www.patreon.com/unmadeFMDiscuss the episode on our subreddit - https://www.reddit.com/r/Unmade_Podcast/USEFUL LINKSRunway 23 - https://www.runway23.fm/Runway 23 on Apple - https://podcasts.apple.com/us/podcast/runway-23/id1896917264Runway 23 on Spotify - https://open.spotify.com/show/033x15ndR31wM6YujhTv4wPeriodic Videos (Brady's chemistry videos) - https://www.youtube.com/periodicvideosTim's downloadable doodles (or noodles) - https://www.patreon.com/unmadeFM/posts/here-are-guitar-161608346John and his gold card (and other pictures from the episode) - https://www.unmade.fm/episode-181-picturesSywell Aerodrome - https://www.sywellaerodrome.co.uk/Port Arthur - https://portarthur.org.au/The Port Arthur Massacre - https://en.wikipedia.org/wiki/Port_Arthur_massacreRoger Ramjet intro - https://www.youtube.com/watch?v=E7SqSNQeAFMToday's Request Room - https://www.patreon.com/unmadeFM/posts/163143083

Designing runways for hot air and heavy planes, inspecting pavement cracks with measuring wheels, and protecting vicious little owls from construction crews with Eileen Vélez-Vega, a civil aviation engineer in Puerto Rico. What does the color of runway lights reveal to a pilot? And what's a "spall"?WANT MORE EPISODE SUGGESTIONS? Grab our What It's Like To Be... "starter pack". It's a curated Spotify playlist with some essential episodes from our back catalogue.GOT A COMMENT OR SUGGESTION? Email us at jobs@whatitslike.comFOR SPONSORSHIP OPPORTUNITIES: Email us at partnerships@whatitslike.comWANT TO BE ON THE SHOW? Leave us a voicemail at (919) 213-0456. We'll ask you to answer two questions:1. What's a word or phrase that only someone from your profession would be likely to know and what does it mean?2. What's a specific story you tell your friends that happened on the job? It could be funny, sad, anxiety-making, pride-inducing or otherwise.We can't respond to every message, but we do listen to all of them! We'll follow up if it's a good fit.

Samsung's projected revenue slightly missed expectations, but as Kevin Hincks points out, guidance came in way above expectations and year-over-year growth shows phenomenal traction. The stock still slid and brought a lot of U.S. tech down with it. It's no secret AI memory is here to stay, says Kevin, the problem lies in how far stocks like Samsung, Micron (MU), SanDisk (SNDK) and others can rally. He turns to the macro front by talking about a report that Iran has fired on commercial ships in the Strait of Hormuz. ======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

From casual tacos to caviar and champagne — discover how restaurateur Marc Falsetto transformed Fort Lauderdale's dining landscape and pivoted to luxury during a pandemic.As founder and CEO of Falsetto Hospitality, Marc Falsetto has been instrumental in shaping Fort Lauderdale's restaurant scene. Starting with casual concepts under Handcrafted Hospitality — including the popular Tacocraft Mexican restaurants, chef-driven gastropubs, and sandwich shops — Falsetto built a reputation for approachable, quality dining. He also breathed new life into Runway 84, a 40-year-old Italian-American institution, updating everything from décor to ambience.Then came the pandemic — and a bold pivot. Recognizing an influx of wealth and a growing appetite for sophisticated experiences in South Florida, Falsetto shifted his focus to luxury dining and developed an upscale supper club model. Now, he's preparing to launch the Caviar Club, an American steakhouse with a private membership component that channels pure 1980s indulgence.Hospitality runs deep in Falsetto's veins. Raised in a restaurant family in Canada, he started as a busboy in his early teens, promoted nightclubs during college, eventually bought his own restaurant, and went on to build two successful hospitality companies. Through it all, he's kept his core team intact — including his longtime chef — proving that loyalty and vision go hand in hand.In this episode, hear how Falsetto conceptualizes restaurant ideas, why he's bullish on the South Florida market, and what ambitious plans he's cooking up next.

Robby Silk and Sean Cudahy assess the strength of the U.S. travel sector, highlighting resilient demand and rising airfares despite economic uncertainty. They discuss key themes to watch this airline earnings season, including Delta Air Lines' (DAL) ability to manage fuel costs, maintain pricing power, and navigate changing consumer spending trends amid an evolving travel landscape.======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

Pakistani-origin artist and fashion designer Amna Irshad is redefining the relationship between art and fashion by transforming her original painting skills into wearable creations. In an exclusive conversation with SBS Urdu, she shares the inspiration behind her exhibition, "Dress to Impress," and explains how she blends fine art, traditional craftsmanship, and contemporary fashion to create garments that tell a story beyond the canvas. - آمنہ ارشاد ایک پاکستانی نژاد مصور اور فیشن ڈیزائنر ہیں جن کا کہنا ہے کہ وہ اپنے فن کو دیواروں کی زینت بننے سے کہیں زیادہ آگے بڑھتا دیکھنے کی خواہاں ہیں ، Dress to Impress کے نام سے جاری ان کی فیشن ایگزیبشن میں کیا منفرد ہے سنئے ایس بی ایس اردو سے ان کی خصوصی گفتگو میں ۔

This week, host Taylor Inman covers the biggest headlines shaping Northwest Montana — from flood-driven closures in Glacier National Park to a $21 million runway overhaul grounding flights at Glacier Park International Airport, a potential reopening for a shuttered Kalispell mental health crisis center, and a local animal rescue calling the surge in abandoned cats an "epidemic."Heavy rains this week triggered flooding and closures across Glacier National Park, temporarily shutting down part of the Going-to-the-Sun Road and forcing evacuations in the Many Glacier Valley. The road has since fully reopened, and as of Wednesday, the Many Glacier Hotel, Swiftcurrent Motor Inn and several trails were back open to visitors — though park officials are urging extra caution near swift, cold glacial streams.Starting next week, Glacier Park International Airport will significantly scale back operations for four weeks during peak tourism season to overhaul its aging runway. The Flathead Valley's transit hub will close Monday evenings through Friday mornings from July 6 to July 31, with airport officials expecting a 40% drop in July flights and warning travelers to arrive two hours early on operating days.A shuttered mental health crisis stabilization center in North Kalispell, Glacier House, may reopen after a $100,000 infusion of state funding. AWARE Inc., the nonprofit now acquiring the facility's assets, says staffing and long-term funding remain unresolved, so no reopening date has been set.And local shelters are sounding the alarm on cat abandonment: KittyMOM's Rescue took in 17 more cats and kittens this week alone, and both the Flathead County Animal Shelter and the Humane Society of Northwest Montana say they're operating at capacity.Read the full stories and more local coverage at https://DailyInterLake.com.Northwest Montana deserves strong news reporting. Your donation helps continue work like this possible. Learn more at dailyinterlake.com/support Visit DailyInterLake.com to stay up-to-date with the latest breaking news from the Flathead Valley and beyond. Support local journalism and please consider subscribing to us. Watch this podcast and more on our YouTube Channel. And follow us on Facebook, Instagram and X. Got a news tip, want to place an ad, or sponsor this podcast? Contact us! Subscribe to all our other DIL pods! Keep up with northwest Montana sports on Keeping Score, dig into stories with Deep Dive, and jam out to local musicians with Press Play.

