Podcasts about supply chain issues

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In this episode, Noel sits down with David Mytton, founder and CEO of Arcjet, to unpack the React2Shell vulnerability and why it became such a serious remote code execution risk for apps using React server components and Next.js. They explain how server-side features introduced in React 19 changed the attack surface, why cloud providers leaned on WAF mitigation instead of instant patching, and what this incident reveals about modern JavaScript supply chain risk. The conversation also covers dependency sprawl, rushed patches, and why security as a feature needs to start long before production. Links X: https://x.com/davidmytton Blog: https://davidmytton.blog Resources Multiple Threat Actors Exploit React2Shell: https://cloud.google.com/blog/topics/threat-intelligence/threat-actors-exploit-react2shell-cve-2025-55182 We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Fill out our listener survey (https://t.co/oKVAEXipxu)! https://t.co/oKVAEXipxu Let us know by sending an email to our producer, Elizabeth, at elizabeth.becz@logrocket.com (mailto:elizabeth.becz@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Check out our newsletter (https://blog.logrocket.com/the-replay-newsletter/)! https://blog.logrocket.com/the-replay-newsletter/ Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understanding where your users are struggling by trying it for free at LogRocket.com. Try LogRocket for free today. (https://logrocket.com/signup/?pdr) Chapters

In this episode of Atlanta Business Radio, Lee interviews Shuron Hall, a business banking executive at Bank of America Atlanta, about the annual Business Owner Report. They discuss key findings on labor shortages, supply chain disruptions, inflation, and the growing adoption of AI and digital tools among small and mid-sized businesses. Sharon highlights how AI […]

October 20, 2025 ~ Paul Eisenstein, editor of Headlight.news, joins Kevin to discuss how the Auto Supply chain issues are continuing and what does it mean for the Michigan auto industry. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode of Organic Matters, host Hannah Quinn-Mulligan interviews Pat O'Sullivan, the CEO of gourmet catering company Master Chefs in Limerick. Pat discusses buying 20 acres of land to establish Ellan farm and grow organic vegetables for his catering business, and talks about his plans for the future, creating his own on-site processing facilities on the farm and connecting his chefs with food production. He also speaks about a bio district that is currently being established in the Mid West. Pat considers that this initiative is not only of value to his business, in order to buy more local organic produce, but also for the wider community of organic producers, as well as the tourism and hospitality sector in the area.

Navigating Future Uncertainties: Gold, AI, and Crisis Investing with Doug and Matt In this episode, Doug and Matt tackle critical questions from their community concerning the future of gold ownership in a world trending towards digital currencies, the implications of AI advancements, and the shifting landscape of international finance. They discuss practical solutions for protecting and growing your wealth, including investing in high-tech stocks and crisis programs, and the importance of international diversification. They also touch on geopolitical conflicts, supply chain disruptions, and the shifting buyer base in Uruguay as a potential 'Plan B' destination. Tune in for a detailed foresight into these vital issues and insights on safeguarding your financial future. 00:00 Introduction and Time Constraints 00:08 Owning Physical Gold: Practical Considerations 03:03 International Banking and Upcoming Conference 06:31 Supply Chain Issues and Economic Chaos 11:51 Future Predictions: AI, Robots, and Economic Shifts 18:14 Investment Strategies and Crisis Investing 24:05 Uruguay's Real Estate Market and Diversification 26:08 Geopolitical Dynamics and Strongman Politics 30:40 Conclusion and Final Thoughts

In the final instalment of The Inspired Series with Luke Mangan, recorded live at Foodservice Australia 2025 and presented by Straight To The Source, chef and restaurateur Ross Lusted pulls back the curtain on the realities of the modern food industry. From reinventing his career path to leading hotel kitchens, Ross shares insights on leadership, innovation, resilience, staffing, and what it takes to survive (and thrive) in a changing restaurant landscape. Takeaways Ross Lusted transitioned from dentistry to the culinary arts. Melbourne's market-centric dining scene is vibrant and diverse. Hotels offer a unique journey in hospitality compared to standalone restaurants. Innovative cooking methods are key to restaurant success. Partnerships in the restaurant industry can enhance opportunities. Staffing challenges are prevalent across the hospitality sector. Supply chain issues impact the availability of quality ingredients. The restaurant market is competitive, requiring resilience and adaptability. Understanding market demands is crucial for pricing strategies. Opening a restaurant during tough times can lead to future success. Sound bites "I was going to be a dentist." "I love the idea of restaurants." "We won a few awards." Chapters 00:00 Introduction to the Culinary Journey 01:08 Exploring Melbourne's Culinary Scene 02:18 From Dentistry to Culinary Arts 03:42 The Allure of Hotel Dining 04:46 Building Successful Restaurants 06:11 Innovative Cooking Methods at Woodcut 08:23 Navigating Partnerships in the Restaurant Industry 09:39 Challenges in Staffing and Work Ethic 11:00 The Impact of Supply Chain Issues 13:07 Resilience in the Restaurant Business culinary journey, Melbourne dining, hotel dining, restaurant industry, innovative cooking, staffing challenges, supply chain issues, hospitality, chef interviews, Australian cuisineSee omnystudio.com/listener for privacy information.

Shane McMurray - How do tariffs and supply chain issues affect wedding businesses?What if your costs doubled overnight? What happens to your business when tariffs and supply chain issues change in a heartbeat? Are you relying too much on a single supplier? In this episode, I talk about the unpredictable nature of tariffs, how they impact different segments of the wedding industry—from bridal shops to service providers—and what proactive steps you can take, like contract updates and diversifying your supply chain, to stay resilient in uncertain times.Listen to this new episode for practical ideas on protecting your business, managing costs, and preparing your contracts for sudden market shifts.About Shane:Shane helps businesses grow profits, attract qualified leads, refine pricing, close more sales, and uncover key opportunities using unbiased, independent research on the wedding market. His work has been featured in The New York Times, Forbes, NPR, and more, and is trusted by government agencies, investors, and researchers. With a B.S. in IT, an MBA in E-Business, and over 30 years' experience in data and 20 years in wedding industry research, he deliver insights that identify your core customer and sharpen your marketing strategy.Link: https://wedding.report/Contact Shane: LinkedIn - Shane McMurrayText or call 520-906-8025If you have any questions about anything in this, or any of my podcasts, or have a suggestion for a topic or guest, please reach out directly to me at Alan@WeddingBusinessSolutions.com or visit my website Podcast.AlanBerg.com Please be sure to subscribe to this podcast and leave a review (thanks, it really does make a difference). If you want to get notifications of new episodes and upcoming workshops and webinars, you can sign up at www.ConnectWithAlanBerg.com  View the full transcript on Alan's site: https://alanberg.com/blog/Are you going to Wedding MBA? Use the promo code - Alan - to save $20 off your tickets, at www.WeddingMBA.com And don't worry, if you can't use your tickets this year, they're transferrable or you can hold them to use next year. I'm Alan Berg. Thanks for listening. If you have any questions about this or if you'd like to suggest other topics for "The Wedding Business Solutions Podcast" please let me know. My email is Alan@WeddingBusinessSolutions.com. Look forward to seeing you on the next episode. Thanks. Listen to this and all episodes on Apple Podcast, YouTube or your favorite app/site: Apple Podcast: http://bit.ly/weddingbusinesssolutions YouTube: www.WeddingBusinessSolutionsPodcast.tv Spotify: https://spoti.fi/3sGsuB8 Stitcher: http://bit.ly/wbsstitcher Google Podcast: http://bit.ly/wbsgoogle iHeart Radio: https://ihr.fm/31C9Mic Pandora: http://bit.ly/wbspandora ©2025 Wedding Business Solutions LLC & AlanBerg.com

Jacob and Nikhil sit down with Otto Sipe. Otto is the CEO and Co-Founder of Photon Health, which enables patients to select their own pharmacies with price and inventory transparency. The company has raised over $16 million from investors including Flare Capital Partners and Notation Capital. They discuss where pharmacies and PBMs are headed, the evolution of E-Prescribing, the impact of GLP-1s & AI, and more. (0:00) Intro(0:51) History and Evolution of E-Prescribing(3:02) Challenges in Current E-Prescribing Systems(6:28) Photon Health's Innovative Approach(8:17) Patient and Provider Behavior Changes(11:21) Pharmacy Industry Landscape and Future(13:43) Interactions with PBMs and Market Dynamics(16:48) Future of PBMs and Drug Pricing(20:38) Quality and Marketplace Experience in Pharmacies(23:30) Advising Independent Pharmacies for Future Success(24:24) Challenges and Strategies in Retail Pharmacy(25:45) Pharmacy Economics and Supply Chain Issues(30:21) The Role and Potential of Pharmacists(36:01) AI in Pharmacy: Photon's Approach(38:28) Quickfire Out-Of-Pocket: https://www.outofpocket.health/

In this episode, the hosts engage in a lively discussion about their current wristwatches, sharing personal experiences with watch performance and maintenance. They delve into the intricacies of custom watch building, highlighting the challenges and joys of creating unique timepieces. The conversation shifts to the automotive community, where they address supply chain issues exacerbated by the COVID-19 pandemic, and how these changes have affected consumer expectations and business practices. The episode concludes with reflections on the importance of trust and relationships in the current market landscape. In this conversation, the speakers discuss the challenges and frustrations associated with custom orders and the risks of pre-payment in the automotive parts industry. They highlight the importance of customer service and communication, particularly in managing expectations regarding product availability and delivery times. The discussion also touches on the impact of tariffs on consumer goods and the future of manufacturing, emphasizing the need for more domestic production and the implications for consumer choice.

Evan Conrad, co-founder of SF Compute, joined us to talk about how they started as an AI lab that avoided bankruptcy by selling GPU clusters, why CoreWeave financials look like a real estate business, and how GPUs are turning into a commodities market. Chapters: 00:00:05 - Introductions 00:00:12 - Introduction of guest Evan Conrad from SF Compute 00:00:12 - CoreWeave Business Model Discussion 00:05:37 - CoreWeave as a Real Estate Business 00:08:59 - Interest Rate Risk and GPU Market Strategy Framework 00:16:33 - Why Together and DigitalOcean will lose money on their clusters 00:20:37 - SF Compute's AI Lab Origins 00:25:49 - Utilization Rates and Benefits of SF Compute Market Model 00:30:00 - H100 GPU Glut, Supply Chain Issues, and Future Demand Forecast 00:34:00 - P2P GPU networks 00:36:50 - Customer stories 00:38:23 - VC-Provided GPU Clusters and Credit Risk Arbitrage 00:41:58 - Market Pricing Dynamics and Preemptible GPU Pricing Model 00:48:00 - Future Plans for Financialization? 00:52:59 - Cluster auditing and quality control 00:58:00 - Futures Contracts for GPUs 01:01:20 - Branding and Aesthetic Choices Behind SF Compute 01:06:30 - Lessons from Previous Startups 01:09:07 - Hiring at SF Compute Chapters 00:00:00 Introduction and Background 00:00:58 Analysis of GPU Business Models 00:01:53 Challenges with GPU Pricing 00:02:48 Revenue and Scaling with GPUs 00:03:46 Customer Sensitivity to GPU Pricing 00:04:44 Core Weave's Business Strategy 00:05:41 Core Weave's Market Perception 00:06:40 Hyperscalers and GPU Market Dynamics 00:07:37 Financial Strategies for GPU Sales 00:08:35 Interest Rates and GPU Market Risks 00:09:30 Optimal GPU Contract Strategies 00:10:27 Risks in GPU Market Contracts 00:11:25 Price Sensitivity and Market Competition 00:12:21 Market Dynamics and GPU Contracts 00:13:18 Hyperscalers and GPU Market Strategies 00:14:15 Nvidia and Market Competition 00:15:12 Microsoft's Role in GPU Market 00:16:10 Challenges in GPU Market Dynamics 00:17:07 Economic Realities of the GPU Market 00:18:03 Real Estate Model for GPU Clouds 00:18:59 Price Sensitivity and Chip Design 00:19:55 SF Compute's Beginnings and Challenges 00:20:54 Navigating the GPU Market 00:21:54 Pivoting to a GPU Cloud Provider 00:22:53 Building a GPU Market 00:23:52 SF Compute as a GPU Marketplace 00:24:49 Market Liquidity and GPU Pricing 00:25:47 Utilization Rates in GPU Markets 00:26:44 Brokerage and Market Flexibility 00:27:42 H100 Glut and Market Cycles 00:28:40 Supply Chain Challenges and GPU Glut 00:29:35 Future Predictions for the GPU Market 00:30:33 Speculations on Test Time Inference 00:31:29 Market Demand and Test Time Inference 00:32:26 Open Source vs. Closed AI Demand 00:33:24 Future of Inference Demand 00:34:24 Peer-to-Peer GPU Markets 00:35:17 Decentralized GPU Market Skepticism 00:36:15 Redesigning Architectures for New Markets 00:37:14 Supporting Grad Students and Startups 00:38:11 Successful Startups Using SF Compute 00:39:11 VCs and GPU Infrastructure 00:40:09 VCs as GPU Credit Transformators 00:41:06 Market Timing and GPU Infrastructure 00:42:02 Understanding GPU Pricing Dynamics 00:43:01 Market Pricing and Preemptible Compute 00:43:55 Price Volatility and Market Optimization 00:44:52 Customizing Compute Contracts 00:45:50 Creating Flexible Compute Guarantees 00:46:45 Financialization of GPU Markets 00:47:44 Building a Spot Market for GPUs 00:48:40 Auditing and Standardizing Clusters 00:49:40 Ensuring Cluster Reliability 00:50:36 Active Monitoring and Refunds 00:51:33 Automating Customer Refunds 00:52:33 Challenges in Cluster Maintenance 00:53:29 Remote Cluster Management 00:54:29 Standardizing Compute Contracts 00:55:28 Unified Infrastructure for Clusters 00:56:24 Creating a Commodity Market for GPUs 00:57:22 Futures Market and Risk Management 00:58:18 Reducing Risk with GPU Futures 00:59:14 Stabilizing the GPU Market 01:00:10 SF Compute's Anti-Hype Approach 01:01:07 Calm Branding and Expectations 01:02:07 Promoting San Francisco's Beauty 01:03:03 Design Philosophy at SF Compute 01:04:02 Artistic Influence on Branding 01:05:00 Past Projects and Burnout 01:05:59 Challenges in Building an Email Client 01:06:57 Persistence and Iteration in Startups 01:07:57 Email Market Challenges 01:08:53 SF Compute Job Opportunities 01:09:53 Hiring for Systems Engineering 01:10:50 Financial Systems Engineering Role 01:11:50 Conclusion and Farewell

