Podcast appearances and mentions of schmidt futures

Discusses Active Physical Intelligence, a model designed for real-time data collection and acquisition, which serves as an adaptive foundation.  Our guests today are the co-founders of KavAI: Tara Javidi and Sam Bigdeli.  Tara has been appointed as the inaugural holder of the Jerzy (George) Lewak Endowed Chair in the Jacobs School of Engineering at the University of California, San Diego (UCSD). Tara and UCSD have been selected to join the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a program of Schmidt Futures, to accelerate the next scientific revolution by applying AI to research in science, technology, engineering, and mathematics (STEM). Sam is the CEO at KavAI, which aims to revolutionize various industries, saving time, labor, and financial resources. He is also a founding advisor at XIRA Connect and a partner at Competitive Knowledge Inc., which invests in entrepreneurs with unique technologies and helps transform their visions into reality. Sam previously held the position of Chief Operating Financial Officer at Advanced MP Technology.  Additional resources: KavAI: https://www.kavai.com/ What is Active Physical Intelligence?: https://www.kavai.com/dev/active-physical-intelligence CITI Program's course catalog: https://about.citiprogram.org/course-catalog  

Syed K. Jamal Founder & CEO Board Member Ford Fellow Executive Producer WTIA Alum Measures what matters On a mission to transform education with creative economy Sponsors The Jason Cavness experience is brought to you by Breeze Docs. Request for Proposals AKA RFPs, can be very challenging for Small & Medium-sized Businesses. Breeze Docs, the RFP response platform of choice for SMBs across North America, uses AI to help companies quickly complete RFPs, security questionnaires, and other important business documents.  If you'd like to start winning more RFPs and reduce completion times by up to 80 percent, visit breezedocs.ai to book a demo. By mentioning the Jason Cavness Experience, you will qualify for a free upgrade from Breeze Solo to Breeze AI+ valued at $6,000. Follow the Breeze at www.breezedocs.ai Sign up for free upgrade here  https://www.breezedocs.ai/rfp-response-software-jason-caveness CavnessHR: Seattle's Got Tech Sign up to demo your tech and win prizes for being the best tech  https://docs.google.com/forms/d/e/1FAIpQLSdBV98Am90oAoP08vWaS870Uk7Zp7WVDCwF6PALwlJf5NgmWw/viewform?usp=header Go to www.thejasoncavnessexperience.com for the podcast on your favorite platforms Syed's Bio Syed is an Indian-American entrepreneur and strategic advisor, focused on empowering young people to make informed career decisions and fostering meaningful cross-cultural collaborations. As the Chairman of the Tacoma-Kochi Friendship City Committee, he leads efforts to strengthen film and educational partnerships between India and the United States. An executive producer at 222 Pictures and a trained filmmaker (Mass Communication Research Center, Jamia, New Delhi), Syed serves on the Board of Advisors for The Way Home: Journey of Family and Faith, a documentary exploring the resilience of three generations of Tibetan women striving to preserve their cultural heritage. Syed is also on the board of Tasveer, the only Oscar-qualifying South Asian Film Festival in the world. In this role, he is excited to build film institute partnerships to inspire and engage young people through film production and storytelling. With a dynamic career spanning media, higher education, and nonprofits in both India and the US, Syed brings a unique blend of creative vision and strategic expertise. He actively volunteers with the World Trade Center Tacoma as its India Ambassador, serves on the Board of Directors of the World Affairs Council of Tacoma, and mentors aspiring entrepreneurs through Bridge for Billions.  Additionally, he curates transformative impact projects for Collegey.com and evaluates student initiatives for Rise, a prestigious global talent program by Schmidt Futures and the Rhodes Trust. As a leader in organizational strategy, Syed drives innovation, builds high-impact partnerships, and ensures measurable client outcomes. His professional journey includes pivotal roles in media, academia, and international education, underpinned by his personal experience as an International Ford Foundation Fellow pursuing graduate studies in international affairs. This global perspective informs his vision for initiatives like Collegey and Branta, both of which aim to inspire and support the next generation of changemakers. In 2011, Syed joined the Fulbright Commission to advance the US Department of State's public diplomacy efforts through EducationUSA.  As Communications Manager, he led groundbreaking digital outreach campaigns, cultivated strategic partnerships, and conducted recruitment programs and workshops in collaboration with US Foreign Service Officers. Since transitioning from EducationUSA, Syed has consulted for leading youth and higher education organizations across India/South Asia, Southeast Asia, and the Middle East. In 2015, he founded Branta, a consulting firm that bridges global education and youth networks in the US and youth-centered initiatives in emerging markets. Syed's expertise lies at the intersection of the creative economy, public diplomacy, social entrepreneurship, and impact-driven programming. His passion for fostering global citizenship, project-based learning, and cross-cultural innovation continues to shape his contributions to the education and creative economy sectors.  We talk about the following and other items Syed's Background and Journey The Importance of Poetry and Nature Biking and Favorite Poets Cultural Differences in Poetry Empowering Youth in Career Decisions The Future of Higher Education The Role of College Tacoma's Transformation and Strengths The Creative Economy in Tacoma The Role of Nonprofits in Tacoma Becoming a Filmmaker The Power of Camera Angles in Filmmaking The Impact of Lighting on Perception Changes in the Filmmaking Industry The Evolution of Storytelling Humanizing Homelessness The Role of South Asian Film Festivals The Importance of Social Capital Religious and Cultural Practices in India The World Trade Center and International Trade I nnovation and Creativity Immigrating to the United States The Cost of Private Education The Value of Public Schools The Impact of Socioeconomic Disparities Originality and Courage in Creativity India-Pakistan Relations Introducing Grid City Studio Building Tacoma as a Creative Hub Engaging the Community  Syed's Social Media LinkedIn: https://www.linkedin.com/in/skjamal/ Personal Website: https://www.gobranta.com/ceofounder Syed's Advice   I am not very good at giving advice. I would say just, think about your story a lot. You have a story. Don't underestimate your story. Your story is a collective story of your parents, your neighborhood, your neighbors, your books. It's all part of your story, so don't underestimate your story. Please tell your story, talk about yourself, talk about, the environment you grew up in, things that bothers you. Talk about it. It matters a lot when we talk about our personal things. A lot of people, a lot of time people shy away, they avoid talking about themselves because they think it's showing off.  I don't think it's showing off. You are at your most authentic self when you just talk about your story as your story. So please don't underestimate your stories. We might pick up one of your stories and make a movie out of it.

Renaissance Philanthropy — in my opinion, the most exciting S&T philanthropic venture in the US — is getting a one-year check-in. Kumar Garg first appeared on the show right before I went on paternity leave, and now we're back for round two. Before founding Renaissance Philanthropy, Kumar worked in the Obama Office of Science and Technology Policy and spent time at Schmidt Futures. We discuss… How Renaissance ⁠catalyzed⁠ over $200 million in philanthropic funding in its first year, The goals of the organization and how it has responded to Trump's S&T funding cuts, What sets Renaissance apart from traditional philanthropic organizations, and lessons for China-focused research foundations, AI applications in education, from tutoring to dyslexia screening, Donor psychology, “portfolio regret,” and how to build trust within a philanthropic network. Thanks to ElevenLabs for sponsoring this episode. Check out the ElevenReader text-to-speech app here. Outro music: Mercy, Mercy, Mercy - Cannonball Adderley (YouTube Link) Learn more about your ad choices. Visit megaphone.fm/adchoices

Renaissance Philanthropy — in my opinion, the most exciting S&T philanthropic venture in the US — is getting a one-year check-in. Kumar Garg first appeared on the show right before I went on paternity leave, and now we're back for round two. Before founding Renaissance Philanthropy, Kumar worked in the Obama Office of Science and Technology Policy and spent time at Schmidt Futures. We discuss… How Renaissance ⁠catalyzed⁠ over $200 million in philanthropic funding in its first year, The goals of the organization and how it has responded to Trump's S&T funding cuts, What sets Renaissance apart from traditional philanthropic organizations, and lessons for China-focused research foundations, AI applications in education, from tutoring to dyslexia screening, Donor psychology, “portfolio regret,” and how to build trust within a philanthropic network. Thanks to ElevenLabs for sponsoring this episode. Check out the ElevenReader text-to-speech app here. Outro music: Mercy, Mercy, Mercy - Cannonball Adderley (YouTube Link) Learn more about your ad choices. Visit megaphone.fm/adchoices

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

Erin sits down with NCITE researcher Evan Perkoski, Ph.D., to discuss his team's research on terrorist recruitment trends. They also discuss his upcoming project, funded by Schmidt Futures, which will study how AI is impacting all aspects of terrorist organizations, including their marketing, financial, and training operations. Perkoski is an associate professor and director of undergraduate studies of political science at the University of Connecticut. Check out the NCITE team's recruitment research here: https://digitalcommons.unomaha.edu/cgi/viewcontent.cgi?article=1117&context=ncitereportsresearch

Tom Kalil is the CEO of Renaissance Philanthropy. He also served in the White House for two presidents (under Obama and Clinton); where he helped establish incentive prizes in government through challenge.gov; in addition to dozens of science and tech program. More recently Tom served as the Chief Innovation Officer at Schmidt Futures, where he helped launch Convergent Research. Matt Clancy is an economist and a research fellow at Open Philanthropy. He writes ‘New Things Under the Sun', which is a living literature review on academic research about science and innovation. We talked about: What is ‘influence without authority'? Should public funders sponsor more innovation prizes? Can policy entrepreneurship be taught formally? Why isn't ultra-wealthy philanthropy much more ambitious? What's the optimistic case for increasing US state capacity? What was it like being principal staffer to Gordon Moore? What is Renaissance Philanthropy? You can get in touch through our website or on Twitter. Consider leaving us an honest review wherever you're listening to this — it's the best way to support the show. Thanks for listening!

In this episode of Trending in Education, Kumar Garg, President of Renaissance Philanthropy, rejoins host Mike Palmer for his second appearance after first appearing in the Spring of 2021. The conversation delves into Garg's evolution from Schmidt Futures to launching Renaissance Philanthropy, and their work at the intersection of AI and learning science. We discuss the historical underfunding of education R&D compared to other sectors and explore the immense potential of AI in transforming learning experiences. The conversation covers the Learning Engineering Virtual Institute, the importance of interdisciplinary expertise, recent research with the Walton Family Foundation, and future ambitions for integrating cutting-edge technology into education. We also reference Renaissance's Pattern Language for High Impact Philanthropic Giving. Subscribe where you get your podcasts. Video versions now available on Youtube and Spotify. TIMESYAMPS 00:00 Welcome and Introduction 00:38 Kumar Garg's Journey and Renaissance Philanthropy 02:39 The Intersection of AI and Learning Science 05:45 Building "Bilingual" Teams for Educational Innovation 06:55 Renaissance's Bold Goals and Partnerships 08:44 Recent Initiatives and Future Directions 13:09 Challenges and Opportunities in AI for Education 27:34 The Importance of Trust and Equity in Educational Technology 33:22 Conclusion and Call to Action

To discuss America's comparative advantages in national competition and the structural forces that drive (and limit) innovation, ChinaTalk interviewed Kumar Garg.  Formerly an Obama official in the Office of Science and Technology Policy, Kumar spent several years at Schmidt Futures focusing on science and technology philanthropy. He has been a mentor and cheerleader for ChinaTalk over the years, and he is the president of the newly established Renaissance Philanthropy. We discuss: The inspiration behind Renaissance Philanthropy and its focus on mid-scale, field-transforming ideas Strategies for identifying underexplored, high-impact projects — including weather forecasting, carbon sequestration, and datasets on neurocognition Structural challenges for R&D funding at the level of government and universities The role of focused research organizations like OpenAI in accelerating progress and understanding long-term drivers of productivity A wide angle-view of US-China competition and strategic innovation The underresearched importance of alliance management. Outtro music: Song 1 - If ye love me - Thomas Tallis and the Cambridge Singers (Youtube Link) Song 2 - Recercare (I) - Francesco Spinacino and Robert Meunier (Youtube Link) Learn more about your ad choices. Visit megaphone.fm/adchoices

To discuss America's comparative advantages in national competition and the structural forces that drive (and limit) innovation, ChinaTalk interviewed Kumar Garg.  Formerly an Obama official in the Office of Science and Technology Policy, Kumar spent several years at Schmidt Futures focusing on science and technology philanthropy. He has been a mentor and cheerleader for ChinaTalk over the years, and he is the president of the newly established Renaissance Philanthropy. We discuss: The inspiration behind Renaissance Philanthropy and its focus on mid-scale, field-transforming ideas Strategies for identifying underexplored, high-impact projects — including weather forecasting, carbon sequestration, and datasets on neurocognition Structural challenges for R&D funding at the level of government and universities The role of focused research organizations like OpenAI in accelerating progress and understanding long-term drivers of productivity A wide angle-view of US-China competition and strategic innovation The underresearched importance of alliance management. Outtro music: Song 1 - If ye love me - Thomas Tallis and the Cambridge Singers (Youtube Link) Song 2 - Recercare (I) - Francesco Spinacino and Robert Meunier (Youtube Link) Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of Moments to Movements, we delve into the impact of the Sustainable Development Goals (SDGs), particularly focusing on SDG #4: Quality Education. Our guests, Nathan Baek and Mohammad Shehadat, share their experiences and insights as young leaders dedicated to creating meaningful change in the realm of education.You'll learn about:Nathan Baek's journey as the founder of the Microphone Initiative, where he specializes in teaching the SDGs, combating age-based discrimination, and giving youth a voice on a global stage.Mohammad Shehadat's unique perspective as a peacebuilding and youth activist, shaped by his experiences as a Syrian refugee. Mohammad discusses the challenges faced by asylum seekers in accessing education and how he is using his platform to advocate for education as a tool for peace and development.Discover more about Nathan and Mohammad and their impactful work:Follow Nathan Baek on LinkedIn, and learn more about Microphone Initiative by visiting their website. Nathan was also selected as a Rise Global Winner in 2022 for his work in Quality Education. You can learn more about Rise, an initiative of Schmidt Futures and the Rhodes Trust, here. You can learn more about Mohammad Shehadat in the three article links below.How Mohammad is helping Syrian refugees resume their education & gain new skills | UNESCOFrom Syrian refugee to global youth leader: The inspiring story of Mohammad Shehadat | UNESCOIntersectional Peacebuilding: An interview with Mohammad Shehadat | UNOYMoments to Movements is presented by Peace First.It was produced and edited by Ernesto Chavezvaldivia. Researched with help from Nadia Posada.