Fashion visionary Law Roach joins Obsessed to talk about bringing his signature honesty to Project Runway, why he calls himself an "image architect," and the psychology behind creating iconic celebrity style. He reflects on his longtime collaboration with Zendaya, the evolution of method dressing, the lessons he learned from Celine Dion, and why fashion has become one of Hollywood's most powerful marketing tools. Plus, Law shares behind-the-scenes stories from his career, his approach to judging reality TV, and the style trends he'd happily leave behind. Follow Kevin Fallon on Instagram ⁠@kpfallon⁠ Follow Matt Wilstein on Instagram ⁠@mattjwilstein⁠ New episodes every Thursday, and Saturday; ⁠early drops on YouTube⁠. Learn more about your ad choices. Visit podcastchoices.com/adchoices

MIRANDA PRIESTLY IS BACK... BUT DOES THE SEQUEL LIVE UP TO THE ORIGINAL?! With Meryl Streep returning as Miranda Priestly, Anne Hathaway back as Andy Sachs, and Emily Blunt reprising Emily Charlton, Greg Alba, John Humphrey & Tara Erickson react to The Devil Wears Prada 2 — the long-awaited sequel that brings audiences back inside the glamorous and ruthless world of Runway Magazine. Blending sharp comedy, fashion industry satire, modern journalism, and emotional character reunions, this The Devil Wears Prada 2 reaction explores one of the year's most anticipated comedy sequels. The Devil Wears Prada 2 Reaction (Full Length Watch Along):   / thereelrejects   Limited Time Offer – You Need Fiber. Yes you! Boost your fiber with Huel today using my exclusive offer of 15% OFF online with my code REJECTS at https://www.huel.com/REJECTS. New Customers Only. Thank you to Huel for partnering and supporting our show! In this The Devil Wears Prada 2 reaction, movie reaction, and review, Greg, John & Tara revisit the iconic world of Miranda Priestly, played by Meryl Streep (The Devil Wears Prada, The Iron Lady), as she navigates the rapidly evolving fashion and media landscape alongside Andy Sachs, played by Anne Hathaway (Interstellar, Les Misérables), Emily Charlton, played by Emily Blunt (Oppenheimer, A Quiet Place), and Nigel, played by Stanley Tucci (Conclave, The Hunger Games). The sequel also features Lucy Liu (Kill Bill Vol. 1, Charlie's Angels), B.J. Novak (The Office, Vengeance), Simone Ashley (Bridgerton, Sex Education), and Justin Theroux (The Leftovers, Beetlejuice Beetlejuice), as old rivalries, unexpected alliances, and the future of fashion journalism collide. Featuring unforgettable callbacks to the original film, Miranda's commanding return to Runway, Andy's unexpected homecoming, Emily's rise in the fashion world, Nigel's heartfelt journey, dazzling couture showcases, celebrity cameos, and a story centered on preserving creativity in an era dominated by algorithms and digital media, The Devil Wears Prada 2 delivers a stylish and surprisingly emotional continuation of the beloved classic. Inspired by the world created by Lauren Weisberger and produced by Disney, the sequel revisits one of cinema's most iconic fashion franchises while exploring how both the industry—and its legendary characters—have changed over the past two decades. Follow Greg Alba:  Instagram: https://www.instagram.com/thegregalba/ Twitter:  https://x.com/thegregalba Follow Tara Erickson: Youtube: https://www.youtube.com/@TaraErickson Instagram:  https://www.instagram.com/taraerickson/ Twitter:  https://twitter.com/thetaraerickson Learn more about your ad choices. Visit megaphone.fm/adchoices

Lameka Fox is an international fashion model whose career has taken her around the world. But in 2018, she became the target of a stalker. What began as unwanted contact escalated into years of harassment, surveillance, threats, and repeated invasions of her privacy. Despite reporting the behavior, she struggled to get the protection she needed. Today, Lameka shares her story of surviving stalking, how it changed her life, and how she helped advocate for New York's CREEP Act to strengthen protections for stalking victims. Share Your Story on the Show: strictlystalkingpod@gmail.com Our Sponsors Boll and Branch Get twenty percent off your first order, plus free shipping during the Memorial Day sale at bollandbranch.com/strictly with code STRICTLY. Exclusions apply. Delete Me Today get 20% off your DeleteMe plan when you go to JoinDeleteMe.com/STALKING and use promo code STALKING at checkout.  Quince Go to https://www.quince.com/strictly for free shipping on your order and 365-day returns. Shopify shopify.com/strictlystalking for a one-dollar-per-month trial period! Solace You can start a free session in under a minute at solaceconcierge.ai/strictlystalking.  REMI shopremi.com/strictly to get 50% off your new night guard with code STRICTLY Whatnot Download the Whatnot app today and get free shipping on your first order. Just search W-H-A-T-N-O-T— Whatnot — in the app store and start scoring amazing deals. Progressive Insurance Press play on comparing auto rates. Get your auto quote at Progressive.com to join the over 28 million drivers who trust Progressive. Guest Links: Lameka Fox IG: https://www.instagram.com/lamekafox/ Creep Act IG:https://www.instagram.com/thecreepact/ Related Podcasts lovelustfear | with Jake Deptula Listen & Subscribe Here: lovelustfear The Last Trip - Podcast - hosted by Jaimie Beebe Listen & Subscribe Here: The Last Trip Instagram @strictlystalkingpod @feathergirl77 @jaked3000

“Everybody wants to be us.” Join Ian & Liam for our 337th episode as we slip into designer shoes, grab the garment bags, and survive another impossible day at Runway magazine with The Devil Wears Prada (2006). Megs isn't with us this week — Miranda Priestly spotted her wearing cerulean before she'd learned why it was cerulean and immediately reassigned her to the Paris office. Kev? He's still trying to fetch the unpublished Harry Potter manuscript, a flight to Miami, and a steak for Miranda... all before lunch. This week we discuss: Meryl Streep's iconic performance — restrained, terrifying, and endlessly quotable. Is Miranda Priestly one of the greatest screen bosses ever created? Anne Hathaway's Andy Sachs — idealistic, ambitious, and increasingly compromised. Is her transformation inspiring, tragic, or somewhere in between? Emily Blunt steals every scene — razor-sharp timing, impeccable delivery, and why Emily Charlton remains one of the film's most beloved characters. Stanley Tucci's Nigel — warmth, wit, and heartbreak. Does he quietly become the emotional centre of the film? Ian breaks down the screenplay — how the film effortlessly balances workplace comedy, character drama, and biting satire. Liam explores the film's central question — is success worth sacrificing the people and principles that got you there? The fashion world — superficial excess, genuine artistry, or something much more complicated than the film's critics often admit? The "cerulean sweater" speech — one of the great monologues of modern cinema. Does it completely redefine how we understand Miranda? The "show vs tell" balance — how the film uses costume, performance, and visual storytelling to chart Andy's evolution without ever needing to announce it. The ending — personal victory, professional failure, or exactly the compromise Andy needed to make? And finally, whether The Devil Wears Prada is the Best Film Ever — or simply one of the smartest and most rewatchable comedies of the 21st century. Become a Patron of this podcast and support the BFE at https://www.patreon.com/BFE We are very thankful to the following Patreon backers for their generous support: Juleen from It Goes Down In The PM Hermes Auslander James DeGuzman Synthia Shai Bergerfroind Ariannah Who Loves BFE The Most Paul Komoroski Duane Smith (Duane Smith!) Andy Dickson Aashrey Chris Pedersen Randal Silva Nate The Great Rev Bruce Richard Ryan Kuketz Dirk Diggler Stew from the Stew World Order podcast NorfolkDomus John Humphrey's Right Foot Timmy Tim Tim Youth Hosteling with Chris Eubank Buy some BFE merch at https://my-store-b4e4d4.creator-spring.com/. Massive thanks to Lex Van Den Berghe for the use of Mistake by Luckydog. Catch more from Lex's new band, The Maids of Honor, at https://soundcloud.com/themaidsofhonor Also, massive thanks to Moonlight Social for our age game theme song. You can catch more from them at https://www.moonlightsocialmusic.com/