We are calling for the world's best AI Engineer talks for AI Architects, /r/localLlama, Model Context Protocol (MCP), GraphRAG, AI in Action, Evals, Agent Reliability, Reasoning and RL, Retrieval/Search/RecSys , Security, Infrastructure, Generative Media, AI Design & Novel AI UX, AI Product Management, Autonomy, Robotics, and Embodied Agents, Computer-Using Agents (CUA), SWE Agents, Vibe Coding, Voice, Sales/Support Agents at AIEWF 2025! Fill out the 2025 State of AI Eng survey for $250 in Amazon cards and see you from Jun 3-5 in SF!Coreweave's now-successful IPO has led to a lot of questions about the GPU Neocloud market, which Dylan Patel has written extensively about on SemiAnalysis. Understanding markets requires an interesting mix of technical and financial expertise, so this will be a different kind of episode than our usual LS domain.When we first published $2 H100s: How the GPU Rental Bubble Burst, we got 2 kinds of reactions on Hacker News:* “Ah, now the AI bubble is imploding!”* “Duh, this is how it works in every GPU cycle, are you new here?”We don't think either reaction is quite right. Specifically, it is not normal for the prices of one of the world's most important resources right now to swing from $1 to $8 per hour based on drastically inelastic demand AND supply curves - from 3 year lock-in contracts to stupendously competitive over-ordering dynamics for NVIDIA allocations — especially with increasing baseline compute needed for even the simplest academic ML research and for new AI startups getting off the ground.We're fortunate today to have Evan Conrad, CEO of SFCompute, one of the most exciting GPU marketplace startups, talk us through his theory of the economics of GPU markets, and why he thinks CoreWeave and Modal are well positioned, but Digital Ocean and Together are not.However, more broadly, the entire point of SFC is creating liquidity between GPU owners and consumers and making it broadly tradable, even programmable:As we explore, these are the primitives that you can then use to create your own, high quality, custom GPU availability for your time and money budget, similar to how Amazon Spot Instances automated the selective buying of unused compute.The ultimate end state of where all this is going is GPU that trade like other perishable, staple commodities of the world - oil, soybeans, milk. Because the contracts and markets are so well established, the price swings also are not nearly as drastic, and people can also start hedging and managing the risk of one of the biggest costs of their business, just like we have risk-managed commodities risks of all other sorts for centuries. As a former derivatives trader, you can bet that swyx doubleclicked on that…Show Notes* SF Compute* Evan Conrad* Ethan Anderson* John Phamous* The Curve talk* CoreWeave* Andromeda ClusterFull Video PodLike and subscribe!Timestamps* [00:00:05] Introductions* [00:00:12] Introduction of guest Evan Conrad from SF Compute* [00:00:12] CoreWeave Business Model Discussion* [00:05:37] CoreWeave as a Real Estate Business* [00:08:59] Interest Rate Risk and GPU Market Strategy Framework* [00:16:33] Why Together and DigitalOcean will lose money on their clusters* [00:20:37] SF Compute's AI Lab Origins* [00:25:49] Utilization Rates and Benefits of SF Compute Market Model* [00:30:00] H100 GPU Glut, Supply Chain Issues, and Future Demand Forecast* [00:34:00] P2P GPU networks* [00:36:50] Customer stories* [00:38:23] VC-Provided GPU Clusters and Credit Risk Arbitrage* [00:41:58] Market Pricing Dynamics and Preemptible GPU Pricing Model* [00:48:00] Future Plans for Financialization?* [00:52:59] Cluster auditing and quality control* [00:58:00] Futures Contracts for GPUs* [01:01:20] Branding and Aesthetic Choices Behind SF Compute* [01:06:30] Lessons from Previous Startups* [01:09:07] Hiring at SF ComputeTranscriptAlessio [00:00:05]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel, and I'm joined by my co-host Swyx, founder of Smol AI.Swyx [00:00:12]: Hey, and today we're so excited to be finally in the studio with Evan Conrad from SF Compute. Welcome. I've been fortunate enough to be your friend before you were famous, and also we've hung out at various social things. So it's really cool to see that SF Compute is coming into its own thing, and it's a significant presence, at least in the San Francisco community, which of course, it's in the name, so you couldn't help but be. Evan: Indeed, indeed. I think we have a long way to go, but yeah, thanks. Swyx: Of course, yeah. One way I was thinking about kicking on this conversation is we will likely release this right after CoreWeave IPO. And I was watching, I was looking, doing some research on you. You did a talk at The Curve. I think I may have been viewer number 70. It was a great talk. More people should go see it, Evan Conrad at The Curve. But we have like three orders of magnitude more people. And I just wanted to, to highlight, like, what is your analysis of what CoreWeave did that went so right for them? Evan: Sell locked-in long-term contracts and don't really do much short-term at all. I think like a lot of people had this assumption that GPUs would work a lot like CPUs and the like standard business model of any sort of CPU cloud is you buy commodity hardware, then you lay on services that are mostly software, and that gives you high margins and pretty much all your value comes from those services. Not really the underlying. Compute in any capacity and because it's commodity hardware and it's not actually that expensive, most of that can be sort of on-demand compute. And while you do want locked-in contracts for folks, it's mostly just a sort of de-risk situation. It helps you plan revenue because you don't know if people are going to scale up or down. But fundamentally, people are like buying hourly and that's how your business is structured and you make 50 percent margins or higher. This like doesn't really work in GPUs. And the reason why it doesn't work is because you end up with like super price sensitive customers. And that isn't because necessarily it's just way more expensive, though that's totally the case. So in a CPU cloud, you might have like, you know, let's say if you had a million dollars of hardware in GPUs, you have a billion dollars of hardware. And so your customers are buying at much higher volumes than you otherwise expect. And it's also smaller customers who are buying at higher amounts of volume. So relative to what they're spending in general. But in GPUs in particular, your customer cares about the scaling law. So if you take like Gusto, for example, or Rippling or an HR service like this, when they're buying from an AWS or a GCP, they're buying CPUs and they're running web servers, those web servers, they kind of buy up to the capacity that they need, they buy enough, like CPUs, and then they don't buy any more, like, they don't buy any more at all. Yeah, you have a chart that goes like this and then flat. Correct. And it's like a complete flat. It's not even like an incremental tiny amount. It's not like you could just like turn on some more nodes. Yeah. And then suddenly, you know, they would make an incremental amount of money more, like Gusto isn't going to make like, you know, 5% more money, they're gonna make zero, like literally zero money from every incremental GPU or CPU after a certain point. This is not the case for anyone who is training models. And it's not the case for anyone who's doing test time inference or like inference that has scales at test time. Because like you, your scaling laws mean that you may have some diminishing returns, but there's always returns. Adding GPUs always means your model does actually get. And that actually does translate into revenue for you. And then for test time inference, you actually can just like run the inference longer and get a better performance. Or maybe you can run more customers faster and then charge for that. It actually does translate into revenue. Every incremental GPU translates to revenue. And what that means from the customer's perspective is you've got like a flat budget and you're trying to max the amount of GPUs you have for that budget. And it's very distinctly different than like where Augusto or Rippling might think, where they think, oh, we need this amount of CPUs. How do we, you know, reduce that? How do we reduce our amount of money that we're spending on this to get the same amount of CPUs? What that translates to is customers who are spending in really high volume, but also customers who are super price sensitive, who don't give a s**t. Can I swear on this? Can I swear? Yeah. Who don't give a s**t at all about your software. Because a 10% difference in a billion dollars of hardware is like $100 million of value for you. So if you have a 10% margin increase because you have great software, on your billion, the customers are that price sensitive. They will immediately switch off if they can. Because why wouldn't you? You would just take that $100 million. You'd spend $50 million on hiring a software engineering team to replicate anything that you possibly did. So that means that the best way to make money in GPUs was to do basically exactly what CoreWeave did, which is go out and sign only long-term contracts, pretty much ignore the bottom end of the market completely, and then maximize your long-term contracts. With customers who don't have credit risk, who won't sue you, or are unlikely to sue you for frivolous reasons. And then because they don't have credit risk and they won't sue you for frivolous reasons, you can go back to your lender and you can say, look, this is a really low risk situation for us to do. You should give me prime, prime interest rate. You should give me the lowest cost of capital you possibly can. And when you do that, you just make tons of money. The problem that I think lots of people are going to talk about with CoreWeave is it doesn't really look like a cloud platform. It doesn't really look like a cloud provider financially. It also doesn't really look like a software company financially.Swyx [00:05:37]: It's a bank.Evan [00:05:38]: It's a bank. It's a real estate company. And it's very hard to not be that. The problem of that that people have tricked themselves into is thinking that CoreWeave is a bad business. I don't think CoreWeave is explicitly a bad business. There's a bunch of people, there's kind of like two versions of the CoreWeave take at the moment. There's, oh my God, CoreWeave, amazing. CoreWeave is this great new cloud provider competitive with the hyperscalers. And to some extent, this is true from a structural perspective. Like, they are indeed a real sort of thing against the cloud providers in this particular category. And the other take is, oh my gosh, CoreWeave is this horrible business and so on and blah, blah, blah. And I think it's just like a set of perception or perspective. If you think CoreWeave's business is supposed to look like the traditional cloud providers, you're going to be really upset to learn that GPUs don't look like that at all. And in fact, for the hyperscalers, it doesn't look like this either. My intuition is that the hyperscalers are probably going to lose a lot of money, and they know they're going to lose a lot of money on reselling NVIDIA GPUs, at least. Hyperscalers, but I want to, Microsoft, AWS, Google. Correct, yeah. The Microsoft, AWS, and Google. Does Google resell? I mean, Google has TPUs. Google has TPUs, but I think you can also get H100s and so on. But there are like two ways they can make money. One is by selling to small customers who aren't actually buying in any serious volume. They're testing around, they're playing around. And if they get big, they're immediately going to do one of two things. They're going to ask you for a discount. Because they're not going to pay your crazy sort of margin that you have locked into your business. Because for CPUs, you need that. They're going to pay your massive per hour price. And so they want you to sign a long-term contract. And so that's your other way that you can make money, is you can basically do exactly what CoreWeave does, which is have them pay as much as possible upfront and lock in the contract for a long time. Or you can have small customers. But the problem is that for a hyperscaler, the GPUs to... To sell on the low margins relative to what your other business, your CPUs are, is a worse business than what you are currently doing. Because you could have spent the same money on those GPUs. And you could have trained model and you could have made a model on top of it and then turn that into a product and had high margins from your product. Or you could have taken that same money and you could have competed with NVIDIA. And you could have cut into their margin instead. But just simply reselling NVIDIA GPUs doesn't work like your CPU business. Where you're able to capture high margins from big customers and so on. And then they never leave you because your customers aren't actually price sensitive. And so they won't switch off if your prices are a little higher. You actually had a really nice chart, again, on that talk of this two by two. Sure. Of like where you want to be. And you also had some hot takes on who's making money and who isn't. Swyx: So CoreUv locked up long-term contracts. Get that. Yes. Maybe share your mental framework. Just verbally describe it because we're trying to help the audio listeners as well. Sure. People can look up the chart if they want to. Evan: Sure. Okay. So this is a graph of interest rates. And on the y-axis, it's a probability you're able to sell your GPUs from zero to one. And on the x-axis, it's how much they'll depreciate in cost from zero to one. And then you had ISO cost curves or ISO interest rate curves. Yeah. So they kind of shape in a sort of concave fashion. Yeah. The lowest interest rates enable the most aggressive. form of this cost curve. And the higher interest rates go, the more you have to push out to the top right. Yeah. And then you had some analysis of where every player sits in this, including CoreUv, but also Together and Modal and all these other guys. I thought that was super insightful. So I just wanted to elaborate. Basically, it's like a graph of risk and the genres of places where you can be and what the risk is associated with that. The optimal thing for you to do, if you can, is to lock in long-term contracts that are paid all up front or in with a situation in which you trust the other party to pay you over time. So if you're, you know, selling to Microsoft or something or OpenAI. Which are together 77% of the revenue of CoreUv. Yeah. So if you're doing that, that's a great business to be in because your interest rate that you can pitch for is really low because no one thinks Microsoft is going to default. And like maybe OpenAI will default, but the backing by Microsoft kind of doesn't. And I think there's enough, like, generally, it looks like OpenAI is winning that you can make it's just a much better case than if you're selling to the pre-seed startup that just raised $30 million or something pre-revenue. It's like way easier to make the case that the OpenAI is not going to default than the pre-seed startup. And so the optimal place to be is selling to the maximally low risk customer for as long as possible. And then you never have to worry about depreciation and you make lots of money. The less. Good. Good place to be is you could sell long-term contracts to people who might default on you. And then if you're not bringing it to the present, so you're not like saying, hey, you have to pay us all up front, then you're in this like more risky territory. So is it top left of the chart? If I have the chart right, maybe. Large contracts paid over time. Yeah. Large contracts paid over time is like top left. So it's more risky, but you could still probably get away with it. And then the other opportunity is that you could sell short-term contracts for really high prices. And so lots of people tried that too, because this is actually closer to the original business model that people thought would work in cloud providers for CPUs. It works for CPUs, but it doesn't really work for GPUs. And I don't think people were trying this because they were thinking about the risk associated with it. I think a lot of people are just come from a software background, have not really thought about like cogs or margins or inventory risk or things that you have to worry about in the physical world. And I think they were just like copy pasting the same business model onto CPUs. And also, I remember fundraising like a few years ago. And I know based on. Like what we knew other people were saying who were in a very similar business to us versus what we were saying. And we know that our pitch was way worse at the time, because in the beginning of SF Compute, we looked very similar to pretty much every other GPU cloud, not on purpose, but sort of accidentally. And I know that the correct pitch to give to an investor was we will look like a traditional CPU cloud with high margins and we'll sell to everyone. And that is a bad business model because your customers are price sensitive. And so what happens is if you. Sell at high prices, which is the price that you would need to sell it in order to de-risk your loss on the depreciation curve, and specifically what I mean by that is like, let's say you're selling it like $5 an hour and you're paying $1.50 an hour for the GPU under the hood. It's a little bit different than that, but you know, nice numbers, $5 an hour, $1.50 an hour. Great. Excellent. Well, you're charging a really high price per GPU hour because over time the price will go down and you'll get competed out. And what you need is to make sure that you never go under, or if you do go under your underlying cost. You've made so much money in the first part of it that the later end of it, like doesn't matter because from the whole structure of the deal, you've made money. The problem is that just, you think that you're going to be able to retain your customers with software. And actually what happens is your customers are super price sensitive and push you down and push you down and push you down and push you down, um, that they don't care about your software at all. And then the other problem that you have is you have, um, really big players like the hyperscalers who are looking to win the market and they have way more money than you, and they can push down on margin. Much better than you can. And so if they have to, and they don't, they don't necessarily all the time, um, I think they actually keep pride of higher margin, but if they needed to, they could totally just like wreck your margin at any point, um, and push you down, which meant that that quadrant over there where you're charging a high price, um, and just to make up for the risk completely got destroyed, like did not work at all for many places because of the price sensitivity, because people could just shove you down instead that pushed everybody up to the top right-hand corner of that, which is selling short-term. Contracts for low prices paid over time, which is the worst place to be in, um, the worst financial place to be in because it has the highest interest rate, um, which means that your, um, your costs go up at the same time, your, uh, your incoming cash goes down and squeezes your margins and squeezes your margins. The nice thing for like a core weave is that most of their business is over on the, on the other sides of those quadrants that the ones that survive. The only remaining question I have with core weave, and I promise I get to ask if I can compute, and I promise this is relevant to SOF Compute in general, because the framework is important, right? Sure. To understand the company. So why didn't NVIDIA or Microsoft, both of which have more money than core weave, do core weave, right? Why didn't they do core weave? Why have this middleman when either NVIDIA or Microsoft have more money than God, and they could have done an internal core weave, which is effectively like a self-funding vehicle, like a financial instrument. Why does there have to be a third party? Your question is like... Why didn't Microsoft, or why didn't NVIDIA just do core weave? Why didn't they just set up their own cloud provider? I think, and I don't know, and so correct me if I'm wrong, and lots of people will have different opinions here, or I mean, not opinions, they'll have actual facts that differ from my facts. Those aren't opinions. Those are actually indeed differences of reality, is that NVIDIA doesn't want to compete with their customers. They make a large amount of money by selling to existing clouds. If they launched their own core weave, then it would be a lot more money. It'd make it much harder for them to sell to the hyperscalers, and so they have a complex relationship with there. So not great for them. Second is that, at least for a while, I think they were dealing with antitrust concerns or fears that if they're going through, if they own too much layers of the stack, I could imagine that could be a problem for them. I don't know if that's actually true, but that's where my mind would go, I guess. Mostly, I think it's the first one. It's that they would be competing directly with their primary customers. Then Microsoft could have done it, right? That's the other question. Yeah, so Microsoft didn't do it. And my guess is that... NVIDIA doesn't want Microsoft to do it, and so they would limit the capacity because from NVIDIA's perspective, both they don't want to necessarily launch their own cloud provider because