Valuetainment - ＂Threatening Established Players＂ - Meta AXES 8,000 Jobs As The AI Takeover Begins

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00:00:30.600 Facebook layoffs.

00:00:31.800 I don't know what page that story is on, but this is a very, very interesting story.

00:00:37.760 Rob, if you have what page the story is.

00:00:39.960 So Facebook is laying off a bunch of people today.

00:00:43.820 But guess what they announced to their employees?

00:00:45.600 If you just tell me the page, I'll go to it.

00:00:47.580 The meta layoffs are addendum page 7.

00:00:51.160 I see it.

00:00:51.680 Perfect.

00:00:52.080 So Facebook is laying off 8,000 employees today amid AI transformation.

00:00:57.720 But guess what they're telling their employees?

00:00:59.380 Don't come to work today.

00:01:00.700 What do you mean?

00:01:01.600 No, no, while we're doing this, just work from home today.

00:01:03.420 Don't come to work today.

00:01:04.200 Why don't I need to come to work today?

00:01:06.000 Well, here's why.

00:01:07.180 For the last month, employees at Meta have been on the edge.

00:01:09.920 April, they were told that 8,000 of them were 10% of the workforce will be laid off on May 20th.

00:01:14.640 May 20th is here as Meta made itself, remade itself for the artificial intelligence age.

00:01:20.540 On Monday, they learned another 7,000 would be reassigned to new AI initiatives.

00:01:26.120 The act started to fall in Singapore, where at 4 a.m. local time, Wednesday, emails went out to workers who were being laid off.

00:01:33.260 Employees in Britain, U.S., and elsewhere will be notified Wednesday morning in their respective time zone.

00:01:38.000 Meta's offices were set to be mostly empty on Wednesday after Janelle Gale, the company's head of human resources,

00:01:45.620 told employees this week that they should work from home on the office walls.

00:01:49.100 Some workers had hung up flyers sharing a petition to stop Meta's new program to track their data for AI training

00:01:57.060 Eight employees said some workers scavenged the office for free snacks and laptop chargers on Monday

00:02:03.260 In case they no longer had jobs by the end of the week

00:02:05.400 Said the employees who declined to be identified for fear of retaliation

00:02:09.400 The turmoil of Meta, which owns Facebook and Instagram

00:02:12.820 WhatsApp offers an up-close of layoffs in the AI age.

00:02:17.380 Last week, the networking giant Cisco said it would eliminate 4,000 jobs

00:02:21.060 that has shifted more resources to AI.

00:02:23.380 Microsoft Block Coinbase recently announced layoffs or buyouts

00:02:26.160 because of the powerful technology.

00:02:28.360 So, Tom, we're seeing this going into companies like Meta,

00:02:33.120 massive company, multi-trillion-auto company.

00:02:35.400 How important of a story is this?

00:02:36.980 I think it's very important.

00:02:38.280 We covered this about a month, month and a half ago.

00:02:40.700 I 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.

00:02:50.140 And 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.

00:03:01.660 Now, what is Reality Labs?

00:03:03.480 That is the name that Facebook gave to the group that was building Metaverse.

00:03:07.660 So in other words, they have been delaying, and the people that were there put the comments on.

00:03:12.660 By the way, Reddit suddenly becomes the conscious of Facebook because everything can go out there,

00:03:16.560 and people have burner accounts on Reddit and whatnot.

00:03:19.280 You found out that at Reality Labs that was formerly, what would they call it, Oculus,

00:03:24.500 they were going to put on the goggles and all that.

00:03:27.380 So that was bloat.

00:03:28.380 So what I'm getting to is there was a lot of bloat that was delayed layoffs that Facebook did early in the year that Wall Street loves.

00:03:36.460 Wall Street loves it when you take a one-time charge and it's not long-term because now you've reduced operating expenses.

00:03:43.380 As long as you're showing growth, now your P.E. is up.

00:03:46.220 Life is good.

00:03:47.200 Good things are happening.

00:03:48.360 But what this is signaling is a bigger contraction.

00:03:52.620 And 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.