In this conversation, Puja Mehra talks to Dr. Shruti Rajagopalan about the historical context of the 1991 Economic Liberalisation of India. She illustrates how the economy in india worked through the manufacture of a bicycle and goes on to explain the impact of those economic reforms, the careful planning that went into it, the people who brought it to fruition, the political turmoil at the time and much more.About Dr. Shruti Rajagopalan: Dr. Shruti Rajagopalan is a Senior Research Fellow at the Mercatus Center at George Mason University, where she leads the Indian Political Economy Program and Emergent Ventures India. She is also a Fellow at the Classical Liberal Institute at NYU School of Law and an Innovation Fellow with Schmidt Futures. Dr. Rajagopalan's research interests include law and economics, public choice theory, and constitutional economics, with her work published in various academic journals and media outlets such as The New York Times, Financial Times, Wall Street Journal, Project Syndicate, Bloomberg, Real Clear Politics, Mint, The Hindu: Business Line, and The Indian Express. She hosts the Ideas of India podcast and writes the Get Down and Shruti substack on Indian political economy and culture.SHOW NOTES(01:04) Interview starts(03:57) The humble bicycle(06:49) The license stack for starting a bike shop(13:32) License convolution(19:37) Wartime controls led to central planning(22:44) How would License Raj unravel(25:17) How the 1991 political crisis came to be(27:57) Finance ministers of the time(30:14) The Assassination of Rajiv Gandhi and it consequences(34:15) The team that liberalised India(36:09) The Devaluation of the Rupee(39:22) Fixing Imports and Exports(41:53) The Careful Planning of the Economic Reforms(47:50) The Advantage of Small Firms(50:46) FDIs and foreign expertise(54:10) The far reaching impacts of the Economic Reforms(58:02) The Case Study of India as a blueprint for Economic ReformsFor more of our coverage check out thecore.inSubscribe to our NewsletterFollow us on:Twitter | Instagram | Facebook | Linkedin | Youtube

On Episode 7 of "Practical History" I chat with Nick Cohen of the philanthropic organization Schmidt Futures. Nick's graduate training in history has helped him run the company's programs designed to identify and support the world's top talent in science and tech, and to harness their superpowers for the public good. Nick shares how he has translated the insights from his MA thesis to design and evaluate the international programs he manages, why he sees science and culture as inseparable, and what he found most exciting—and surprising—about working on a team that helped the journalist Fareed Zakaria research his forthcoming book, The Age of Revolutions. We also talk about why history departments should go beyond acknowledging non-academic career pathways for their students and celebrate those pathways instead. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

On Episode 7 of "Practical History" I chat with Nick Cohen of the philanthropic organization Schmidt Futures. Nick's graduate training in history has helped him run the company's programs designed to identify and support the world's top talent in science and tech, and to harness their superpowers for the public good. Nick shares how he has translated the insights from his MA thesis to design and evaluate the international programs he manages, why he sees science and culture as inseparable, and what he found most exciting—and surprising—about working on a team that helped the journalist Fareed Zakaria research his forthcoming book, The Age of Revolutions. We also talk about why history departments should go beyond acknowledging non-academic career pathways for their students and celebrate those pathways instead. Learn more about your ad choices. Visit megaphone.fm/adchoices

Dr. Britt Wray is a science communicator and the author of two books. Her latest is Generation Dread: Finding Purpose in an Age of Climate Anxiety, which is a national bestseller. Dr. Wray is also the director of CIRCLE (Community-minded Interventions for Resilience, Climate Leadership, and Emotional wellbeing) at Stanford Psychiatry, a research and action initiative in the Stanford School of Medicine. Her first book, the Rise of the Necrofauna: The Science, Ethics, and Risks of De-Extinction was named a best book of 2017 by the New Yorker. She most recently is a top award winner of the Eric and Wendy Schmidt Awards for Excellence in Science Communications, which was bestowed upon her by the National Academies in partnership with Schmidt Futures.Climate change evokes a myriad of emotions unique to each individual. It can stir outrage in some, sadness in others, a sense of helplessness for some, and dread for the future in others. There is no universally right or wrong reaction, as our responses are shaped by our distinct relationships with the world and the diverse circumstances in which we live. The perception of climate change varies; for some, it may feel abstract, while for others, the impacts are undeniably profound and far-reaching.But as Dr. Wray points out, we know that climate change as we are experiencing it is anthropogenic, meaning it's the result of human behavior. And yet so little has been studied about the human behavioral response to climate change. How do we individually and collectively feel about climate change, and what do those feelings drive us to do? This is the sweet spot of Britt's work.In this episode, we cover: An overview of Dr. Wray's research on climate distressHer work as the Director of CIRCLE (Community-minded Interventions for Resilience, Climate Leadership, and Emotional Wellbeing) at Stanford PsychiatryAn overview of climate anxiety and its impact on peopleThe concept of solastalgia and broken record, record breakingThe importance of community and social connections in addressing climate anxietyThe need for evaluation and evidence-based interventions for climate anxietyIncluding behavioralists and psychologists when addressing climate changeThe potential role of guilt in motivating action on climate changeThe impact of climate change on reproductive decisions and parentingDr. Wray's book and newsletterThe importance of open and vulnerable conversations about climate changeEpisode recorded on Jan 29, 2024 (Published on Feb 26, 2024) Get connected with MCJ: Jason Jacobs X / LinkedInCody Simms X / LinkedInMCJ Podcast / Collective / YouTube*If you liked this episode, please consider giving us a review! You can also reach us via email at content@mcjcollective.com, where we encourage you to share your feedback on episodes and suggestions for future topics or guests.

Lydia Logan is the Vice President of Global Education and Workforce Development, Corporate Social Responsibility at IBM, where she leads IBM's community and university skilling initiatives that create more inclusive and effective schools and workforces. Her programs help fulfill IBM's pledges to skill 30 million people worldwide by 2030, and to train two million learners in AI through 2026, particularly those from historically underresourced, underserved, and underrepresented communities. She also develops and manages strategic global partnerships with IBM's clients, non-profit organizations, government, and content and curriculum developers that relate to education and career readiness. For this role, she applies her decades of leadership and programmatic expertise in the realms of philanthropy, education, public policy, and economic development. These experiences inform the strategic development and execution of acclaimed global career readiness programs, particularly IBM SkillsBuild.   Prior to IBM, Lydia successfully spearheaded education initiatives while serving in senior leadership roles at Verizon, the Eli and Edythe Broad Foundation, and Kimsey Foundation.In addition, she was VP and executive director of the Institute for a Competitive Workforce at the U.S. Chamber of Commerce, where she led national policy and program initiatives to improve education and workforce development.Earlier in her career, she led Chiefs for Change, a national membership organization of Chief State School Officers.Recommended Resources:IBM SkillsBuildPrincipled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4 by John BaileyTools Competition by Schmidt Futures

Nonprofitnewsfeed.com   Nonprofit Sector Confronts International Aid Challenges and Navigates Donor Dynamics In this week's episode of the Nonprofit News Feed by Whole Whale, hosts George and Nick delve into pressing issues within the nonprofit world, including the complexities of the USAID food program, philanthropic trends in New York City, and the unpredictable nature of billionaire-backed philanthropy. USAID Food Aid Under Scrutiny The episode kicks off with a critical look at the U.S. international food aid program. An NPR investigation revealed that Catholic Relief Services discovered rotting grain intended for Haiti, spotlighting inefficiencies in non-emergency food aid delivery. Current legislation requires non-emergency aid from USAID to be sourced from U.S. suppliers, but experts argue for more regional and direct cash assistance approaches. The Biden administration is pushing for reforms in the upcoming farm bill to address these stringent restrictions, highlighting the tension between international development professionals and American farmers. Wealthy Donors Pulling Back in NYC The conversation shifts to New York City, where wealthy donors are reportedly hesitating to contribute to the city's escalating problems, including homelessness and the migrant crisis. Mayor Eric Adams' emphasis on the severity of these issues without federal aid is speculated to be discouraging donors, underscoring the need for hopeful messaging to inspire philanthropic investment. The hosts reflect on the importance of nonprofits in the city and the potential impact of donor withdrawal on their operations. Schmidt Futures: A Cautionary Tale of Philanthropic Instability The episode also examines the case of Schmidt Futures, the philanthropic arm of former Google CEO Eric Schmidt, as reported by Forbes. The organization's sudden program shifts and leadership changes exemplify the volatility that can arise when nonprofits rely heavily on individual billionaire donors. The hosts discuss the broader implications for the sector and the necessity of recognizing these dependencies as potential risks. GLAAD's Emmy Recognition for LGBTQ+ Advocacy Ending on a positive note, the hosts celebrate GLAAD's recognition at the Emmys for its advocacy work in the LGBTQ+ community. Amidst challenging times for trans rights, the Academy's accolade highlights the influence of media representation and GLAAD's critical role in shaping narratives. Closing Thought: The Power of Nonprofits in Shaping Narratives The episode concludes with a reflection on the power of nonprofits, not only in addressing immediate needs but also in influencing societal perspectives through storytelling and media consultation. The joke shared between the hosts adds a light-hearted touch, reinforcing the community spirit that underpins the nonprofit sector. In Summary: This episode underscores the complex relationship between policy, philanthropy, and nonprofit impact, offering a nuanced perspective on current challenges and the evolving landscape of aid and donor engagement.

Nonprofitnewsfeed.com   Nonprofit Sector Confronts International Aid Challenges and Navigates Donor Dynamics In this week's episode of the Nonprofit News Feed by Whole Whale, hosts George and Nick delve into pressing issues within the nonprofit world, including the complexities of the USAID food program, philanthropic trends in New York City, and the unpredictable nature of billionaire-backed philanthropy. USAID Food Aid Under Scrutiny The episode kicks off with a critical look at the U.S. international food aid program. An NPR investigation revealed that Catholic Relief Services discovered rotting grain intended for Haiti, spotlighting inefficiencies in non-emergency food aid delivery. Current legislation requires non-emergency aid from USAID to be sourced from U.S. suppliers, but experts argue for more regional and direct cash assistance approaches. The Biden administration is pushing for reforms in the upcoming farm bill to address these stringent restrictions, highlighting the tension between international development professionals and American farmers. Wealthy Donors Pulling Back in NYC The conversation shifts to New York City, where wealthy donors are reportedly hesitating to contribute to the city's escalating problems, including homelessness and the migrant crisis. Mayor Eric Adams' emphasis on the severity of these issues without federal aid is speculated to be discouraging donors, underscoring the need for hopeful messaging to inspire philanthropic investment. The hosts reflect on the importance of nonprofits in the city and the potential impact of donor withdrawal on their operations. Schmidt Futures: A Cautionary Tale of Philanthropic Instability The episode also examines the case of Schmidt Futures, the philanthropic arm of former Google CEO Eric Schmidt, as reported by Forbes. The organization's sudden program shifts and leadership changes exemplify the volatility that can arise when nonprofits rely heavily on individual billionaire donors. The hosts discuss the broader implications for the sector and the necessity of recognizing these dependencies as potential risks. GLAAD's Emmy Recognition for LGBTQ+ Advocacy Ending on a positive note, the hosts celebrate GLAAD's recognition at the Emmys for its advocacy work in the LGBTQ+ community. Amidst challenging times for trans rights, the Academy's accolade highlights the influence of media representation and GLAAD's critical role in shaping narratives. Closing Thought: The Power of Nonprofits in Shaping Narratives The episode concludes with a reflection on the power of nonprofits, not only in addressing immediate needs but also in influencing societal perspectives through storytelling and media consultation. The joke shared between the hosts adds a light-hearted touch, reinforcing the community spirit that underpins the nonprofit sector. In Summary: This episode underscores the complex relationship between policy, philanthropy, and nonprofit impact, offering a nuanced perspective on current challenges and the evolving landscape of aid and donor engagement.

Sydney Skybetter sits down with choreorobotics innovator, Dr. Catie Cuan. They discuss her personal and professional trajectory, and try to answer the question: why dance with a robot? About Catie: An engineer, researcher, and artist, Dr. Catie Cuan is a pioneer in the nascent field of ‘choreorobotics' and works at the intersection of artificial intelligence, human-robot interaction, and art.  She is currently a Postdoc in Computer Science at Stanford University. Catie recently defended her PhD in robotics via the Mechanical Engineering department at Stanford, where she also completed a Master's of Science in Mechanical Engineering. The title of her PhD thesis is “Compelling Robot Behaviors through Supervised Learning and Choreorobotics”, which was funded by the National Institutes of Health, Google, and Stanford University. During her PhD, she led the first multi-robot machine learning project at Everyday Robots (Google X) and Robotics at Google (now a part of Google Deepmind). She has held artistic residencies at the Smithsonian, Everyday Robots (Google X), TED, and ThoughtWorks Arts. Catie is a prolific robot choreographer, having created works with nearly a dozen different robots, from a massive ABB IRB 6700 industrial robot to a tabletop IDEO + Moooi robot. Catie is also a 2023 International Strategy Forum (ISF) fellow at Schmidt Futures and the former co-founder of caali, an embodied media company. Read the transcript, and find more resources in our archive: https://www.are.na/choreographicinterfaces/dwr-ep-6-irl-a-conversation-with-choreoroboticist-catie-cuan Like, subscribe, and review here: https://podcasts.apple.com/us/podcast/dances-with-robots/id1715669152  What We Discuss with Catie (Timestamps): 0:00:15: Introduction to Dr. Catie Cuan 0:02:23: Catie's PhD thesis on supervised learning for compelling robot behaviors. 0:03:19: How Catie balanced her dance career with her work in tech. 0:05:35: The skepticism and terror of bringing dance into a STEM environment. 0:06:20: Navigating elite STEM environments as a woman of color. 0:07:41: The history of dance and robotics at Stanford University 0:11:56: Contrasts between STEM and embodied practices. 0:12:44: Catie's relationship with the CRCI community. 0:13:30: The importance of artists in contemplating the meaning of new technologies. 0:14:31: Challenges of creating a complex dance performance with robots. 0:16:24: Lack of templates for realizing installation, performance, and robotics research. 0:19:58: Safety considerations and rules for performing with robots. 0:20:51: Why Boston Dynamics Spot robots and their expressive capabilities. 0:23:32: Contemplating the ethical implications of robot applications. 0:25:27: The future of Choreo Robotics and the importance of imagination. 0:26:00: Dance's role in depicting a universe of creativity and joy. 0:27:35: Choreographers are essential for successful deployment of robots. 0:28:26: Robot dances becoming more prevalent in various contexts. 0:30:04: Dance is essential to culture and human identity. 0:31:20: Dancing with robots is not a novel concept. 0:32:00: Show credits & thanks The Dances with Robots Team Host: Sydney Skybetter Co-Host & Executive Producer: Ariane Michaud Archivist and Web Designer: Kate Gow Podcasting Consultant: Megan Hall Accessibility Consultant: Laurel Lawson Music: Kamala Sankaram Audio Production Consultant: Jim Moses Assistant Editor: Andrew Zukoski Student Associate: Rishika Kartik About CRCI The Conference for Research on Choreographic Interfaces (CRCI) explores the braid of choreography, computation and surveillance through an interdisciplinary lens. Find out more at www.choreographicinterfaces.org Brown University's Department of Theatre Arts & Performance Studies' Conference for Research on Choreographic Interfaces thanks the Marshall Woods Lectureships Foundation of Fine Arts, the Brown Arts Institute, and the Alfred P. Sloan Foundation for their generous support of this project. The Brown Arts Institute and the Department of Theatre Arts and Performance Studies are part of the Perelman Arts District.  