it's competing with their customers, but also they don't want only one customer or only a few customers. It's really bad for NVIDIA if you have customer concentration, and Microsoft and Google and Amazon, like Oracle, to buy up your entire supply, and then you have four or five customers or so who pretty much get to set prices. Monopsony. Yeah, monopsony. And so the optimal thing for you is a diverse set of customers who all are willing to pay at whatever price, because if you don't, somebody else will. And so it's really optimal for NVIDIA to have lots of other customers who are all competing against each other. Great. Just wanted to establish that. It's unintuitive for people who have never thought about it, and you think about it all day long. Yeah. Swyx: The last thing I'll call out from the talk, which is kind of cool, and then I promise we'll get to SF Compute, is why will DigitalOcean and Together lose money on their clusters? Why will DigitalOcean and Together lose money on their clusters?Evan [00:16:33]: I'm going to start by clarifying that all of these businesses are excellent and fantastic. That Together and DigitalOcean and Lambda, I think, are wonderful businesses who build excellent products. But my general intuition is that if you try to couple the software and the hardware together, you're going to lose money. That if you go out and you buy a long-term contract from someone and then you layer on services, or you buy the hardware yourself and you spin it up and you get a bunch of debt, you're going to run into the same problem that everybody else did, the same problem we did, same problem the hyperscalers did. And that's exactly what the hyperscalers are doing, which is you cannot add software and make high margins like a cloud provider can. You can pitch that into investors and it will totally make sense, and it's like the correct play in CPUs, but there isn't software you could make to make this occur. If you're spending a billion dollars on hardware, you need to make a billion dollars of software. There isn't a billion dollars of software that you can realistically make, and if you do, you're going to look like SAP. And that's not a knock on SAP. SAP makes a f**k ton of money, right? Right. Right. Right. Right. There aren't that many pieces of software that you could make, that you can realistically sell, like a billion dollars of software, and you're probably not going to do it to price-sensitive customers who are spending their entire budget already on compute. They don't have any more money to give you. It's a very hard proposition to do. And so many parties have been trying to do this, like, buy their own compute, because that's what a traditional cloud does. It doesn't really work for them. You know that meme where there's, like, the Grim Reaper? And he's, like, knocking on the door, and then he keeps knocking on the next door? We have just seen door after door after door of the Grim Reeker comes by, and the economic realities of the compute market come knocking. And so the thing we encourage folks to do is if you are thinking about buying a big GPU cluster and you are going to layer on software on top, don't. There are so many dead bodies in the wake there. We would recommend not doing that. And we, as SF Compute, our entire business is structured to help you not do that. It's helped disintegrate these. The GPU clouds are fantastic real estate businesses. If you treat them like real estate businesses, you will make a lot of money. The cloud services you can make on that, all the software you want to make on that, you can do that fantastically. If you don't own the underlying hardware, if you mix these businesses together, you get shot in the head. But if you combine, if you split them, and that's what the market does, it helps you split them, it allows you to buy, like, layer on services, but just buy from the market, you can make lots of money. So companies like Modal, who don't own the underlying compute, like they don't own it, lots of money, fantastic product. And then companies like Corbeave, who are functionally like really, really good real estate businesses, lots of money, fantastic product. But if you combine them, you die. That's the economic reality of compute. I think it also splits into trading versus inference, which are different kinds of workloads. Yeah. And then, yeah, one comment about the price sensitivity thing before we leave this. This topic, I want to credit Martin Casado for coining or naming this thing, which is like, you know, you said, you said this thing about like, you don't have room for a 10% margin on GPUs for software. Yep. And Martin actually played it out further. It's his first one I ever saw doing this at large enough runs. So let's say GPT-4 and O1 both had a total trading cost of like a $500 billion is the rough estimate. When you get the $5 billion runs, when you get the $50 billion runs, it is actually makes sense to build your own. You're going to have to get into chips, like for OpenEI to get into chip design, which is so funny. I would make an ASIC for this run. Yeah, maybe. I think a caveat of that that is not super well thought about is that only works if you're really confident. It only works if you really know which chip you're going to do. If you don't, then it's a little harder. So it makes in my head, it makes more sense for inference where you've already established it. But for training there's so much like experimentation. Any generality, yeah. Yeah. The generality is much more useful. Yeah. In some sense, you know, Google's like six generations into the CPUs. Yeah. Yeah. Okay, cool. Maybe we should go into SF Compute now. Sure. Yeah.Alessio [00:20:37]: Yeah. So you kind of talked about the different providers. Why did you decide to go with this approach and maybe talk a bit about how the market dynamics have evolved since you started a company?Evan [00:20:47]: So originally we were not doing this at all. We were definitely like forced into this to some extent. And SF Compute started because we wanted to go train models for music and audio in general. We were going to do a sort of generic audio model at some points, and then we were going to do a music model at some points. It was an early company. We didn't really spec down on a particular thing. But yeah, we were going to do a music model and audio model. First thing that you do when you start any AI lab is you go out and you buy a big cluster. The thing we had seen everybody else do was they went out and they raised a really big round and then they would get stuck. Because if you raise the amount of money that you need to train a model initially, like, you know, the $50 million pre-seed, pre-revenue, your valuation is so high or you get diluted so much that you can't raise the next round. And that's a very big ask to make. And also, I don't know, I felt like we just felt like we couldn't do it. We probably could have in retrospect, but I think one, we didn't really feel like we could do it. Two, it felt like if we did, we would have been stuck later on. We didn't want to raise the big round. And so instead, we thought, surely by now, we would be able to just go out. To any provider and buy like a traditional CPU cloud would sell offer you and just buy like on demand or buy like a month or so on. And this worked for like small incremental things. And I think this is where we were basing it off. We just like assumed we could go to like Lambda or something and like buy thousands of at the time A100s. And this just like was not at all the case. So we started doing all the sales calls with people and we said, OK, well, can we just get like month to month? Can we get like one month of compute or so on? Everyone told us at the time, no. You need to have a year long contract or longer or you're out of luck. Sorry. And at the time, we were just like pissed off. Like, why won't nobody sell us a month at a time? Nowadays, we totally understand why, because it's the same economic reason. Because if you if they had sold us the month to month or so on and we canceled or so on, they would have massive risk on that. And so the optimal thing to do was to only to just completely abandon the section of the market. We didn't like that. So our plan was we were going to buy a year long contract anyway. We would use a month. And then we would. At least the other 11 months. And we were locked in for a year, but we only had to pay on every individual month. And so we did this. But then immediately we said, oh, s**t, now we have a cloud provider, not a like training models company, not an AI lab, because every 30 days we owed about five hundred thousand dollars or so and we had about five hundred thousand dollars in the bank. So that meant that every single month, if we did not sell out our cluster, we would just go bankrupt. So that's what we did for the first year of the company. And when you're in that position. You try to think how in the world you get out of that position, what that transition to is, OK, well, we tend to be pretty good at like selling this cluster every month because we haven't died yet. And so what we should do is we should go basically be like this broker for other people and we will be more like a GPU real estate or like a GPU realtor. And so we started doing that for a while where we would go to other people who had who was trying to sell like a year long contract with somebody and we'd go to another person who like maybe this person wanted six months and somebody else on six months or something and we'd like combine all these people. Together to make the deal happen and we'd organize these like one off bespoke deals that looked like basically it ended up with us taking a bunch of customers, us signing with a vendor, taking some cut and then us operating the cluster for people typically with bare metal. And so we were doing this, but this was definitely like a oh, s**t, oh, s**t, oh, s**t. How do we get out of our current situation and less of a like a strategic plan of any sort? But while we were doing this, since like the beginning of the company, we had been thinking about how to buy GPU clusters, how to sell them effectively, because we'd seen every part of it. And what we ended up with was like a book of everybody who's trying to buy and everyone is trying to sell because we were these like GPU brokers. And so that turned into what is today SF Compute, which is a compute market, which we think we are the functionally the most liquid GPU market of any capacity. Honestly, I think we're the only thing that actually is like a real market that there's like bids and asks and there's like a like a trading engine that combines everything. And so. I think we're the only place where you can do things that a market should be able to do. Like you can go on SF Compute today and you get thousands of H100s for an hour if you want. And that's because there is a price for thousands of GPUs for an hour. That is like not a thing you can reasonably do on kind of any other cloud provider because nobody should realistically sell you thousands of GPUs for an hour. They should sell it to you for a year or so on. But one of the nice things about a market is that you can buy the year on SF Compute. But then if you need to sell. Back, you can sell back as well. And that opens up all these little pockets of liquidity where somebody who's just trying to buy for a little bit of time, some burst capacity. So people don't normally buy for an hour. That's not like actually a realistic thing, but it's like the range somebody who wants, who is like us, who needed to buy for a month can actually buy for a month. They can like place the order and there is actually a price for that. And it typically comes from somebody else who's selling back. Somebody who bought a longer term contract and is like they bought for some period of time, their code doesn't work, and now they need to like sell off a little bit.Alessio [00:25:49]: What are the utilization rates at which a market? What are the utilization rates at which a market? Like this works, what do you see the usual GPU utilization rate and like at what point does the market get saturated?Evan [00:26:00]: Assuming there are not like hardware problems or software problems, the utilization rate is like near 100 percent because the price dips until the utilization is 100 percent. So the price actually has to dip quite a lot in order for the utilization not to be. That's not always the case because you just have logistical problems like you get a cluster and parts of the InfiniBand fabric are broken. And there's like some issue with some switch somewhere and so you have to take some portion of the cluster offline or, you know, stuff like this, like there's just underlying physical realities of the clusters, but nominally we have better utilization than basically anybody because, but that's on utilization of the cluster, like that doesn't necessarily translate into, I mean, I actually do think we have much better overall money made for our underlying vendors than kind of anybody else. We work with the other GPU clouds and the basic pitch to the other GPU clouds is one. So we can sell your broker so we can we can find you the long term contracts that are at the prices that you want, but meanwhile, your cluster is idle and for that we can increase your utilization and get you more money because we can sell that idle cluster for you and then the moment we find the longer, the bigger customer and they come on, you can kick off those people and then go to the other ones. You get kind of the mix of like sell your cluster at whatever price you can get on the market and then sell your cluster at the big price that you want to do for long term contract, which is your ideal business model. And then the benefit of the whole thing being on the market. Is you can pitch your customer that they can cancel their long term contract, which is not a thing that you can reasonably do if you are just the GPU cloud, if you're just the GPU cloud, you can never cancel your contract, because that introduces so much risk that you would otherwise, like not get your cheap cost of capital or whatever. But if you're selling it through the market, or you're selling it with us, then you can say, hey, look, you can cancel for a fee. And that fee is the difference between the price of the market and then the price that they paid at, which means that they canceled and you have the ability to offer that flexibility. But you don't. You don't have to take the risk of it. The money's already there and like you got paid, but it's just being sold to somebody else. One of our top pieces from last year was talking about the H100 glut from all the long term contracts that were not being fully utilized and being put under the market. You have on here dollar a dollar per hour contracts as well as it goes up to two. Actually, I think you were involved. You were obliquely quoted in that article. I think you remember. I remember because this was hidden. Well, we hid your name, but then you were like, yeah, it's us. Yeah. Could you talk about the supply and demand of H100s? Was that just a normal cycle? Was that like a super cycle because of all the VC funding that went in in 2003? What was that like? GPU prices have come down. Yeah, GPU prices have come down. And there's some part that has normal depreciation cycle. Some part of that is just there were a lot of startups that bought GPUs and never used them. And now they're lending it out and therefore you exist. There's a lot of like various theories as to why. This happened. I dislike all of them because they're all kind of like they're often said with really high confidence. And I think just the market's much more complicated than that. Of course. And so everything I'm going to say is like very hedged. But there was a series of like places where a bunch of the orders were placed and people were pitching to their customers and their investors and just the broader market that they would arrive on time. And that is not how the world works. And because there was such a really quick build out of things, you would end up with bottlenecks in the supply chain somewhere that has nothing to do with necessarily the chip. It's like the InfiniBand cables or the NICs or like whatever. Or you need a bunch of like generators or you don't have data center space or like there's always some bottleneck somewhere else. And so a lot of the clusters didn't come online within the period of time. But then all the bottlenecks got sorted out and then they all came online all at the same time. So I think you saw a short. There was a shortage because supply chain hard. And then you saw a increase or like a glut because supply chain eventually figure itself out. And specifically people overordered in order to get the allocation that they wanted. Then they got the allocations and then they went under. Yeah, whatever. Right. There was just a lot of shenanigans. A caveat of this is every time you see somebody like overordered, there is this assumption that the problem was like the demand went down. I don't think that's the case at all. And so I want to clarify that. It definitely seems like a shortage. Like there's more demand for GPUs than there ever was. It's just that there was also more supply. So at the moment, I think there is still functionally a glut. But the difference that I think is happening is mostly the test time inference stuff that you just need way more chips for that than you did before. And so whenever you make a statement about the current market, people sort of take your words and then they assume that you're making a statement about the future market. And so if you say there's a glut now, people will continue to think there's a glut. But I think what is happening at the moment. My general prediction is that like by the winter, we will be back towards shortage. But then also, this very much depends on the rollout of future chips. And that comes with its own. I think I'm trying to give you like a good here's Evan's forecast. Okay. But I don't know if my forecast is right. You don't have to. Nobody is going to hold you to it. But like I think people want to know what's true and what's not. And there's a lot of vague speculations from people who are not that close to the market actually. And you are. I think I'm a closer. Close to the market, but also a vague speculator. Like I think there are a lot of really highly confident speculators and I am indeed a vague speculator. I think I have more information than a lot of other people. And this makes me more vague of a spectator because I feel less certain or less confident than I think a lot of other people do. The thing I do feel reasonably confident about saying is that the test time inference is probably going to quite significantly expand the amount of compute that was used for inference. So a caveat. This is like pretty much all the inference demand is in a few companies. A good example is like lots of bio and pharma was using H100s training sort of the bio models of sorts. And they would come along and they would buy, you know, thousands of H100s for training and then just like not a lot of stuff for inference. Not in any, not relative to like an opening iron anthropic or something because they like don't have a consumer product. Their inference event, if they can do it right. There's really like only one inference event that matters. And obviously I think they're going to run into it. And Batch and they're not going to literally just run one inference event. But like the one that produces the drug is the important one. Right. And I'm dumb and I don't know anything about biology, so I could be completely wrong here. But my understanding is that's kind of the gist. I can check that for you. You can check that for me. Check that for me. But my understanding is like the one that produces the sequence that is the drug that, you know, cures cancer or whatever. That's the important deal. But like a lot of models look like this where they're sort of more enterprising use cases or they're so prior to something that looks like test time inference. You got lots and lots of demand for training and then pretty much entirely fell off for inference. And I think like we looked at like Open Router, for example, the entirety of Open Router that was not anthropic or like Gemini or OpenAI or something. It was like 10 H100 nodes or something like that. It's just like not that much. It's like not that many GPUs actually to service that entire demand. But that's like a really sizable portion of the sort of open source market. But the actual amount of compute needed for it was not that much. But if you imagine like what an OpenAI needs for like GPT-4, it's like tremendously big. But that's because it's a consumer product that has almost all the inference demand. Yeah, that's a message we've had. Roughly open source AI compared to closed AI is like 5%. Yeah, it's like super small. Super small. It's super small. Super small. But test time inference changes that quite significantly. So I will... I will expect that to increase our overall demand. But my question on whether or not that actually affects your compute price is entirely based on how quickly do we roll out the next chips. The way that you burst is different for test time.Alessio [00:34:01]: Any thoughts on the third part of the market, which is the more peer-to-peer distributed, some are like crypto-enabled, like Hyperbolic, Prime Intellect, and all of that. Where do those fit? Like, do you see a lot of people will want to participate in a peer-to-peer market? Or just because of the capital