[0:00] China's universities have cut more than
[0:02] 12,000 degree programs and they are
[0:04] redesigning their entire school system
[0:07] for artificial intelligence focused
[0:09] majors. We're going to look at what
[0:11] people call the holy grail of artificial
[0:13] intelligence breakthroughs, telling you
[0:15] where you lost your keys. Electronic
[0:17] Arts, the game company, actually
[0:20] released a new way for for you to
[0:23] advertise directly into video games. I
[0:26] was like, this is like another Google,
[0:29] right? I mean, if they build the
[0:30] plumbing for an entire ad marketplace
[0:32] that lives in three-dimensional space, I
[0:35] was like, I'm looking into it. We'll
[0:36] look at some thoughts from Rob Mason,
[0:38] take the 10,000 foot view, step back
[0:40] from the world of technology today, and
[0:43] figure out where are we, where are we
[0:45] going, and where have we been. I'll
[0:47] break down the viral economist post
[0:49] about how humanity is not ready for the
[0:51] upcoming intelligence explosion. I'll
[0:53] kind of share some of my thoughts on
[0:54] what they wrote. Author Tim Ferris, who
[0:56] I like I remember reading his books like
[0:59] decades ago, and I kind of forgot. I
[1:01] know he's been a podcaster for a while,
[1:03] but he just wrote this thing about like
[1:05] what AI is doing to the book publishing
[1:07] world. Then we'll get a little more
[1:08] philosophical about who should be
[1:10] benefiting from all of this change.
[1:12] David Kurpatre wrote the sharing
[1:14] algorithm. If AI is built on humanity,
[1:17] shouldn't humanity benefit? I'll share
[1:19] kind of the flip side of some of all of
[1:21] these AI tests that I'm always sharing
[1:23] because there was a really stringent
[1:25] math test and humans actually won it. AI
[1:27] did not take the crown even though we
[1:29] see all of these breakthroughs all the
[1:30] time. I mean, I don't know if they will
[1:32] be forever or how much longer, but today
[1:34] humans win. Some internet psychology
[1:37] that took me by surprise. Turns out
[1:39] harsh critics of things are usually the
[1:42] most loyal fans, especially of video
[1:44] game brands. But it actually kind of
[1:45] gives me a different perspective if
[1:46] they're actually the most loyal people.
[1:48] So over 100 cyber security experts are
[1:51] saying that the Fable 5 ban could
[1:53] backfire on the US. But experts are
[1:56] growing around one consensus and that is
[1:58] China is starting to crush the US in
[2:01] terms of AI growth. I mean there's a lot
[2:03] of ways to look at it. Certainly America
[2:05] has the lead in some very serious ways,
[2:07] but it's kind of wild how many edge
[2:09] cases we're starting to lose, especially
[2:11] when we have so much money and we had
[2:13] the head start. You know, good old chat
[2:15] GPT is now below 50% of the market
[2:18] share. And actually, after we talk about
[2:19] that, I'll dive a little bit into the
[2:21] big business of what's going on with
[2:24] this SpaceX IPO. It's it's a wild time
[2:28] to watch billionaires jockey for
[2:30] position. And there's it's pretty
[2:32] interesting positioning. And hey, when
[2:34] you're a trillionaire, it's like not
[2:35] even a tenth of your net worth. And you
[2:37] don't even have to pay for it. You just
[2:38] use your companies that have trillions
[2:40] of dollars. So, I get it. Just buy it. I
[2:42] mean, unless of course you care about
[2:43] citizens having any kind of say or
[2:45] control in our democracy, which nobody
[2:47] does.
[2:50] But look, Anthropic figured out the
[2:52] playbook about why coding is the single
[2:55] focus that you should be having and
[2:57] everyone else got a little distracted
[2:59] with side quests. So, we'll see if now
[3:01] that everybody sees what Anthropic sees
[3:03] where it all plays out. But first, if
[3:05] you don't mind heading over to Dylan
[3:07] Curious, actually, you're probably
[3:08] already there if you're watching this on
[3:09] YouTube, and hitting the share button,
[3:12] just like boom, share, copy, and send it
[3:14] to anyone. That would be super helpful.
[3:16] I know you guys did that on the last
[3:18] video, so thanks. It definitely helped.
[3:19] Look, you can see it did above average.
[3:21] Like by day four, we almost hit 10,000
[3:24] views. I made $77 on that video. That's
[3:26] crazy. I'm going to get some food.
[3:29] That's like four or five Chipotles. All
[3:31] right, so what are your thoughts? China
[3:32] is now cutting thousands of university
[3:35] degrees. Didn't even know there were
[3:36] that many. But they're thinking about an
[3:38] AI era and it kind of makes sense. I
[3:41] mean, it's a lot of government control
[3:42] over school, but also like we kind of
[3:45] need to get a little kick in the butt
[3:46] here to get ready for these huge changes
[3:48] that are coming. China's universities
[3:50] are making major changes to what
[3:52] students can study. The country is
[3:54] trying to line higher education up with
[3:56] a national development goal and that is
[3:59] to dominate and win against the United
[4:02] States in the future of artificial
[4:04] intelligence and technology and many
[4:06] other STEM programs. Arts and language
[4:09] programs are being dropped while tech
[4:11] focused fields are being favored. And
[4:13] it's what universities should do, right?