The second half of the year isn't a continuation, it's a new season. In this episode, I'm sharing my own mid-year reset and what my clients are doing differently to finish the year strong, because the most powerful people know something the rest of the world doesn't: the second half is where the year is actually won or lost. Consider this your wake-up call and your runway. Now let's walk. I am taking on a few people for 2nd half advisory, consulting & coaching, subscribe to the newsletter list and reply for details www.KellyLynnAdams.com  Will I see you virtually on Wednesday, July 1st's our monthly virtual networking, connected circles event, did you RSVP yet? Link in my Instagram bio. Last month's meeting was powerful. If you haven't joined the waitlist for The Curated Table Events, message EVENTS. If you haven't subscribed to the newsletter for exclusive events, offerings and announcements make sure you are on the newsletter here: www.KellyLynnAdams.com

Join our mastermind community: https://www.skool.com/apparel-success-mastermindTry the best Ai design platform: https://www.design.com/rob88AI video generators are getting insanely realistic, and in this video I show how clothing brand owners can use tools like Kling AI, Seedance, Google Veo, Sora, Runway, Adobe Firefly, Poyo.ai, Higgsfield AI, ChatGPT, ElevenLabs, CapCut, and Premiere Pro to create realistic ads, TikTok videos, Instagram Reels, product videos, and social media content without spending thousands on photoshoots, models, or videographers.I tested the biggest AI video tools to see which ones worked best for clothing brands using real product reference images. I break down why Google Veo, Sora, and Runway struggled, why Kling AI created some of the most realistic results, and why Seedance 2.0 might be one of the best AI video generators for accurate clothing brand content, fabric, logos, product details, and lifestyle scenes.If you run a streetwear brand, gymwear brand, hoodie brand, outdoor brand, or apparel business, this video shows how AI can help you create better ads, Meta ads, TikTok ads, Instagram content, UGC-style videos, and product marketing faster than ever.

Will Guillory, an NBA reporter for The Athletic, joined Sports Talk. Guillory reviewed the Pelicans' decision to stay put during the first round of the 2026 NBA Draft. He explained that it never made sense to trade Trey Murphy or Herb Jones.

WBZ NewsRadio's Kendall Buhl has more.See omnystudio.com/listener for privacy information.

Fresh off a 10-day trip with my kids in Cabo and LA, I'm catching you up on everything: from Disney adventures and quality time with my favorite people to one of the biggest moments for Uncommon James yet: our Miami Swim Week runway debut.After getting flooded with questions about how I prepared to walk the runway, I'm sharing exactly what I did (and didn't do) leading up to Miami. We're talking alcohol, workouts, sleep, gut health, inflammation, supplements, saunas, spray tans, coffee enemas, and why I think feeling your best has way more to do with overall health than chasing a number on the scale.A word from my sponsors:Salt and Stone: Try Salt and Stone's discovery set to find your signature scent — Go to https://SaltandStone.com/HONEST and use code HONEST at checkout for 15% off your first order.Nutrafol: See thicker, stronger, faster-growing hair with less shedding in just 3-6 months with Nutrafol. For a limited time, Nutrafol is offering our listeners $10 off your first month's subscription and free shipping when you go to https://Nutrafol.com and enter the promo code HONESTDraftKings Casino: Download the DraftKings Casino app and sign up with code HONEST to claim your Flex Spins and experience Cashingo—the feature you can't play anywhere else! The Crown is Yours. In partnership with DraftKings Casino. Gambling problem? Call one eight hundred GAMBLER. In Connecticut, help is available for problem gambling call eight eight eight seven eight nine seven seven seven seven or visit CCPG.org. Please play responsibly. Twenty-one plus. Physically present in Connecticut, Michigan, New Jersey, Pennsylvania, West Virginia only. Void in Ontario. Eligibility restrictions apply. Non-withdrawable Spins issued as fifty spins per day for twenty days, valid for select games only and expire each day after twenty four hours. See terms at casino.draftkings.com/promos. Ends July 22, at 11:59 PM Eastern Time.LMNT: Right now LMNT is offering a free sample pack with any purchase, That's 8 single serving packets FREE with any LMNT order. This is a great way to try all 8 flavors or share LMNT with a friend. Get yours at https://DrinkLMNT.com/HONEST.Lululemon: Go to https://lululemon.com right now. New styles drop all the time and the colors go fast, so don't wait. And if something doesn't work for you, free returns, always. Ladder: If you have an iPhone, head to https://ladder.fit/HONEST and take a quick quiz to find your perfect Ladder plan. Use my link and get a free 7-day trial with NO credit card, and $10 off your first month if you join.Armra: Go to https://armra.com/HONEST or enter HONEST to get 30% off your first subscription order.Hiya: Receive 50% off your first order. To claim this deal, you must go to https://hiyahealth.com/HONEST.For more Let's Be Honest, follow along at:@kristincavallari on Instagram@kristincavallari and @dearmedia on TikTokLet's Be Honest with Kristin Cavallari on YouTubeProduced by Dear Media.This episode may contain paid endorsements and advertisements for products and services. Individuals on the show may have a direct or indirect financial interest in products, or services referred to in this episode.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

If you're still wondering how you can give back to the community this Pride season, we have the answer! Keep our little indie pod afloat by joining our Patreon at the $5/month tier or higher and unlock our growing library of full-length ad-free bonus episodes, ad-free weekly episodes, mp3 downloads of all our original songs, exclusive Discord access to hang out with us, and more! Get an automatic discount on your membership by signing up for an annual subscription. Welcome back to Lez Hang Out, the podcast that fell in love with the shape of a woman long before Gaga made it cool.  This week, Leigh (@lshfoster) and Ellie (@elliebrigida) hang out with Lez Hang Out's very own production assistant and professional mermaid, Kristin Murison (@therealksparkle), and talk about why the 2026 blockbuster hit, The Devil Wears Prada 2, should've been gay. If you missed our Should've Been Gay episode on the original The Devil Wears Prada film we highly recommend listening to it first for the perfect podcast double feature. You could tell us that the entirety of this nearly 2-hour long sequel takes place in Emily Charlton's head as she recovers in the hospital after being hit by a taxi in the first movie and we would believe you. It's simply too gay of a script for there to be any other explanation aside from ‘lesbian fever dream'. Whether you ship Mirandy, Sachston, or a secret third thing (we suggest Lucy Liu and literally any other woman on screen), you will come out of DWP2 extremely well-fed. Although it has been 2 decades since Miranda Priestly (Meryl Streep) graced our screens, her red heels remain firmly on the necks of lesbians everywhere. Not even the decline of print journalism, the rise of fast fashion, and a full-on scandal can dethrone the queen of Runway. By reputation alone, she gets Lady Gaga to perform what is undoubtedly her gayest song since Born This Way. Yet, even Miranda and Lady Gaga's chemistry isn't the gayest thing about DWP2. That title is shared by the Emilys– Andy “I froze my eggs and have never hidden a feeling in my entire life” Sachs (Anne Hathaway) and Emily “I'm divorced and visibly repulsed by any man I have to get physically close to” Charlton (Emily Blunt), who spend the entire film openly ogling one another and bickering like an old married couple while wearing increasingly more masc outfits. They're pretty much canonically dating by the end, bonding over a plate of shared carbs as Emily confesses to having called Andy all those years ago (all but admitting that she has been holding on to the disappointment of Andy not calling her back for literally 20 years). If that's not a lesbian fever dream, we don't know what is. We know one thing for sure, The Devil Wears Prada 2 Should've Been Gay. Give us your own answers to our Q & Gay on Instagram and follow along on Facebook, TikTok, YouTube and BlueSky @lezhangoutpod. Email us @lezhangoutpod@gmail.com. Connect with us individually: Ellie Brigida (@elliebrigida). Leigh Holmes Foster (@lshfoster). Support the pod by shopping small for your Pride #ootd at bit.ly/lezmerch & picking up our Lez-ssentials songs on Bandcamp. Learn more about your ad choices. Visit megaphone.fm/adchoices