00:04:04.000 And 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.

00:04:13.660 So 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.

00:04:26.380 And 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.

00:04:34.680 So this is related to it. In Q1 2026, this was the largest global VC investment period of all time.

00:04:47.560 $331 billion globally venture funded investment.

00:04:52.560 Now, did that go into small companies that are there, people with a hoodie trying to get someone in there?

00:04:57.560 Nope.

00:04:58.720 50% of it went into four companies, OpenAI, Anthropic, XAI, and Waymo.

00:05:04.100 50% of four companies.

00:05:05.140 50% of it.

00:05:06.440 Wow.

00:05:07.180 And then 80% of the total went into AI, and 65% of the 80% or 50% of the total was only OpenAI, Anthropic, XAI, and Waymo.

00:05:18.400 But wait a minute.

00:05:18.960 Who's got all that money?

00:05:20.280 That's a ton of money.

00:05:21.220 You 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.

00:05:32.180 They would jump into things like late-stage Uber before Uber went public.

00:05:36.840 That's where the money came from.

00:05:38.380 You know where this money came from?

00:05:39.640 Check this out.

00:05:40.720 It came from the following.

00:05:44.140 SoftBank put $30 billion in 2026 into OpenAI.

00:05:48.300 That's Japan.

00:05:49.820 Middle East and Gulf states, check this out.

00:05:52.000 MGX, that's the UAE's version of PIF, which is Saudi's public investment fund, right?

00:05:58.420 So MGX was UAE, took the lead.

00:06:02.240 They're the lead in OpenAI's $122 billion round.

00:06:06.560 And they also invested in, remember, put two chips on two companies,

00:06:10.620 Anthropix's $30 billion Series G that just happened,

00:06:13.780 and then Humane, PIF, put $3 billion into XAI,

00:06:18.140 And 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.

00:06:40.420 You are now having to go right past the big U.S. banks that used to do these things, and I named them.

00:06:49.180 You know, people like T. Rowe Price, Fidelity, all have big CBC, corporate venture capital groups.

00:06:55.620 But 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.

00:07:04.680 They get rid of the bloat that they had with the old metaverse, and boom, then 10,000 people are out there looking for jobs.

00:07:14.160 It's all happening, and the question is, you know, Carpathie, who is joining Anthropic now on pre-training, pre-training is important.

00:07:24.300 That's step one.

00:07:25.280 That's where you somehow assimilate huge, massive stacks of data and let the AI go digest it like food.

00:07:32.540 And that's what he's going to work on is pre-training.

00:07:34.940 And so the question is, do you have Anthropic now having to go scale to meet it?

00:07:41.560 And something you said about the alignment, are they really aligned on safety?

00:07:45.780 Or did they just go hire the scaling guy in advance of the IPO?

00:07:51.060 And now they've got to go jumping into pre-training because they've joined the scaling race.

00:07:55.220 Luke, thoughts?

00:07:55.780 it's a lot there with facebook with the money going into 330 billion 50 percent going to four

00:08:02.120 companies it's fascinating on number levels number one who has to play now right so who has to play

00:08:09.440 it's these big sovereign wealth funds then you get into okay how you know we're in this race with 0.94

00:08:14.620 china are we going to be able to firewall technology historically it's a little trickier 0.81

00:08:21.140 if it's not in our borders let's see this foreign-owned infrastructure or foreign investment 0.92

00:08:25.520 We don't know. Number two, it ties into the war. What happens when the biggest hyperscaler

00:08:34.660 infrastructure was in the UAE? Iran's drones were targeted at very specific

00:08:43.080 parts of that infrastructure. Where is it at? From a financing standpoint, the longer this war

00:08:50.340 drags on. The more, you know, the Saudis, Saudis ran a, they're running a nearly, I believe,

00:08:57.200 20% budget deficit. They've spent three quarters of their projected deficit for the year in the

00:09:03.480 first quarter. So they are going to blow. So they're going to need to go out and borrow money

00:09:07.120 just to finance this. So where are, or are they going to sell other assets to make sure they make