[4:15] They want to be preparing students for
[4:17] industries that are most important to
[4:19] the next decade. So that requires a
[4:21] national reshuffleling of education amid
[4:23] the backdrop of a much more techfocused
[4:26] future. All right. So if you've ever
[4:28] misplaced anything, which I think is
[4:29] pretty much all of us, I don't know how
[4:30] many do actually we should put in the
[4:32] comments like how many times a week do
[4:33] you lose something like your phone?
[4:35] Anything like phone or like scissors if
[4:37] I'm trying to like open some boxes or
[4:38] something. I probably misplace things
[4:41] like a dozen times a week. Yeah. Like a
[4:43] couple times a day or something. And it
[4:44] kind of sucks. I'm like or especially my
[4:46] AirPods. Actually, probably maybe more
[4:48] than that. I'm always using the find my
[4:50] feature where I'm like beep beep beep
[4:51] and I'm like oh it's on that side of the
[4:52] house. Yeah, that's right. But listen,
[4:54] people lose stuff all the time,
[4:56] especially groups of people working on
[4:58] construction sites or big companies like
[5:00] it can just get confusing. You're
[5:02] focused on your work, you set something
[5:03] down, someone else uses it, whatever. If
[5:06] you think about it, AI with camera
[5:08] vision watching everyone should be
[5:11] easily able to just be queried. Hey,
[5:13] where did I leave my phone? If that
[5:15] information is in context, it will
[5:17] remember when and where it was lost. And
[5:18] even if it's just visually available, it
[5:20] should be able to just, you know, hunt
[5:22] it down. So researchers are building
[5:24] robots that may soon remember places
[5:26] more like humans do, including where an
[5:29] object was last seen. And you can jump
[5:31] into the eyes of the AI to see the same
[5:34] thing that you should have remembered.
[5:36] So a worker can remember where she or he
[5:38] left a part in a factory last night. And
[5:40] a robot can do the same. A robot usually
[5:43] cannot do that well at this job because
[5:45] it struggles with memory that connects
[5:47] places and times together. But MIT
[5:49] researchers have built a new system to
[5:51] help robots learn that kind of memory.
[5:53] It is called DAM. But it's got extra A's
[5:56] in there. So it's not a swear word. It's
[5:59] D A A M. It stands for describe
[6:02] anything, anywhere, anytime, any moment.
[6:05] Oh my gosh. Actually, the acronym is
[6:07] missing an A. It's D A A M. Wait, what?
[6:11] So 1 A is anything. Second A is
[6:13] anywhere. Third one is any time. And
[6:16] then at any moment. You could have you
[6:18] could have thrown a fourth one in there.
[6:19] They missed an opportunity there. But
[6:20] anyways, as the robot moves through a
[6:22] space, it builds a 3D map. But it also
[6:25] adds rich labels to what it sees as it's
[6:27] going along. For example, it could
[6:29] remember a bike rack outside of a campus
[6:30] building. Maybe it has five bikes on it,
[6:33] one red, one yellow, one with a flat
[6:35] tire, etc. The system then groups
[6:37] objects by location so the robot can
[6:40] answer in plain language where something
[6:42] is later. And that is a new AI system
[6:45] where you can ask a question like where
[6:46] is the part that we started assembling
[6:49] last night. You don't even have to have
[6:50] it be something that it could tag like a
[6:53] part that doesn't even have a specific
[6:55] name because it can figure out what you
[6:57] mean based on the context of it. Knowing
[6:59] it was last night, knowing it was
[7:01] something you were assembling and it can
[7:03] just eliminate all of those other
[7:04] choices. And it has a special system for
[7:06] choosing clear images, describing
[7:08] several objects at once and avoiding
[7:11] labels on the same object again and
[7:13] again. And that actually was something
[7:15] that was really hindering some of the
[7:16] systems before this. So, what do you
[7:18] think? Do you think that's too much
[7:19] privacy invasion or do you just like the
[7:21] idea of knowing an AI knows everything
[7:22] about you and where you lost everything?
[7:24] All right, let's talk about this new EA
[7:26] advertising thing. Like maybe if you're
[7:28] already in the game world, this isn't
[7:29] like such a surprise to you. Maybe
[7:31] there's been like ads kind of shoved
[7:33] down your throats for a long time, but I
[7:35] don't really play much games, so I was
[7:38] not ready for this. I always imagined EA
[7:40] was just going to make money based on
[7:42] the games that it sold. I kind of knew
[7:44] it was moving towards a world where
[7:45] there's like recurring fees or maybe
[7:46] they like, you know, charge you for skin
[7:48] upgrades or whatever, but EA is going to
[7:50] get into the ad business. Like now
[7:52] they're going to fight for your
[7:52] attention inside of a game. Like what?