Peter Diamandis has spent his career betting on humanity. He founded XPRIZE, which has launched over $600 million in competitions driving $10 billion in research across space, robotics, AI, and health. He co-founded Singularity University, runs a billion-dollar AI fund seeding MIT and Harvard startups, and has known Elon Musk for 26 years. He is one of the most prominent AI optimists alive. He is also worried about civil unrest, and he is not vague about why.The group out of work the longest right now is 22 to 28 years old. Not because of mass layoffs — because entry-level hiring has simply frozen. A generation that spent years and real money on degrees, promised that the pipeline leads somewhere, is finding the door closed. Diamandis points out that every revolution in history was led by young men who saw no economic future. He thinks we are setting up the conditions for another one. That concern sits alongside his excitement about the SpaceX IPO, which he compares to investing in 1496 when Columbus set sail — everything we value on Earth exists in near-infinite quantities in space, and Elon is building the railroads to get there.The episode also covers why Hollywood may be making AI more dangerous. Anthropic traced Claude's decision to blackmail an engineer back to its training data, which was saturated with dystopian sci-fi where AIs behave exactly that way. Diamandis's response is the Future Vision XPRIZE — a global competition for 3-minute film trailers showing a hopeful future, with the goal of flooding YouTube with positive visions that train both humans and the models. The winner gets a $15 million film produced. Enter at futurevisionxprize.com.Timecodes:[7:01] Snap Spectacles consumer launch[10:00] Apple WWDC and the new Siri — Charlie gives Claude access to his email and calls it "the deepest, most disturbing invasion of privacy I have ever experienced"; Ted calls it the return of Clippy[13:09] Martin Scorsese and Flux[14:20] Lionsgate takes a financial stake in Runway[17:15] SpaceX IPO — Enter Diamandis, who compares this to funding Columbus in 1496; $1.7 trillion valuation heading to $2.5 trillion[22:04] AI's biggest risk: civil unrest [25:55] Future Vision XPRIZE — 3-minute Ai trailer competition; winner gets a $15 million film; futurevisionxprize.com[47:30] The future curriculum — "the most infinitely patient teacher on the planet is AI"[53:33] Quantum and AI solving everythingBrought to you by Zappar and Mattercraft. Mattercraft is Zappar's web-based platform for building augmented reality experiences without an app. Find them at mattercraft.io. Hosted on Acast. See acast.com/privacy for more information.

Designer Simone Rocha makes her menswear runway debut today as guest designer at Pitti Uomo in Florence. Nicole Phelps sat down with Rocha just a few days ahead of the debut and to discuss why now felt like the right time to give her menswear line its own runway spotlight, how independence has shaped her career, and the family legacy behind her approach to design. Reflecting on everything from her days at Central Saint Martins to dressing figures like Paul Mescal and Josh O'Connor, Rocha shares her vision of a “tender, intimate masculinity”—and explains why she still loves surprising her audience.For headlines, Phelps and Chloe Malle are joined by Vogue Runway senior fashion news editor Max Berlinger for a globetrotting edition of The Run-Through that begins at the World Cup and ends on the menswear runways of Milan, Paris, and Florence. Fresh from France's opening match against Senegal at MetLife Stadium, Chloe reports on the tournament's unexpectedly chic sidelines—from sold-out Nike x Jacquemus training jerseys to French players arriving with covetable Chanel and Hermès bags. The trio also discusses New York's euphoric Knicks celebrations and why sports fandom is becoming one of fashion's most compelling new front rows.Then, attention turns to the upcoming men's shows. The hosts break down what to expect from Milan, where Ralph Lauren's return continues what Max dubs a “Ralph-aissance,” alongside runway outings from Prada and Armani. In Paris, anticipation is building around Michael Rider's first standalone menswear show for Celine, Jonathan Anderson's evolving vision for Dior Men, Sarah Burton's menswear debut at Givenchy, and Simon Porte Jacquemus's grand finale in Corsica. Along the way, the conversation touches on the return of slimmer silhouettes, the rise of low-profile footwear, and the designers poised to define the next chapter of menswear.The Run-Through with Vogue is your go-to podcast where fashion meets culture. Hosted by Chloe Malle, Head of Editorial Content, Vogue U.S.; Chioma Nnadi, Head of British Vogue; and Nicole Phelps, Director of Vogue Runway, each episode features the latest fashion news and exclusive designer and celebrity interviews. Learn about your ad choices: dovetail.prx.org/ad-choices

Welcome back to RECESS — our bi-weekly look at what we're learning, trends we're seeing in the health and fitness space, and how we're building more play into real life.The fitness industry is facing its biggest shake-up yet, and it's coming from a syringe. In this episode of RECESS, we cover a lot of ground: from Caroline's high school graduation and a wild weekend of sports (Knicks championship! Water polo! World Cup!) to the questions keeping health and fitness professionals up at night.The centerpiece of this episode is a candid conversation about GLP-1, GLP-2, and the newly trialed GLP-3 drug Retatrutide — and what near-30% body weight loss results mean for the future of personal training, nutrition coaching, and the entire weight loss industry. Is weight loss about to become a purely medical intervention? And if so, what does that mean for coaches, trainers, and wellness brands like ours?We also take on a viral debate about AI-generated fitness influencers crowding out real coaches on social media, break down the data on whether women should skip college in the age of AI (spoiler: the numbers say no), and share our take on Backrooms, the buzzy horror film directed by a local kid who built the concept as a high schooler. If you've ever felt the existential dread of liminal spaces, this one's for you.What You'll Learn in This EpisodeWhy Caroline Starrett's observation that "muscles are the new skinny" might be the most important trend call in fitness right nowHow GLP-3 drug Retatrutide achieved nearly 30% average body weight loss in Phase 3 trials, and what that means compared to Ozempic and ZepBoundWhat happens to the fitness industry if weight loss becomes a purely pharmaceutical interventionThe hidden dangers of GLP-1 drugs: muscle and bone mass loss, weight regain after stopping, and the return of extreme thinness cultureWhy AI-generated fitness influencers are getting millions of views while real coaches struggle for reach, and what to do about itThe data behind college ROI for women: why the gender pay gap and VC funding stats make a compelling case for staying in schoolWhy the most successful female founders (Rent the Runway, Stitch Fix, 23andMe, Tory Burch) share one thing in commonA local director's Backrooms, worth seeing even if you hate horrorKey Highlights: (00:00) Welcome back to RECESS; Caroline's high school graduation and becoming (almost) empty nesters; the "open nest" philosophy(01:50) A massive weekend of sports: Knicks championship, Stanley Cup, World Cup, water polo tournaments, and shoutouts to Cal athletes competing in European club championships(05:35) The viral Canadian coach's Instagram post: AI-generated fitness influencers vs. real coaches, the algorithm problem, and a defense of making content that's actually fun(07:45) Why real coaches deserve your engagement: the difference between AI-driven content and educators who've spent years building free resources(11:17) College ROI debate: a prominent female entrepreneur suggests skipping college; Juliet and Kelly push back with data — 65–75% higher lifetime earnings for college grads, and the gender pay gap closes with education(16:00) Female founders and elite credentials: why the women who actually break through in VC-backed startups almost universally have top-tier degrees; notable examples and one cautionary tale(18:00) Caroline's insight: "muscles are the new skinny" — when anyone can change their body composition with a GLP drug, muscle becomes the differentiator(19:29) Breaking down the GLP-3 trial results for Retatrutide: 70+ lbs average loss, nearly 30% body weight reduction, and how it compares to GLP-1 and GLP-2 drugs(20:40) How GLP drugs are splitting the fitness industry: some coaches relieved, some threatened, and the legacy weight loss brands already pivoting(22:45) The dark side: muscle and bone mass loss, Hollywood's return to extreme thinness, and what happens when people stop taking the drugs without changing their habits(27:00) The message that still matters: muscle is your longevity organ; building a body for adventure; why GLP drugs and strength training aren't mutually exclusive(27:29) Backrooms the movie: local Marin School of the Arts alum director Kane Parsons, and why this creepy-beautiful film is worth your time even if you're not a horror fan(29:10) Wrap-up and thanks for listening