David Shacklette is the Product Manager for the Harvard Skills Lab, a Schmidt Futures funded research initiative and startup that designs performance-based assessment tools that can be used by universities, businesses, and individuals to provide a clearer picture of the foundational skills (sometimes called “soft skills”) required for individuals and teams to succeed in the labor market. Prior to joining the Skills Lab, David has held product roles at Fortune Magazine, where most notably he launched and scaled Fortune's first education vertical (fortune.com/education) in partnership with 2U, and has previously held a variety of operational and leadership roles in venture capital and early-stage startups in the Bay Area. David holds a Master's degree in Symbolic Systems from Stanford University, where he focused on topics in the fields of Educational Neuroscience and AI.Recommended Resources:https://www.skillslab.dev/game-libraryForked Lightning by David DemingGet ready to explore the future of education! Join Edtech Insiders for a virtual conference featuring 30+ of the top voices shaping the future of Al + Education. A full day of keynote speakers, panel discussions, and networking!Register now here: AI+EDU Virtual Conference

Tier two (R2) research and smaller institutions, including two-year, minority-serving, and tribal colleges, can now build solid research infrastructures and perform groundbreaking discoveries through research enterprises on the same scale as larger R1 and flagship universities. In this episode of Changing Higher Ed®, Drumm speaks with Sethuraman Panchanathan, Director of the National Science Foundation (NSF). They discuss how his organization helps democratize ideas in higher education, enabling all colleges and universities to solve real-world problems and revitalize their communities. The NSF achieves this through programs like the Nationally Transformative Equity and Diversity (GRANTED) and Enabling Partnership to Increase Innovation Capacity (EPIIC). Dr. Panch also discusses NSF's mission and vision. He talks about its recent $44 million program that helps fund projects across the US. Additionally, Drumm refers to another NSF program as "a tech transfer on steroids." Moreover, they explore what smaller institutions with few resources need to do to start conducting research.   Podcast Highlights NSF's Regional Innovation Engines is a $44 million investment that partners with communities to utilize regional potentials like the Hazleton pilot converting hemp into carbon-negative building materials through collaboration with Penn State University and community colleges. The cross-cutting TIP Directorate pulls discoveries into the industry, creating impactful solutions by fostering partnerships and bringing back new ideas to address real-world problems. GRANTED and EPIIC programs support the growth of research infrastructure and capacity at national and minority-serving institutions, enhancing access to resources and regional innovation ecosystems. NSF's strategic focus includes research, education, partnerships, and research infrastructures, with initiatives like BP Innovate, EDU Racial Equity in STEM, and the Robert Noyce Teacher Scholarship Program to promote inclusion and quality in STEM education.   NSF partners with organizations like the Bill and Melinda Gates Foundation, Schmidt Futures, and the Walton Family Foundation to improve the quality of US STEM education for all students. GRANTED provides investment in research infrastructure, and institutions can reach out to the program coordinator to present competitive ideas and connect with successful participating institutions.    Read the transcript →   About Our Podcast Guest The Honorable Sethuraman Panchanathan is the 15th director of the U.S. National Science Foundation (NSF), nominated by the President in 2019 and confirmed by the U.S. Senate in 2020. With over three decades of experience, he is a leader in science, engineering, and education. Before joining NSF, Panchanathan served as the executive vice president of the Arizona State University (ASU) Knowledge Enterprise, where he significantly advanced research innovation and strategic partnerships. His scientific contributions have earned him numerous awards, including Honorary Doctorates and the IEEE-USA Public Service Award. Panchanathan's leadership extends to various interagency councils and committees, including the National Advisory Council on Innovation and Entrepreneurship and the Interagency Arctic Research Policy Committee. He is also known for his extensive publication record and mentorship of over 150 graduate students, postdocs, and research scientists. Panchanathan is a fellow of multiple prestigious academies and societies, including the National Academy of Inventors and the American Association for the Advancement of Science. He is married to Sarada "Soumya" Panchanathan, an academic pediatrician and informatician, and they have two adult children, Amritha and Roshan.   About the Host  Dr. Drumm McNaughton, the host of Changing Higher Ed®, is a consultant to higher ed institutions in governance, accreditation, strategy and change, and mergers. To learn more about his services and other thought leadership pieces, visit his firm's website: https://changinghighered.com/.   The Change Leader's Social Media Links   LinkedIn: https://www.linkedin.com/in/drdrumm/ Twitter: @thechangeldr Email: podcast@changinghighered.com   #ChangingHigherEd #HigherEdResearch #HigherEdPodcast

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: Who Was the Funder that Counterfactually Resulted in LEEP Starting?, published by Joey on July 4, 2023 on The Effective Altruism Forum. Lead Exposure Elimination Project (LEEP) is an outstanding Charity Entrepreneurship-incubated charity recognized externally for its impactful work by RP, Founders Pledge, Schmidt Futures, and Open Philanthropy. It's one of the clearest cases of new charities having a profound impact on the world. However, everything is clear in hindsight; it now seems obvious that this was a great idea and team to fund, but who funded LEEP at the earliest stage? Before any of the aforementioned bodies would have considered or looked at them, who provided funding when $60k made the difference between launching and not existing? The CE Seed Network, so far, has been a rather well-kept secret. They are the first people to see each new batch of CE-incubated charities and make a decision on whether and how much to support them. A handful of donors supported LEEP in its earliest days, culminating in the excellent charity we see today. Some of them donated anonymously, never seeking credit or the limelight, just quietly making a significant impact. Others engaged deeply and regularly with the team, eventually becoming trusted board members. Historically, the Seed Network has been a small group (~30) of primarily E2G-focused EAs, invited by the CE team or alumni from the CE program to join. However, now we are opening it up for expressions of interest for those who might want to join in future rounds. Our charity production has doubled (from 5 to 10 charities a year) and although our Seed Network has grown, there is still room for more members to join to support our next batches of charities. We have now created a website to describe how it works. On that website, there's an application form for those who might be a good fit to be a member in the future. It's not a great fit for everyone as it focuses on the CE (near-termist) cause areas and donors who could donate over $10k a year to new charities and can make a decision on whether and whom to fund with how much in a short period of time when we send out the newest project proposals (~9 days). But for those who fit, we think it's one of the most impactful ways to donate. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org

Lead Exposure Elimination Project (LEEP) is an outstanding Charity Entrepreneurship-incubated charity recognized externally for its impactful work by RP, Founders Pledge, Schmidt Futures, and Open Philanthropy. It's one of the clearest cases of new charities having a profound impact on the world. However, everything is clear in hindsight; it now seems obvious that this was a great idea and team to fund, but who funded LEEP at the earliest stage? Before any of the aforementioned bodies would have considered or looked at them, who provided funding when $60k made the difference between launching and not existing? The CE Seed Network, so far, has been a rather well-kept secret. They are the first people to see each new batch of CE-incubated charities and make a decision on whether and how much to support them. A handful of donors supported LEEP in its earliest days, culminating in the excellent charity we see today. Some of them donated anonymously, never seeking credit or the limelight, just quietly making a significant impact. Others engaged deeply and regularly with the team, eventually becoming trusted board members. Historically, the Seed Network has been a small group (~30) of primarily E2G-focused EAs, invited by the CE team or alumni from the CE program to join. However, now we are opening it up for expressions of interest for those who might want to join in future rounds. Our charity production has doubled (from 5 to 10 charities a year) and although our Seed Network has grown, there is still room for more members to join to support our next batches of charities. We have now created a website to describe how it works. On that website, there's an application form for those who might be a good fit to be a member in the future. It's not a great fit for everyone as it focuses on the CE (near-termist) cause areas and donors who could donate over $10k a year to new charities and can make a decision on whether and whom to fund with how much in a short period of time when we send out the newest project proposals (~9 days). But for those who fit, we think it's one of the most impactful ways to donate.--- First published: July 4th, 2023 Source: https://forum.effectivealtruism.org/posts/t6JzBxtrXjLRufE8o/who-was-the-funder-that-counterfactually-resulted-in-leep --- Narrated by TYPE III AUDIO. Share feedback on this narration.

This post is a summary of some of my work as a field strategy consultant at Schmidt Futures' Act 2 program, where I spoke with over a hundred experts and did a deep dive into antimicrobial resistance to find impactful investment opportunities within the cause area. The full report can be accessed here.Antimicrobials, the medicines we use to fight infections, have played a foundational role in improving the length and quality of human life since penicillin and other antimicrobials were first developed in the early and mid 20th century.Antimicrobial resistance, or AMR, occurs when bacteria, viruses, fungi, and parasites evolve resistance to antimicrobials. As a result, antimicrobial medicine such as antibiotics and antifungals become ineffective and unable to fight infections in the body.AMR is responsible for millions of deaths each year, more than HIV or malaria (ARC 2022). The AMR Visualisation Tool, produced by Oxford University and IHME, visualises IHME data which finds that 1.27 million deaths per year are attributable to bacterial resistance and 4.95 million deaths per year are associated with bacterial resistance, as shown below.Source:https://forum.effectivealtruism.org/posts/W93Pt7xch7eyrkZ7f/cause-area-report-antimicrobial-resistanceNarrated for the Effective Altruism Forum by TYPE III AUDIO.Share feedback on this narration.

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: [Linkpost] Longtermists Are Pushing a New Cold War With China, published by Mohammad Ismam Huda on May 27, 2023 on The Effective Altruism Forum. Jacob Davis, a writer for the socialist political magazine Jacobin, raises an interesting concern about how current longermist initiatives in AI Safety are in his assessment escalating tensions between the US and China. This highlights a conundrum for the Effective Altruism movement which seeks to advance both AI Safety and avoid a great power conflict between the US and China. This is not the first time this conundrum has been raised which has been explored on the forum previously by Stephen Clare. The key points Davis asserts are that: Longtermists have been key players in President Biden's choice last October to place heavy controls on semiconductor exports. Key longtermist figures advancing export controls and hawkish policies against China include former Google CEO Eric Schmidt (through Schmidt Futures and the longtermist political fund Future Forward PAC), former congressional candidate and FHI researcher Carrick Flynn, as well as other longtermists in key positions at Gerogetown Center for Security and Emerging Technology and the RAND Corporation. Export controls have failed to limit China's AI research, but have wrought havoc on global supply chains and seen as protectionist in some circles. I hope this linkpost opens up a debate about the merits and weaknesses of current strategies and views in longtermist circles. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.

In this episode, Radar podcast host Steven Van Belleghem and his #nexxworks friends Peter Hinssen, Pascal Coppens, Julie Vens - De Vos and Laurence Van Elegem discuss generative AI's data problem, private company versions of ChatGPT, Drake, Grimes, Twitter, TikTok, Walmart versus Amazon, Schmidt Futures and AI investment strategies, our Never Normal Tour with Mediafin in New York (guided by nexxworks Founder Peter Hinssen and General Editor at 'De Tijd' Isabel Albers), the human energy crisis, Apple's new high-yield savings account with a whopping 4.15% interest rate, its Buy Now Pay Later services, the return of (travel in) China, the EV price war, Chinese EV car company BYD successes, CATL's next-generation sodium-ion battery, youth unemployment in China, inflation going down in China, why some companies are looking for old steel warships, the power of proximity, the end of Buzzfeed news and much, much more. Shownotes: You can check the Amazon and Walmart chart Julie was talking about here. The website haveibeentrained.com allows artists to opt-in or opt-out of AI training. Here is the link to the website with the latest AI hits. www.heygen.com is where you can upload an avatar of yourself and create a video. ai.syllaby.io will help you write a script for your video. Here is Steven and Pascal's video about Tesla and BYD. Check our awesome Never Normal Tour with Mediafin in New York here. Enjoy! For more inspiration about business and technology, go to nexxworks.com. Want to learn more about our learning and inspiration programs? Visit https://www.nexxworks.com/experiences/upcoming-experiences.

On this podcast, we strive to connect fascinating and successful people to the next generation. But today, I'd like to change it up a bit and, in partnership with the Rise initiative, highlight some of the fascinating and successful people of my generation.Throughout the past few weeks, I've been talking with winners of the Rise Challenge from various years. For the finale of this trilogy, I'll be speaking with Tony Wang. For his Rise project, Tony developed an AI tool to address pharmaceutical monopolization.Rise is a program that finds promising young people and provides "opportunity for life as they work to serve others." An initiative of Schmidt Futures and the Rhodes Trust, Rise is the anchor program of a $1 billion commitment from Eric and Wendy Schmidt to find and support global talent.Topics:How Tony tackled the monopolization of healthcare research by addressing anti-biotic resistanceThe process: How did you build this?How to break down large projects into manageable piecesWhat is the future of this project?"What books have had an impact on you?""What advice do you have for other young people?"Tony Wang is a Chinese-American advocate living in the United States. Tony hopes to democratize medical research and create equality in healthcare, especially by addressing AI bias. For his Rise project, Tony developed an AI tool to address pharmaceutical monopolization, for which he was named an International Science & Engineering Fair (ISEF) Finalist. Tony hopes to create sustainable, ethical AI systems to fight for marginalized groups, especially racial minorities and the LGBTQIA+ community.Socials! -Lessons from Interesting People substack: https://taylorbledsoe.substack.com/Website: https://www.aimingforthemoon.com/Instagram: https://www.instagram.com/aiming4moon/Twitter: https://twitter.com/Aiming4MoonFacebook: https://www.facebook.com/aiming4moonTaylor's Blog: https://www.taylorgbledsoe.com/YouTube: https://www.youtube.com/channel/UC6 

Google doesn't tell its employees how to innovate; it manages their inventive chaos. Their secret? Mix free-flowing ideas with disciplined decision-making. In this week's All Star Episode, former Google CEO Eric Schmidt shares his strategies to manage chaos. CEO of Google from 2001-2015, and now the co-founder of Schmidt Futures, Schmidt reveals the hidden secret in Google's famous “20% time” policy, their approach to hiring smart creatives, and the parallels between leading Google and piloting small airplanes. Plus, the decision he made to support a crazy idea that he was certain would bankrupt the company“ALL STAR EPISODES” are filled with the transformative, unconventional wisdom that you've come to know from Masters of Scale. Have an idea for an All Star Episode from our library? Let us know at hello@mastersofscale.com.Read a transcript of this episode: https://mastersofscale.com/Subscribe to the Masters of Scale weekly newsletter at http://eepurl.com/dlirtXSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