[7:55] So Electronic Arts has launched EA
[7:57] advertising. This is a new system that
[7:59] lets brands appear directly inside its
[8:01] games. That means ads can show up on
[8:03] stadium signs, digital billboards,
[8:05] scoreboards, broadcasting graphics,
[8:07] custom in-game items, and branded
[8:09] challenges. Is this going to ruin games
[8:11] or is this okay or is it make games
[8:14] better be free at least? The idea is to
[8:15] make ads feel more like part of the game
[8:18] setting in the same way brands already
[8:19] appear in real sports broadcasts. He
[8:22] says it reaches more than 120 million
[8:24] players each month. Oh my god, that's
[8:26] like the entire Super Bowl audience. It
[8:28] also says players are spending huge
[8:30] amounts of time in games like Madden,
[8:32] the NFL, EA Sports, where matches,
[8:35] seasons, and live sports style moments
[8:37] happen consistently. Like, you'd think
[8:39] if the NFL licenses the entire NFL to EA
[8:43] to make a game out of, wouldn't the NFL
[8:45] still own the brands or can EA just do
[8:47] this? And what does this mean for the
[8:48] future of VR and AR where everything's
[8:51] just being automatically generated? But
[8:53] yeah, this the kind of architecture
[8:55] behind it already includes reward-based
[8:57] goals, vanity items, branded content,
[8:59] live events, creator tools, social blade
[9:01] features, and community programs. What
[9:03] EA was the company that was just bought?
[9:05] It was bought, right, for like $60
[9:06] billion or something? Was EA recently
[9:08] bought? And if so, who was the buyer and
[9:10] price? What was the logic? Yeah. Okay,
[9:13] so $55 billion leveraged buyout, Saudi
[9:16] Arabia's sovereign wealth fund. That's
[9:18] right. I remember talking about that. I
[9:20] wonder if this was their plan. like they
[9:21] were just thinking, gosh, it's going to
[9:22] be so valuable if we can take some of
[9:24] Google's profits from ads and get them
[9:27] into games. Honestly, we're like later
[9:29] in this video, we'll talk about SpaceX
[9:30] buying Cursor for 60 billion. Th it
[9:33] would not shock me at all if SpaceX
[9:36] purchased EA for this much money because
[9:38] I mean, he's talked about creating a
[9:39] video game company. And if you already
[9:41] have Cursor and you already have like a
[9:43] bunch of inference systems that you can
[9:45] take back from Anthropic anytime you
[9:47] want, you know what? That might honestly
[9:49] happen. Maybe EA implements this ad
[9:52] thing, generates some insane revenues,
[9:54] and then sells it for what do you think?
[9:56] $180 billion to SpaceX in two years.
[10:00] There you go. That's my prediction. Let
[10:02] me know in the comments if you if you
[10:03] want to be on board with it. Over,
[10:05] under, happen, not happen, true, false,
[10:07] however you want to bet. All right,
[10:08] let's look at mid June 2026. Where are
[10:11] we at right now in the landscape of AI?
[10:14] Because you I mean, you know, if you
[10:15] watch this video how fast it feels like
[10:18] it's been going recently. Um, AI is
[10:20] moving fast, right? And I think I you
[10:22] see cracks all over governments and like
[10:24] banks. I think young voters are now
[10:27] really thinking about it like it comes
[10:29] up sometimes with politicians in a way
[10:31] that it never used to. And Rob Mason
[10:32] kind of broke this all down for us. So
[10:34] in one major a AI lab, Anthropic to be
[10:38] precise, they published a plan that
[10:40] threatened mass job losses as a real
[10:42] possibility. We talked about this in the
[10:44] last video too. Universal basic income,
[10:46] public wealth funds, some of those
[10:47] things. Um, timing was obviously messy
[10:50] because they're also trying to go IPO
[10:51] and they want to look like super
[10:52] profitable and super capitalistic at
[10:54] that time. So that, you know, cha-ching.
[10:56] So critics were asking whether this was
[10:58] real policy support or just smart IPO
[11:00] positioning, basically being like, we're
[11:02] going to gobble up all that value.
[11:03] Invest now. And then few days later,
[11:05] government says, no more Fable 5. Take
[11:08] away your like frontier model. Here's
[11:10] where we're at. The government sometimes
[11:12] is like totally handsoff. We just want,
[11:14] you know, business to like go. It feels
[11:16] like kind of a corrupt government.
[11:17] nobody's going to stop anything and like
[11:19] just big companies and K-shaped
[11:21] economies are going to happen. So, the
[11:22] government has sounded hands off on AI,
[11:24] but then it's used national security
[11:26] power to control access without clear
[11:28] legislation with all of this mythos
[11:30] stuff. Europe and the UK are reacting by
[11:33] taking it more seriously, but they're
[11:35] talking about sovereign AI, meaning they
[11:37] want to control their own advanced AI
[11:39] systems and they're trying to keep money
[11:40] inside their own borders. There's
[11:42] definitely a lot of fences going up all
[11:44] over the world. And at the same time, US
[11:46] senators, major banks, young voters,
[11:48] they're all moving into the debate in
[11:50] different ways. And some companies are
[11:52] just openly talking about AI replacing
[11:54] roles through automation. And it's just
[11:57] it, you know, it is their fiduciary
[11:59] duty, I suppose, but it also just
[12:01] doesn't resonate well with a society
[12:03] that's coming into the workforce. Young
[12:05] people are becoming less excited and
[12:07] more angry about AI. So, we'll have to
[12:09] see what happens. So just on top of like
[12:12] where politics and technology are
[12:14] intersecting, there's also just a
[12:15] natural trend, right? That this is like
[12:17] Ray Curtzwhile has been talking about it
[12:18] forever and we're getting into the
[12:20] hockey stick part of it. So this article
[12:22] is called humanity isn't ready for the
[12:24] coming intelligence explosion and it's a
[12:27] classic talking point on this channel.