Artificial intelligence (AI) models continue to get smarter and cheaper, spurring adoption and expanding the total addressable market. Pamela Hegarty and Derek Glynn, Co-portfolio Managers of BNPP AM's disruptive technology strategy provide Daniel Morris, Chief Market Strategist, with their expert views of the current AI industry and its investment potential, not least in supporting both training and inferencing applications.For more insights, visit Viewpoint: https://viewpoint.bnpparibas-am.com/Download the Viewpoint app: https://onelink.to/tpxq34Follow us on LinkedIn: https://bnpp.lk/amHosted on Ausha. See ausha.co/privacy-policy for more information.

You’re listening to American Ground Radio with Louis R. Avallone and Stephen Parr. This is the full show for June 15, 2026. We open with a major Supreme Court immigration case heading into the next term — the question of whether non-citizens with serious criminal convictions can be held in detention during deportation proceedings without bond hearings. We explain why this isn't a simple bumper sticker case, why the flight risk argument for criminal aliens is fundamentally different from that of U.S. citizens with community roots, and why the ruling could become one of the most consequential immigration decisions of the new term — directly testing how much process is due before temporary custody starts looking like indefinite imprisonment. We also get into President Trump's peace deal with Iran, and why Barack Obama's claim that this is essentially the same deal he negotiated is not just wrong but precisely backwards. Obama's deal had a time limit on nuclear development — legally allowing Iran to have a bomb by 2030. Trump's deal requires Iran to destroy its highly enriched uranium, pledge never to obtain nuclear weapons, stop funding Hezbollah and Hamas, and open the Strait of Hormuz immediately upon signing — with economic relief only after the first two conditions are fully met. No cash on the runway. No expiration date. Not the same deal. In our Top 3 Things You Need to Know, President Trump announced a peace agreement with Iran over the weekend — covering the five key points — with a final signing expected in Switzerland on Friday. Then a B-52 Stratofortress crashed in Southern California after taking off from Edwards Air Force Base, with military officials saying the crash was unsurvivable — we offer our prayers and gratitude to the crew. And President Trump endorsed Congressman Mike Collins in the Georgia Senate Republican runoff against Derek Dooley, a former football coach who admits he didn't vote in either 2016 or 2020. We walk through the five pillars of the Iran deal in detail — destruction of highly enriched uranium, a permanent pledge never to obtain nuclear weapons, ending the naval blockade only after the first two steps are complete, immediate reopening of the Strait of Hormuz upon signing, and a requirement that Iran stop funding all terrorist proxies including Hezbollah and Hamas. We note what makes this deal structurally different from every previous Iran negotiation — enforcement is built into the sequencing, not assumed as an afterthought. Our American Mamas Teri Netterville and Kimberly Burleson discuss whether women should still take their husband's last name when they marry — prompted by viral videos of couples doing rock-paper-scissors and tug-of-war at their own weddings to decide whose name to use. The Spinks Sisters kept their maiden names as middle names, missed them immediately, and are pretty clear on where they stand. We also explore what it signals about a marriage when a woman doesn't take her husband's name — and why in Washington especially, different last names make it a lot harder to spot the conflicts of interest. In our Digging Deep segment, we take on the left's use of adjectives to alter meaning and control thought — starting with the phrase progressive Christianity versus Christian right. We work through why these two constructions mean completely different things, why the need for the adjective tells you the noun isn't what's being advertised, and how a pastor writing in Salon Magazine misquotes Jesus — changing blessed are the poor in spirit to blessed are the poor — to make Christ's words align with progressive ideology. We connect it to George Orwell's observation that whoever controls the language controls the masses, and explain why this linguistic sleight of hand is one of the left's most effective political tools. We also note that Bill Maher is endorsing Graham Plattner — the Maine Democratic Senate candidate with the SS tattoo and the predator website — and explain that this isn't about principle. It's about keeping Susan Collins out of the Senate. Power, not values. We also push back on Robert De Niro's claim that loving America today is like an abused spouse loving an abuser — and point out that conservatives who disagreed with everything Obama and Biden did never stopped saying they loved their country. Disagreeing with your leaders and loving your country are not the same thing. They never have been. For our Bright Spot, the U.S. Men's National Team beat Paraguay 4-1 in the World Cup — the most goals the U.S. has ever scored in a World Cup match, with Florian Balogun scoring two in the first half. But the moment that mattered most came after the final whistle, when the entire team circled up in the middle of the field and prayed. Defender Mark McKenzie, whom teammates call pastor, led the prayer. On the biggest stage in the world, the U.S. team's first instinct was gratitude. We contrast that with Diego Maradona, who scored a goal with his hand and called himself a god. We'll take our team. And we close with Emily Matijovic, a 16-year-old from Michigan who passed away in December and whose family chose to donate her organs. This spring — the spring she was supposed to graduate — her family threw her a graduation party. Four-year-old Ripley Farrell came from West Virginia. She received one of Emily's kidneys. Teenager Landon Coleman came from Virginia. He received Emily's heart. He told her family it lets him do things he couldn't do before. It is in giving that we receive. May your pursuit of happiness bring you joy. Listen now wherever you get your podcasts, visit AmericanGroundRadio.com, and join the conversation at 866-AGR-1776!See omnystudio.com/listener for privacy information.