00:09:14.760 that's, that has market implications that ultimately puts interest rates up, which we're

00:09:19.420 seeing go across the world um i think it's it's all it also points to you know to richard's point

00:09:25.080 it's it to the extent there is a disruption at a meta um i mean this sounds very familiar to i think

00:09:31.880 any american engineer listening to this where over the last 20 years they they trained their

00:09:36.440 replacement over in a in a low-cost country and then were let go it's to the extent that the meta

00:09:41.780 is almost doing this with an ai where people are training the model internally and then being let

00:09:46.260 go. And then, you know, like, like I said, with Richard's point, it ultimately is an opportunity

00:09:51.520 for entrepreneurship. If, if you can use the AI well, as an entrepreneur, you can compete in the

00:09:59.340 same way that iTunes and, and distributed music, if you will, changed and broke the monopoly of

00:10:07.420 the record companies and the, and the, and, you know, now it comes down if to be successful in

00:10:12.820 the music business. I mean, there's a lot more musicians, there's a lot more choice, but you,

00:10:17.900 you, you are not beholden to the record companies, to getting radio airtime, to the, to the, to the

00:10:22.520 promotional companies. If you can play and you can work, you've got a shot. And so that's the,

00:10:28.800 you know, there, there's a whole slew of, you know, from the very good of, Hey, if you can play,

00:10:33.060 you've got a shot. So if you're a great thinker and you use AI, well, you can take on any company,

00:10:39.040 no matter their market cap from anywhere in the world.

00:10:41.800 There's probably some poor kid sitting in India today 0.95

00:10:44.980 that's an absolute genius and working in a garage, 1.00

00:10:50.220 living at home, and is going to come up with the next big thing

00:10:53.060 in the next three years.

00:10:54.380 And he's not going to have graduated from MIT or Stanford

00:10:57.280 or any of these places.

00:10:58.680 AI can do that.

00:10:59.400 And the flip side of it is this disruption side

00:11:01.820 at the other end of the spectrum of companies have data.

00:11:07.660 Corporate America, maybe the biggest underappreciated asset in America is all these companies' data.

00:11:12.700 I'm told that, for example, Procter & Gamble holds the value of their data at basically zero on their balance sheet.

00:11:20.640 There's no explicit is what I've been told.

00:11:23.440 And if that's the case, think about what's the actual monetary value of Procter & Gamble's data.

00:11:29.540 It's immeasurable.

00:11:30.580 And so if they can use that data, use AI, wow, A, it's great for corporate America.

00:11:37.020 And 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.

00:11:45.820 And usually doing more with less in the corporate world is doing more earnings with less people.

00:11:51.640 Richard?

00:11:52.280 Yeah, so the threat is clearly to the big companies are threatened by AI and the established players, exactly as Luke explained.

00:12:02.140 and that's also where we have the more bloated employment practices

00:12:07.900 because inside companies, it's politics, it's hierarchies,

00:12:11.640 people building little empires, they're hiring their team

00:12:14.720 and there's competition inside companies between groups and players

00:12:19.240 and you get all these games and fun and games.

00:12:22.540 But small firms cannot afford any of that.

00:12:27.200 The small firms, micro-businesses, they're extremely lean structures

00:12:30.800 And 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.

00:12:51.340 Now, 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.

00:13:02.860 That's something AI has not figured out yet and that they haven't been able to train AI to do.

00:13:08.380 So entrepreneurs are safe.

00:13:10.900 In fact, it's the other way around.

00:13:13.120 Entrepreneurs now, you know, get more opportunities and they're getting a big boost if they use this.

00:13:18.960 And I think they will because, you know, that's the whole point.

00:13:22.140 In small firms, people are more flexible and they are able to think outside the box.

00:13:28.160 But the funding thing is the limit.

00:13:30.560 So I think actually we should argue.

00:13:32.360 And interestingly, you know, we have at the end of the week a new Fed chair sworn in.

00:13:38.500 And so Kevin Walsh has actually said that he believes productivity is going to go up thanks to AI.

