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

**Harry Stebbings** (0:00)
Our guest today is the most prominent AI investor in the ecosystem, Anj Midha. Why is he the most prominent? Three reasons. Number one, he's one of the founding investors of Anthropic. Number two, he led AI investments for Andreessen Horowitz, where he made investments in Black Forest Labs, Mistral, Sesame, among others. And then third and finally, today he's the founder of AMP, where he provides compute and invests in the world's best AI companies. But before we dive into the show today, you have the idea, but often with AI tools, you hit a wall. Well, Base 44 is where that friction disappears, turning how you talk into how you build. Full stack web and mobile apps, sites, autonomous super agents, all built in minutes, not a weekend spent on damn configuration. Base 44 ships it all out of the box, the backend, the database, the authentication and the hosting. It handles the heavy lifting, so you can just stay in the flow. It doesn't just replace the busy work, it multiplies you, it makes you so much more capable, an effective version of yourself. In this market, being fast is the baseline, but to win, you gotta be first. And Base 44 is that edge. It's the move that lets you skip the troubleshooting and get straight to the breakthrough. Launch your next big thing at base44.com, that's base44.com. After Base 44 helps you launch, Corgi helps you cover what comes next. My word, what an arresting first line. Get your arse covered with Corgi Insurance. And I'll tell you why. If you're running a business right now, you already know this pain all too well. Getting insurance, it's really slow, it's confusing, and my word, it's full of paperwork. Well, that's exactly why Corgi is here to change the game. Corgi is the first and only insurance carrier, designed specifically for tech companies, allowing you to get covered in minutes instead of days. Corgi provides essential coverages for all growth stages, such as D&O, E&O liability, cyber, commercial, general liability, and more. Get your arse covered, I love the way we say arse, with Corgi Insurance alongside thousands of other startups at corgi.com/20vctoday.
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**Anj Midha** (3:32)
You have now arrived at your destination.

**Harry Stebbings** (3:35)
Anj, I am so looking forward to this, dude. I have stalked the shit out of you for the last three or four days. I spoke to Bing Gordon. I had a catch up with Bing before this. Very nice to speak to him. So thank you so much for joining me today, dude.

**Anj Midha** (3:48)
Thanks for having me. It's too long. It only took us what? Eight years, nine years? I forget when it was.

**Harry Stebbings** (3:52)
I was 12 when we last did it.

**Anj Midha** (3:54)
Yeah. Well, 12 in startup land is 25, right?

**Harry Stebbings** (3:59)
Dude, I'm confused. Help me out. I had Demis on the show the other day from DeepMind. He was like, yeah, I'm not sure if we're seeing scaling laws, but we are definitely seeing slightly diminishing returns slash performance as we scale. So potentially, are we getting to a stage where increased computers are no longer leading to increased performance?

**Anj Midha** (4:19)
Oh, no, absolutely not. That's 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, what about material science? You know, 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, you know, 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, it's well in the life.