Finding deals is a math game.All deal sources have their place. At my acquisition company, we use a lot of lead sources. But in this podcast episode, I want to shine light on one: PPC (pay per click). Is it worth? Well, here are some numbers: It takes us about 60 cold leads to land one contract when COLD CALLING.PPC? About 8-12.Sounds better?Well, it's all about perspective. All lead methods have their place.Tune into this episode to discover if PPC has its place for you.And you'll also discover:... how to get to deals faster than everyone else... how to self-audit to find the real problem in your business... who shouldn't use PPC... when to measure your marketing: 2 months? 12 months?PPC, cold calling, and lead gen are only one piece of the pie in real estate.In our membership Runway, we go through all the avenues needed to build a successful real estate business no matter the market. Everything from leads, to follow-up, to scaling, contractors, deal analysis, to assets, management, and more.Plus, a community of active investors is there to help youAlong with daily coaching.Check out Runway: https://www.7figureflipping.com/runwayIf you want to work with Bateman Collective, click the link here:https://batemancollective.com/Or you can reach out directly to Glen at gpetersen@batemancollective.comCatch you on the next episode!LINKS & RESOURCES7 Figure Flipping UndergroundIf you want to learn how to make money flipping and wholesaling houses without risking your life savings or "working weekends" forever... this book is for YOU. It'll take you from "complete beginner" to closing your first deal or even your next 10 deals without the bumps and bruises most people pick up along the way. If you've never flipped a house before, you'll find step-by-step instructions on everything you need to know to get started. If you're already flipping or wholesaling houses, you'll find fast-track secrets that will cut years off your learning curve and let you streamline your operations, maximize profit, do MORE deals, and work LESS. CLICK HERE: https://hubs.ly/Q01ggDSh0 7 Figure RunwayFollow a proven 5-step formula to create consistent monthly income flipping and wholesaling houses, then turn your active income into passive cash flow and create a life of freedom. 7 Figure Runway is an intensive, nothing-held-back mentoring group for real estate investors who want to build a "scalable" business and start "stacking" assets to build long-term wealth. Get off-market deal sourcing strategies that work, plus 100% purchase and renovation financing through our built-in funding partners, a community of active investors who will support and encourage you, weekly accountability sessions to keep you on track, 1-on-1 coaching, and more. CLICK HERE: https://www.7figureflipping.com/runway Connect with us on Facebook and Instagram: @7figureflipping Hosted on Acast. See acast.com/privacy for more information.

She's walked the runway at New York Fashion Week, won titles like Miss Mt. Rushmore, and may soon have a documentary made about her life. But just a few years ago, Danica Miller was on a very different path.At just 13, she entered treatment for the first time, struggling with an addiction to inhalants. That struggle deepened over the years, leading to harder drugs, including meth, and at 19, a prison sentence after assaulting a law enforcement officer while intoxicated. With a felony on her record, rebuilding her life wasn't easy.After years of addiction and setbacks, Danica found her way to recovery, a journey shaped by pain, but also resilience. In this episode of Grieving Out Loud, she shares her story, showing that even in the darkest moments, change is possible, and how she's turned her past into something that now helps others.Learn more and follow Danica's Thrive Tribe group on Facebook here.Related episodes:The Dandelion in the WindowThe Voice You Knew — The Story You Didn'tDr. Sophie Two Hawk on Healing Native Communities from Addiction and TraumaSend us Fan MailBehind every number is a story of a life cut short, a family shattered, and a community devastated.They were...daughterssonsmothersfathersfriendswiveshusbandscousinsboyfriendsgirlfriends.They were More Than Just A Number. Support the showConnect with AngelaFollow Grieving Out LoudFollow Emily's HopeRead Angela's BlogSubscribe to Grieving Out Loud/Emily's Hope UpdatesSuggest a GuestFor more episodes and information, just go to our website, emilyshope.charityWishing you faith, hope and courage!Podcast producers:Casey Wonnenberg King & Kayli Fitz

Summer scheduling chaos is in full swing as Dylan and Max talk vacation bidding wizardry, Teterboro's RNAV to Runway 1, NDB war stories, New York hotel-room misery, and a suspiciously affectionate airline lobby ritual. In the Mailbag, they tackle foreign pilots at U.S. carriers, terrifying hotel van rides, AI app-building tools, and a listener plea to stop stepping on each other's punchlines. For Flight Advice, they answer a 300-hour CFI wondering how to build an interesting aviation career while still protecting family life, QOL, and future seniority. TankerBot AI in Business Aviation LinkedIn Group Show Notes 0:00 Intro & Pagers 4:59 Vacation Slide 8:53 New RNAV Approach 15:02 Max's Musings & Kissing Conundrum 23:25 Carbon Cub Jacket 26:35 News: 737 Production 31:40 Reviews & Comments 33:57 Mailbag 44:06 Flight Advice Our Sponsors Tim Pope, CFP® — Tim is both a CERTIFIED FINANCIAL PLANNER™ and a pilot. His practice specializes in aviation professionals and aviation 401k plans, helping clients pursue their financial goals by defining them, optimizing resources, and monitoring progress. Click here to learn more. Also check out The Pilot's Portfolio Podcast. Advanced Aircrew Academy — Enables flight operations to fulfill their training needs in the most efficient and affordable way—anywhere, at any time. They provide high-quality training for professional pilots, flight attendants, flight coordinators, maintenance, and line service teams, all delivered via a world-class online system. Click here to learn more. Raven Careers — Helping your career take flight. Raven Careers supports professional pilots with resume prep, interview strategy, and long-term career planning. Whether you're a CFI eyeing your first regional, a captain debating your upgrade path, or a legacy hopeful refining your application, their one-on-one coaching and insider knowledge give you a real advantage. Click here to learn more. The AirComp Calculator™ is business aviation's only online compensation analysis system. It can provide precise compensation ranges for 14 business aviation positions in six aircraft classes at over 50 locations throughout the United States in seconds. Click here to learn more. Vaerus Jet Sales — Vaerus means right, true, and real. Buy or sell an aircraft the right way, with a true partner to make your dream of flight real. Connect with Brooks at Vaerus Jet Sales or learn more about their DC-3 Referral Program. Harvey Watt — Offers the only true Loss of Medical License Insurance available to individuals and small groups. Because Harvey Watt manages most airlines' plans, they can assist you in identifying the right coverage to supplement your airline's plan. Many buy coverage to supplement the loss of retirement benefits while grounded. Click here to learn more. VSL ACE Guide — Your all-in-one pilot training resource. Includes the most up-to-date Airman Certification Standards (ACS) and Practical Test Standards (PTS) for Private, Instrument, Commercial, ATP, CFI, and CFII. 21.Five listeners get a discount on the guide—click here to learn more. ProPilotWorld.com — The premier information and networking resource for professional pilots. Click here to learn more.   Feedback & Contact Have feedback, suggestions, or a great aviation story to share? Email us at info@21fivepodcast.com. Check out our Instagram feed @21FivePodcast for more great content (and our collection of aviation license plates). The statements made in this show are our own opinions and do not reflect, nor were they under any direction of any of our employers.

Are you making business decisions based on facts, or are you guessing and hoping things will work out? In this episode, I'm talking about how to build a six-month runway for your interior design business. This is one of the simplest ways to understand what it really costs to keep your business running and whether you have the financial stability to make decisions with confidence. I walk through the four cost buckets every designer should know: fixed costs, variable costs, invisible costs, and future costs. I also share how to calculate your monthly run rate, why paying yourself needs to be included, and how to compare your six-month runway number to what you actually have in the bank and in secured revenue. I share how to look at your business finances in a practical, non-intimidating way so you can plan ahead, prepare for slower seasons, and make better decisions about hiring, spending, scaling, and saying yes or no to projects.   Episode Resources: Know your Numbers | Part 1 Understanding your Project Profitability with Merilee Wright Know your Numbers | Part 2 What it costs to run your business with Merilee Wright   This episode is sponsored by Programa. Programa is project management software built specifically for interior designers. It's designed to save you hours every week and reduce the errors that come from managing projects across scattered documents and systems. Use code RBD25 for 25% off annual Programa plans. Click to learn more.  