requirements at the end of the day, it doesn't really matter?Evan [00:34:20]: I'm like wildly skeptical of these, to be frankly. The dream is like steady at home, right? I got this $15.90. Nobody has $15.90. $14.90 sitting at home. I can rent it out. Yeah. Like, I just don't really think this is going to ever be more efficient than a fully interconnected cluster with InfiniBand or, you know, whatever the sort of next spec might be. Like, I could be completely wrong. But speaking of... I mean, like, SpeedoLite is really hard to beat. And regardless of whatever you're using, you just like can't get around that physical limitation. And so you could like imagine a decentralized market that still has a lot of places where there's like co-location. But then you would get something that looks like SF Compute. And so that's what we do. That's why we take our general take is like on SF Compute, you're not buying from like random people. You're buying from the other GPU clouds, functionally. You're buying from data centers that are the same genre of people that you would work with already. And you can specify, oh, I want all these nodes to be co-located. And I don't think you're really going to get around that. And I think I buy crypto for the purposes of like transferring money. Like the financial system is like quite painful and so on. I can understand the uses of it to sort of incentivize an initial market or try to get around the cold start problem. We've been able to get around the cold start problem just fine. So it didn't actually need that at all. What I do think is totally possible is you could launch a token and then you could like subsidize the crypto. You could compute prices for a bit, but like maybe that will help you. I think that's what Nuus is doing. Yeah, I think there's lots of people who are trying to do things like this, but at some point that runs out. So I would, I think generally agree. I think the only thread in that model is very fine grained mixture of experts that can be like algorithms can shift to adapt to hardware realities. And the hardware reality is like, okay, it's annoying to do large co-located clusters. Then we'll just redesign attention or whatever in our architecture to distribute it more. There was a little bit buzz of block attention last year that Strong Compute made a big push on. But I think like, you know, in a world where we have 200 experts in MOE model, it starts to be a little bit better. Like, I don't disagree with this. I can imagine the world in which you have like, in which you've redesigned it to be more parallelizable, like across space.Evan [00:36:43]: But assuming without that, your hardware limitation is your speed of light limitation. And that's a very hard one to get around.Alessio [00:36:50]: Any customers or like stories that you want to shout out of like maybe things that wouldn't have been economically viable like others? I know there's some sensitivity on that.Evan [00:37:00]: My favorites are grad students, are folks who are trying to do things that would normally otherwise require the scale of a big lab. And the grad students are like the worst pilots. They're like the worst possible customer for the traditional GPU clouds because they will immediately turn if you sell them a thing because they're going to graduate and they're not going to go anywhere. They're not going to like, that project isn't continuing to spend lots of money. Like sometimes it does, but not if you're like working with the university or you're working with the lab of some sort. But a lot of times it's just like the ability for us to offer like big burst capacity, I think is lovely and wonderful. And it's like one of my favorite things to do because all those folks look like we did. And I have a special place in my heart for that. I have a special place in my heart for young hackers and young grad students and researchers who are trying to do the same genre of thing that we are doing. For the same reason, I have a special place in my heart for like the startups, the people who are just actively trying to compete on the same scale, but can't afford it time-wise, but can afford it spike-wise. Yeah, I liked your example of like, I have a grant of 100K and it's expiring. I got to spend it on that. That's really beautiful. Yeah. Interesting. Has there been interesting work coming out of that? Anything you want to mention? Yeah. So from like a startup perspective, like Standard Intelligence and Find, P-H-I-N-D. We've had them on the pod.Swyx [00:38:23]: Yeah. Yeah.Evan [00:38:23]: That was great. And then from grad students' perspective, we worked a lot with like the Schmidt Futures grantees of various sorts. My fear is if I talk about their research, I will be completely wrong to a sort of almost insulting degree because I am very dumb. But yeah. I think one thing that's maybe also relevant startups and GPUs-wise. Yeah. Is there was a brief moment where it kind of made sense that VCs provided GPU clusters. And obviously you worked at AI Grants, which set up Andromeda, which is supposedly a $100 million cluster. Yeah. I can explain why that's the case or why anybody would think that would be smart. Because I remember before any of that happened, we were asking for it to happen. Yeah. And the general reason is credit risk. Again, it's a bank. Yeah. I have lower risk than you due to credit transformation. I take your risk onto my balance sheet. Correct. Exactly. If you wanted to go for a while, if you wanted to go set up a GPU cluster, you had to be the one that actually bought the hardware and racked it and stacked it, like co-located it somewhere with someone. Functionally, it was like on your balance sheet, which means you had to get a loan. And you cannot get a loan for like $50 million as a startup. Like not really. You can get like venture debt and stuff, but like it's like very, very difficult to get a loan of any serious price for that. But it's like not that difficult to get a loan for $50 million. If you already have a fund or you already have like a million dollars under your assets somewhere or like you personally can like do a personal guarantee for it or something like this. If you have a lot of money, it is way easier for you to get a loan than if you don't have a lot of money. And so the hack of a VC or some capital partner offering equity for compute is always some arbitrage on the credit risk. That's amazing. Yeah. That's a hack. You should do that. I don't think people should do it right now. I think the market has like, I think it made sense at the time and it was helpful and useful for the people who did it at the time. But I think it was a one-time arbitrage because now there are lots of other sources that can do it. And also I think like it made sense when no one else was doing it and you were the only person who was doing it. But now it's like it's an arbitrage that gets competed down. Sure. So it's like super effective. I wouldn't totally recommend it. Like it's great that Andromeda did it. But the marginal increase of somebody else doing it is like not super helpful. I don't think that many people have followed in their footsteps. I think maybe Andreessen did it. Yeah. That's it. I think just because pretty much all the value like flows through Andromeda. What? That cannot be true. How many companies are in the air, Grant? Like 50? My understanding of Andromeda is it works with all the NFTG companies or like several of the NFTG companies. But I might be wrong about that. Again, you know, something something. Nat, don't kill me. I could be completely wrong. But the but you know, I think Andromeda was like an excellent idea to do at the right time in which it occurred. Perfect. His timing is impeccable. Timing. Yeah. Nat and Daniel are like, I mean, there's lots of people who are like... Sears? Yeah. Sears. Like S-E-E-R. Oh, Sears. Like Sears of the Valley. Yeah. They for years and years before any of the like ChatGPT moment or anything, they had fully understood what was going to happen. Like way, way before. Like. AI Grant is like, like five years old, six years old or something like that. Seven years old. When I, when it like first launched or something. Depends where you start. The nonprofit version. Yeah. The nonprofit version was like, like happening for a while, I think. It's going on for quite a bit of time. And then like Nat and Daniel are like the early investors in a lot of the sort of early AI labs of various sorts. They've been doing this for a bit.Alessio [00:41:58]: I was looking at your pricing yesterday. We're kind of talking about it before. And there's this weird thing where one week is more expensive of both one day and one month. Yeah. What are like some of the market pricing dynamics? What are things that like this to somebody that is not in the business? This looks really weird. But I'm curious, like if you have an explanation for it, if that looks normal to you. Yeah.Evan [00:42:18]: So the simple answer is preemptible pricing is cheaper than non-preemptible pricing. And the same economic principle is the reason why that's the case right now. That's not entirely true on SF Compute. SF Compute doesn't really have the concept of preemptible. Instead, what it has is very short reservations. So, you know, you go to a traditional cloud provider and you can say, hey, I want to reserve contract for a year. We will let you do a reserve contract for one hour, which is the part of SFC. But what you can do is you can just buy every single hour continuously. And you're reserving just for that hour. And then the next hour you reserve just for that next hour. And this is obviously like a built in. This is like an automation that you can do. But what you're seeing when you see the cheap price is you're seeing somebody who's buying the next hour, but maybe not necessarily buying an hour after that. So if the price goes up. Up too much. They might not get that next hour. And the underlying part of this of where that's coming from the market is you can imagine like day old milk or like milk that's about to be old. It might drop its price until it's expired because nobody wants to buy the milk that's in the past. Or maybe you can't legally sell it. Compute is the same way. No, you can't sell a block of compute that is not that is in the past. And so what you should do in the market and what people do do is they take. They take a block. A block of compute. And then they drop it and drop it and drop it and drop into a floor price right before it's about to expire. And they keep dropping it until it clears. And so anything that is idle drops until some point. So if you go and use on the website and you set that that chart to like a week from now, what you'll see is much more normal looking sort of curves. But if you say, oh, I want to start right now, that immediate instant, here's the compute that I want right now is the is functionally the preemptible price. It's where most people are getting the best compute or like the best compute prices from. The caveat of that is you can do really fun stuff on SFC if you want. So because it's not actually preemptible, it's it's reserved, but only reserved for an hour, which means that the optimal way to use as of compute is to just buy on the market price, but set a limit price that is much higher. So you can set a limit price for like four dollars and say, oh, if the market ever happens to spike up to four dollars, then don't buy. I don't want to buy that at that price for that price. I don't want to buy that at that price for that price for an hour. But otherwise, just buy at the cheapest price. And if you're comfortable with that of the volatility of it, you're actually going to get like really good prices, like close to a dollar an hour or so on, sometimes down to like 80 cents or whatever. You said four, though. Yeah. So that's the thing. You want to lower the limit. So four is your max price. Four is like where you basically want to like pull the plug and say don't do it because the actual average price is not or like the, you know, the preemptible price doesn't actually look like that. So what you're doing when you're saying four is always, always, always give me this compute. Like continue to buy every hour. Don't preempt me. Don't kick me off. And I want this compute and just buy at the preemptible price, but never kick me off. The only times in which you get kicked off is if there is a big price spike. And, you know, let's say one day out of the year, there's like a four dollar an hour price because of some weird fluke or something. If there are other periods of time, you're actually getting a much lower price than you. It makes sense. Your your average cost that you're actually paying is way better. And your trade off here is you don't literally know what price you're going to get. So it's volatile. But your actual average historically has been like everyone who's done this has gotten wildly better prices. And this is like one of the clever things you can do with the market. If you're willing to make those trade offs, you can get a lot of really good prices. You can also do other things like you can only buy at night, for example. So the price goes down at night. And so you can say, oh, I want to only buy, you know, if the price is lower than 90 cents. And so if you have some long running job, you can make it only run on 90 cents and then you recover back and so on. Yeah. So what you can kind of create as like a spot inst is what other the CPU world has. Yes. But you've created a system where you can kind of manufacture the exact profile that you want. Exactly. That is not just whatever the hyperscalers offer you, which is usually just one thing. Correct. SF Compute is like the power tool. The underlying primitives of like hourly compute is there. Correct. Yeah, it's pretty interesting. I've often asked OpenAI. So like, you know, all these guys. Cloud as well. They do batch APIs. So it's half off of whatever your thing is. Yeah. And the only contract is we'll return in 24 hours. Sure. Right. And I was like, 24 hours is good. But sometimes I want one hour. I want four hours. I want something. And so based off of SF Compute's system, you can actually kind of create that kind of guarantee. Totally. That would be like, you know, not 24, but within eight hours, within four hours, like the work half of a workday. Yes. I can return your results to you. And then I can return it to you. And if your latency requirements are like that low, actually it's fine. Yes. Correct. Yeah. You can carve out that. You can financially engineer that on SFC. Yeah. Yeah. I mean, I think to me that unlocks a lot of agent use cases that I want, which is like, yeah, I worked in a background, but I don't want you to take a day. Yeah. Correct. Take a couple hours or something. Yeah. This touches a lot of my like background because I used to be a derivatives trader. Yeah. And this is a forward market. Yeah. A futures forward market, whatever you call it. Not a future. Very explicitly not a future. Not yet a futures. Yes. But I don't know if you have any other points to talk about. So you recognize that you are a, you know, a marketplace and you've hired, I met Alex Epstein at your launch event and you're like, you're, you're building out the financialization of GPUs. Yeah. So part of that's legal. Mm-hmm. Totally. Part of that is like listing on an exchange. Yep. Maybe you're the exchange. I don't know how that works, but just like, talk to me about that. Like from the legal, the standardization, the like, where is this all headed? You know, is this like a full listed on the Chicago Mercantile Exchange or whatever? What we're trying to do is create an underlying spot market that gives you an index price that you can use. And then with that index price, you can create a cash settled future. And with a cash settled future, you can go back to the data centers and you can say, lock in your price now and de-risk your entire position, which lets you get cheaper cost of capital and so on. And that we think will improve the entire industry because the marginal cost of compute is the risk. It's risk as shown by that graph and basically every part of this conversation. It's risk that causes the price to be all sorts of funky. And we think a future is the correct solution to this. So that's the eventual goal. Right now you have to make the underlying spot market in order to make this occur. And then to make the spot market work, you actually have to solve a lot of technology problems. You really cannot make a spot market work if you don't run the clusters, if you don't have control over them, if you don't know how to audit them, because these are super computers, not soybeans. They have to work. In a way that like, it's just a lot simpler to deliver a soybean than it is to deliver it. I don't know. Talk to the soybean guys. Sure. You know? Yeah. But you have to have a delivery mechanism. Your delivery mechanism, like somebody somewhere has to actually get the compute at some point and it actually has to work. And it is really complicated. And so that is the other part of our business that we go and we build a bare metal infrastructure stack that goes. And then also we do auditing of all the clusters. You sort of de-risk the technical perspective and that allows you to eventually de-risk the financial perspective. And that is kind of the pitch of SF Compute. Yeah. I'll double click on the auditing on the clusters. This is something I've had conversations with Vitae on. He started Rika and I think he had a blog post which kind of shone the light a little bit on how unreliable some clusters are versus others. Correct. Yeah. And sometimes you kind of have to season them and age them a little bit to find the bad cards. You have to burn them in. Yeah. So what do you do to audit them? There's like a burn-in process, a suite of tests, and then active checking and passive checking. Burn-in process is where you typically run LINPACK. LINPACK is this thing that like a bunch of linear algebra equations that you're stress testing the GPUs. This is a proprietary thing that you wrote? No, no, no. LINPACK is like the most common form of burn-in. If you just type in burn-in, typically when people say burn-in, they literally just mean LINPACK. It's like an NVIDIA reference version of this. Again, NVIDIA could run this before they ship, but now the customers have to do it. It's annoying. You're not just checking for the GPU itself. You're checking like the whole component, all the hardware. And it's a lot of work. It's an integration test. It's an integration test. Yeah. So what you're doing when you're running LINPACK or burn-in in general is you're stress testing the GPUs for some period of time, 48 hours, for example, maybe seven days or so on. And you're just trying to kill all the dead GPUs or any components in the system that are broken. And we've had experiences where we ran LINPACK on a cluster and it rounds out, sort of comes offline when you run LINPACK. This is a pretty good sign that maybe there is a problem with this cluster. Yeah. So LINPACK is like the most common sort of standard test. But then beyond that, what you do is we have like a series of performance tests that replicate a much more realistic environment as well that we run just assuming if LINPACK works at all, then you run the next set of tests. And then while the GPUs are in operation, you're also going through and you're doing active tests and passive tests. Passive tests are things that are running in the background while somebody else is running, while like some other workload is running. And active tests are during like idle periods. You're running some sort of check that would otherwise sort of interrupt something. And then the active tests will take something offline, basically. Or a passive check might mark it to get taken offline later and so on. And then the thing that we are working on that we have working partially but not entirely is automated refunds, which is basically like, is the case that the hardware breaks so much. And there's only so much that we can do and it is the effect of pretty much the entire industry. So a pretty common thing that I think happens to kind of everybody in the space is a customer comes online, they experience your cluster, and your cluster has the same problem that like any cluster has, or it's I mean, a different problem every time, but they experience one of the problems of HPC. And then their experience is bad. And you have to like negotiate a refund or some other thing like this. It's always case by case. And like, yeah, a lot of people just eat the cost. Correct. So one of the nice things about a market that we can do as we get bigger and have been doing as we can bigger is we can immediately give you something else. And then also we can automatically refund you. And you're still gonna experience it like the hardware problems aren't going away until the underlying vendors fix things. But honestly, I don't think that's likely because you're always pushing the limits of HPC. This is the case of trying to build a supercomputer. that's one of the nice things that we can do is we can switch you out for somebody else somewhere, and then automatically refund you or prorate or whatever the correct move is. One of the things that you say in this conversation with me was like, you know, you know, a provider is good when they guarantee automatic refunds. Which doesn't happen. But yeah, that's, that's in our contact with all the underlying cloud providers. You built it in already. Yeah. So we have a quite strict SLA that we pass on to you. The reason why

In this episode, Energy expert Robert Bryce breaks down the global energy crisis, the impact of rising electricity costs, and the realities of renewable energy. He explains why energy policies are hurting the working class, how wind and solar energy face major challenges, and why nuclear power could be a key solution. Bryce also discusses electric vehicles (EVs), the expansion of data centers, and the politics of energy regulations. Get the facts on energy affordability, infrastructure challenges, and the role of fossil fuels in the world's energy future.

ABUNDANT MONTANA MADISON BROWNING TRT: 10:18 LOCAL POTATOES/GETTING AROUND THE SHORT GROWING SEASON/CSA/BUY LOCALLY

The Future of Natural Refrigerants:Insights from NASRCIn this episode of the AdvancedRefrigeration Podcast, hosts Brett Wetzel and Kevin Kompas are joined byspecial guests Danielle Wright and Rusty Walker from the North AmericanSustainable Refrigeration Council (NASRC). They discuss various aspects of techniciantraining and development, the current and future plans ofNASRC, and the challenges and innovations within the refrigeration industry,particularly regarding natural refrigerants such as CO2, propane, and ammonia.Also covered is the significance of proper training, the evolution ofrefrigeration technology, and various technical aspects of system efficiencyand maintenance. Don't miss this comprehensive conversation packed withinsights, technical know-how, and a touch of humor.00:00 Opening Banter and Introductions00:21 Welcome to the AdvancedRefrigeration Podcast01:20 Introducing NASRC and Its Mission01:46 Technician Training and Events04:00 Workforce Development Initiatives06:23 Challenges and Solutions inRefrigeration Training10:43 Refrigeration Curriculum andCertification12:12 CO2 Systems and Industry Trends15:02 Supply Chain Issues and Solutions19:19 CO2 Dryers and Charging Setups19:58 Old Gas Tanks and Urban Myths21:43 Pressure Relief and Valve Ideas23:42 Backup Units and Generators25:26 TD Control and ManufacturerInsights28:45 Fan Control and Efficiency34:01 High Pressure Myths and ElectronicsChallenges37:15 Training and Future ofRefrigeration

The Future of Natural Refrigerants: Insights from NASRCIn this episode of the Advanced Refrigeration Podcast, hosts Brett Wetzel and Kevin Kompas are joined by special guests Danielle Wright and Rusty Walker from the North American Sustainable Refrigeration Council (NASRC). They discuss various aspects of technician training and development, the current and future plans of NASRC, and the challenges and innovations within the refrigeration industry, particularly regarding natural refrigerants such as CO2, propane, and ammonia. Also covered is the significance of proper training, the evolution of refrigeration technology, and various technical aspects of system efficiency and maintenance. Don't miss this comprehensive conversation packed with insights, technical know-how, and a touch of humor.00:00 Opening Banter and Introductions00:21 Welcome to the Advanced Refrigeration Podcast01:20 Introducing NASRC and Its Mission01:46 Technician Training and Events04:00 Workforce Development Initiatives06:23 Challenges and Solutions in Refrigeration Training10:43 Refrigeration Curriculum and Certification12:12 CO2 Systems and Industry Trends15:02 Supply Chain Issues and Solutions19:19 CO2 Dryers and Charging Setups19:58 Old Gas Tanks and Urban Myths21:43 Pressure Relief and Valve Ideas23:42 Backup Units and Generators25:26 TD Control and Manufacturer Insights28:45 Fan Control and Efficiency34:01 High Pressure Myths and Electronics Challenges37:15 Training and Future of Refrigeration

What's going on today? Potential snow, Supply chain Issues, and The Super bowl matchup full 1833 Mon, 27 Jan 2025 13:04:28 +0000 oXtTPJyBpZiQ9seHtoOWDVgwonPLjTsb news,a-newscasts,top picks The Big K Morning Show news,a-newscasts,top picks What's going on today? Potential snow, Supply chain Issues, and The Super bowl matchup The Big K Morning Show 2024 © 2021 Audacy, Inc. News News News News news News News News News News False https:

Adam Maguire, from the RTÉ Business Desk

- Congressional report condemns junk science push behind masks, lockdowns and jabs - Says Fauci and EcoHealth Alliance lied to the world - School lockdowns harmed children, both physically and mentally - The government ran misinformation campaigns to deceive the public - Full interview with Michael Yon, covering Bitcoin, gold, robots, famine - Comet impacts, volcanic explosions, gobar gas as renewable energy For more updates, visit: http://www.brighteon.com/channel/hrreport NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com

A new study published in JAMA found that drug-related supply chain issue reports were 40% less likely to result in meaningful drug shortages in Canada compared with the US. Authors Kate Suda, PharmD, MS, of University of Pittsburgh School of Medicine, and Mina Tadrous, PharmD, PhD, of University of Toronto, discuss this and more with JAMA Deputy Editor Joseph S. Ross, MD, MHS. Related Content: Differences in Drug Shortages in the US and Canada Understanding Drug Supply Shortages in the US and Canada

Larry Culp, Chairman and CEO of GE Aerospace says the company is working with suppliers to address supply chain issues which have slowed delivery of engines. He is joined by Bloomberg's Haslinda Amin.See omnystudio.com/listener for privacy information.

Right About Now with Ryan AlfordJoin media personality and marketing expert Ryan Alford as he dives into dynamic conversations with top entrepreneurs, marketers, and influencers. "Right About Now" brings you actionable insights on business, marketing, and personal branding, helping you stay ahead in today's fast-paced digital world. Whether it's exploring how character and charisma can make millions or unveiling the strategies behind viral success, Ryan delivers a fresh perspective with every episode. Perfect for anyone looking to elevate their business game and unlock their full potential.Right About Now NewsletterFree Podcast Monetization CourseJoin The NetworkFollow Us On InstagramSubscribe To Our Youtube ChannelVibe Science MediaSUMMARYIn this episode of Weekly Business News, host Ryan Alford, Chris Hansen and Brianna Hall tackle some of the most pressing issues in business and current events. The trio dives into the political landscape, focusing on Donald Trump, Elon Musk, and the Department of Justice's potential breakup of Google. They also discuss McDonald's lawsuit against major meatpackers over price inflation, exploring its impact on the fast food giant and consumers. With a blend of humor and sharp analysis, the conversation covers the economic ripple effects of rising meat prices and the growing challenges of attaining the American dream.TAKEAWAYSDiscussion of natural disasters and their impact on communities, particularly hurricanes.Examination of the political landscape, focusing on the alliance between Donald Trump and Elon Musk.Analysis of Vice President Kamala Harris's media presence and public appeal.Consideration of the Department of Justice's potential breakup of Google due to monopolistic practices.Exploration of the implications of regulating powerful companies like Google.Overview of McDonald's lawsuit against major meatpackers for price inflation.Discussion on the economic implications of rising meat prices and inflation.Reflection on the cost of achieving the American dream in today's economy.Analysis of the long-term effects of the COVID-19 pandemic on economic stability.Emphasis on the importance of staying informed about business and political developments. If you enjoyed this episode and want to learn more, join Ryan's newsletter https://ryanalford.com/newsletter/ to get Ferrari level advice daily for FREE. Learn how to build a 7 figure business from your personal brand by signing up for a FREE introduction to personal branding https://ryanalford.com/personalbranding. Learn more by visiting our website at www.ryanisright.comSubscribe to our YouTube channel www.youtube.com/@RightAboutNowwithRyanAlford.

What did you think of todays show??Rising mortgage rates and supply chain disruptions are shaking up the real estate market. What should your next move be as an investor? In this episode, we break down why rates are rising despite recent cuts, the impact of global events on the economy, and what it all means for real estate investors.Hosts Mike and Dylan share their predictions for the housing market, including how supply chain issues and increasing foreclosure rates could change your investment strategies through the end of this year and into 2025. Tune in to learn how to leverage today's market conditions in your real estate business!Topics discussed:Understanding bonds and their impact on mortgage rates (2:10)What does the rate cut mean for the housing market? (10:28)How global events are impacting the economy/real estate market (12:43)Should you change your investment strategy? (16:39)Deal analysis: Would you buy this property? (22:14)Sellers you should target in 2025 (25:33)Learn more about the Collecting Keys SCALE Community! https://collectingkeys.com/scale/Check out the FREE Collecting Keys “Invest Anywhere” Guide to learn how to find deals in ANY MARKET Completely virtually (this is how we scaled to over a dozen markets)!https://instantinvestor.collectingkeys.com/invest-anywhereFollow us on Instagram!https://www.instagram.com/collectingkeyspodcast/https://www.instagram.com/mike_invests/https://www.instagram.com/investormandan/https://www.instagram.com/dylan_does_dealsThis episode was produced by Podcast Boutique https://www.podcastboutique.com

Bumper to Bumper Radio, the car guys on KTAR, 92.3 FM in Phoenix, AZ, broadcast every Saturday from 11:00 am ...

The COVID-19 pandemic did more than just highlight the vulnerabilities in the global supply chain—it exposed systemic issues that had been brewing for years.  As the world grappled with unprecedented shortages in everything from medical supplies to consum er goods, it became clear that these vulnerabilities were not merely accidental; they were the byproduct of […] The post 454: Covid Supply Chain Issues Should Not Have Been a Surprise appeared first on Wealth Formula.

00:00 From Immigrant Parents to Entrepreneurship05:19 Building a Gender-Neutral Fashion Brand09:53 Overcoming Funding and Supply Chain Challenges20:09 Authenticity and Care20:19 Clothing Has No Gender21:18 Inclusivity vs. Exclusivity22:36 Financial Progress25:45 Starting with Jeans28:11 The Challenge of Capital29:28 Building a Community31:07 Small Team, Big Impact34:40 Expanding the Product Line36:24 The Next Levi's

Recently, I've been hearing rumors about supply chain issues rearing their ugly heads again, and I was too busy to focus on them at the time and certainly didn't feel it in my day-to-day world. But I came across an article and took the time to do some research on this topic and I want to share the information I found with you and why it is so important for you to continue to lean into your construction management services.   If you're interested in joining my course, you can use my code ‘Masterclass' to receive $150 off the price. That special discount will expire on July 18th at midnight EST.  If you have questions, feel free to schedule a course discovery call with me by scrolling down to the bottom of the page here: https://www.reneedevignierdesign.com/renovation-management-interior-designers    Find the full shownotes at: https://devignierdesign.com/supply-chain-issues   

5G Guys Season 4 Finale: Highlights, Insights, and Future Trends Join Wayne Smith and Dan McVaugh in the season 4 finale of the 5G Guys podcast as they recap the highlights and key insights from this season. They discuss notable guests, emerging trends in 5G and wireless technology, the impact of satellite networks like Starlink, regulatory issues such as net neutrality, and the latest business and finance trends in the telecom industry. Tune in to hear their predictions for the future, including the impact of AI, energy demands, and advancements in the wireless ecosystem. Stay informed and get ready for what's next in the world of 5G! __________________________ Links Referenced in the Show __________________________      BEAD Funding Status ➡︎  https://www.internetforall.gov/ __________________________ Connect With Our Sponsor __________________________      Vertex Innovations ➡︎ https://vertex-us.com/ __________________________ Connect With Us __________________________      5G Guys Website ➡︎  https://5gguys.com        Social:        ·       Facebook: https://www.facebook.com/5Gguys      ·       LinkedIn: https://www.linkedin.com/groups/12515882      ·       X: https://twitter.com/5gGuys   _______________________________ Submit Your Ideas or Feedback ➡︎ https://5gguys.com/contact-2 _______________________________ Subscribe to the 5G Guys Weekly Newsletter ➡︎ https://mailchi.mp/5gguys/subscribe-to-the-5g-guys _______________________________ ⏰Episode Minute-by-Minute⏰ 00:00 Preview 00:58 5G Guys Podcast Introduction 01:19 Meet the Hosts: Dan and Wayne 01:38 Season Recap: Highlights and Guests 02:28 Private Networks and Satellite Connectivity 03:46 Net Neutrality and Regulations 04:06 Jim Patterson's Insights and Industry News 04:44 First Responder Networks 05:20 Advanced Positioning and Location Services 05:44 Fixed Wireless Access with Samsung 06:40 Season 4 Theme One - Wireless Technology Ecosystem 08:55 Season 4 Theme Two - The Business & Finance of Wireless Telecom 11:35 Verizon's Rebranding and Industry Changes 13:11 Carrier Spending and Vendor Impact 15:49 Supply Chain Issues and Future Outlook 16:48 Data Centers and Hyperscalers 23:24 Future Topics and Predictions 24:45 Energy Demands and Smart Grids 30:13 Season Wrap-Up and Farewell

Today on the podcast, special guest SRAM CEO Ken Lousberg joins Jeff for an exclusive interview to talk all things MTB and more. From the perceived innovation plateau to supply chain issues and the future of bicycle drivetrains, no topic is off limits. Tune in! Our YouTube channel: www.youtube.com/channel/UCczlFdoHUMcFJuHUeZf9b_Q Worldwide Cyclery YouTube Channel: www.youtube.com/channel/UCxZoC1sIG-vVtLsJDSbeYyw Worldwide Cyclery Instagram: https://www.instagram.com/worldwidecyclery/ MTB Podcast Instagram: https://www.instagram.com/mtbpodcast/ Submit any and all questions to podcast@worldwidecyclery.com