00:13:48.960 And that has implications for monetary policy.

00:13:52.280 And he's going to run monetary policy with that in mind.

00:13:55.940 Well, and I'm, you know, I mean, this is a message to him, really, and to his people.

00:14:00.540 There's some good people at the Fed.

00:14:02.360 For example, Mickey Bowman, who's the vice chair, she actually, you know, is a great supporter of small banks, local banks, community banks.

00:14:10.140 That's her thing.

00:14:11.760 Well, so what are the implications for monetary policy, you know, of AI?

00:14:17.920 It 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.

00:14:40.460 That was the United States because it was all pioneering new things

00:14:43.860 and also new technology and entrepreneurship.

00:14:47.480 And at that time, it was so much easier to establish banks to fund this

00:14:52.620 because we need the funding.

00:14:54.520 And nobody's figured out anything better and more efficient

00:14:56.600 than this decentralized mechanism for decentralized local decision-making,

00:15:01.480 which is having many local banks.

00:15:03.640 And, you know, we discussed China when the Chinese,

00:15:06.500 Deng 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.

00:15:32.080 And it is actually principle that the Prussian army introduced.

00:15:35.780 You know, the officer in the field has to have decision-making power.

00:15:40.620 That was the idea of the Prussian king, and he put it in the laws.

00:15:43.260 It was even in the Prussian constitution and the laws concerning the army.

00:15:48.320 Whereas Britain and then later the United States in the Second World War,

00:15:53.560 they used the old, which is actually the central planning idea,

00:15:57.800 that the officer gets instructions not just what to do, but also how to do it.

00:16:02.080 And that's the most frustrating thing, because in the fog of war, things change very quickly.

00:16:07.300 But you have orders to do this, which doesn't make any sense, right?

00:16:10.440 And this is how you become very ineffective.

00:16:12.500 And, you know, there's studies, military studies, on the First World War,

00:16:16.700 done by all sorts of international researchers, looking at the German army and the British army.

00:16:21.800 And the German army was much more effective.

00:16:24.880 And the same in the Second World War, American army and German army.

00:16:28.520 I 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.

00:16:40.180 You know, doesn't mean you have to win the war because, of course, you can be so outnumbered.

00:16:45.020 But that's established.

00:16:46.700 And why was that?

00:16:47.440 Because of this old Prussian principle that the officer in the field had decision-making power.

00:16:52.400 Now, for this to work, and the Prussians understood this, and later Germany understood this very well, you have to train people.

00:16:59.060 So education is very important, because they have to be able to make these decisions.

00:17:04.980 But you want to decentralize this.

00:17:07.620 And in the economy, this is reflected by a structure of many, many small firms.

00:17:15.220 And they get their money from banks.

00:17:17.120 And this is what works.

00:17:18.000 It's very well established.

00:17:18.920 And so having, like China, moving to 5,000 banks with all these local branches

00:17:26.360 and then essentially millions of local loan officers

00:17:32.020 receiving hundreds of millions of applications from small firms.

00:17:36.720 And they are trained to do this.

00:17:39.500 They select the most effective, most promising applications.

00:17:45.020 And when a bank lends, this is the other important thing,

00:17:47.480 why this is directly linked to monetary policy.

00:17:49.980 When a bank gives a loan, it's actually money creation.

00:17:52.760 People tend to forget this because, you know,

00:17:54.440 the textbooks and the mainstream media

00:17:57.360 still talks about banks as intermediaries.

00:17:59.100 They gather deposits and they lend this money,

00:18:02.440 which is not true, actually.

00:18:05.140 And what I've empirically shown with my empirical tests,

00:18:08.000 you know, if you Google,

00:18:08.980 can banks individually create money out of nothing?

00:18:12.020 You know, get the paper.

00:18:12.940 It's published in a highly ranked finance journal.

00:18:15.060 or the other one, lost century in economics,

00:18:18.200 you find the proof that banks,

00:18:21.540 when a bank gives a loan,

00:18:23.420 it's allowed by our system,

00:18:25.080 this system has been around for centuries,

00:18:27.300 to create new money.