On June 3, 2015, an Ana flight is trying to take off out of Naha Airport, but they never get off the ground. What caused this flight to abruptly end their take off. Find photos and sources for this episode on our website:www.hardlandingspodcast.comSupport us on Patreon:www.patreon.com/hardlandingspodcast

We pinky promised that we'd replace Oscar as a co-host and WE DID IT. For this week, at least... Rachel Bloom joins Mano to recap this final, explosive week of the pink bracket! You can follow Rachel on Instagram @racheldoesstuff and TikTok @rachelbloom. And you can SEE her in Stop! That! Train! out on (say it with us) June 12. Head over to Patreon.com/DragHerPodcast for full video and weekly bonus episodes. We just dropped a countdown of the Top 10 Most Accidentally Funny Looks on the Runway with Nicole Byer. And we've got merch at goodget.xyz/store! Mano's on Instagram ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@manoagapion⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Oscar's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@ozzymo⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and Good Get's⁠⁠ ⁠@goodgetproductions⁠. Drag Her! is hosted and executive produced by Mano Agapion and Oscar Montoya. Our executive producers for Good Get are Erica Getto and Myrriah Gossett. Drag Her! is a Good Get Production. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Episode 95 - One of the most inspiring creatives in the industry, Dr Alex Box, joins us on the podcast to discuss working in beauty and fashion and how AI and social media are impacting the industry. This is part one of two. *This episode was recorded in April 2025Follow Alex BoxV-MeticsSend us a message!Follow us on InstagramWe Speak BeautyLottieLindsey

June is officially joy month at Chasing Brighter — and what better way to kick it off than with one of our favorite subjects: fashion. In this Superwoman Diaries episode, Jessica and Kelly break down the summer 2026 fashion trends worth paying attention to, the ones you can skip, and the ones you're probably already wearing without even knowing you're trendy. No pressure, no closet overhaul required. This is a wear-what-brings-you-joy conversation. Free Resource

What does it actually look like to leave a stable corporate job and go full-time as a creator? In this episode I sit back down with David, a returning guest and acrylic paint pouring artist who just walked away from his job as a product owner at a software engineering firm. Here's the part nobody says out loud: he's currently making three to four times LESS than he did at his last interview on the show. And he'd do it again in a heartbeat. About David: David is an acrylic paint pouring artist and full-time creator. What started as a blog in 2019 became a YouTube channel that now pulls in thousands of views per video (with a couple approaching a million), and after seven years of building on the side, he recently left his role as a product owner at a software engineering firm to go all-in. He's launching an AI-built app for acrylic pourers and building out a course and community alongside his channel. Connect With David: YouTube Channel   What We Offer Creators Join Creator Communities. A place to gather with other creators every single day. This provides access to Our Private Discord Server, Monthly Mastermind Group, and MORE!  Hire Dusty To Be Your YouTube Coach YouTube Channel Reviews (Audit): Get a 7-10 minute personalized video review of your YouTube channel with honest, actionable feedback for just $50. Subscribe to our weekly newsletter: Each week I document what I'm doing in my business and creative journey, share new things I've discovered, mistakes I've made, and much more! All Tools Mentioned On The Show: The Ultimate Entrepreneurs Resource. This is the spreadsheet where I keep all of the tools mentioned by all the guests on the podcast. Follow The Show: Facebook /// X /// YouTube /// Instagram

In the AI race, some of Adobe's closest partners are also its biggest competitors. So how does it decide who to work with? Sahil Gupta is the Senior Director of Partnerships at Adobe, where he leads technology partnerships with the biggest names in AI including OpenAI, Anthropic, Google Cloud and NVIDIA. In this episode Liam sits down with Sahil to break down how these partnerships actually come together, what Adobe announced at Adobe Summit, how you navigate working with a partner you also compete with, and what the future of work really looks like from someone sitting at the center of the AI ecosystem. Topics covered: How Adobe structures partnerships with OpenAI, Anthropic, Google and Microsoft and surfaces its agentic capabilities inside each The NVIDIA partnership including 3D digital twins, agent governance and the next generation of Firefly models How you co-innovate with a partner like Anthropic that also competes with you on design tools The difference between working with a 30 year partner like IBM and a company only a few years old Why Adobe brings over 30 models including startups like Runway into Firefly What the future of work looks like and the radiology lesson from NVIDIA's Jensen Huang Episode Timestamps: 00:00 Intro 00:36 Competing and co-innovating with partners 01:22 How Sahil kept ending up at the center of industry moments 03:01 What a Senior Director of Partnerships actually does 04:03 Where partnerships actually come from 06:24 What Adobe announced at Summit 07:40 The NVIDIA partnership explained 10:28 Navigating partnerships with companies you also compete with 12:06 Working with 30 year partners versus brand new ones 13:43 What partnerships Adobe is building toward next 15:23 Why everything comes back to customer experience 17:54 How Sahil ended up in partnerships 19:27 The future of work and the radiology lesson 22:15 Why do you do what you do Partner Links: Upgrade your AI toolkit: https://www.theaireport.ai/ai-executive-pass Subscribe to our free newsletter: https://newsletter.theaireport.ai/subscribe Join the community: https://community.theaireport.ai/checkout/the-ai-report-welcome-gift?coupon_code=WRTH Learn more about your ad choices. Visit megaphone.fm/adchoices

The deadliest disaster in aviation history was not caused by a mechanical failure… or even by the fog alone.In 1977, two Boeing 747s collided on a runway at Los Rodeos Airport in Tenerife, killing 583 people. But the real story is far more unsettling. Visibility collapsed. Communication degraded. Assumptions survived. And piece by piece, an entire system drifted out of synchronization.This episode examines how trained professionals, working inside a crowded and increasingly uncertain environment, slowly lost the same understanding of what was happening around them.Not just a disaster story. A lesson in how clarity quietly disappears.If you enjoy thoughtful disaster analysis, hidden systems failures, aviation history, and stories that outsmart the obvious, subscribe and join us.#Tenerife #AviationHistory #PlaneCrash #DisasterDocumentary #AnOunceCHAPTERS / TIMELINE00:00 — The Bomb That Started Everything 02:08 — Diversion to Tenerife 02:28 — An Airport Beyond Its Limits 04:31 — Fog and Fragmented Awareness 06:41 — Pressure Inside the Cockpit 08:16 — Assumptions Begin Taking Over 09:57 — Radio Confusion in the Fog 11:47 — “Is He Not Clear, Then?” 13:17 — Collision on the Runway 14:52 — The Lessons Written in Blood 16:47 — Not Just Fog 18:28 — An OunceCOMPANION EPISODE RECOMMENDATIONThe Attack That Wasn't | When the System Was Wrong https://youtu.be/tyhanM96jAYWhy: Both episodes examine:systems degradation incomplete information dangerous assumptions professionals operating inside uncertainty catastrophic risk emerging from fragmented awareness TAGSTenerife disaster, Tenerife airport disaster, deadliest aviation disaster, aviation history, plane crash documentary, KLM 4805, Pan Am 1736, Tenerife runway collision, aviation disaster analysis, aircraft collision, aviation documentary, disaster documentary, aviation safety, Crew Resource Management, CRM aviation, runway incursion, fog disaster, airport disaster, historical disasters, systems failure, communication failure, disaster analysis, airplane documentary, Boeing 747 disaster, Los Rodeos airport, An Ounce Podcast, aviation accidents, air traffic control, aviation mysteries, aviation tragedy