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: D&D.Sci Alchemy: Archmage Anachronos and the Supply Chain Issues Evaluation & Ruleset, published by aphyer on June 18, 2024 on LessWrong. This is a follow-up to last week's D&D.Sci scenario: if you intend to play that, and haven't done so yet, you should do so now before spoiling yourself. There is a web interactive here you can use to test your answer, and generation code available here if you're interested, or you can read on for the ruleset and scores. RULESET There are two steps to brewing a potion: STEP 1: MAGICAL POTENCY Any ingredient that doesn't exist in the mundane world is Magical, while any ingredient that exists in the mundane world is not: Magical Not Magical Angel Feather Badger Skull Beholder Eye Beech Bark Demon Claw Crushed Diamond Dragon Scale Crushed Onyx Dragon Spleen Crushed Ruby Dragon Tongue Crushed Sapphire Dragon's Blood Eye of Newt Ectoplasm Ground Bone Faerie Tears Oaken Twigs Giant's Toe Powdered Silver Troll Blood Quicksilver Vampire Fang Redwood Sap The first step of potion-brewing is to dissolve the magical potency out of the Magical Ingredients to empower your potion. This requires the right amount of Magical Ingredients: too few, and nothing magical will happen and you will produce Inert Glop, while too many and there will be an uncontrolled Magical Explosion. If you include: 0-1 Magical Ingredients: 100% chance of Inert Glop. 2 Magical Ingredients: 50% chance of Inert Glop, 50% chance OK. 3 Magical Ingredients: 100% chance OK. 4 Magical Ingredients: 50% chance OK, 50% chance Magical Explosion. 5+ Magical Ingredients: 100% chance Magical Explosion. If your potion got past this step OK, move on to: STEP 2: DIRECTION Some ingredients are used to direct the magical power into the desired resulting potion. Each potion has two required Key Ingredients, both of which must be included to make it: Potion Key Ingredient 1 Key Ingredient 2 Barkskin Potion* Crushed Onyx Ground Bone Farsight Potion Beholder Eye Eye of Newt Fire Breathing Potion Dragon Spleen Dragon's Blood Fire Resist Potion Crushed Ruby Dragon Scale Glibness Potion Dragon Tongue Powdered Silver Growth Potion Giant's Toe Redwood Sap Invisibility Potion Crushed Diamond Ectoplasm Necromantic Power Potion* Beech Bark Oaken Twigs Rage Potion Badger Skull Demon Claw Regeneration Potion Troll Blood Vampire Fang *Well. Sort of. See the Bonus Objective section below. Some ingredients (Angel Feather, Crushed Sapphire, Faerie Tears and Quicksilver) aren't Key Ingredients for any potion in the dataset. Angel Feather and Faerie Tears are nevertheless useful - as magical ingredients that don't risk creating any clashing potion, they're good ways to add magical potential to a recipe. Crushed Sapphire and Quicksilver have no effect, including them is entirely wasteful. If you've gotten through Step 1, the outcome depends on how many potions you've included both the Key Ingredients of: 0 potions: with nothing to direct it, the magical potential dissolves into an Acidic Slurry. 1 potion: you successfully produce that potion. 2 or more potions: Sometimes (1/n of the time, where n is # of potions you included) a random one of the potions will dominate, and you will produce that one. The rest of the time, the clashing directions will produce Mutagenic Ooze. So, for example, if you brew a potion with: Dragon Spleen, Dragon Scale, Dragon Tongue and Dragon's Blood: You have included 4 magical ingredients, and the Key Ingredients of one potion (Fire Breathing). 50% of the time you will get a Magical Explosion, 50% of the time you will get a Fire Breathing Potion. Badger Skull, Demon Claw, Giant's Toe, Redwood Sap. You have included 2 magical ingredients, and the Key Ingredients of two potions (Rage and Growth). 50% of the time you will get Inert Glop, 25% of the time Mutagenic Ooze, 12.5% of the time G...

When supply chains run smoothly, the economies they support do too. But when even the smallest disruption occurs, supply chains can quickly turn into the equivalent of a daisy chain — where one event sets off a cascading impact down the entire logistics value chain. Experts fear that this is [...]

Mazda CEO Masahiro Moro says he believes traditional internal combustion vehicles will continue to dominate the market over the next five years. He talks about the carmaker's EV production plan, supply chain issues and more with hosts Alix Steel and Romaine Bostick. See omnystudio.com/listener for privacy information.

In this episode of the Industrial Advisors podcast, hosts Bill Condon and Matt McGregor review the industrial market performance for Q1 2024. They discuss the rise in vacancy rates across various submarkets, except for the Eastside, reaching an overall rate of 7%. The conversation also covers tenant and landlord markets, submarket performances, including South Seattle and Kent Valley, and the impact on different market sizes. The impacts of COVID on buying patterns, the shift in demand from durable goods to experiences, and the role of 3PLs in current market dynamics are analyzed. Additionally, they touch on investment sales activity, user market demand, challenges in the multi-story market, the implications of a bridge collapse on the supply chain, and development trends. The episode concludes with predictions for tenant velocity, investment activities, and vacancy rates in the upcoming quarters. 00:43 Diving into the Q1 2024 Industrial Market Review 00:52 Vacancy Rates and Market Dynamics Discussion 02:32 Submarket Analysis: South Seattle, Kent Valley, and Pierce County 06:29 Tenant and Landlord Market Trends 08:50 Investment Sales and Market Opportunities 13:00 The Impact of Multi-Story Developments and Amazon's Activity 16:08 Port Activity, Supply Chain Issues, and Development Insights 19:39 Q1 Recap and Predictions for the Upcoming Quarters You can find every episode of this show on Apple Podcasts, Spotify or YouTube, For more, visit industrialadvisors.com

Are you curious about the journey from considering weight loss shots to actually receiving them? In today's episode, Dr. Joseph Moleski dives into the topic of weight loss shots, exploring their efficacy and medical implications. Dr. Joe, a primary care physician, answers questions about how these shots affect appetite and metabolism, and addresses concerns regarding side effects and supply chain issues. The conversation also touches on the procedure for acquiring the medication. Dr. Joe also highlights how his clinic assists individuals in their weight loss journey. "If you're thinking about getting gastric bypass surgery, try the shots first because this is going to create that same feeling of like, 'Oh, I've eaten too much.'" What you will learn: The effectiveness of weight loss shots Supply chain issues with name brands Side effects and long-term effects Exercise and calorie deficit Learn more about Dr. Joe and STL Medical Weight Loss by visiting: Website Book an Appointment Facebook Instagram

See omnystudio.com/listener for privacy information.

The technology promises faster computations of large-scale supply chain problems.

The 'New Normal' encompasses persistent challenges like frequent cyberattacks disrupting digital infrastructures, unexpected bank closures shaking financial trust, and fragile supply chains causing global delays and shortages. These multifaceted crises are reshaping risk management and contingency planning in today's interconnected and digitalized world. Subscribe & click the

Wharton professor of operations, information and decisions Marshall Fisher talks about the Biden administration's new White House Council on Supply Chain Resilience and how it may impact the economy. Hosted on Acast. See acast.com/privacy for more information.

Honeywell International CEO Vimal Kapur talks about the company's investment strategy and supply chain constraints with Bloomberg's David Westin. See omnystudio.com/listener for privacy information.

It was a busy week for Airbus and particularly Boeing in Dubai. The airframers racked up more than 330 firm orders for new aircraft from Emirates, Ethiopian, FlyDubai, and others at the airshow. Edward Russell and Jay Shabat discuss. Plus, Korean Air's summer quarter results. Reading List Emirates' Tim Clark on ‘Trust' in Boeing, Supply Chain Issues and the End of Innovation Emirates Makes $52 Billion Deal With Boeing At Dubai Airshow

In this episode Nana Bonsu discuss the challenges faced by business leaders who are heavily invested in their businesses. Nana, an expert in business growth and transitions, shares his strategies for helping businesses execute their ideas and plan for long-term transitions. Listen in as Deborah and Nana also discuss the importance of vision, risk assessment, and understanding business valuation. Nana introduces his retro strategy approach, which delivers high-impact results in a short time frame, and encourages listeners to seek objective assessments of their businesses and leverage free resources for insights and innovation.   Nana Bonsu is the President of Infinite Horizons, Inc., a firm dedicated to helping businesses that want to grow but are too dependent on their owners and key employees or both. He is a Certified Value Builder Advisor and a Certified Strategy X Implementation Partner. He also hosts a weekly podcast show called "Build Value By Choice". He has over 17 years' experience either co-launching multiple business ventures or consulting for business leaders. Furthermore, he has worked in multiple industries and was a member of a team of chemical engineers and scientists who invented fat-free cottage cheese.He resides in Maryland with his wife and daughter.   You can connect with Nana in the following ways: Listen to the podcast: https://podcasts.apple.com/us/podcast/build-value-by-choice/id1587355904?ign-itscg=30200&ign-itsct=podcast_box_link Download the ebook: https://bit.ly/SOP-Guidebook Website: https://infhorizons.com/ Connect on social: https://linktr.ee/nmbonsu   Whether you are a C-Suite Leader of today or tomorrow, take charge of your career with confidence and leverage the insights of The CEO's Compass: Your Guide to Get Back on Track.  To learn more about The CEO's Compass, you can get your copy here: https://amzn.to/3AKiflR    Other episodes you'll enjoy: C-Suite Goal Setting: How To Create A Roadmap For Your Career Success - http://bit.ly/3XwI55n Natalya Berdikyan: Investing in Yourself to Serve Others on Apple Podcasts -http://bit.ly/3ZMx8yw Questions to Guarantee You Accomplish Your Goals - http://bit.ly/3QASvym  See omnystudio.com/listener for privacy information.

Nancy Rimbergas is the founder and creator of Earth Based Body, a skincare brand that focuses on using locally-sourced Arizona ingredients. Earth Based Body's products are carefully crafted to celebrate the desert environment, utilizing ingredients such as prickly pear cactus, Sonoran lemons, and desert aloe. These ingredients are known for their hydrating properties and are native to the Tucson region, where Earth Based Body is based. By utilizing these locally-sourced ingredients, Nancy aims to provide effective and natural skincare solutions that help combat dry skin. With a commitment to purity and environmental consciousness, Earth Based Body is a brand that skincare enthusiasts can trust. Nancy's dedication to utilizing the power of nature in skincare makes her a respected figure in the industry. She is also offering  20% off your first online purchase with code FINDINGARIZONA.  WEBSITE: https://earthbasedbody.com/discount/FINDINGARIZONA INSTAGRAM: https://www.instagram.com/earthbasedbody/ FACEBOOK: https://www.facebook.com/EarthBasedBody/ 00:04:35 - Importance of Using Local Ingredients  00:07:28 - Starting the Business  00:09:33 - Curating Products with a Purpose  00:11:05 - Support and Challenges  00:16:34 - The Beginning and Packaging Choices  00:17:58 - Dealing with Natural Ingredient Variations  00:19:15 - Packaging Changes and Supply Chain Issues  00:21:49 - Positive Changes and Art Collaboration  00:25:19 - Product Line and Daily Operations  00:33:11 - The Importance of Community and Diversity  00:34:08 - Collaboration and Appreciation for Local Artists  00:35:30 - Building Relationships and Personalizing the Space  00:38:22 - Helping Others Tell Their Stories  00:39:13 - Goals and Future Plans  SUPPORT: If you love this episode, please share it with someone you know will also enjoy it! Not for us, but for our guests, leave a review on iTunes. While you are listening, post a screenshot on social media and make sure to tag @FindingArizonaPodcast so we can thank you!  Leave us a five star review!  https://podcasts.apple.com/us/podcast/finding-arizona-podcast/id969100902?mt=2   Want to be a guest or a sponsor of the show? Send us a message on the https://www.findingarizonapodcast.com/contact  --- Send in a voice message: https://podcasters.spotify.com/pod/show/finding-arizona-podcast/message