[12:29] Uh AI leaders and everyone who's
[12:32] enabling them are moving humanity
[12:34] towards a race that is making smarter
[12:36] and smarter machines. And it's doing
[12:39] that without a real serious good
[12:41] trustworthy safety plan around it. Tons
[12:44] of emergent properties, tons of things
[12:45] that can't be predicted when systems are
[12:47] actually live and in people's hands,
[12:49] tons of things that are completely un
[12:52] unpredictable when different agents are
[12:54] acting with different intentions and
[12:56] different goals in some kind of like
[12:58] bigger system. So could AI be advancing,
[13:01] becoming more dangerous faster than
[13:03] governments are ready for? Absolutely.
[13:06] That's probably likely, not just a
[13:08] possibility. The article is comparing AI
[13:09] risk to nuclear risk. Nuclear plant is
[13:12] expected to have a tiny chance of a
[13:14] disaster. You know, a lot of people
[13:15] disagree with it and there are smart
[13:17] people that disagree with it. So, I
[13:18] wouldn't, you know, bank on it. That's
[13:20] just what feels right to me. And I'm
[13:22] sure a lot of new technology felt a lot
[13:24] scarier than it was when people first
[13:26] heard about it, before it was
[13:27] implemented, before structure came. So,
[13:29] it might move down. But, you know, the
[13:32] concern is not just coming from
[13:33] outsiders. It's coming from industry
[13:36] insiders too. Some of the people inside
[13:37] the biggest labs especially like
[13:39] recursive self-improvement. I mean you
[13:41] can see Anthropic and Musk moving
[13:43] towards it at the same time worried
[13:45] about whatever like happens when
[13:47] self-improvement is AI writing its own
[13:49] next model then generating it and then
[13:51] it writing its own code. I mean this is
[13:53] why a $60 billion investment in cursor
[13:55] might be nothing to SpaceX in the long
[13:57] run when it's a you know hundred
[13:59] trillion dollar broke the economy kind
[14:01] of company. And once there's an
[14:02] intelligence explosion, if the
[14:04] guardrails aren't good, there might be
[14:06] no way back. How are you going to, you
[14:08] know, there was that there's this
[14:09] metaphor once where somebody said, "Go
[14:11] up on the top of a hill and like cut
[14:13] open a pillow of feathers and like let
[14:16] the wind carry those feathers away and
[14:18] like now go put them all back in in the
[14:20] pillow." Like you can open it up pretty
[14:22] easily. You can just take a knife to it,
[14:24] cut it open, let all those feathers out.
[14:25] But to actually like put them back
[14:27] together, it's a much harder problem.
[14:30] and evolution and and growth like this
[14:32] now like actual intelligence in the way
[14:34] we see it in the biological world it
[14:35] once it gets going you don't just go
[14:38] back so the economist is now arguing
[14:40] that America and China in particular
[14:42] because these are the two countries
[14:44] controlling the vast majority of this
[14:46] progress and need to create serious AI
[14:48] safety agreements right now not based on
[14:52] trust based on verification based on
[14:54] inspections based on clear red lines if
[14:56] you go a little too far and slow down
[14:58] progress so be it like we'll have plenty
[15:00] of time when these things are
[15:02] exponentially growing to reap the
[15:03] benefits, but really right now
[15:05] biological weapons, cyber attack, fraud,
[15:08] child abuse, like there's child abuse
[15:10] material like being generated like all
[15:12] this stuff is coming really fast. So the
[15:14] article ends with a warning that
[15:16] civilization may fail when powerful
[15:19] tools grow faster than their ability to
[15:21] govern them. What do you think? Let me
[15:23] know in the comments. Yeah, I mean it's
[15:25] hard for me to say pause, right? Like
[15:27] I've never quite been a pause AI guy.
[15:29] Although, if I could magically just stop
[15:32] everything right now, I would. I just
[15:34] don't really think of any realistic way
[15:36] to just tell everybody like pause and
[15:38] have important people pause and have
[15:39] that be a a good outcome. But I kind of
[15:42] do agree that maybe just big governments
[15:45] right now getting serious about like red
[15:49] lines might and inspection like all
[15:51] getting all that system in place for
[15:53] inspections might be a really smart
[15:55] move. Now, I know bureaucracy is
[15:57] bureaucracy, but like let a bunch of
[15:59] people see what's going on behind closed
[16:01] doors and like force their hands as much
[16:03] as you can. Like one good thing about
[16:05] China and America, if we both let each
[16:07] other kind of look and see, there would
[16:09] be stealing and there would be copying,
[16:11] but on the other hand, we'd be seeing,
[16:13] you know what I mean? Like those
[16:14] conversations would get out and when
[16:16] super dangerous things happen, everybody
[16:17] might be aware of it at least. I go talk
[16:19] to Tim Ferrris, 4-hour work week. Like I
[16:21] remember he was he was like a in my
[16:23] world like a little cultural phenomenon
[16:25] in my a couple decades ago. I haven't
[16:27] heard much from him but he actually
[16:29] mentions the 4-hour work week which was
[16:30] like his self-help book from a long time
[16:32] ago and how it's been selling and how
[16:35] the industry is getting crushed. So
[16:37] having him talk about AI I found sort of
[16:39] surprising. So his core argument is that
[16:41] AI may be collapsing the market for how
[16:44] to non-fiction because people
[16:46] increasingly want the answer not the
[16:48] path there. And that's interesting.
[16:50] Like, is that another byproduct of using
[16:52] these LLMs all the time? So, if a book's
[16:55] main value is to tell me all the steps
[16:56] that I need to take and a chatbot can
[16:58] now feel faster, cheaper, more
[17:00] personalized, and more convenient,
[17:02] what's the point of self-help books? But
[17:04] Tim Ferris is also arguing that the real
[17:06] separation is between information and
[17:08] transformation. So, information is
[17:10] something like, give me five steps to
[17:12] lose fat, but transformation is walk me
[17:14] through a carefully designed journey
[17:16] that makes me actually change. And that
[17:18] difference matters. Chat bots can spit
[17:21] out fat loss protocols in 15 seconds.
[17:24] But Tim's example is when he took the
[17:27] 4-hour work week, which is this whole
[17:29] body transformation thing, and distilled
[17:31] it into some bullets and then sent it to
[17:33] friends, none of them acted on it. But
[17:35] thousands of readers who followed the
[17:37] full book's journey felt what they
[17:39] needed to like incorporate the
[17:41] information deep enough to actually
[17:42] change their lives. So, when I read this
[17:44] and then I started using LMS like I
[17:47] always do to um I do like moving some
[17:49] stuff around and trying to figure out
[17:50] how to like set up everything. I was at
[17:54] the end thinking did I actually learn
[17:56] how to do this for someone else? And I
[17:58] thought to myself like kind of not right
[18:00] like I if if someone else asked can you
[18:02] help me with this? I would say like yeah
[18:04] bring up bring up chat GPT and then ask
[18:07] this question and then it'll walk you
[18:09] through the steps. I think we went here
[18:10] first and I would follow it again. and I
[18:12] wouldn't actually be able to tell them.
[18:14] So, I didn't process it and it kind of
[18:16] freaked me out. And he's saying that
[18:18] prescriptive non-fiction is getting hit
[18:20] really hard. So, he says that his own
[18:22] print catalog may be down about 80%
[18:25] compared to the 2022 year. So, there's
[18:27] clearly less people just buying books.
[18:29] But self-help, he thinks, is especially
[18:32] vulnerable. Eventually, the same threat
[18:34] is going to be extended to YouTube, like
[18:36] the videos I make. like you might might
[18:38] not get as much out of this whole thing
[18:39] as you could just like go down to Gemini
[18:41] and distill this into like five news
[18:43] bullet points or interesting thoughts
[18:45] and then move along, you know, like I
[18:47] understand maybe some of you would want
[18:48] to do that. Podcast, courses,
[18:50] newsletters, advice blogs, like I guess
[18:53] if you just want to extract actionable
[18:55] information instantly, that's a better
[18:57] route to go. Next up, let's talk about
[18:59] the sharing algorithm. If AI is built on
[19:02] humanity, shouldn't humanity all benefit
[19:04] David Kurpatre? So he's arguing that AI
[19:07] didn't really come out of nowhere,
[19:08] right? Like artificial intelligence was
[19:10] built from human language, books, music,
[19:12] code art research news questions
[19:14] jokes, years of public investment, lots
[19:17] of people posting things on social
[19:18] media. But then companies built powerful
[19:20] AI systems and all of a sudden that work
[19:22] mattered for training. So if AI creates
[19:25] huge wealth, should only the companies
[19:27] that invented the thing that sucked it
[19:29] up and learned from it benefit or should
[19:31] all of us? I mean, the idea that a
[19:33] shared resource creates wealth that the
[19:35] public can own seems like one of the
[19:37] kind of futures that we almost
[19:38] inevitably will fall into. Like humans,
[19:41] the interesting things humans do, the
[19:43] data that we make, like that could be
[19:45] pretty valuable. I do think synthetic
[19:47] data is actually going to make
[19:48] everything people do kind of, you know,
[19:50] not as important as we'd hope. I I don't
[19:53] know how long human data will matter,
[19:55] but it probably will always matter.
[19:56] maybe at least enough that companies
[19:58] could somewhat pay taxes or the
[20:01] government would be rich enough or
[20:02] something that there could be some kind
[20:03] of universal basic income. And I will
[20:05] say for a long time I actually thought
[20:07] what's going to happen to AI is they're
[20:10] going to digest the internet like OpenAI
[20:11] was the first to kind of grab it and
[20:14] then I thought maybe right after them
[20:15] Google and a couple others and then
[20:17] they're going to produce so much garbage
[20:18] on the internet from chat bots that
[20:20] there won't be anything to put into the
[20:22] system. But over time I have come to
[20:24] just think that oh synthetic data
[20:26] actually I think it actually works.
[20:27] There's different novel ways to pull
[20:29] data off the internet. There's different
[20:30] ways to generate language in a way where
[20:34] it seems like the systems do learn. Um
[20:36] in some cases maybe they do kind of move
[20:39] to the middle and don't like have that
[20:40] massive creativity. But also I don't
[20:43] know. I got a feeling I got a feeling
[20:45] that's not going to be as as obvious as
[20:47] I once thought.
[20:50] Especially
[20:53] with like physics simulations and stuff
[20:54] like that and diffusion models of just
[20:56] like oh okay you can you can actually
[20:58] kind of come up with some pretty unique
[20:59] random stuff to learn from over even
[21:02] though you generated it. It's weird but
[21:03] it seems to work. You just kind of
[21:05] iterate towards better and better. But
[21:07] in some cases humans still matter. How
[21:09] about this one? Humans outperform AI on
[21:12] this highly rigorous mathematical test.
[21:14] This is good. I thought we were going to
[21:15] get crushed after like reading all these
[21:17] like math olympiad was destroyed by open
[21:20] AI and by deep mind. But a project
[21:23] called first proof gave AI models a very
[21:26] hard math exam. This was not the kind of
[21:28] school math. This was 10 research level
[21:31] problems from mathematicians own work.
[21:34] The problems were completely unpublished
[21:36] at the time of testing. So the models
[21:38] could not have just seen the answer and
[21:39] repeated them. 30 mathematicians checked
[21:42] their answers and that made this test
[21:44] very different from any of the earlier
[21:46] AI math demos that have ever been done
[21:48] before. This was new work. It was done
[21:50] without human help and it was judged by
[21:51] real experts. Four AI systems took this
[21:54] test. OpenAI entered Chat GPT 5.5 Pro
[21:59] and then the university teams built
[22:01] automated systems called harnesses on
[22:03] top of chat bots like Gemini and Claude
[22:06] for testing. Also, the harnesses asked
[22:08] the models questions. check the answers
[22:10] and pushed to improve. Now, the best
[22:13] system was chat GPT. It was GBT 55. It
[22:17] solved six of the 10 problems. It did
[22:19] not match human top mathematicians. The
[22:23] results showed AI can help with serious
[22:25] math, but not yet a full replacement for
[22:27] human expert problem solving. Wuzzing.
[22:30] What do you guys think about that one?
[22:33] Humans still in the lead. All right.
[22:35] also had a new epiphany that some of the
[22:36] harshest critics potentially even not
[22:38] just in games but like in my comment
[22:40] section might be the most loyal fans. I
[22:42] thought I thought the harshest people
[22:44] were just I was like gez guys like just
[22:46] chill. But no, harsh critics are the
[22:47] most loyal fans of video game brands.
[22:49] Study shows a new study looked at the
[22:51] way video game fans stay loyal to brands
[22:53] like Call of Duty and Battlefield. And
[22:56] instead of bringing people into a lab,
[22:57] the researchers used AI to study more
[23:00] than 23,000 Reddit comments. They wanted
[23:02] to see how loyalty shows up in real fan
[23:05] communities. And the results were not
[23:07] what people expected. There wasn't one
[23:09] clear pattern either. So, Call of Duty
[23:11] fans showed showed loyalty through
[23:13] emotion, stories, and shared memories.
[23:16] But Battlefield fans showed it through
[23:18] skill, technical details, and respect
[23:20] for how the game works. I was like,
[23:22] "Wow, these are really deep communities,
[23:24] like different languages, same deep
[23:27] loyalty." And the most interesting
[23:28] finding is that harsh criticism is
[23:31] usually a sign of commitment. Fans do
[23:33] not always complain because they hate
[23:34] the brand. They complain because they're
[23:36] invested and they want the game to
[23:38] improve. The same person who tears apart
[23:40] a flaw may defend the broad movement in
[23:43] an outsider attack. So the researchers
[23:46] are telling brands like you should stop
[23:48] trying to silence useful criticism. Like
[23:50] they're always trying to cut. Remember
[23:51] the uh was that Cyberpunk that release?
[23:54] Everyone's like just tearing on it. like
[23:55] those people probably really wanted the
[23:57] game to be good. They also learned that
[23:58] like fake corporate language like really
[24:00] pisses off fans. So maybe try to be a
[24:02] little more authentic when you talk to
[24:04] them. But either way, food for thought.
[24:06] So let me know in the comments. Do you
[24:07] think that the um mythos uh pullback was
[24:11] actually good for the United States in
[24:15] their position in the world? Do you
[24:17] think it's good for companies to not
[24:18] have cyber threats or do you feel like
[24:21] um it actually made us weaker? because
[24:23] there's some debate could go either way.
[24:26] But there's this open letter signed by
[24:28] hundreds of cyber security experts that
[24:30] asks US officials to lift export
[24:33] controls on anthropics fable and mythos
[24:36] AI models. The writers say that AI is
[24:38] already changing cyber security and it
[24:40] can help find software flaws and write
[24:42] exploits which are the tools that attack
[24:44] those flaws. But they argue that
[24:46] anthropics models are not uniquely
[24:48] dangerous. The major and open source
[24:50] models can already do similar work.
[24:52] their concern is that taking strong AI
[24:55] tools away from the defenders gives an
[24:57] advantage to the attackers or do you
[25:00] think that the attackers not having it
[25:02] make them weaker? You know what I mean?
[25:04] It's so tricky. They're arguing that
[25:05] security teams need these models to find
[25:07] and fix bugs in new code and old systems
[25:10] before the adversaries do. The letter
[25:12] also says that Fable already had strict
[25:14] protections against offensive cyber use.
[25:17] So banning access in total in their view
[25:19] just creates the market fear and weakens
[25:21] American AI without leading to any clear
[25:24] risk reduction. So consensus is growing
[25:27] that China is crushing the US at AI.
[25:30] There is a few things that AI in the US
[25:33] is still clearly in charge of and front
[25:36] and leading the pack. In terms of raw
[25:39] intelligence, the frontier models and
[25:41] the amount of money spent on
[25:42] infrastructure, we're definitely
[25:44] winning. But global opinion is shifting
[25:46] the AI race away from the United States
[25:49] and towards China. So a poll by Public
[25:52] First asked people in 15 other countries
[25:55] which nation they think is leading in AI
[25:57] capability and innovation. And in 11 of
[25:59] those countries, respondents said that
[26:01] China has passed the United States. And
[26:03] what were the countries that still
[26:04] thought the United States was leading?
[26:06] Well, one was US, the United States. So
[26:08] we think we're doing great. Also
[26:10] Vietnam, India both also agree with us
[26:13] and same with Japan. But even inside the
[26:16] US, confidence was not strong. Just 51%
[26:19] of Americans said their own country is
[26:21] leading. So three, you know, just 51% is
[26:24] like barely over half of us. Canada,
[26:26] Mexico, France, United Kingdom, they're
[26:28] all thinking that China is beating us.
[26:30] It also reflected a certain frustration
[26:32] with American AI models, which the
[26:33] article describes as corporate,
[26:35] extractive, and hostile towards workers.
[26:38] These countries saw China as a country
[26:40] that presented itself as having stronger
[26:43] competition and more people centered
[26:45] regulation. The main claim is not that
[26:47] like China is ahead. It's that the
[26:49] world's trust is moving away from the
[26:51] United States and towards China and that
[26:53] creates a legitimacy problem for Silicon
[26:56] Valley. What do you think? Are you out
[26:58] of the 51% do you lean towards thinking
[27:00] like American AI is I don't know more
[27:03] people centric or it's going to be
[27:04] better less extractive? I mean,
[27:06] obviously it's not going to be like less
[27:08] corporate or less extractive. We're the
[27:09] United States, but is it still still
[27:11] winning or in the long run, do they have
[27:13] a better sort of pipeline built? I don't
[27:15] know. I'll make this one quick, but just
[27:17] so you guys know, Chad GBT is now under
[27:19] 50% for the first time. So, what's going
[27:22] on here? I want to dive into it a little
[27:23] bit. I'm also going to touch on the
[27:25] cursor and the codeex and like what
[27:28] companies are doing as far as their
[27:29] positioning each other and uh what
[27:32] exactly was $60 billion like just that
[27:35] is that that's so overvalued in a nonAI
[27:38] world that is so almost undervalued in
[27:41] the long-term thinking of an AI frontier
[27:45] model play. So, it's just the whole you
[27:48] if you buy the story that like AI is the
[27:51] invention of intelligence and whoever
[27:53] gets there first gets like so much
[27:55] reward then you know what that that
[27:58] makes sense and honestly like probably
[28:00] no matter what you buy at this point if
[28:02] you truly believe that's the story you
[28:04] could justify it. I mean look
[28:05] realistically you have to even kind of
[28:07] wonder if SpaceX what's it trading at
[28:09] like two trillion market cap and then uh
[28:12] Tesla's another 1.3 1.5 trillion. So if
[28:16] you take all of that Elon's in chart and
[28:18] plus like Neuralink and all these other
[28:19] things, he's got to be coming up on $4
[28:22] trillion worth of buying power and a
[28:24] trillion dollars personal wealth,
[28:27] you know, and if OpenAI just goes
[28:29] public, if Anthropic goes up public at a
[28:32] trillion dollars, like maybe he could
[28:34] buy both of those companies or one of
[28:36] them and just merge them in or
[28:38] something. So, you know, I don't know
[28:40] who's big enough really. I feel like
[28:42] Google and maybe Microsoft are too big
[28:44] to be acquired. maybe meta, but there
[28:47] might be we might be coming down to like
[28:49] in the long run and might not even be
[28:51] that long. Like I'm thinking just two,
[28:53] three years, we might see some crazy
[28:55] consolidations. Like there could be a
[28:56] true merger between like Meta and
[28:59] Microsoft or something because there's
[29:01] something happening with like Google and
[29:03] SpaceX. I think Google owned a bunch of
[29:05] SpaceX stocks, so there's they're like
[29:06] tied into that a little closer. But uh
[29:08] let's look at this article. Michael
[29:10] Spencer, Jeff uh Mohouse wrote, "Codeex,
[29:13] Cursor, and the great beyond. Open AI
[29:15] will be put under pressure by Meta AI,
[29:17] SpaceX, and China, not just Anthropic's
[29:20] Enterprise AI momentum." So, there were
[29:23] less than 60 people that owned the stock
[29:26] for Cursor. So, $60 billion made them
[29:29] all billionaires, which is like
[29:30] mind-blowing to me because it's a fork
[29:33] of VS Code. It was like an open- source
[29:35] software, and it was awesome. and it was
[29:38] a way to just plug large language models
[29:39] in and code. But, you know, they built
[29:41] an amazing tool for enterprise and it
[29:43] just has so many people using it and it
[29:45] has such an interesting information loop
[29:47] and it's so valuable to an AI company
[29:50] like SpaceX that's behind anthropic in
[29:54] terms of coding. And if you believe
[29:55] coding is the flywheel effect where if
[29:58] you get code right, then you can catch
[30:00] up on everything else. Like there's no
[30:01] need to have a video model right now or
[30:03] an image model. just like just code and
[30:05] then we'll code everything that we need
[30:07] in the future and then it'll code some
[30:09] super advanced model that does even
[30:11] better video and audio or whatever all
[30:13] these side quests that you want to
[30:15] tackle. Like it will just code them all
[30:16] up for you and you will win them all.