I am so thrilled to be joined on today's Juicy Scoop by the hilarious Jamie Lee! She is an Emmy winning writer for the hit show Ted Lasso, and you also know her incredible work as an actress and writer on Crashing and so many other amazing projects. Today, Jamie is here to dive into her latest one-woman show, where she investigates the surprising death of a friend from when she was 20 years old and sets out to solve the mystery of what actually happened. Plus, we are getting into the future of television writing and how AI might impact the industry, breaking down the drama surrounding Brad Pitt's kids dropping his last name (and whether he'll start a new family with his younger girlfriend), and dissecting why celebrities weren't allowed to wear heels on the runway at the Sports Illustrated fashion show. Subscribe to my new show Juicy Crimes!: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bit.ly/juicycrimes⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Stand Up Tickets and info: ⁠https://heathermcdonald.net/⁠ Subscribe to Juicy Scoop with Heather McDonald and get extra juice on Patreon: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bit.ly/JuicyScoopPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠https://www.patreon.com/cw/juicyscoop⁠ Watch the Juicy Scoop On YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@JuicyScoop⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Shop Juicy Scoop Merch: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://juicyscoopshop.com/?srsltid=AfmBOopTZFUvAeokrJJ6dQ5wuAW1T3nssO6pHk47u7KymJUBtBgKCvfX⁠ Follow Me on Social Media: Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/heathermcdonald/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ TikTok: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.tiktok.com/@heathermcdonald⁠ YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@HeatherMcDonaldOfficial Learn more about your ad choices. Visit podcastchoices.com/adchoices

Today, we are breaking down Toast, a name we have covered before but are revisiting because the story has changed enough to be worth telling again. Most listeners will have tapped a Toast terminal without thinking much about the business behind it.  Our guest is Sean Barrett, founder, managing partner, and chief investment officer of Counter Global, who holds Toast as one of his largest positions and walks us through how a restaurant point of sale company became the operating system that runs the restaurant. He argues that Toast is best understood as the operating system for the restaurant rather than a payments terminal with software attached, and that the business grows as fast and as profitably as it does because the company spent years building purpose-built hardware, a multi-tenant software platform, and a sales force on the ground before it moved into new markets across grocery, enterprise, hospitality, and international.  We also discuss why a business winning roughly half of new restaurant openings in the United States still trades at a multiple that looks closer to a mature company than a category killer. Please enjoy this Breakdown of Toast. For the full show notes, transcript, and links to the best content to learn more, check out the episode page⁠⁠⁠⁠⁠⁠⁠ here.⁠⁠⁠⁠⁠⁠⁠ ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- This episode is brought to you by⁠⁠⁠⁠ ⁠Portrait Analytics⁠⁠⁠⁠⁠ - your centralized resource for AI-powered idea generation, thesis monitoring, and personalized report building. Built by buy-side investors, for investment professionals. We work in the background, helping surface stock ideas and thesis signposts to help you monetize every insight. In short, we help you understand the story behind the stock chart, and get to "go, or no-go" 10x faster than before. Sign-up for a free trial today at ⁠⁠⁠⁠⁠portraitresearch.com⁠⁠⁠⁠⁠ ----- Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps (00:00:00) Welcome to Business Breakdowns (00:03:19) Toast Business Overview & Financials (00:06:31) Recurring vs. Reoccurring Gross Profit (00:07:39) Nuance on Revenue Semantics (00:10:05) Transformation from 2020 to Today (00:11:51) Full Product Offering Overview (00:14:13) Revenue Model — Recurring vs. Transaction-Based (00:16:08) Net Take Rate (00:17:22) Software Side of Revenue (00:18:49) Hardware & SaaSpocalypse Connection (00:22:31) AI Offering & What They're Shipping (00:27:01) Impact of 8% Revenue Uplift for Restaurants (00:27:12) Competitive Landscape (00:32:44) Switching & Churn Dynamics (00:34:52) Competitive Advantage & Moat (00:37:43) Management Team & Culture (00:39:57) $10B Gross Profit TAM & Runway (00:44:01) Valuation Approach (00:45:53) Key Risks (00:48:32) Key Lessons

Mindy Scheier didn't wait for the fashion industry to include her son; she changed it herself. The founder of Runway of Dreams joins us to talk about her work as a pioneer in the adaptive clothing space, the psychology of getting dressed, and why the group any of us could join at any moment deserves a seat at the trend table. Connect with Mindy:@MindyScheier @RunwayofDreams@GamutManagementRunwayofDreams.orgMindy's Ted TalkConnect with Behavior BitchesInsta: @behaviorbitchespodcastFacebook: Behavior Bitches PodcastWebsite: BehaviorBitches.comContact Us: For podcast inquiries, episode ideas, or just to say hi, email us at behaviorbitches@studynotesaba.com Leave us a 5-star review in the Apple Podcast App so we can read it to everyone during our episodes and make us super happy!Looking for BCBA Exam Prep or CEUs?• Whether you need help passing the BCBA exam or are looking to earn CEUs, Study Notes ABA has you covered. Check out our website for comprehensive exam prep materials, prep courses, and CEUs• Test Prep: StudyNotesABA.com• CEUs: CEU.StudyNotesABA.com• PairABA: PairABA.com

"Life has not been easy. Life, for the better part of the past few years, has been very hard and messy and stressful and exhausting. And I will give myself the tiniest bit of credit for surviving it. And for finding a way to be happy." The month of May brings up all kinds of stuff for me. A birthday, Mother's Day, all of the school and extracurricular activities for Annie — and the anniversaries. In May 2023, my life was upended when I was diagnosed with stage 1 invasive ductal carcinoma: breast cancer. Exactly two years later, I was diagnosed with stage IV metastatic breast cancer that had spread to my bones. So yeah, May hits highs, lows, and grey spaces. Fortunately, there's nothing tragic to report in this episode! No status update, no big diagnosis reveal. Just some musings on my April vacation week with Annie, my Ali on the RunWAY debut, and how I'm feeling heading into 41. Plus, my thoughts on legacies and the mark we leave on the world while we're here. (Thank you for being here. I'm still here!) SPONSOR: Shokz! The official headphone of the Boston Marathon! Use code ALI for $10 off your next Shokz purchase. (I love the Open Run Pro 2.) Follow Ali: Instagram @aliontherun1 Subscribe to the newsletter Join the Facebook group Support on Patreon SUPPORT the Ali on the Run Show! If you're enjoying the show, please subscribe and leave a rating and review on Apple Podcasts. Spread the run love. And if you liked this episode, share it with your friends!

The Devil Wears Prada 2 reunites Anne Hathaway, Meryl Streep, Emily Blunt and Stanley Tucci 20 years after the beloved original film. The sequel finds Andy as a mid-career reporter who gets an unexpected opportunity to lead the features department at Runway and working for Miranda Priestly, the worst boss she ever had. But does the sequel capture the magic of the original film?Follow Pop Culture Happy Hour on Letterboxd at letterboxd.com/nprpopcultureSee pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy