8,000 people have been laid off from the company and 7,000 more have been reassigned to new AI initiatives. This is the latest in a growing list of announcements from companies across the tech space that have laid off employees.
00:02:38.280We covered this about a month, month and a half ago.
00:02:40.700I remember one of the things that I had done research and found out was that there was a lot of people, the first layoff that they were announcing, they announced in January 2026.
00:02:50.140And in that January 2026 announcement was hidden the fact that there was 1,500, then another 700, then another 1,000 that were all supposedly related to Reality Labs.
00:03:48.360But what this is signaling is a bigger contraction.
00:03:52.620And the big statement inside of the Facebook announcement that I saw, 7,000 people internally being reassigned to AI initiatives from whatever they were working on.
00:04:04.000And I was trying to find on Reddit and other places how much of that was Reality Labs, and the answer is a good amount of it is, but I didn't find any, like, hard figures.
00:04:13.660So if you were working on various things, smart engineers are being put on the product that they think needs more smart engineers, which is AI, which I thought was very, very interesting how this happened.
00:04:26.380And to give you the scope of AI and maybe get right back, kind of reflect on banking we just talked about, Pat, you want some very interesting investment stories.
00:04:34.680So this is related to it. In Q1 2026, this was the largest global VC investment period of all time.
00:05:21.220You know, this used to be that when you reach this way, you would hear about Fidelity, T. Rowe Price, and BlackRock, all who have venture arms, and they would jump into things like WeWork.
00:05:32.180They would jump into things like late-stage Uber before Uber went public.
00:06:02.240They're the lead in OpenAI's $122 billion round.
00:06:06.560And they also invested in, remember, put two chips on two companies,
00:06:10.620Anthropix's $30 billion Series G that just happened,
00:06:13.780and then Humane, PIF, put $3 billion into XAI,
00:06:18.140And then not to be outdone, you know who led Anthropic Series G? Singapore, GIC and Temasek. These are giant sovereign funds that are now putting the money in because the dollars are so big. You don't go down. You don't go to Sequoia. You don't go to Benchmark. You don't go to the usual suspects there, Kleiner Perkins.
00:06:40.420You are now having to go right past the big U.S. banks that used to do these things, and I named them.
00:06:49.180You know, people like T. Rowe Price, Fidelity, all have big CBC, corporate venture capital groups.
00:06:55.620But look at the amount of this money coming from there into AI internationally, and then you look at 7,000 people at Facebook get shifted over to AI.
00:07:04.680They get rid of the bloat that they had with the old metaverse, and boom, then 10,000 people are out there looking for jobs.
00:07:14.160It's all happening, and the question is, you know, Carpathie, who is joining Anthropic now on pre-training, pre-training is important.
00:11:30.580And so if they can use that data, use AI, wow, A, it's great for corporate America.
00:11:37.020And B, the better they can use it, the more efficient they can be, great for corporate America, but more efficient means doing more with less.
00:11:45.820And usually doing more with less in the corporate world is doing more earnings with less people.
00:12:11.640people building little empires, they're hiring their team
00:12:14.720and there's competition inside companies between groups and players
00:12:19.240and you get all these games and fun and games.
00:12:22.540But small firms cannot afford any of that.
00:12:27.200The small firms, micro-businesses, they're extremely lean structures
00:12:30.800And it boils down to entrepreneurs, their ideas, their creativity, and their entrepreneurial energy, flexibility, speed, and quick decisions, intuition, understanding, and having a hunch that this could now become a thing and actually going for it.
00:12:51.340Now, this is something, this entrepreneurial spirit, and I think at Vault, you know, there will be a lot of, you know, input and discussions of things like that and that are relevant there.
00:13:02.860That's something AI has not figured out yet and that they haven't been able to train AI to do.
00:14:02.360For example, Mickey Bowman, who's the vice chair, she actually, you know, is a great supporter of small banks, local banks, community banks.
00:14:11.760Well, so what are the implications for monetary policy, you know, of AI?
00:14:17.920It is this point that we now have an additional reason, bigger reason than ever before, to have a new drive where we say, hey, this is a bit like in the first half or middle part of the 19th century where America was an emerging market economy and was growing really fast, you know, double-digit growth.
00:14:40.460That was the United States because it was all pioneering new things
00:14:43.860and also new technology and entrepreneurship.
00:14:47.480And at that time, it was so much easier to establish banks to fund this
00:15:03.640And, you know, we discussed China when the Chinese,
00:15:06.500Deng Xiaoping had this explained in Japan to him, and he got it very quickly, and he moved from central banking, central planning, one bank, Soviet system, to the decentralized model that the Asian high-growth economies actually adopted from Germany and originally Prussia, which used to be, that was the first high-growth economy even earlier, and they had many, many small local banks, because it's important.
00:15:32.080And it is actually principle that the Prussian army introduced.
00:15:35.780You know, the officer in the field has to have decision-making power.
00:15:40.620That was the idea of the Prussian king, and he put it in the laws.
00:15:43.260It was even in the Prussian constitution and the laws concerning the army.
00:15:48.320Whereas Britain and then later the United States in the Second World War,
00:15:53.560they used the old, which is actually the central planning idea,
00:15:57.800that the officer gets instructions not just what to do, but also how to do it.
00:16:02.080And that's the most frustrating thing, because in the fog of war, things change very quickly.
00:16:07.300But you have orders to do this, which doesn't make any sense, right?
00:16:10.440And this is how you become very ineffective.
00:16:12.500And, you know, there's studies, military studies, on the First World War,
00:16:16.700done by all sorts of international researchers, looking at the German army and the British army.
00:16:21.800And the German army was much more effective.
00:16:24.880And the same in the Second World War, American army and German army.
00:16:28.520I mean, again, the German army was much more effective with, I mean, usually outnumbered, you know, 10 to 1 or even more, you know, on the Eastern Front, you know, 50 or 100 to 1 and extremely effective.
00:16:40.180You know, doesn't mean you have to win the war because, of course, you can be so outnumbered.