On this podcast, we strive to connect fascinating and successful people to the next generation. But today and throughout March, I'd like to change it up a bit and, in partnership with the Rise initiative, highlight some of the fascinating and successful people of my generation. Throughout this month, I'll be talking with three of the winners of the Rise Challenge from various years. For part two of this trilogy, I'll be speaking with Rishabh "Rishi" Ambavanekar. For his Rise project, he built a low-cost, brain-computer interface (BCI) to help stroke victims communicate via translation of their inner dialogue. Rise is a program that finds promising young people and provides "opportunity for life as they work to serve others." An initiative of Schmidt Futures and the Rhodes Trust, Rise is the anchor program of a $1 billion commitment from Eric and Wendy Schmidt to find and support global talent.Topics:How overcoming OCD and his dad's TIA inspired Rishi to build an inner speech translator for stroke victimsHow to research and learn material outside your comfort zoneHow to deal with the "dauntingness" of new topicsUtilizing “inner speech” to build brain-computer interface (BCI)The future of his projectAdvice to other young innovators tackling intimidating projects"What books and media have inspired you?""What advice do you have for other young people?"Rishi Ambavanekar is an inventor and scientist from the US. After overcoming OCD, he grew passionate about neuroscience. Upon learning about his father's transient ischemic attack (TIA), he decided to focus on supporting stroke recovery. For his Rise project, he built a low-cost, brain-computer interface (BCI) to help stroke victims communicate via translation of their inner dialogue. Rishi is also proud to be named a 2022 ISEF finalist, FTC innovation award semifinalist, and an avid app developer. In the future, he plans to pursue a PH.D. and start a business.Socials! -Lessons from Interesting People substack: https://taylorbledsoe.substack.com/Website: https://www.aimingforthemoon.com/Instagram: https://www.instagram.com/aiming4moon/Twitter: https://twitter.com/Aiming4MoonFacebook: https://www.facebook.com/aiming4moonTaylor's Blog: https://www.taylorgbledsoe.com/YouTube: https://www.youtube.com/channel/UC6 

ISF IN FOCUS: The International Strategy Forum, a program of Schmidt Futures, bets early on the next generation of problem solvers with extraordinary potential in geopolitics, innovation, and public leadership to strengthen progress and security amid technological innovation and a changing world order. In this episode, ISF Director Helen Zhang introduces the program at its first-ever Global Summit, which brought together 117 rising leaders from North America, Africa, Asia, and Europe. We discuss how ISF and its network of fellows are tackling some of the hardest problems in science, society, and around the world.

On this podcast, we strive to connect fascinating and successful people to the next generation. But today and throughout March, I'd like to change it up a bit and, in partnership with the Rise initiative, highlight some of the fascinating and successful people of my generation. Throughout this month, I'll be talking with three of the winners of the Rise Challenge from various years. To begin this trilogy, I'll be speaking with Hawi ‘Annette' Odhiamno in honor of international women's day. For her Rise project, she built on an existing project, designing a prototype for a water system to support farming in Kenya. Rise is a program that finds promising young people and provides opportunity for life as they work to serve others. An initiative of Schmidt Futures and the Rhodes Trust, Rise is the anchor program of a $1 billion commitment from Eric and Wendy Schmidt to find and support global talent.Topics:Hawi's project: creating sustainable agriculture for farmers in KenyaHow to learn material outside of your comfort zoneHow Hawi created an instruction manual in both English and SwahiliThe future of her project"What skills did you gain?"How to balance projects and high schoolHawi's advice to other young innovators"What books have had an impact on you?""What advice do you have for teenagers?"From Kenya, Hawi works at the intersection of technology and agriculture. For her Rise project, she built on an existing project, designing a prototype for a water system to support farming in Kenya. Her model uses only recycled materials, and she has involved farmers themselves in its design. She also created instruction booklets for the rural farmers in both English and Swahili (for accessibility). In the future, she hopes to study International Relations and Chinese to create sustainable relations within countries in East Africa.Socials! -Lessons from Interesting People substack: https://taylorbledsoe.substack.com/Website: https://www.aimingforthemoon.com/Instagram: https://www.instagram.com/aiming4moon/Twitter: https://twitter.com/Aiming4MoonFacebook: https://www.facebook.com/aiming4moonTaylor's Blog: https://www.taylorgbledsoe.com/YouTube: https://www.youtube.com/channel/UC6 

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: After launch. How are CE charities progressing?, published by Ula Zarosa on March 6, 2023 on The Effective Altruism Forum. TL;DR: Charity Entrepreneurship have helped to kick-start 23 impact-focused nonprofits in four years. We believe that starting more effective charities is the most impactful thing we can do. Our charities have surpassed expectations, and in this post we provide an update on their progress and achievements to date. About CE At Charity Entrepreneurship (CE) we launch high-impact nonprofits by connecting entrepreneurs with the effective ideas, training and funding needed to launch and succeed. We provide: Seed grants (ranging from $50,000 to $200,000 per project) In-depth research reports with promising charity ideas Two months of intensive training Co-founder matching (this is particularly important) Stipends Co-working space in London Ongoing connection to the CE Community (~100 founders, funders and mentors) (Applications are now open to our 2023/2024 programs, apply by March 12, 2023).We estimate that on average: 40% of our charities reach or exceed the cost-effectiveness of the strongest charities in their fields (e.g., GiveWell/ACE recommended). 40% are in a steady state. This means they are having impact, but not at the GiveWell-recommendation level yet, or their cost-effectiveness is currently less clear-cut (all new charities start in this category for their first year). 20% have already shut down or might in the future. General update To date, our CE Seed Network has provided our charities with $1.88 million in launch grants. Based on the updates provided by our charities in Jan 2023, we estimate that: 1. They have meaningfully reached over 15 million people, and have the potential to soon reach up to 2.5 billion animals annually with their programs. For example: Suvita: Reached 600,000 families with vaccination reminders, 50,000 families reached by immunization ambassadors, and 95,000 women with pregnancy care reminders 14,000 additional children vaccinated Fish Welfare Initiative: 1.14 million fish potentially helped through welfare improvements 1.4 million shrimp potentially helped Family Empowerment Media: 15 million listeners reached in Nigeria In the period overlapping with the campaign in Kano state (5.6 million people reached) the contraceptive uptake in the region increased by 75%, which corresponds to 250,000 new contraceptive users and an estimated 200 fewer maternal deaths related to unwanted pregnancies Lead Exposure Elimination Project: Policy changes implemented in Malawi alone are expected to reach 215,000 children. LEEP has launched 9 further paint programs, which they estimate will have a similar impact on average Shrimp Welfare Project: The program with MER Seafood (now in progress) can reach up to 125 million shrimp/year. Additional collaborations could reach >2.5 billion shrimp per annum 2. They have fundraised over $22.5 million USD from grantmakers like GiveWell, Open Philanthropy, Mulago, Schmidt Futures, Animal Charity Evaluators, Grand Challenges Canada, and EA Animal Welfare Fund, amongst others. 3. If implemented at scale, they can reach impressive cost-effectiveness. For example: Family Empowerment Media: the intervention can potentially be 22x more effective than cash transfers from GiveDirectly (estimated by the team, 26x estimated by Founders Pledge) Fish Welfare Initiative: 1.3 fish or 2 shrimp potentially helped per $1 (estimated by the team, ACE assessed FWI cost-effectiveness as high to very high) Shrimp Welfare Project: approximately 625 shrimp potentially helped per $1 (estimated by the team) Suvita: when delivered at scale, effectiveness is at a similar range to GiveWell's top charities (estimated by external organizations, e.g. Founders Pledge, data on this will be available later this year) Giving G...

Welcome to Future in Focus, a podcast from Schmidt Futures. We're launching this series with five conversations featuring Schmidt Futures' International Strategy Forum and eight of our fellows from around the world. Working on five continents at the frontlines of today's most pressing challenges, these fellows are charting the future of technology, innovation, democracy, and security. Tune into the series to learn more about their work, and follow Schmidt Futures at www.schmidtfutures.com.

It was only three decades ago that astronomers first discovered planets outside our solar system. Since then, astrophysicists have found more of these "exoplanets" — including some Earth-like worlds that exist in their star's habitable zone. Today, astronomy has moved far beyond pointing a lens at the night sky, so I've brought on Gioia Rau to describe her work on exoplanets, as well as how AI and recent declines in launch costs will change astronomy.Gioia is an astrophysicist and program scientist at Schmidt Futures. Previous to joining Schmidt Futures, Gioia was a research scientist at NASA's Goddard Space Flight Center.In This Episode* NASA's exoplanet discoveries (1:19)* Innovation in telescopes and astronomy (5:57)* The near future for astronomy (16:02)* Americans' enthusiasm for space (22:04)Below is an edited transcript of our conversation.NASA's exoplanet discoveriesJames Pethokoukis: When I hear that there's been a discovery, that NASA has discovered an Earth-sized world inside the habitable zone of its star, I think, are there people there? Is there intelligent life there? When you hear that, what do you think? What strikes you? What are the implications you draw? What do you want know more of?Gioia Rau: That's a great question. As a scientist, I have many questions after this discovery. I would like to … discover which other molecules are in there. I would like to understand better what the size of this planet [is], what is its atmosphere and its surroundings. But as a human, as a person, and also as a scientist, it completely blows my mind. I'm so excited by the multiple discoveries. The James Webb Space Telescope is great to understand the atmosphere of these exoplanets, but what really kept us going from zero to 5,300—where we are now in terms of how many exoplanets have been confirmed—is first Kepler and then TESS.What is TESS?TESS is another telescope of NASA. It has discovered many, many exoplanets. It has scanned both atmospheres of the sky. And actually, at NASA, my group has used TESS with light curves … [and a] neural network, and so through artificial intelligence we were able to discover 181 new planet candidates. Those are incredible machines. Let's say TESS is our searcher, but then to really understand what is in there, what's the composition of this planet, we need …How many Earth-like, in a very broad sense, worlds have we found that are in habitable zones?That's a very good question, and I don't have the number on the top of my head, but those are just a bunch.At some point we had discovered none. And it wasn't that long ago that we probably had not discovered any of these?Right. The difficulty is in defining what is Earth-like. There are multiple meanings of this. One is the distance from the parent star that is similar to the distance between the Earth and our own sun. So this is called a “habitable zone.” But another measure of Earth-like is the size of the planet, or the fact that it's rocky versus gaseous. Definitely, TESS is the telescope that has helped us a lot with such discoveries.And even before we had found any of these, I imagine there was considerable speculation that obviously they had to exist, there had to be all kinds of planets outside our solar system. But we had not discovered them. And yet, I imagine it's been a pretty wonderful run we've had from going from pure speculation to beginning to analyze what these planets, whether they're Earth-sized or not, what other worlds are like.Absolutely, and it's just about 30 years, 33 years, that we've known that, actually, other planets, exoplanets—which by definition are planets outside our own solar system­­­­­­—exist. Before it was, as you mentioned, just a speculation. But the first ever planet was discovered around 33 years ago. And so since then, really our revolution began. And, actually, these two scientists that co-authored and discovered the first exoplanet have just recently been awarded the Nobel Prize.Innovation in telescopes and astronomyIt might seem to some people that NASA hasn't really done much since the Apollo program. But there's a lot more to space science than crewed missions. It seems to me like NASA's doing a whole lot of things right now.Absolutely. The time we are living now is a time of revolution for so many aspects in space exploration. Not only human exploration, which of course during the Apollo time peaked, and now hopefully also with the Artemis mission, named after the sister of Apollo in Greek mythology, is coming. But the James Webb Space Telescope, which is really a marvel of engineering. We never before have thought that we could put a telescope inside the rocket like an origami and then deploy it in the atmosphere. And we are discovering with Webb so many different things about the universe. Our early universe: Webb is basically a machine to look back in time. With its infrared vision, we will be able to look back over 13.5 billion years. But also with Webb we can discover galaxies over time, again, with the infrared sensitivity. So to discover even the earliest and faintest galaxies. We can discover the life cycle of the stars, as in the infrared, Webb which is able to look through the dust clouds which are otherwise opaque to the visible light. But also we are, as we mentioned before, able to see the atmosphere of these exoplanets, and so understand if in there there are building blocks of life elsewhere in the universe, but also understand how our own solar system was formed.Currently, we're learning about exoplanets through astronomy. We aren't sending probes. Are we nearing the point where there isn't much we can learn without getting closer to these worlds? Or can you imagine further innovations which would allow us to learn a lot more about an exoplanet without sending something there?This is a great question. We had Hubble in the past, the Hubble Space Telescope, through Kepler and TESS, now with James Webb and in the future with the Nancy Grace Roman Space Telescope, we will be able to understand so many different aspects of the “zoology” of this planet, so to say, but also on the composition of the atmosphere and so on. And so basically up to now, [there are] five principle methods to discover exoplanets. For example, one of those is transit, the method that Kepler and TESS use; but another one is gravitational microlensing, which the Nancy Grace Roman Space Telescope will use.Now, what is that?Gravitational microlensing is basically an observational effect that was predicted in 1936 by Einstein using the theory of general relativity. But this effect was never actually proved up to now in space. Basically when one star in the sky passes near or in front of another, then the light rays of the background star become basically bent due to the gravitational force, the gravitational attraction of the foreground star. And so this star then is actually acting as a virtual magnifying glass or a lens, and so it amplifies the brightness of the background source star. And so we refer to the foreground star as a lens star, and if the lens star harbors a planetary system, so an exoplanetary system, then those planets can actually also act as lenses, and so each of these planets will be producing a sharp division in the brightness of the source. And so we discovered the presence of each of the planets in this way, and we are able to measure also its mass and separation from the star. And this technique also tells us how common Earth-like planets are. This is a great method for Earth-like planets and has guided also the design of this future space mission, the Nancy Grace Roman Space Telescope.What would you like to be able to find out about an exoplanet, that you currently can't, but you think you might be able to 10 years from now or 20 years from now?There are several aspects that are currently unknown, probably what we need the most, that the Roman space telescope will also help us understand—Roman will be launched in May, 2027, according to the forecast, and it'll be operational a few months after—but basically Roman will have a wide field instrument that will bring us a panoramic view, a wide field of view, that is 200 times larger than Hubble Space Telescope in the infrared. It will also combine the power of imaging and spectroscopy, and so in this way, we will uncover thousands of exoplanets beyond our own solar system. We will have basically a sense of the “zoology” of the exoplanets, but also, we will have in the future, hopefully, much higher resolution of spectroscopy which will really [help us] understand what molecules are there beyond what JWST is able to tell us. And also if there is water, if we can go there, considering that many of these planets are not that far away, I mean in an astronomical point of view, right? They are just a dozen or hundreds of light years away, which is not that far away.How did you get involved in this to begin with? As a kid were you a space nut, you loved reading about it or watching documentaries? What got you interested in the field?Since I was a little kid, I was literally dreaming about space. I was very curious about everything about science in general. But something about space was extremely fascinating for me. This feeling of looking at the universe and feeling small in comparison of the immensity of the cosmos, dreaming of exploration while watching the space shuttle launches in the ‘90s. And also, you know, this question that we are still trying to uncover: What is out there? How does the universe work? How did we get here? Those were all fascinating to me as a kid. And yes, since I [was] very little kid, I wanted to work for NASA. I even wrote NASA a letter when I was about age eight. I wanted to attend their summer camp—obviously from my accent, I was not born in the US, so unfortunately at the time, it was precluded for foreigners to attend their summer camps. But they wrote me back. They were like, “Study and one day you'll come back here.” And so I didn't give up.And just explain a little bit about the thrust of your work now at Schmidt Futures.At Schmidt Futures we do several things for astronomy in general and for space. Fascination of space, of course, drove me to do research. Like very hands-on research. And then of course, I evolved and I started to lead research groups and to have my own students and interns and so on, which I love. I love to mentor young students and get them inspired to do science. But then also I like this more managerial or programmatic aspect, at Schmidt Futures we are really forging what the future of astronomy and astrophysics will be in the next five­­, 10 years and beyond. And so this has been extremely thrilling to me.The near future for astronomyYou were talking about how this is kind of a revolutionary period in space science. How important in this period, and let's say over the next decade, are two things? (1) Artificial intelligence to help process all this data, and (2) the fact that it's getting cheaper to put probes in space and put telescopes in space. I imagine those costs are going to continue to come down.Absolutely. I believe that the future of astronomy and astrophysics in general will be about an accelerated timeline and about cutting, drastically, costs. And so this is where also I really want to focus, especially for future of astrophysics. Concerning artificial intelligence and its use in astronomy, this is truly revolutionizing how we do astronomy. NASA is doing a lot in this sense. As I mentioned earlier, through AI we discovered a bunch of new planet candidates. But AI in general is revolutionizing astronomy in many ways from understanding cosmology to understanding the shape of galaxies and how they form. And I'm noticing more and more AI-based applications to the exploration of astronomical data. And so this is definitely, I believe, the future of astronomy. In a decade or so there will be more AI-based applications to analyze astronomical data than manual ones.I know there's ideas about putting a variety of telescopes on the Moon. And there's all this concern lately about our sky being cluttered with satellites, and a lot of astronomers are complaining about the Elon Musk Starlink, that it's obscuring views. But I would imagine that putting some kind of telescope—and radio telescopes, I imagine a variety of them—that would be helpful, right? Putting them on the Moon as opposed to having them on Earth?Oh yeah, absolutely. Actually, I believe that the future of [ground]-based astronomy, as we call it, versus space-based—“space-based” are all the telescopes that [orbit] around earth or in space …, versus [ground]-based are the telescope that we build on Earth—but the future of space-based astronomy is actually from the Moon and also beyond the Moon. In particular, for the radio wavelength domain, our radio telescope on the far side of the Moon will have tremendous advantages compared to Earth-based and also Earth-orbiting telescopes. For example, such a telescope could observe the universe at wavelengths greater than 10 meters, which are reflected actually by Earth's ionosphere and so are up to now completely, largely unexplored by humans. But also the Moon acts as a physical shield that isolates the lunar surface telescope from any radio interferences or noises from the Earth-based sources, from the ionosphere and from Earth-orbiting satellites, and also from the sun's radio noise, during the lunar night. And so, such a radio lunar-based telescope will enable tremendous scientific discoveries, for example, in the field of cosmology, by observing the early universe in this range of 10- to 50-meter wavelength span, which has been unexplored completely by humans to date.Is there any film that you think portrays what you do at all realistically? If the answer is no, what space, science-fiction movies do you find inspirational? I'm guessing maybe Contact, but maybe there are some others?Exactly. Contact inspired me when I was growing up for several reasons. I started during the holiday—but I didn't have the time to finish it—to watch Don't Look Up. But I watched the first half an hour, and I have to say that Leonardo DiCaprio was very much into the professor type. And so all the dynamics that happened had a scientific but also a bureaucratic level, so to say. But since we are talking about movies, a movie that I love, and it's really inspirational for very many points of view, is Interstellar. Many scientists will say that it's a movie that is completely wrong and so forth. When I watch a movie, I like to watch a movie as a person detached from my scientific point of view, just because it's a movie and it's fiction. Many movies are completely untrue for several aspects, so why are we going to investigate how physically true it is? It's a movie, right? We need to enjoy it.Americans' enthusiasm for spaceWhen you're traveling and you tell people what you do, I imagine people are pretty enthusiastic, because my theory is that people are super interested if we popularize and we let people know what actually is happening. There's been a lot happening other than Moon landings over the past half century, and maybe a lot more happening over the next 10 or 20 years.Absolutely, yeah. I completely agree with you. When I travel and I get to speak with people and “What do you do?” I say I'm an astrophysicist. It blows their mind just because people don't have any idea about actually what we do. They think that we look through a telescope. That's part of what we do in the free time, maybe. But the reality is way beyond that. I believe space is such a source of huge inspiration for mankind, for all of us. And so it's definitely on us, the scientists, astrophysicists, to be a great outreach source, to be great communicators, to make space and science in general more accessible and comprehensible to society and to all people. This will benefit the knowledge of all, but also it'll benefit science as a return of making it more accessible, more comprehensible.When was the last time that you looked into the IP of a physical telescope? Was it 20 years ago? Was it yesterday?Fun fact: for my nephews, the sons of my brother—they're twins—for their birthday I gave them a small, few inches refractor Newtonian telescope, and so now that they went off to college, they were like, “Hey aunt, you want it?” And I was like, “Are you sure? Because I will say yes.” And so with our very young daughter we've looked at it very recently, so it was not that so long ago. That's why I say it's something that we do in our free time, and many astrophysicists have this passion also to have more telescopes or to be astrophotographers, because this is a passion of many of us. In general, coming back to what you said before, and why space is important and why the US, with all the problems that are in the world, why we should actually invest in space and use this money there and not on other problems: First of all, I hope it was clear that all of this space can be very inspiring for young kids and to motivate them, but also for adults to look at the beauty of our universe, and also as a reminder to us all to be humble. We are just one extremely small piece in the huge cosmic puzzle of the universe. But also there are so many other benefits of space exploration: [NASA's impact on the US economy], how when we apply ourselves to the challenges of space exploration, we make discoveries that can help the world in many ways. For example, studying how food grows in orbit or on Mars might yield insight into growing food in extreme conditions on Earth or when climate change will hit even harder.Also, now the budget is not that expensive. It's only about 0.5 percent of the total federal budget. It's even smaller than for other nations. And also a cosmic perspective can also give us insight on the importance of protecting our own planet's sustainability and so encouraging investments and efforts then. And not to mention, of course, that studying space may one day save us all. And so we have to explore space to find and study asteroids and comets in our cosmic neighborhoods to defend our own Earth and to understand that, actually, Earth is unique in its habitability up to now. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