00:18:29.700 So the loan money that a company gets

00:18:31.880 is actually newly created money

00:18:33.640 that's added to the money supply

00:18:35.340 and that has macroeconomic consequences.

00:18:37.580 So if banks mostly lend

00:18:39.460 for productive business investment

00:18:40.860 to entrepreneurs, small firms,

00:18:43.140 that's when you get maximum growth.

00:18:45.060 So the question is with the regulation.

00:18:46.700 They need to deregulate to open it up.

00:18:48.500 Exactly.

00:18:48.980 Right now it's still too hard.

00:18:49.740 That's the restriction.

00:18:50.580 Well, let's see if they're going to do that or not because there's – the market needs it.

00:18:54.520 Every time, like even we talked about it last time with the quantitative easing when money went in,

00:18:58.480 money went to the rich, money went to the big companies, money went to buybacks, money went to bailout,

00:19:02.680 and it didn't go to the people that needed it.

00:19:04.400 So we need to – and I do – the president needs to see this.

00:19:07.740 I think they're aware of this, and hopefully something changes about it.

00:19:10.660 I want to remind you guys that the Vol Conference we do once a year, Rob, if you want to –

00:19:14.720 For those guys that are small business owners and you want to find how to compete in a market like this, don't go about it yourself.

00:19:20.320 Be in a community with other people.

00:19:21.680 They can share with you what they're doing.

00:19:23.160 We grew this thing from first event being 440 people to last year nearly 8,000 people.

00:19:29.540 This year we're expecting 12,000 people at MGM Grand Arena.

00:19:33.300 Rob, I don't know if they've given you the video or not.

00:19:34.920 If you do have it, if you want to play the clip, go for it.

00:19:37.320 And it's a great opportunity for all of us to get together in one place where we talk about business, family.

00:19:43.200 There's no walking on eggshells.

00:19:44.560 We'll talk about every single thing at one event.

00:19:46.480 Go ahead, Rob.

00:19:47.580 Successful business people speak a language others don't.

00:19:50.100 It's like when I lived in Germany at age 10 and a month later I'm speaking German.

00:19:53.640 Because I immerse myself in a community of Germans, I speak that language.

00:19:57.500 The same applies for business.

00:19:58.860 So studies have shown that 65% of people that immerse themselves in a new language

00:20:04.260 completely feel like a different person on the other side.

00:20:07.200 So what does it mean?

00:20:08.140 You go to a business conference, you're at the VOL conference,

00:20:10.640 12,000 other people around you for four days.

00:20:12.760 we're speaking a language that we're fluent in, in business, how we walk into Rome, how

00:20:17.800 we negotiate a deal, how we hire somebody, how we raise capital, how we come up with

00:20:22.460 a new strategy.

00:20:23.380 The more you're around it, you all of a sudden start speaking that language fluently.

00:20:27.440 So when you go back home, you do deals in a different way.

00:20:30.200 You handle your business in a different way.

00:20:32.380 If you want to get fluent and speak in a business language, once a year we host a conference

00:20:36.280 called the Vault Conference.

00:20:37.860 This year for the first time, we're doing it at the MGM Grand Arena in Las Vegas, where

00:20:41.760 we go through this 296-page manual with 12,000 people over four days in one room.

00:20:48.560 If you haven't yet registered, click on the link above or below.

00:20:51.960 Bring your spouse, bring your partner, bring your peers.

00:20:54.480 Let's spend four days to get out of Las Vegas, August 31st through September 3rd.

00:20:59.040 Looking forward to seeing you there.

00:21:00.540 Go to vault2026.com, get your ticket.

00:21:02.840 Again, vault2026.com, get your ticket.

00:21:05.720 Cannot wait to see you and your family at the Vault Conference together.

00:21:08.840 If you enjoyed this video, you want to watch more videos like this, click here.

00:21:11.760 And if you want to watch the entire podcast, click here.

Valuetainment - May 21, 2026

＂Threatening Established Players＂ - Meta AXES 8,000 Jobs As The AI Takeover Begins

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