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Anj Midha

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2026-04-14
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2026-04-14
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  1. “Well, step one is you get there first before people realize how valuable it is. I've been beating the drum beat on this for four years now. When I got to A16Z as a general partner, the first thing I did is I sat down with Mark and Benn and said, we need more compute. We need compute access for these incubations I'm going to do. And they said, no problem, Ange, let's set up a program. What do you need? So we used our balance sheet to start procuring compute through the oxygen program. That gave me the ability to build pretty deep relationships with the industry and build trust with compute partners who now we have lots and lots of relationships with that we're scaling in ways that would be very hard if I didn't have that time and the flexibility to understand what is required to really get that infrastructure right you know we've talked a little”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  2. “Access. And many of those teams today can't afford to pay an extraordinary prices for compute infrastructure today. And so, you know what? Yeah, we're happy to provide them access of that in a way that's mission aligned.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  3. “There are many up and down the stack because we see ourselves as a full stack scaling partner to the best frontier technology teams. And we also kind of see ourselves a little bit as our job is to propose independent standards for AI as an institution try to eventualize the adoption of those standards through profit generating businesses. We have a venture capital business. We also have an infrastructure business. A good example of this for now is we're actually giving away most of our compute at cost. Now, if you're a shareholder, you'd go, wait on, you have billions of dollars of compute infrastructure. You're giving away at cost? Yes, because we think that's the right thing for humanity. And we think that's the right way long term to have a healthy independent ecosystem, which is what our mission is. Our mission says AMP is a public benefit holdings company. Our vision is to ensure there's a healthy, independent frontier technology ecosystem. Our mission is to maximize the world's frontier output. To do that long term, the teams that are truly doing innovation, pushing the frontier of science and engineering need compute.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  4. “Okay, so tell him to give me a call when they'd like to be investors in the world's fastest growing business of all time. And then they can lecture me about public benefit governance and market share adoption. Public benefit governance gives the leadership the ability to make decisions that sometimes are not legible to shareholders as best for them.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  5. “No, what are you talking about? Look, I started AMP as a public benefit corporation because I think it's actually a very aligned model. Have you heard of REI, right? REI is a public benefit corporation. They make billions of dollars in revenue and profit. Have they ever been hauled up in front of Congress? No, like Ben and Jerry's public benefit corporation, have they been hauled up in front of Congress? No, it's because they self-moderated, right? At a time and they said, here's our mission. We have to build a business. Those things are not in conflict long term. If your goal in life is long-term to push humanity forward in some stable, reliable way, there always tensions where you have your mission and then you have your profit motive and you've got to be able to moderate between those two. I think public benefit governance allows you to do that. And I think we need more public benefit charters in Silicon Valley and in technology. And I think we will get there. If you look at the arc of infrastructure businesses, for example, right?”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  6. “I'm not sure I would because the world is a very different place today. And at the time, it really did feel like there was no one they could trust.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  7. “Well, so I've known Tom forever. Tom was one of the lead authors on GPT 3. We'd been friends for many years. And so Tom gave me a call and said Anj, for various reasons. We want to leave and start this new lab, call anthropic. We're going to need a lot of capital. We're going to need compute. I had already sold.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  8. “Well, I can't speak for OpenAI too much because I'm not involved there directly, but Anthropic, I will say, you know, the mission and vision has always been very, I think it's always been very American aligned, right? They've always said, hey, America is the crown jewel of the world in terms of innovation. This is where we're located. Again, Tropic is located in Silicon Valley. And I think the company really, really wants to do what's best for the American government and the American way of life, which is democracy and freedom. It turns out the world's largest enterprise customers are governments and Fortune 500 companies. And many of those that are overseas need these workloads to be running locally.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  9. “Me, yeah, independence at scale at every part of the AI infrastructure stack, like land, PowerShell in Europe, that's sovereign, it's local, compute infrastructure that's local, and models that are trained locally. By the way, fully open so they can be deployed and customized globally wherever needed, but certainly in Europe, like the full independent stack is the bet. Yeah.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  10. “Handle mission critical infrastructure at scale for AI. So you call up someone called Arthur Mensch, who is a French scientist from DeepMind, turned entrepreneur and starts a lab called Mistral, who is running massive workloads, and you say, Arthur, would you actually build infrastructure that can be secure locally? And that's why suddenly in July of 2025 at Vivatech in Paris, you have President Macron and Jensen standing on stage next to Arthur, a 33-year-old scientist unveiling a gigawatt AI infrastructure facility in Paris. Why? Because the context, the mission-critical context of those workloads is so important to be run locally that you can't run them on Amazon AWS GCP or Azure, and it's the first time in 15 years that the sort of hyperscaler dominance is up for grabs for startups.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  11. “Yeah, okay, the US Cloud Act says that there's any data workloads, cloud workloads running on infrastructure that is managed by an American company, then the U.S. government has to be able to access that data. Now, if you happen to be running military defense mission-critical workloads in Europe on AI infrastructure that is managed by an American company, well, that context, which is super critical, can't be sent over across the border. That's an example of a unique and sensitive context that needs to be run locally. And so if your ASML, your CMACGM that's doing logistics at scale, and some of this logistics is with mission-critical supplies, you can't have your supply chain data being processed by an AI bot that's running on servers that is subject to the cloud act. So what do you do? You look for local infrastructure partners, you start going, hey, who are the providers? AI infrastructure providers in Europe that we trust? Well, it turns out there aren't that many who can actually”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  12. “Yeah, this is a good question. Okay, if we want to sort of unlock frontier progress generally across a bunch of domains, then where are the bottlenecks and where will the value accrue? Context is not necessarily the moat. I would not say yet. I think venture capitalists are very quick to analyze moats, but I would say context feedback loops where you have unique and differentiated access is where progress will be most legible to you. And if there are other teams who don't have access to that content, it'll also be where you have a superior business model. And so here's an example I give in the class, right? Sovereign data. Are you familiar with the Cloud Act?”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  13. “Automation of those tasks, especially where there's coding involved, starting to be somewhat recursive, right? Where if you have a good coding model, then you can say, okay, let me automate like data analysis, let me automate data cleaning and so on. Some people would call that recursive self-improvement, totally happening, but it's not like I can just say to a coding model, please bootstrap a physical R&D lab for me in Menlo Park, get all the permitting, go find Anch to raise money from, go set up the physical infrastructure and just like bootstrap all this data. That's just an entirely different kind of frontier and execution and sort of problem.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  14. “Of different things. Yeah. You know, when I went to grad school for machine learning, I went to Stanford for bioinformatics, which was a machine learning applied to healthcare. The space was not as good as marketing as it is today. So super intelligence, love it. At the end of the day, what are we talking about? We're talking about very powerful models within some domain. And we are seeing within distribution very, very powerful capabilities that are, you can definitely call them superhuman because there's no way, for example, I as an individual scientist could analyze the reams and reams of data coming out of the lab here without AI models. There's just no chance. And so the fact that you can take all of the data from training from a physical lab and just throw it at a bunch of AI models and ask it to analyze things is a superhuman capability. We didn't have that before. Okay, fine. So let's call that super intelligence. Within coding, within material science, within each of these domain distributions, we are seeing capabilities that are superhuman. We didn't have them before. And in fact, I would say we're even starting to see.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  15. “Wherever there are some unique context feedback loops that are missing today, that's where you probably have the biggest bottlenecks on capabilities. And so what you should be doing if you're trying to advance the frontiers is going, okay, these models suck, for example, about a year ago, as an example, I realized there was a lot of talk about models being good at physics and chemistry. AI for science. And I was a visiting scientist at the Applied Physics Department at Stanford. And we started benchmarking these models. Claude, Gemini, and so on. And surprise, they sucked. They were so bad. There's this disconnect between the marketing hype of AI for science and the reality where these models are terrible at the time, at least they were starting to get good at code, but they were terrible at scientific analysis.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  16. “Was a huge bottleneck where we were trying to figure out which algorithms scale. Are there some limits to the transformer architecture versus diffusion models? And what I've come to realize is if you solve the culture problem, you can solve the research and the algorithmic problem. Then the bottlenecks of context feedback, which is what is the data you need to keep doing frontier research over and over again, is step number one, because actually I think that is also where you have the most business and commercial advantage. There's lots of alpha and value to be gained in pre-training, mid-training, and so on. But that last mile where you deploy a model or an agent in some new domain and then you collect feedback on how it's performing in real time. And then like I was saying, here we do physical verification of material science at periodics.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  17. “A very mission driven culture where they're like, we want to move the frontier of coding or the frontier of material science, the algorithmic stuff takes care of itself. That's actually not the bottleneck anymore, in my view. Two, three years ago”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  18. “So there's four or five. It's context, feedback, which I'm happy to talk about, it's compute, there's capital, which you need to continuously sort of deploy the compute in context feedback loops. And then there's culture. And I think that culture actually might be the most important bottleneck of all time. But those are the four, I would say. Now, look, algorithmic innovation, I think, is a function of culture, basically. Because if you have the right culture, you get to attract the best researchers. The best researchers, the best research talent, then wants to work on pushing the frontier. And algorithmic innovation just falls out of having a really good team that's very flexible on what kind of architecture they want to use. If you have the right culture, the algorithmic innovation bottleneck solves itself. Because then the researchers are not focused or tied to one architecture versus another. They're not going, I'm all in on LLMs or transformers versus diffusion models. The best scientists and researchers just want to solve the problem, the mission.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source

  19. “Oh no, absolutely not Not true at all. In certain domains that are well explored, like coding, for example, yes, there's an increasing amount of compute required to get an incremental gain in some eval that's super saturated. But if you said, Anj, what about material science? I'm sitting here at periodic labs office. This is my latest incubation is called periodic labs. I spent three days a week here in Mendel Park. We have a 30,000 square foot facility where we have LLMs that then predict new materials, new superconductors. We then have robots synthesize those new materials and then we have physical machines like x-ray diffraction machines validate whether those materials have the properties that were predicted by the LLMs. And then we pipe that verification data back into our training run, how many other times we need. And I can tell you throwing more compute at the problem is probably having super exponential gains right now per iteration. So it depends on which domain you're talking about, which modality. There's no saturation in superconductor discovery, for example, at all. The bitter lesson is holding is well.”

    2026-04-14 · The Twenty Minute VC · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · IDENTIFIED FROM THE TRANSCRIPT · source