What is a "policy entrepreneur"? Can people become policy entrepreneurs if they're not already a political office holder? Aside from literally speaking to the POTUS, what are some ways that policy entrepreneurs can make progress on their goals? Why is it so hard for some people to articulate actionable plans that would accomplish their goals? What is market shaping? Why do some government departments have no budget for R&D?Tom Kalil is Chief Innovation Officer at Schmidt Futures. In this role, Tom leads initiatives to harness technology for societal challenges, improve science policy, and identify and pursue 21st century moonshots. Prior to Schmidt Futures, Tom served in the White House for two Presidents (Obama and Clinton), helping to design and launch national science and technology initiatives in areas such as nanotechnology, the BRAIN initiative, data science, materials by design, robotics, commercial space, high-speed networks, access to capital for startups, high-skill immigration, STEM education, learning technology, startup ecosystems, and the federal use of incentive prizes. Follow him on Twitter at @tkalil2050.

What is a "policy entrepreneur"? Can people become policy entrepreneurs if they're not already a political office holder? Aside from literally speaking to the POTUS, what are some ways that policy entrepreneurs can make progress on their goals? Why is it so hard for some people to articulate actionable plans that would accomplish their goals? What is market shaping? Why do some government departments have no budget for R&D?Tom Kalil is Chief Innovation Officer at Schmidt Futures. In this role, Tom leads initiatives to harness technology for societal challenges, improve science policy, and identify and pursue 21st century moonshots. Prior to Schmidt Futures, Tom served in the White House for two Presidents (Obama and Clinton), helping to design and launch national science and technology initiatives in areas such as nanotechnology, the BRAIN initiative, data science, materials by design, robotics, commercial space, high-speed networks, access to capital for startups, high-skill immigration, STEM education, learning technology, startup ecosystems, and the federal use of incentive prizes. Follow him on Twitter at @tkalil2050.[Read more]

This podcast episode is from an informational webinar hosted by the Naturalistic Decision Making Association on December 15th, 2022. The webinar outlines the purpose and parameters of CTA in E/Affect, a challenge sponsored by Schmidt Futures to strengthen the case for Cognitive Task Analysis in the workplace. What is Cognitive Task Analysis? CTA is a toolkit used by psychologists, researchers, and instructional designers to understand how high-performing professionals make complex decisions. The deep insights revealed through CTA can be used to design training programs that help novices achieve proficiency at a rapid pace. Two-Stage Program The grant will support a year-long project carried out in two stages. Stage 1: CTA in Effect [DEADLINE: February 15th, 2023] The first stage will solicit case studies of CTA's ROI and award $10,000 in total prize money to the most compelling submissions. Stage 2: CTA in Affect [To take place throughout 2023] The second stage will identify high-value areas of opportunity for CTA-based training programs. An Invitation to Partners & Practitioners Are you an experienced CTA practitioner? Do you represent a company that would like to learn more about how CTA can preserve institutional knowledge and accelerate training? If the answer to either question is yes, this podcast and the challenge it describes will be of value to you. Learn more about Naturalistic Decision Making and Cognitive Task Analysis at NaturalisticDecisionMaking.org. Thank you to Schmidt Futures for their generous sponsorship of this initiative and support of the NDMA and its mission. Learn more about their work at SchmidtFutures.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: [Link-post] Politico: "Ex-Google boss helps fund dozens of jobs in Biden's administration", published by Pranay K on December 24, 2022 on The Effective Altruism Forum. Politico article from Thursday December 22, 2022: "Ex-Google boss helps fund dozens of jobs in Biden's administration" 1. Summary: In three sentences: "Eric Schmidt, the former CEO of Google who has long sought influence over White House science policy, is helping to fund the salaries of more than two dozen officials in the Biden administration under the auspices of an outside group, the Federation of American Scientists." It is worth noting that Schmidt Futures (Schmidt's philanthropic ventures) does not directly fund these officials' salaries: Schmidt Futures provides < 30% to the Federation of American Scientists' "Day One fund" which funds these officials' salaries. Eric Schmidt seems to me to have called for the US government to aggressively invest in AI development. Some more context: Eric Schmidt chaired the National Security Commission on Artificial Intelligence from 2018-2021, in which the commision called on the US government to spend $40 billion on AI development. Schmidt Futures (Schmidt's philanthropic ventures) funds < 30% of the contributions to the Day One Project, a project within the Federation of American Scientists (FAS), which (among other things) provides the salaries of "FAS fellows" who hold "more than two dozen officials in the Biden administration" (from the main Politico article being discussed in this post). This includes 2 staffers in the Office of Science and Technology Policy (a different Politico article). The FAS is a "nonprofit global policy think tank with the stated intent of using science and scientific analysis to attempt to make the world more secure" (Wikipedia). The Day One project was started to recruit people to fill "key science and technology positions in the executive branch" (from the main Politico article). 2. My question: Are Schmidt's projects harmfully advancing AI capabilities research? I've seen discussion among the EA community about how OpenAI and Anthropic may be harmfully advancing AI capabilities research. (The best discussion that comes to mind is this recent Scott Alexander post about ChatGPT; if anyone knows any other resources discussing this hypothesis - for or against - please comment below). I have not seen much discussion about Eric Schmidt's harmful or beneficial contributions to AI development in the US government. What do people think about this? Is this something that should concern us? 3. Some more excerpts from the article about AI “Schmidt is clearly trying to influence AI policy to a disproportionate degree of any person I can think of,” said Alex Engler, a fellow at the Brookings Institution who specializes in AI policy. “We've seen a dramatic increase in investment toward advancing AI capacity in government and not much in limiting its harmful use.” Schmidt's collaboration with FAS [Federation of American Scientists] is only a part of his broader advocacy for the U.S. government to invest more in technology and particularly in AI, positions he advanced as chair of the federal National Security Commission on Artificial Intelligence from 2018 to 2021. The commission's final report recommended that the government spend $40 billion to “expand and democratize federal AI research and development” and suggested more may be needed. “If anything, this report underplays the investments America will need to make,” the report stated. “Other countries have made AI a national project. The United States has not yet, as a nation, systematically explored its scope, studied its implications, or begun the process of reconciling with it,” they wrote. “If the United States and its allies recoil before the implications of these capabilities and halt...

Jason Berkenfeld joins The Great Battlefield podcast to talk about his career in tech and politics and his role at Schmidt Futures where they are searching for up and coming leaders and helping to support them.

As the boundaries of the virtual world continue to shift, how can organizations work together to design a metaverse that's enriching and welcoming for all? New technology has the potential to reshape how businesses interact with the world, but it's time for leaders to commit to a responsible metaverse – one that's built on the core principles of ethics, safety and inclusivity. In this episode, we'll speak with Jessica Lindl, Vice President of Social Impact at Unity Technologies; Denise Zheng, Global Lead for Responsible Metaverse at Accenture; and Eli Sugarman, Fellow at Schmidt Futures. 

Tom Kalil is Chief Innovation Officer at Schmidt Futures. In this role, Tom leads initiatives to harness technology for societal challenges, improve science policy, and identify and pursue 21st-century moonshots.Session summary: Tom Kalil | Foresight Fellows Career Counseling - Foresight InstituteThe Foresight Institute is a research organization and non-profit that supports the beneficial development of high-impact technologies. Since our founding in 1987 on a vision of guiding powerful technologies, we have continued to evolve into a many-armed organization that focuses on several fields of science and technology that are too ambitious for legacy institutions to support.Allison Duettmann is the president and CEO of Foresight Institute. She directs the Intelligent Cooperation, Molecular Machines, Biotech & Health Extension, Neurotech, and Space Programs, Fellowships, Prizes, and Tech Trees, and shares this work with the public. She founded Existentialhope.com, co-edited Superintelligence: Coordination & Strategy, co-authored Gaming the Future, and co-initiated The Longevity Prize. Apply to Foresight's virtual salons and in person workshops here!We are entirely funded by your donations. If you enjoy what we do please consider donating through our donation page.Visit our website for more content, or join us here:TwitterFacebookLinkedInEvery word ever spoken on this podcast is now AI-searchable using Fathom.fm, a search engine for podcasts.  Hosted on Acast. See acast.com/privacy for more information.

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: AI Governance Needs Technical Work, published by Mauricio on September 5, 2022 on The Effective Altruism Forum. Summary and introduction People who want to improve the trajectory of AI sometimes think their options for object-level work are (i) technical safety work and (ii) non-technical governance work. But that list misses things; another group of arguably promising options is technical work in AI governance, i.e. technical work that mainly boosts AI governance interventions. This post provides a brief overview of some ways to do this work—what they are, why they might be valuable, and what you can do if you're interested. I discuss: Engineering technical levers to make AI coordination/regulation enforceable (through hardware engineering, software/ML engineering, and heat/electromagnetism-related engineering) Information security Forecasting AI development Technical standards development Grantmaking or management to get others to do the above well Advising on the above Other work Acknowledgements Thanks to Lennart Heim, Jamie Bernardi, Luke Muehlhauser, Gabriel Mukobi, Girish Sastry, and an employee at Schmidt Futures for their feedback on this post. Mistakes are my own. This post is mostly informed by various conversations with AI governance researchers, as well as earlier writings on specific kinds of technical work in AI governance. Context What I mean by “technical work in AI governance” I'm talking about work that: Is technical (e.g. hardware/ML engineering) or draws heavily on technical expertise; and Contributes to AI's trajectory mainly by improving the chances that AI governance interventions succeed[1] (as opposed to by making progress on technical safety problems or building up the communities concerned with these problems). Neglectedness As of writing, there are (by one involved expert's estimate) ~8-15 full-time equivalents doing this work with a focus on especially large-scale AI risks.[2] Personal fit For you to have a strong personal fit for this type of work, technical skills are useful, of course (including but not necessarily in ML), and interest in the intersection of technical work and governance interventions presumably makes this work more exciting for someone. Also, whatever it takes to make progress on mostly uncharted problems in a tiny sub-field[3] is probably pretty important for this work now, since that's the current nature of these fields. That might change in a few years. (But that doesn't necessarily mean you should wait; time's ticking, someone has to do this early-stage thinking, and maybe it could be you.) What I'm not saying I'm of course not saying this is the only or main type of work that's needed. (Still, it does seem particularly promising for technically skilled people, especially under the debatable assumption that governance interventions tend to be more high-leverage than direct work on technical safety problems.) Types of technical work in AI governance Engineering technical levers to make AI coordination/regulation enforceable To help ensure AI goes well, we may need good coordination and/or regulation.[4] To bring about good coordination/regulation on AI, we need politically acceptable methods of enforcing them (i.e. catching and penalizing/stopping violators).[5] And to design politically acceptable methods of enforcement, we need various kinds of engineers, as discussed in the next several sections.[6] Hardware engineering for enabling AI coordination/regulation To help enforce AI coordination/regulation, it might be possible to create certain on-chip devices for AI-specialized chips or other devices at data centers. As a non-exhaustive list of speculative examples: Devices on network switches that identify especially large training runs could be helpful. They could help enforce regulations that apply only to trai...

Welcome to a new series that spotlights individuals within the Stephen M. Kellen Term Member Program. Drawing on the enormous amount of talent and expertise within the Council's Term Member Program, this series features a term member in conversation with a fellow term member discussing their career path, how they got to where they are, the challenges they have faced along the way, and the current work they are doing. We hope this regular series will provide an opportunity for Council term members to better engage and learn from one another, draw upon shared experiences within the group, and connect across geographies. This installment in this series features third-year term member Asha Castleberry-Hernandez, senior advisor in the Bureau of Near Eastern Affairs at the U.S. Department of State and major in the U.S. Army Reserve, in conversation with second-year term member Brian Mateo, associate dean of civic engagement for Bard College. For those of you who do not know her yet, Asha is a distinguished national security expert whose career includes serving as the Kuwait desk officer at U.S. Army Central, working on security cooperation with the Office of Military Cooperation and the Kuwait Ministry of Defense, and senior key leadership engagement officer for Combined Joint Task Force-Operation Inherent Resolve in Iraq and Kuwait. During the Obama administration, Asha served at the U.S. Mission at the United Nations working peacekeeping operations in Africa. In 2020, Asha ran as a Democratic candidate for Congress in New York District 17. In addition to her work in government, she is a founder of Diversity in National Security Network, board member of Women of Color Advancing Peace, Security, and Conflict Transformation, and international strategy fellow with Schmidt Futures.

Synopsis: In this special episode, The Straits Times' foreign editor Bhagyashree Garekar speaks with Mr Eric Schmidt, the former Google chairman who started the philanthropic initiative Schmidt Futures. Mr Schmidt, 67, was chief executive of Google (2001-11) and executive chairman of the firm and its successor Alphabet (2011-17). The billionaire now runs Schmidt Futures, a New York-based philanthropic organisation that he co-founded with his wife in 2017 with the ambitious idea of building "a network of the sharpest minds on earth to solve hard problems in science and society". He was in Singapore last week for his foundation's Asia-focused initiative, which included the S. Rajaratnam Endowment Dialogue jointly presented by his foundation, Temasek Foundation, the S. Rajaratnam School of International Studies and The Straits Times. Highlights (click/tap above): 01:08 Why the US should win the technology rivalry with China 02:43 Schmidt on how the US needs to lead in semi conductors, artificial intelligence, synthetic biology, and why Singapore is the perfect partner because of its knowledge economy 05:08 Ensuring artificial intelligence is not abused, or used for evil 06:50 Schmidt Futures funding programmes to resolve problems in AI now, and why China and the West are not ready to debate uncomfortable issues Produced by: Bhagyashree Garekar (bhagya@sph.com.sg) & ST Video Edited by: ST Video and Penelope Lee Subscribe to the Asian Insider Podcast channel and rate us on your favourite audio apps: Channel: https://str.sg/JWa7 Apple Podcasts: https://str.sg/JWa8 Google Podcasts: https://str.sg/wQsB  Spotify: https://str.sg/JWaX SPH Awedio app: https://www.awedio.sg/ Website: http://str.sg/stpodcasts Feedback to: podcast@sph.com.sg Read Bhagyashree Garekar's stories: https://str.sg/whNo Register for Asian Insider newsletter: https://str.sg/stnewsletters --- Discover ST's special edition podcasts: Singapore's War On Covid: https://str.sg/wsfD The Unsolved Mysteries of South-east Asia Embed: https://str.sg/ws76 Stop Scams: https://str.sg/wnBi --- Discover more ST podcast series: In Your Opinion Podcast: https://str.sg/w7Qt SG Extra Podcast: https://str.sg/wX8w  Asian Insider Podcast: https://str.sg/JWa7 Green Pulse Podcast: https://str.sg/JWaf Health Check Podcast: https://str.sg/JWaN #PopVultures Podcast: https://str.sg/JWad ST Sports Talk Podcast: https://str.sg/JWRE Bookmark This! Podcast: https://str.sg/JWas Lunch With Sumiko Podcast: https://str.sg/J6hQ Discover BT Podcasts: https://bt.sg/pcPL Follow our shows then, if you like short, practical podcasts! See omnystudio.com/listener for privacy information.

Synopsis: In this special episode, The Straits Times' foreign editor Bhagyashree Garekar speaks with Mr Eric Schmidt, the former Google chairman who started the philanthropic initiative Schmidt Futures. Mr Schmidt, 67, was chief executive of Google (2001-11) and executive chairman of the firm and its successor Alphabet (2011-17). The billionaire now runs Schmidt Futures, a New York-based philanthropic organisation that he co-founded with his wife in 2017 with the ambitious idea of building "a network of the sharpest minds on earth to solve hard problems in science and society". He was in Singapore last week for his foundation's Asia-focused initiative, which included the S. Rajaratnam Endowment Dialogue jointly presented by his foundation, Temasek Foundation, the S. Rajaratnam School of International Studies and The Straits Times. Highlights (click/tap above): 01:08 Why the US should win the technology rivalry with China 02:43 Schmidt on how the US needs to lead in semi conductors, artificial intelligence, synthetic biology, and why Singapore is the perfect partner because of its knowledge economy 05:08 Ensuring artificial intelligence is not abused, or used for evil 06:50 Schmidt Futures funding programmes to resolve problems in AI now, and why China and the West are not ready to debate uncomfortable issues Produced by: Bhagyashree Garekar (bhagya@sph.com.sg) & ST Video Edited by: ST Video and Penelope Lee Subscribe to the Asian Insider Podcast channel and rate us on your favourite audio apps: Channel: https://str.sg/JWa7 Apple Podcasts: https://str.sg/JWa8 Google Podcasts: https://str.sg/wQsB  Spotify: https://str.sg/JWaX SPH Awedio app: https://www.awedio.sg/ Website: http://str.sg/stpodcasts Feedback to: podcast@sph.com.sg Read Bhagyashree Garekar's stories: https://str.sg/whNo Register for Asian Insider newsletter: https://str.sg/stnewsletters --- Discover ST's special edition podcasts: Singapore's War On Covid: https://str.sg/wsfD The Unsolved Mysteries of South-east Asia Embed: https://str.sg/ws76 Stop Scams: https://str.sg/wnBi --- Discover more ST podcast series: In Your Opinion Podcast: https://str.sg/w7Qt SG Extra Podcast: https://str.sg/wX8w  Asian Insider Podcast: https://str.sg/JWa7 Green Pulse Podcast: https://str.sg/JWaf Health Check Podcast: https://str.sg/JWaN #PopVultures Podcast: https://str.sg/JWad ST Sports Talk Podcast: https://str.sg/JWRE Bookmark This! Podcast: https://str.sg/JWas Lunch With Sumiko Podcast: https://str.sg/J6hQ Discover BT Podcasts: https://bt.sg/pcPL Follow our shows then, if you like short, practical podcasts! See omnystudio.com/listener for privacy information.

Synopsis: In this special episode, The Straits Times' foreign editor Bhagyashree Garekar speaks with Mr Eric Schmidt, the former Google chairman who started the philanthropic initiative Schmidt Futures. Mr Schmidt, 67, was chief executive of Google (2001-11) and executive chairman of the firm and its successor Alphabet (2011-17). The billionaire now runs Schmidt Futures, a New York-based philanthropic organisation that he co-founded with his wife in 2017 with the ambitious idea of building "a network of the sharpest minds on earth to solve hard problems in science and society". He was in Singapore last week for his foundation's Asia-focused initiative, which included the S. Rajaratnam Endowment Dialogue jointly presented by his foundation, Temasek Foundation, the S. Rajaratnam School of International Studies and The Straits Times. Highlights (click/tap above): 01:08 Why the US should win the technology rivalry with China 02:43 Schmidt on how the US needs to lead in semi conductors, artificial intelligence, synthetic biology, and why Singapore is the perfect partner because of its knowledge economy 05:08 Ensuring artificial intelligence is not abused, or used for evil 06:50 Schmidt Futures funding programmes to resolve problems in AI now, and why China and the West are not ready to debate uncomfortable issues Produced by: Bhagyashree Garekar (bhagya@sph.com.sg) & ST Video Edited by: ST Video  Subscribe to the Asian Insider Podcast channel and rate us on your favourite audio apps: Channel: https://str.sg/JWa7 Apple Podcasts: https://str.sg/JWa8 Google Podcasts: https://str.sg/wQsB  Spotify: https://str.sg/JWaX SPH Awedio app: https://www.awedio.sg/ Websites:  https://www.moneyfm893.sg/ http://str.sg/stpodcasts Feedback to: podcast@sph.com.sg Read Bhagyashree Garekar's stories: https://str.sg/whNo Register for Asian Insider newsletter: https://str.sg/stnewsletters --- Discover ST's special edition podcasts: Singapore's War On Covid: https://str.sg/wuJa The Unsolved Mysteries of South-east Asia: https://str.sg/wuZ2 Stop Scams: https://str.sg/wuZB Invisible Asia: https://str.sg/wuZn --- Discover more ST podcast series: Asian Insider: https://str.sg/JWa7 Green Pulse: https://str.sg/JWaf Health Check: https://str.sg/JWaN In Your Opinion: https://str.sg/w7Qt Your Money & Career: https://str.sg/wB2m SG Extra: https://str.sg/wukR #PopVultures: https://str.sg/JWad ST Sports Talk: https://str.sg/JWRE Bookmark This!: https://str.sg/JWas Lunch With Sumiko: https://str.sg/J6hQ Discover ST Podcasts: http://str.sg/stpodcasts Discover BT Podcasts: https://bt.sg/pcPL Follow our shows then, if you like short, practical podcasts! #STAsianInsiderSee omnystudio.com/listener for privacy information.

In this episode of the podcast, Sam Harris speaks with Eric Schmidt about the ways artificial intelligence is shifting the foundations of human knowledge and posing questions of existential risk. Eric Schmidt is a technologist, entrepreneur, and philanthropist. He joined Google in 2001 where he served as chief executive officer and chairman from 2001 to 2011, and as executive chairman and technical advisor thereafter. Under his leadership, Google dramatically scaled its infrastructure and diversified its product offerings while maintaining a culture of innovation. In 2017, he co-founded Schmidt Futures, a philanthropic initiative that bets early on exceptional people making the world better. He serves as chair of The Broad Institute, and formerly served as chair of the National Security Commission on Artificial Intelligence. He is the host of Reimagine with Eric Schmidt, a podcast exploring how society can build a brighter future after the COVID-19 pandemic. Most recently, he is the co-author of The Age of AI: And Our Human Future. Website: https://ericschmidt.com/ Twitter: @ericschmidt Learning how to train your mind is the single greatest investment you can make in life. That’s why Sam Harris created the Waking Up app. From rational mindfulness practice to lessons on some of life’s most important topics, join Sam as he demystifies the practice of meditation and explores the theory behind it.

Robert Esposito spent the first eight years of his career as a litigator at the law firms Morrison & Foerster and Bryan Cave in San Francisco, focusing on intellectual property, consumer protection, and business disputes. In 2018, on the verge of GDPR's enforcement date, Robert made the jump in-house as a product counsel at Facebook, where he helped launch social good products and programs. Later, Robert joined Pandora Media, where he led the development of Pandora's privacy program and worked on digital entertainment services. Robert currently serves as Senior Legal Counsel, Technology and Product Counsel at Hillspire, LLC, which advises a number of initiatives such as Schmidt Futures, which partners with leaders in the public and private sectors to help scale promising new ideas in science, technology, and society. In the past decade, in-house legal departments, primarily at large technology companies, began creating a new role called "product counsel." The product counsel role is amorphous. Most in-house lawyers don't know what product counsel do, let alone the product, engineering, and marketing teams they're meant to serve. Join Robert Esposito, law firm litigator turned in-house product counsel to learn about this "new" type of attorney and how to become one.

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: Research Help Needed for 1Day/IFP “Operation Warp Speed 2.0” Project, published by joshcmorrison on April 14, 2022 on The Effective Altruism Forum. 1Day Sooner and the Institute for Progress are working on a Schmidt Futures-funded project to develop a lobbying campaign for an “Operation Warp Speed 2.0” to create universal coronavirus vaccines. Beyond this pandemic, we want this to create precedent and infrastructure for the broader use of “advanced market commitments” to accelerate development and deployment of vaccines and antibiotics, which would have major longtermist and disease burden benefits. Because of the scale and complexity of the policy we're envisioning, we need help with research. If you're reading this and have 5-10 hours a week over the next 4-6 weeks, we could use your help (and can pay for your time). Why Warp Speed 2.0? Pandemic preparedness and vaccine development for neglected diseases are each seriously underfunded. The GOP is likely to win at least one house of Congress this November and tends to be averse to large government spending. But Operation Warp Speed's success and connection to President Trump give it a unique attraction to a GOP audience. Moreover the advanced purchase commitment framework it utilized (of guaranteeing large purchases of effective vaccines) creates a market-friendly framework that could be supported by conservatives in the U.S. and elsewhere. Beyond the benefits of developing a financing model with potential bipartisan support capable of efficiently funding effective altruist goals, successfully creating a universal coronavirus vaccine would serve as proof of concept for the 100 day prototype vaccine strategy aimed at developing universal vaccines ahead of time to pathogens with pandemic potential. Thus both the campaign's object-level goal (accelerating coronavirus vaccines) and meta-goal (expanding the long-term use of advanced market commitments) have major EA benefits beyond reducing COVID disease burden. What Help Is Needed? Time is of the essence to introduce a strong bill and launch a campaign quickly, but the scale and complexity of the policy (along with its multiple moving parts) make the research needed fairly involved and time consuming. At the same time, we think the key questions we've identified are independent enough from each other that they can be broken into discrete tasks where progress is possible with work on a part-time basis. Basically, we're trying an experiment to emulate the research process at the beginning of 1Day Sooner when our organization relied on a number of EAs to provide research help on challenge trials and eventually produce this piece (as well as a great deal of background knowledge crucial to our informing the public and advocating for effective policy). That work was done almost entirely on a volunteer basis but research assistance on this project would be compensated (typically in the $30-$50/hr range depending on experience). How Can I Get Involved? Email josh@1daysooner.org, reference this post, and include a paragraph about your background and time availability. Also indicate one or two research questions in the agenda below that you might be interested in exploring. We're going to aim to host a kickoff session for people who'll be working on this some time Thursday April 21st, so you should hear from me before then. I have no idea how many will respond so won't know in advance how selective we'll be (if at all). What Questions Need to Be Answered? Here's the current research agenda we'll be working on: Modeling, Quantifying, and Forecasting Impact of Pan-Sarbecovirus Vaccines: Create informal model of impact of potential future COVID-19 disease burden scenarios in the U.S. and globally (currently led by Eric Mannes with supervision by Witold Wiecek, Rachel Glennerster, an...

In this week's episode, Kumar Garg, Vice President, Partnerships at Schmidt Futures, discusses how to bring your science to life through crisp descriptions, engaging visuals, and related communication techniques. We discuss: - How Kumar's first job out of college (deputy communication manager on presidential candidate Howard Dean's campaign in New Hampshire) taught him about the value and principles of strong communications - Lessons from Kumar's earlier experiences in communications that were particularly useful as he helped shape science and technology policy priorities for the Obama Administration for nearly 8 years in the White House - Some of the common disconnects, in terms of lack of understanding, different ways of communicating, misperceptions, etc., Kumar noticed as he interacted with scientists at the highest levels - Effective remedies for bridging communications gaps, whether through recalibrating communications or by other means - Kumar's current work at Schmidt Futures in the middle of many major science and policy issues, now from a different vantage point - Advice Kumar has for listeners thinking about a career in science policy but who are unsure where and how to start - As Kumar worked with scientists during his time in the White House and now at Schmidt Futures, particular skills and attributes he's found certain scientists possess that set them apart - help them be more effective - in the policymaking world - As Kumar looks towards the future, what emerging trends he sees (or would like to see and is working to advance) in terms of scientists getting involved in policymaking or in the communication of scientific information to general audiences

Dana Chermesh is the founder and CEO of inCitu, an Augmented-Reality-powered civic engagement app that democratizes city planning. Dana is an architect from Tel-Aviv, Israel, and an alumna of NYU Masters program in Urban Data Science (2018). During her career as an architect, she specialized in urban renewal and developed a passion for leveraging technology, data and innovation to form smarter, more resilient, and more just cities and city processes. In 2019 Dana co-founded *inCitu*, to bring together data and discourse with the aid of augmented reality helping citizens see the future of their cities. inCitu was incubated inside Eric Schmidt's social impact venture fund.In this conversation, we discuss Dana's deep love and appreciation for cities and urban development. We talk about her goal of developing viable, dynamic, data-driven tools to empower residents and leaders to better deal with 21-century urban challenges. She feels driven by a mission that feels bigger than herself or the company.We go on to discuss Dana's experience at Schmidt Futures, her perspective on the concept of the “metaverse”, and founding a company while being the mother of young children.You can find all of the show notes at thearshow.com.

Hugo speaks with Jim Savage, the Director of Data Science at Schmidt Futures, about the need for data science in executive training and decision, what data scientists can learn from economists, the perils of "data for good", and why you should always be integrating your loss function over your posterior. Jim and Hugo talk about what data science is and isn't capable of, what can actually deliver value, and what people really enjoy doing: the intersection in this Venn diagram is where we need to focus energy and it may not be quite what you think it is! They then dive into Jim's thoughts on what he dubs Executive Data Science. You may be aware of the slicing of the data science and machine learning spaces into descriptive analytics, predictive analytics, and prescriptive analytics but, being the thought surgeon that he is, Jim proposes a different slicing into (1) tool building OR data science as a product, (2) tools to automate and augment parts of us, and (3) what Jim calls Executive Data Science. Jim and Hugo also talk about decision theory, the woeful state of causal inference techniques in contemporary data science, and what techniques it would behoove us all to import from econometrics and economics, more generally. If that's not enough, they talk about the importance of thinking through the data generating process and things that can go wrong if you don't. In terms of allowing your data work to inform your decision making, thery also discuss Jim's maxim “ALWAYS BE INTEGRATING YOUR LOSS FUNCTION OVER YOUR POSTERIOR” Last but definitively not least, as Jim has worked in the data for good space for much of his career, they talk about what this actually means, with particular reference to fast.ai founder & QUT professor of practice Rachel Thomas' blog post called “Doing Data Science for Social Good, Responsibly” (https://www.fast.ai/2021/11/23/data-for-good/). Rachel's post takes as its starting point the following words of Sarah Hooker, a researcher at Google Brain: "Data for good" is an imprecise term that says little about who we serve, the tools used, or the goals. Being more precise can help us be more accountable & have a greater positive impact. And Jim and I discuss his work in the light of these foundational considerations. Links Jim on twitter (https://twitter.com/abiylfoyp/) What Is Causal Inference?An Introduction for Data Scientists (https://www.oreilly.com/radar/what-is-causal-inference/) by Hugo Bowne-Anderson and Mike Loukides Jim's must-watch Data Council talk on Productizing Structural Models (https://www.datacouncil.ai/talks/productizing-structural-models)

D(g)B welcomes Tony Woods, the Director and Head of Talent for Schmidt Futures - the philanthropic initiative created by former Google CEO Eric Schmidt. He recruits engineers, authors, Ph.D. scientists, program administrators, etc and has helped pilot a program to source talent for critical government roles in the tech space, and created partnerships to elevate the talent of young people around the world. And there's SO much more to Tony, like how he was impacted by "don't ask, don't tell" and his newest endeavor with the Quad Fellowship in the Biden Whitehouse.   Tony's top traits of leaders who do DEI well are curiosity, empathy, and brave conversations - you know we love those! Episodes mentioned: Anthony Hayes Lisa Fain    

Making its own news this week, Dartmouth expands its longstanding need-blind admissions policy to include international students. Lee Coffin explores the far-reaching impact of this change with Greg Manne, who oversaw international admissions for Dartmouth before taking a new job as manager of selection and outreach for Rise, an initiative of Schmidt Futures and the Rhodes Trust, which provides lifelong benefits, including scholarships and mentorships, to promising young people working to solve pressing problems around the world.

Doing something that you look forward to, that beautiful thing that you wake up and dream about. That is what I call success. -Jenn Uche Welcome to the inspiring story of Jenn Uche, a 17 year old high school senior who has been chosen as a 2021 Global Rise Winner. This 1 billion dollar philanthropic venture was created and funded by Google co-founder, Eric Schmidt and his wife Wendy and is a collaboration between Schmidt Futures and the Rhodes Trust. To find out more, just go to: www.risefortheworld.com. Talented young people from around the world, between the ages of 15-17 are chosen through a series of essays, submissions and virtual interviews. What is unique about this scholarship is that it is for life and is valued at about $500,000 per student winner. An investment is made early on in the intelligence of these kids to become innovators, leaders, points of light for the next generation. 50,000 teens from 170 countries competed for this award, each one addressing how they would work to solve a particular problem. Jenn was 1 of 100 brilliant students to receive this honor. A student at the Montrose School in Medfield, MA where the mantra is: “where girls are called to greatness”, Jenn she is no stranger to struggle and adversity. She remains hopeful and determined “coming out the other side, like a diamond” and describing herself as a story lover, smile connoisseur, a writer and a visionary. I couldn't wait to bring my recording equipment to Jenn's school to capture the story of a 17 year old woman who is wise beyond her years and destined for greatness. #risefortheworld #empoweringwomen #womensupportingwomen

In Episode 218 of Hidden Forces, Demetri Kofinas speaks with Eric Schmidt and Daniel Huttenlocher. Eric is co-founder of Schmidt Futures and the former CEO & Chairman of Google and Daniel is the inaugural dean of the MIT Schwarzman College of Computing. They are the co-authors, along with Henry Kissinger, of a phenomenal new book titled, “The Age of AI And Our Human Future,” which explores how Artificial Intelligence is transforming human society—and what it means for all of us. Eric and Dan spend the first hour discussing the technical dimensions of artificial intelligence—what it is and how it works—as well as how it will continue to shape and transform our social and physical realities. The second half of the conversation focuses on the national security dimensions of artificial intelligence, as well as the profound philosophical challenges that it poses for humanity, specifically our need to find meaning in a world where machines will provide answers to more and more questions but without the ability, in many cases, to provide us with a rational or methodology by which they arrived at those answer. For those of you who are interested in the field of blockchain and DLT-enabled applications and smart contracts, Demetri had a chance to ask Eric about where he thinks these technologies fit in an AI future, what the main hurdles are going to be, and what some of the interesting projects in the space are. You can access the second part of this episode, as well as the transcript and rundown to this week's conversation through the Hidden Forces Patreon Page. All subscribers gain access to our premium feed, which can be easily added to your favorite podcast application. If you enjoyed listening to today's episode of Hidden Forces you can help support the show by doing the following: Subscribe on Apple Podcasts | Spotify | Stitcher | SoundCloud | YouTube | CastBox | RSS Feed Write us a review on Apple Podcasts Subscribe to our mailing list through the Hidden Forces Website Producer & Host: Demetri Kofinas Editor & Engineer: Stylianos Nicolaou Subscribe & Support the Podcast at https://patreon.com/hiddenforces Join the conversation on Facebook, Instagram, and Twitter at @hiddenforcespod Follow Demetri on Twitter at @Kofinas Episode Recorded on 11/08/2021

Eric Schmidt, Co-Founder of Schmidt Futures and former Google CEO and Chairman, discusses his book “The Age of AI: And Our Human Future.” Hosts: Tim Stenovec and Katie Greifeld. Producer: Paul Brennan. Learn more about your ad-choices at https://www.iheartpodcastnetwork.com

Eric Schmidt, Co-Founder of Schmidt Futures and former Google CEO and Chairman, discusses his book “The Age of AI: And Our Human Future.” Hosts: Tim Stenovec and Katie Greifeld. Producer: Paul Brennan. Learn more about your ad-choices at https://www.iheartpodcastnetwork.com