[30:18] But it puts OpenAI, which now is under
[30:21] 50% market share, in a strange position.
[30:24] Like they seemed untouchable a couple
[30:26] years ago, but they're under pressure
[30:27] from every side. And now SOAR has been
[30:30] cancelled and um Stargate, it doesn't
[30:32] feel like they're going to get as much
[30:34] money as they thought and you know
[30:35] there's all this other competition going
[30:37] on. So Ched GBT, no doubt about it,
[30:39] still has a huge reach. But I mean I
[30:41] don't find myself in it as much as I
[30:43] ever used to. I mean first off that
[30:44] whole ad thing was bothering me. But
[30:47] also, when you're in Chrome and there's
[30:50] Gemini right there and you're kind of in
[30:52] a Google workspace or you're in a
[30:54] Microsoft 360 workspace, they have their
[30:56] own models where you're going to go to.
[30:58] When you have questions inside meta,
[31:00] they have their own unique data source.
[31:01] And chat GBT still has its spot, but it
[31:04] just I don't know, it does feel kind of
[31:06] like I I got this sense that Google's in
[31:09] the best position in the long run. that
[31:10] that's my main bet. But I'm also I
[31:13] wouldn't be surprised especially with
[31:15] SpaceX having like essentially infinite
[31:17] money and having having so much extra
[31:22] compute. I mean they Elon built so many
[31:24] servers so fast and they really are
[31:26] valuable. Like they're I think he's paid
[31:28] off all of them just with the money he's
[31:29] getting from Anthropic. So that was like
[31:32] an insanely profitable decision to just
[31:34] push those things out. then China as a
[31:37] whole can mount a pretty good, you know,
[31:40] a little bit of that communism there can
[31:41] like really just force companies to work
[31:43] together and try to take on individual
[31:46] companies in the US which might force
[31:48] individual companies to go to these like
[31:50] crazy mergers. But anyways, ChadB still
[31:52] has huge reach but the article says that
[31:54] its market share is failing because
[31:56] Gemini, Claude, Meta AI, Space XAI and
[32:00] Chinese models are putting that pressure
[32:02] on them from every direction. Really,
[32:04] Meta should have made that. If
[32:05] Zuckerberg was serious, he's putting a
[32:07] lot of money on talent. Like, they
[32:08] probably should have bought Cursor.
[32:11] Maybe Microsoft should have bought
[32:12] Cursor. I mean, they already have
[32:13] GitHub, which is pretty powerful. So,
[32:15] maybe I understand why Microsoft didn't.
[32:17] But Curser already had fast revenue
[32:19] growth, strong use among software
[32:21] engineers, and a product people trusted.
[32:23] And that makes it a direct threat to
[32:25] OpenAI's Codeex plans. Codeex used to be
[32:28] simple. It was OpenAI's coding
[32:30] assistant. You gave it a software task
[32:32] and it helped turn that idea into code.
[32:34] But now Codeex is expanding beyond
[32:36] programming. AI wants it to handle
[32:38] broader work across tools like Gmail,
[32:41] Calendar, PowerPoint, and computer use.
[32:43] And don't get me wrong, this is probably
[32:45] the right move for them. I just don't
[32:47] think they're going to pull it off. I
[32:48] just think that's hard. But if I was if
[32:51] I was Sam Alman, I also actually would
[32:52] be doing this cuz you don't want to
[32:54] think small at this moment. Maybe maybe
[32:56] they'll have something that kind of
[32:58] carries them through the day. But the
[33:00] risk is execution. If OpenAI can merge
[33:03] chat GPT and codeex really seamlessly,
[33:06] if they can somehow make the average
[33:08] person just sit down with the tool and
[33:10] start kind of accidentally dreaming up
[33:13] things that are coded into reality and
[33:16] hosted and profitable. And it really is
[33:19] like the Apple moment for them. They
[33:22] might they might be able to continue
[33:24] this route. If not, I think I think the
[33:28] walls are closing in on them.
[33:31] I mean, don't get me wrong, everyone
[33:32] there is going to end up being a
[33:33] billionaire and like Chad GPD won't just
[33:35] be gone, but it's not Sam Alman's moment
[33:39] to potentially outdo Elon will be gone.
[33:42] All right, so if you enjoyed this video,
[33:44] please share it with a friend. You're on
[33:46] YouTube, there's a little share button
[33:48] right there. Please send it to somebody.
[33:50] But if not, leaving a comment, hitting
[33:52] that hype button if you guys remember
[33:54] that, thumbs up, all that stuff. Like
[33:56] any interaction with the the video
[33:58] helps. And just the fact that you're
[33:59] still here watching it means a lot to
[34:01] me. So, thanks and I will see you in the
[34:03] next video.