Recorded Live at ASTE 2023, Lester Kovacs, Director of Ideation at Dorman Products, explains Dorman's unique approach to product development, including working closely with technicians, searching through junkyards for challenges, and conducting extensive testing. He also discusses supply chain issues, reaching out to their network for feedback, and upcoming products at Dorman. Lester Kovacs, Director of Ideation, Dorman Products Show Notes: Watch Full Video Uncovering Technician Challenges (00:04:02) Discussion on how Dorman works with technicians to uncover their challenges and develop solutions. Part Availability and Supply Chain Issues (00:05:31) Conversation about supply chain issues and challenges with part availability for older vehicles. The discovery of a new product category (00:08:31) Discussion about finding a new product category and the process of developing that particular product. The challenge of developing new products (00:11:00) Exploration of the challenges faced in developing new products and the need to work against the clock. Testing and validation of new products (00:12:58) Explanation of the testing and validation process for new products, including material testing, dimensional testing, and trial and test on actual vehicles. The incubator analogy (00:15:54) Discusses the role of the incubator in finding and developing ideas, identifying bottlenecks, and resource decisions. Percentage of ideas that make it (00:16:58) Discusses the percentage of ideas that make it through the validation process and the importance of a tight funnel to meet customer expectations. Lester's career journey (00:18:04) Explores Lester's background, starting from his love for cars as a kid. Changing Habits and Customer Perception (00:23:01) Discussion on the challenge of changing habits in the aftermarket industry and the need to shift customer perception of certain parts. Improving Marketing Strategy and Relaunching Products (00:23:25) Exploration of the relaunch of a product line after initial poor sales, including collaboration with customers and counter professionals to improve marketing and sales strategies. Suggestion for Website Enhancement (00:24:32) A suggestion to add a tab on the website to address why customers are not buying certain products, with testimonials and repair pictures to encourage sales. Thanks to our Partner, Dorman Products. Dorman gives people greater freedom to fix vehicles by constantly developing new repair solutions that put owners and technicians first. Take the Dorman Virtual Tour at www.DormanProducts.com/Tour Connect with the Podcast: -Join our Insider List: https://remarkableresults.biz/insider -All books mentioned on our podcasts:

       Did you know that up to one in four active-duty service members struggle to find sufficient nutritious food? In this eye-opening conversation, we're joined by Air Force Captain Dr. Sidney Zven, MD, who shares his groundbreaking research on food insecurity in the military. We discuss the often-unappreciated prevalence of this issue and its impact on recruitment, retention, and overall military readiness.   We also explore the challenges military families face in accessing crucial resources like the Supplemental Nutrition Assistance Program (SNAP) Women and Infants and Children (WIC) program, as well as the logistical issues that arise for those stationed overseas. We discuss the historical stigma surrounding food stamps and WIC and how Military Medicine is working to identify high-risk families and connect them with much-needed benefits. Don't miss this compelling episode that sheds light on a hidden crisis affecting our military families. Discover the potential for policy changes, the role nonprofit and governmental organizations can play in tackling this urgent problem, and the importance of nutrition education for the military community. Join us as we delve into the crucial issue of food insecurity and its impact on the health of our brave service members and their families.   Chapters: (0:00:00) - Combatting Food Insecurity in the Military (0:04:20) - Military Food Insecurity and Government Programs (0:15:55) - Military Families and WIC Challenges (0:19:32) - Military Food Insecurity and Historical Stigma   Chapter Summaries: (0:00:00) - Combatting Food Insecurity in the Military (4 Minutes)      We explore the critical issue of food insecurity in the military, discussing the challenges Service Members face and the innovative solutions and initiatives that Military Medicine is employing to combat this concern. Today we're joined by Air Force Captain Dr Sidney Zven, MD, who tells us about his pathway to medicine and his research into food insecurity in the military. The Department of Defense reported that up to 24% of military service members experienced food insecurity between October of 2020 and January 2021, in comparison to the 10.3% that is expected for the civilian population - one in four Active Duty Service Members may struggle to sufficient nutritious food for their families.     (0:04:20) - Military Food Insecurity and Government Programs (12 Minutes)    We explore the multifaceted issue of food insecurity in the military and how it impacts recruitment, retention, and overall military readiness. We discuss the prevalence of obesity as a contributing factor to military recruit shortage, the impact of food insecurity on families' decisions to stay in the military, and the link between food insecurity and elevated risk of anxiety and depression among military members. We also examine the impact of the COVID-19 pandemic on levels of food insecurity, the Women and Infants and Children (WIC) program, and other state and federal programs available to support service members.   (0:15:55) - Military Families and WIC Challenges (4 Minutes)   We discuss the difficulties encountered in enrolling in WIC and other logistical issues that can arise when dealing with military families, such as the disconnect between providers and local WIC offices, the burden placed on families to navigate the enrollment process, and the double appointments and wait times at WIC offices. We also discuss the process for families stationed overseas and the supply chain issues they may face when utilizing WIC benefits.   (0:19:32) - Military Food Insecurity and Stigma (7 Minutes) The historical stigma associated with receiving food stamps and WIC can be a major barrier to service members needing these resources. The military has made efforts to de-stigmatize these programs and provide more resources for military families. A study conducted at Walter Reed revealed that many families are unknowingly eligible for WIC. A unique approach is being implemented to identify high-risk military families and enroll them in these benefits.  We discuss the importance of nutrition education and how providing access to healthy and affordable food is essential for the well-being of military families. We look at how food insecurity can be addressed through policy changes and the role of governmental and nonprofit organizations in providing resources and support. We also examine the effects of food insecurity on service members' overall health and the importance of providing nutritional education to the military community.   Episode Keywords: Food Insecurity, Military, Active-Duty Service Members, Air Force Captain Dr. Sidney Zven, Multifaceted Impact, Women and Infants and Children (WIC) Program, Logistical Issues, Stigma, Military Medicine, Nutrition Education, Healthy and Affordable Food, Policy Changes, Mental Health, Recruitment, Retention, Military Readiness, Obesity, Anxiety, Depression, COVID-19, Double Appointments, Supply Chain Issues, Eligibility, High-Risk Families Hashtags: #WarDocs #Military #Medicine #Podcast #MilitaryFoodInsecurity #FeedingOurTroops #NourishingDefenders #WICProgram #CombattingHunger #FoodInsecuritySolutions   Honoring the Legacy and Preserving the History of Military Medicine The WarDocs Mission is to honor the legacy, preserve the oral history, and showcase career opportunities, unique expeditionary experiences, and achievements of Military Medicine. We foster patriotism and pride in Who we are, What we do, and, most importantly, How we serve Our Patients, the DoD, and Our Nation.   Find out more and join Team WarDocs at https://www.wardocspodcast.com/ Check our list of previous guest episodes at https://www.wardocspodcast.com/episodes Listen to the “What We Are For” Episode 47. https://bit.ly/3r87Afm WarDocs- The Military MedicinePodcast is a Non-Profit, Tax-exempt-501(c)(3) Veteran Run Organization run by volunteers. All donations are tax-deductible and go to honoring and preserving the history, experiences, successes, and lessons learned in Military Medicine. A tax receipt will be sent to you. WARDOCS documents the experiences, contributions, and innovations of all Military MedicineServices, ranks, and Corps who are affectionately called "Docs" as a sign of respect, trust, and confidence on and off the battlefield, demonstrating dedication to the medical care of fellow comrades in arms.     Follow Us on Social Media Twitter: @wardocspodcast Facebook: WarDocs Podcast Instagram: @wardocspodcast LinkedIn: WarDocs-The Military MedicinePodcast

Dan Gordon, SVP of Solutions Engineering with Redwood Logistics, and Geoff Lochausen, CRO of FreightWaves, will discuss how working together the two organizations have integrated the power of near real-time industry indices directly into supply chain data and operational systems and what this means for the industry. Follow FreightWaves Podcasts Follow the Future of Supply Chain Learn more about your ad choices. Visit megaphone.fm/adchoices

On this episode of REI Mastermind Network, host Jack Hoss welcomes guest Alex Jarbo to discuss the profitability and strategies behind building and investing in short-term rental properties. Alex shares their journey from exploring various asset classes to settling on real estate as a means of forced appreciation and long-term wealth potential. They dive into the specifics of building frame cabins, the average cost and profitability, and the importance of selecting the right general contractor (GC) and vetting them thoroughly. Alex emphasizes the significance of mentors in their success and offers practical tips on marketing and guest experience optimization. They also touch on the challenges faced during COVID and plans for expanding their real estate investments. This is a must-listen episode for anyone interested in the short-term rental market and looking for valuable insights from an experienced investor. Tune in for all this and more on REI Mastermind Network.

On this episode of DTC Pod, Blaine chats with Robbie Salter, one of the founding partners of Jupiter. Robbie shares his journey of creating innovative products and addressing the needs of both men and women. They discuss how to build a brand, starting from scratch, navigating supply chain issues to inventory management, building a CX flywheel, and the importance of having a mission greater than your product.We cover:1. Haircare innovation and product development2. Supply chain challenges and inventory management3. Building a brand strategy consultancy4. Investing in venture capital and startups5. Entrepreneurship and asking questions6. Customer experience and packaging7. Mental health advocacy and giving backTimestamps[00:05:40] Finding a problem worth solving[00:10:01] Developing dandruff care products[00:12:17] Embracing curiosity[00:16:00] Finding manufacturers[00:18:18] Decisions on product ingredients[00:22:56] Packaging vs product quality[00:26:57] Importance of customer experience, female perspective[00:33:09] Overcoming supply chain issues, prioritizing customers[00:36:56] Honesty and transparency[00:40:51] Focus on mental health[00:44:11] Nights and Weekends brand consultancy[00:47:53] Importance of trust in a partnershipRevolutionizing the Haircare Market:"We knew that better was possible. Something that felt a little bit more elevated. When you looked across the category, other categories, and you saw there was innovation being done, both from a packaging perspective, a formulation perspective, a messaging perspective."The Importance of Products Over Packaging:"At the end of the day, I don't think people really care about the package that they received... We knew that we had made the right decisions and that we were on to something good."Becoming a Successful Entrepreneur:"I think what makes a good entrepreneur, one of the qualities that makes a good entrepreneur is a great level of comfort looking stupid when asking questions, right?"Shownotes powered by CastmagicP.S. Get our pod highlights delivered directly to your inbox with the DTC Pod Newsletter!Episode brought to you by Finaloop, the real-time accounting service trusted by hundreds of DTC Brands. Try Finaloop free - no credit card required. Visit finaloop.com/dtcpod and get 14 days free and a 2-month P&L within 24 hours. Past guests & brands on DTC Pod include Gilt, PopSugar, Glossier, MadeIN, Prose, Bala, P.volve, Ritual, Bite, Oura, Levels, General Mills, Mid Day Squares, Prose, Arrae, Olipop, Ghia, Rosaluna, Form, Uncle Studios & many more. Additional episodes you might like:• #175 Ariel Vaisbort - How OLIPOP Runs Influencer, Community, & Affiliate Growth• #184 Jake Karls, Midday Squares - Turning Your Brand Into The Influencer With Content• #205 Kasey Stewart: Suckerz- - Powering Your Launch With 300 Million Organic Views• #219 JT Barnett: The TikTok Masterclass For Brands• #223 Lauren Kleinman: The PR & Affiliate Marketing Playbook• ​​​​#243 Kian Golzari - Source & Develop Products Like The World's Best Brands-----Have any questions about the show or topics you'd like us to explore further?Shoot us a DM; we'd love to hear from you.Want the weekly TL;DR of tips delivered to your mailbox?Check out our newsletter hereFollow us for content, clips, giveaways, & updates!DTCPod InstagramDTCPod TwitterDTCPod TikTokRobbie Salter - Co-CEO and Co-founder of Jupiter Ramon Berrios - CEO of Trend.ioBlaine Bolus - Co-Founder of Seated

Each industry has its own nuances. The chemicals industry is particularly very challenging because of its supply chain issues. The black swan events, such as winter storms or macroeconomic changes, can shake any model, regardless of how sophisticated it might be. But the more information you have about your operations, regardless of whether internal or external supply chain, the more prepared you are likely to be for such events. And even if you are not prepared, the data will help create the playbook and minimize the risks caused by these disruptions.In today's episode, our guest, Beth Schlitt, discusses the supply chain issues of the chemical industry. She shares several stories of recent disruptions and what supply chain leaders need to do to plan the risks. Finally, she shares her insights into how to plan for data governance in larger organizations and why companies must invest in modern technologies such as AI and machine learning.For more information on growth strategies for SMBs using ERP and digital transformation, visit our community at wbs.rocks or elevatiq.com. To ensure that you never miss an episode of the WBS podcast, subscribe on your favorite podcasting platform.

Supply chain issues, paper shortages, production problems, shipping delays, and increased labor costs; these are just some of the issues that our community of product-based business owners have faced over the last few years. The problems extend well beyond our community of makers in that they also affect our manufacturing partners, suppliers, and vendors that we work with.  Today, Ronnie Williams from DeFrance Printing is back on the podcast to share his insights. He and I chatted back in 2018 on episode 60 of Proof to Product about how to save money on printing costs and today he's back to give us an update on paper shortages, shifts in the printing industry, and what we can expect going forward.  Today's episode is brought to you by our Is Wholesale Right for You audio series! This free 12 part audio series will help you decide whether wholesale is a good next step for your specific business. After listening to this audio series, you'll know whether you want to pursue wholesale for your product business and you'll have the confidence and action steps to get started with wholesale. Sign up for the private podcast today! SIGN UP You can view full show notes and more at prooftoproduct.com/299 Connect with Ronnie Defranceprinting.com Instagram: @defranceprint Facebook: @DeFrancePrint Mentioned in this episode: Indigo Xante Kluge French Paper Neenah Paper Keaykolour Mohawk Paper  

We also talk about why some of their bikes look similar, the evolution of VPP suspension, and when we might see a new V10.