Eric Schmidt — The Promises and Perils of AI, The Future of Warfare, Profound Revolutions on the Horizon, and Exploring The Meaning of Life | Brought to you by ShipStation shipping software, ButcherBox premium meats delivered to your door, and Pique Tea premium tea crystals (pu'er, etc.). More on all three below.Eric Schmidt (@ericschmidt) is a technologist, entrepreneur, and philanthropist. He joined Google in 2001, helping the company grow from a Silicon Valley startup to a global technological leader. He served as chief executive officer and chairman from 2001 to 2011 and as executive chairman and technical advisor thereafter. Under his leadership, Google dramatically scaled its infrastructure and diversified its product offerings while maintaining a culture of innovation. In 2017, he co-founded Schmidt Futures, a philanthropic initiative that bets early on exceptional people making the world better.He serves as chair of the Broad Institute and formerly served as chair of the National Security Commission on Artificial Intelligence. He is the host of Reimagine with Eric Schmidt, a podcast exploring how society can build a brighter future after the COVID-19 pandemic. With co-authors Henry A. Kissinger and Daniel Huttenlocher, Eric has a new book out titled The Age of AI: And Our Human Future.Please enjoy!This episode is brought to you by ButcherBox! ButcherBox makes it easy for you to get high-quality, humanely raised meat that you can trust. They deliver delicious, 100% grass-fed, grass-finished beef; free-range organic chicken; heritage-breed pork, and wild-caught seafood directly to your door.Skip the lines for your Thanksgiving turkey. This holiday, ButcherBox is proud to give new members a free turkey. Go to ButcherBox.com/Tim to receive a free 10–14 pound turkey in your first box.*This episode is also brought to you by Pique Tea! I first learned about Pique through my friends Dr. Peter Attia and Kevin Rose, and now Pique's fermented pu'er tea crystals have become my daily go-to. I often kickstart my mornings with their Pu'er Green Tea and Pu'er Black Tea, and I alternate between the two. Their crystals are cold-extracted, using only wild-harvested leaves from 250-year-old tea trees. Plus, they triple toxin screen for heavy metals, pesticides, and toxic mold—contaminants commonly found in tea. I also use the crystals for iced tea, which saves a ton of time and hassle.Pique is offering 15% off of their pu'er teas, exclusively to my listeners. Simply visit PiqueTea.com/Tim, and the discount will be automatically applied. They also offer a 30-day satisfaction guarantee, so your purchase is completely risk free. Just go to PiqueTea.com/Tim to learn more.*This episode is also brought to you by ShipStation. Do you sell stuff online? Then you know what a pain the shipping process is. ShipStation was created to make your life easier. Whether you're selling on eBay, Amazon, Shopify, or over 100 other popular selling channels, ShipStation lets you access all of your orders from one simple dashboard, and it works with all of the major shipping carriers, locally and globally, including FedEx, UPS, and USPS. Tim Ferriss Show listeners get to try ShipStation free for 60 days by using promo code TIM. There's no risk, and you can start your free trial without even entering your credit card info. Just visit ShipStation.com, click on the microphone at the top of the homepage, and type in TIM!If you enjoy the podcast, would you please consider leaving a short review on Apple Podcasts? It takes less than 60 seconds, and it really makes a difference in helping to convince hard-to-get guests. I also love reading the reviews!*For show notes and past guests, please visit tim.blog/podcast.Sign up for Tim's email newsletter (“5-Bullet Friday”) at tim.blog/friday.For transcripts of episodes, go to tim.blog/transcripts.Discover Tim's books: tim.blog/books.Follow Tim:Twitter: twitter.com/tferriss Instagram: instagram.com/timferrissFacebook: facebook.com/timferriss YouTube: youtube.com/timferrissPast guests on The Tim Ferriss Show include Jerry Seinfeld, Hugh Jackman, Dr. Jane Goodall, LeBron James, Kevin Hart, Doris Kearns Goodwin, Jamie Foxx, Matthew McConaughey, Esther Perel, Elizabeth Gilbert, Terry Crews, Sia, Yuval Noah Harari, Malcolm Gladwell, Madeleine Albright, Cheryl Strayed, Jim Collins, Mary Karr, Maria Popova, Sam Harris, Michael Phelps, Bob Iger, Edward Norton, Arnold Schwarzenegger, Neil Strauss, Ken Burns, Maria Sharapova, Marc Andreessen, Neil Gaiman, Neil de Grasse Tyson, Jocko Willink, Daniel Ek, Kelly Slater, Dr. Peter Attia, Seth Godin, Howard Marks, Dr. Brené Brown, Eric Schmidt, Michael Lewis, Joe Gebbia, Michael Pollan, Dr. Jordan Peterson, Vince Vaughn, Brian Koppelman, Ramit Sethi, Dax Shepard, Tony Robbins, Jim Dethmer, Dan Harris, Ray Dalio, Naval Ravikant, Vitalik Buterin, Elizabeth Lesser, Amanda Palmer, Katie Haun, Sir Richard Branson, Chuck Palahniuk, Arianna Huffington, Reid Hoffman, Bill Burr, Whitney Cummings, Rick Rubin, Dr. Vivek Murthy, Darren Aronofsky, and many more.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of Work in Progress, my guest is Rachel Korberg, executive director and co-founder of the Families and Workers Fund (FWF), a coalition of now more than 20 philanthropic groups working together to build an equitable economic recovery and create jobs that enable upward mobility. The Families and Workers Fund was started last year in the early days of the COVID-19 pandemic with the goal of helping ease the financial pain being suffered by low-wage workers—those who lost their jobs and those who had to continue working despite the risk to their health because they needed the money to survive. "We know that before the pandemic, 40% of people in the United States did not earn enough money to afford the basics of rent, childcare, food. People were already in a very precarious position," says Korberg. "And then the layoffs hit hardest among people who were already at the bottom of the labor market. In 2020, nearly half of the lowest paid workers lost their jobs. Those jobs were people who worked in restaurants, people who worked in big box retail, people who worked in hospitality. The effects were really far- and wide-reaching, but they were clustered in people who were already earning the least, who are either in poverty wage jobs or just above it." FWF was created to get money into the hands of those who needed it quickly. Korberg—then a program officer at the Ford Foundation—co-founded it with Darren Walker, president of the Ford Foundation and Eric Braverman, CEO of Schmidt Futures, both of whom remain on as co-chairs of the Fund. That initial coalition grew in short order. "It was really a sleeves rolled up group. We pooled about $10 million over the course of 2020, and rather than do cash transfers directly— which we didn't think was the right role for us—we supported nearly 30 grassroots groups and worker networks that were already in long-term, authentic, trusting relationships with the hardest hit workers and families. And we supported them in doing cash transfer efforts. "For some of them, they had already done work like this in the past, but for a lot, this was a new muscle that they were building and it was really exciting. There's this really virtuous cycle of beyond just the payment. It's also an opportunity to join up around advocacy, community building, and training opportunities." And that's what they've done. Refocusing the Mission Korberg says that while the Fund started as a rapid response to people in need, the organizers quickly realized that it was an unprecedented opportunity to build a more equitable economy, that is why is still exists, and that is why it has evolved. Rather than being a one-time $10 million emergency response fund, today it's a $51 million coalition of about 20 diverse philanthropies with the twin goals of funding job pathways that enable economic security and mobility and repairing the unemployment benefits system. "The confluence of three forces—essential workers, equity, and unprecedented public investment in (job creation)—really come together to create this huge opportunity to reimagine our labor market and economic systems and to go big on ultimately advancing good jobs and delivering a more effective and equitable social safety net," Korberg tells me. She says FWF sees two main strategies in advancing good jobs. "Building ladders into upwardly mobile jobs—and that's usually a train in place model—and then we see approaches that are more about growing the pie of good jobs. So, maybe starting with a job that might not pay very well, that might not have great benefits, and look at what are the different set of incentives or shifts that we can catalyze to make this a better job. For example, rather than only reskilling home health care aides to become x-ray technicians, how can we also make home health care aides a job that pays better and that is a good job and that many people are called to that work and to care work?

America's Place in the World: National Security & Leading From the Front with General John Kelly, Retired U.S. Marine Corps General & 28th White House Chief of Staff. General H.R. Mcmaster, Retired U.S. Army Lieutenant General & 26th United States National Security Advisor. Michele Flournoy, Co-Founder & Managing Partner, WestExec Advisors. Richard Fontaine, Chief Executive Officer, Center for a New American Security.Moderated by Zoe Weinberg, Fellow, Schmidt Futures.SALT New York is a global thought leadership and networking forum at the intersection of finance, technology and public policy. Over the course of three days, leading investors, creators and thinkers will take the stage in support of SALT's mission: empowering big ideas.——————————————————————Watch this video on YouTube: https://www.youtube.com/c/SALTTube/videosFor podcast transcripts and show notes, visit https://www.salt.org/Developed, created and produced by SALT Venture Group, LLC.#SALTNY

On the final episode of season 1 we sit down for an incredible conversation with Jason Wang. Jason shares openly about growing up in poverty, in a neighbourhood where he was exposed to drugs and violence from a very young age. He shares about being subjected to abuse as a child, and about the impact that all of these things had on his life and trajectory. It's easy to see how the result of it all was an aggravated robbery charge that left 15 year old Jason with a 12 year prison sentence.  What is so remarkable about Jason and his story is his resilience and determination throughout his life. Ultimately, this has led him to become entrepreneur in residence for Schmidt Futures. He has created and leads Freeworld, an organization with a mission of bringing high wage careers to millions of returning citizens across America so they can live fulfilling positive lives, prison-free. For more information on Jason: Check out: Freeword Twitter: @JasonWaang For more information on the Field: Instagram: @the.field.podcast Website: thefieldpodcast.com Support the show on Patreon And if you enjoyed this episode, be sure to rate, review, and subscribe!

How do Roombas illustrate the promise and peril of translational research? Which valley of death is really the worst valley of death? And how can woolly mammoths save the planet from climate change?   To discuss, I have on: Andrew Sosanya, Policy Analyst for the Day One Project Adam Marblestone of Schmidt Futures (his policy proposal: https://www.dayoneproject.org/post/focused-research-organizations-to-accelerate-science-technology-and-medicine, his blog https://longitudinal.blog/, geo-engineering https://longitudinal.blog/co2-series-part-3-other-interventions/) Orin Hoffman at The Engine (his policy proposal: https://www.engine.xyz/news-item/a-unified-government-vc-approach-to-crossing-the-valleys-of-death/) Please consider supporting ChinaTalk at https://glow.fm/chinatalk/ Outtro Music: https://www.youtube.com/watch?v=VIh4GFUKaSE  Get bonus content on Patreon See acast.com/privacy for privacy and opt-out information.

How do Roombas illustrate the promise and peril of translational research? Which valley of death is really the worst valley of death? And how can woolly mammoths save the planet from climate change?   To discuss, I have on: Andrew Sosanya, Policy Analyst for the Day One Project Adam Marblestone of Schmidt Futures (his policy proposal: https://www.dayoneproject.org/post/focused-research-organizations-to-accelerate-science-technology-and-medicine, his blog https://longitudinal.blog/, geo-engineering https://longitudinal.blog/co2-series-part-3-other-interventions/) Orin Hoffman at The Engine (his policy proposal: https://www.engine.xyz/news-item/a-unified-government-vc-approach-to-crossing-the-valleys-of-death/) Please consider supporting ChinaTalk at https://glow.fm/chinatalk/ Outtro Music: https://www.youtube.com/watch?v=VIh4GFUKaSE 

Today I'm speaking with Tom Kalil. Tom is Chief Innovation Officer at Schmidt Futures, where he leads projects to harness technology for social impact, improve science policy, and identify and pursue 21st-century moonshots. Tom has previously spent more than a decade in the White House, helping to design and launch national science and technology initiatives in areas such as nanotech, data science, commercial space, and many more. Although I had about a hundred more questions to ask Tom, we cover lots of ground from how to build moonshot cultures to the role of the generalist and the relationship between tech and policy. => Shownotes

On this episode, we hear from Mari Silbey, director of partnerships and outreach at US Ignite, as well as Alex Wyglinski and Casey Canfield, engineering professors and co-leads on a broadband deployment project in Clinton County, Missouri. The deployment, which will use RF-over-fiber to serve a rural community, was selected to receive grant funding through Project Overcome, a $2.7 million joint effort spearheaded by the National Science Foundation and US Ignite – with additional financing from Schmidt Futures – to fund novel broadband projects and find new solutions to closing the digital divide. We discuss more about Project Overcome, as well as details and plans for this specific deployment in Clinton County, Missouri, and the complexities of choosing the right technologies and outreach methods to service rural communities.

Kumar Garg is the Managing Director of Schmidt Futures, a venture facility for public benefit that recently cosponsored the Futures Forum on Learning Tools Competition with Citadel. Kumar joins our host, Mike Palmer, to talk about the winners of the tools competition who were recently announced and to provide his insights and perspectives on learning engineering as well as trends in educational technology and computational thinking. Kumar begins by sharing his origin story which includes an eight-year run in the Obama administration heading up its efforts to grow and develop STEM education in the US. From there we explore the idea of learning engineering which combines insights in computer science, computational thinking, and big data with emerging insights in learning science to create scalable breakthrough innovations in education. Kumar walks through the structure and design of the competition and reflects on the benefits of connecting entrepreneurial innovation with academic research and scientific methods to unlock learning innovation at scale. From there, we discuss Rising on Air and UPchieve as case studies of the types of programs that emerged from the competition before concluding with Kumar's thoughts on the importance of R&D and infrastructure funding to drive the next generation of the learning ecosystem. It's an insightful and far-reaching conversation about the future of Ed Tech that you won't want to miss. If you're enjoying what you're hearing, subscribe to Trending in Education wherever you listen to your podcasts and check us out at TrendinginEducation.com

Kumar Garg, managing director and head of partnerships at Schmidt Futures and the former leader of the White House Office of Science and Technology Policy, discusses a host of initiatives designed to strengthen STEM career pathways. He also breaks down some big ideas in education like learning engineering and educator researchers, and explains why these concepts are more important than ever before. In the course of the discussion, Garg also touches on OER policy, learning R&D and how we might improve education research. 

Prof. Oded Rechavi, professor at the Department of Neurobiology at Tel Aviv University. His lab challenges basic dogmas regarding inheritance and evolution, using simple powerful genetic model organisms. Oded is very active over social media, mostly Twitter, and brings the new media twist towards communicating science and the life of a scientist. Among other things, he organized the first Twitter scientific conference "WOODSTOCK.BIO" He brings great fresh views on the new era of social communication and its integration and value to academics. He is the recipient of many breakthroughs and prestigious awards including the first BLAVATNIK AWARDS FOR YOUNG SCIENTISTS in Israel and he is the first laureate of the Schmidt Futures $2.5M award, which is awarded to exceptional people and helps them achieve more for others by applying advanced science and technology thoughtfully and by working together across fields. Oded's lab website https://www.odedrechavilab.com/ Oded Twitter: Oded Rechavi

Eric Schmidt Will Lead 15-Member Commission and Use What the State Has Learned During COVID-19 Pandemic, Combined with New Technologies, to Improve Telehealth and Broadband Systems Across the State Outlines Results of New Hospitalization Data to Further Reduce Number of New Hospitalizations per Day JetBlue is Donating 100,000 Pairs of Round-Trip Flights for Medical Personnel and Nurses Confirms 2,786 Additional Coronavirus Cases in New York State - Bringing Statewide Total to 323,978; New Cases in 45 Counties

A Case Study of Subnational Coordination in a Crisis: The U.S. National Governors Association and COVID-19Whether on climate change, migration, or humanitarian response, subnational coordination has become an increasingly important feature of responses to crisis across the world in the 21st century. Subnational (provincial, state and municipal) governments are described by McKinsey as "crisis nerve centers" - highly agile, coordinated bodies that can bring together stakeholders and mobilize civil society in support of central government - or in some cases, to compensate for the lack of leadership from central government.Each country's experience of the COVID-19 pandemic has to some extent been shaped by this subnational response. This response has been shaped in turn by that country's history, political system and current political reality. While France's response has been coordinated strongly from Paris, the measures taken in the UK and particularly in Germany, Italy and Spain have been more decentralized, with varying degrees of success. In Turkey, one of the countries currently on the steepest upward curve of cases, the subnational response has evolved from "cooperation to competition to and finally confrontation." In China, local officials in Wuhan were blamed by Beijing for the crisis, and found little support from other regional governments.The response in the United States, which now has the highest number of cases in the world, is particularly unique. Since the earliest days of this mounting crisis, governors have helmed efforts to control the spread of the virus and safeguard public health. As infection rates rise and mitigation measures take their inevitable toll on the economy, the National Governors Association (NGA) has mobilized to provide its members with an unprecedented level of continuous assistance, with a focus on disseminating updated information from the federal government and virtually convening state officials to identify urgent needs and communicate effective practices. These efforts are being led by the NGA Center for Best Practices, a non-profit, 501c(3) devoted to identifying and sharing best practices in state public policy for the nation's governors.This webinar will look at the United States as a case study of subnational coordination in response to crisis. Join us for a discussion with Timothy Blute, Director of the NGA Center for Best Practices, and Tom Kalil, Chief Innovation Officer at Schmidt Futures, to learn more about this pivotal and unprecedented subnational coordination in response to the COVID-19 crisis. Please click here for a funding brief with more details on the NGA's COVID-19 response to date.