Big Brain AI
@realBigBrainAI • 15,526 subscribers
Learn to not get left behind when AI takes over
Shorts
Videos
Architects used to draw every parking space by hand, this TestFit AI does the whole lot in seconds.
Big Brain AI5,529,132 views • 1 month ago
Perplexity CEO Aravind Srinivas on why the equation 1.01^365 = 37.78 is his team's core mantra:
Big Brain AI204,075 views • 10 days ago
This installation by Kim Seonghyun makes AI's invisible logic visible in real time.
Big Brain AI2,427,787 views • 3 months ago
Jensen Huang, NVIDIA CEO: "It even runs large language models" — a $249 AI computer that fits on your desk.
Big Brain AI1,206,927 views • 2 months ago
XPeng's new AI parking feature lets you draw your spot on the screen and the car does the rest.
Big Brain AI1,276,314 views • 3 months ago
The creator of Linux, Linus Torvalds, just unknowingly obliterated Elon Musk in one sentence:
Big Brain AI1,148,344 views • 2 months ago
One person just made a Transformers-level VFX sequence on a single GPU.
Big Brain AI692,064 views • 2 months ago
Jack Dorsey, co-founder of Twitter (now X) and Block, on why treating AI as a "copilot" is a losing strategy: jack argues that most companies are approaching AI in a way that will make it nearly impossible for them to survive. "I think most of the industry is thinking about AI as like a co-pilot, as something that is augmented onto, rather than like how do you just rebuild our whole company with this as the core." His concern is that bolting AI onto existing structures produces companies that look indistinguishable from each other, and from the AI labs themselves. "If it doesn't make sense for your business to do that and you end up being or looking very similar or rhyming too closely with the frontier labs, then I think it's going to be very, very challenging to differentiate and survive." This thinking has been driving his decisions since early 2024, when these tools "really came to bear." That's when his team began building Goose, an agent coding harness, as part of a broader effort to rebuild around AI rather than layer it on top. The core insight? Speeding up old workflows with AI is a short-term gain every competitor will match. Real differentiation comes from rebuilding the company itself around intelligence.
Big Brain AI862,076 views • 2 months ago
Jack Dorsey, co-founder and Head of Block, Inc, on the biggest mistake companies are making with AI right now: "I think most of the industry is thinking about AI as like a co-pilot, as something that is augmented onto rather than like how do you just rebuild our whole company with this as the core." jack believes this mindset of treating AI as an add-on rather than a foundation is where most companies are going wrong. And he draws a sharp line between those who will thrive and those who won't. It comes down to one question: does your business understand something deep about human nature? "Are you building a business that understands something of human nature deeply and it gets deeper every single time, and that's a real tangible signal that just doesn't go away. If you are, then I think you can build your company as an intelligence. If you're not, then it's probably an add-on to something else." And for companies whose AI strategy starts to resemble what the frontier labs are already doing, he has a blunt warning: "If you end up being or looking very similar or rhyming too closely with the frontier labs, then I think it's going to be very, very challenging to differentiate and survive." This urgency isn't theoretical for Jack. Since January 2025, when agent coding tools like Goose and Claude Code became available, he's dedicated three hours every morning to testing their boundaries firsthand. "That whole year I just spent every single day for three hours every morning just pushing myself like can I get it to do something that I didn't think it was capable of or I didn't think I was capable of. Every single day it worked, every single day I was surprised." It's that daily, compounding experience that fuels his conviction. He's watched these tools exceed expectations repeatedly, and yet he sees most leaders failing to grasp how fast things are moving. "The compounding nature of this is pretty incredible, so being able to see that, understand it, and then shift your company to be ahead of it, I think is absolutely critical right now." His sharpest words are for those reducing AI to a simple efficiency play: "They're just living in this abstraction of like, oh yeah, these tools will make everyone in our company 10x more productive. I don't think this is a productivity thing; I think it's a structural thing that needs to shift."
Big Brain AI48,010 views • 6 days ago
Eric Schmidt, former CEO of Google, offers a sobering view: The biggest technological shift in human history is happening, and almost no one is talking about it. Schmidt opens with a startling industry prediction: "We believe as an industry that in the next one year the vast majority of programmers will be replaced by AI programmers. We also believe that within one year you will have graduate level mathematicians that are at the tippy top of graduate math programs." He explains why this matters so much. Programming and math aren't just two fields among many: "Programming plus math are the basis of sort of our whole digital world." And the AI labs are already using AI to build better AI: "The research groups in OpenAI and anthropic and so forth… around 10 or 20% of the code that they're developing in their research programs is being generated by the computer. That's called recursive self-improvement." Eric Schmidt then lays out the timeline most people haven't grasped: "Within 3 to 5 years we'll have what is called general intelligence AGI which can be defined as a system that is as smart as the smartest mathematician physicist artist writer thinker politician." He gives this belief system a name: "I call this by the way the San Francisco consensus because everyone who believes this is in San Francisco it may be the water." But the truly unsettling part comes next. Once AI starts improving itself, humans become optional to the process: "The computers are now doing self-improvement… they don't have to listen to us anymore. We call that super intelligence or ASI… computers that are smarter than the sum of humans. The San Francisco consensus is this occurs within six years." And here's where Schmidt sounds the alarm. The conversation isn't keeping pace with the technology: "This path is not understood in our society. There's no language for what happens with the arrival of this. This is happening faster than our human that our society, our democracy, our laws will address." His closing thought captures why this matters: "That's why it's underhyped. People do not understand what happens when you have intelligence at this level which is largely free."
Big Brain AI633,695 views • 2 months ago
Jonathan Ross, Founder and CEO of AI chip company Groq, offers a contrarian view: AI won't destroy jobs, it will create a labour shortage. He outlines three things that will happen because of AI: First, massive deflationary pressure. "This cup of coffee is going to cost less. Your housing is going to cost less. Everything is going to cost less." He explains this will happen through robots farming coffee more efficiently and better supply chain management, meaning people will need less money. Second, people will opt out of the economy. "They're going to work fewer hours. They're going to work fewer days a week, and they're going to work fewer years. They're going to retire earlier because they're going to be able to support their lifestyle working less." Third, entirely new jobs and industries will emerge. Jonathan points to history as evidence: "Think about 100 years ago. 98% of the workforce in the United States was in agriculture. When we were able to reduce that to 2%, we found things for those other 98% of the population to do." He continues: "The jobs that are going to exist 100 years from now, we can't even contemplate." Software developers didn't exist a century ago. In another century, they won't exist either, "because everyone's going to be vibe coding." The same applies to influencers, a career that would have been unthinkable 100 years ago but now earns people millions. His conclusion: deflationary pressure, workforce opt-outs, and new industries we can't yet imagine will combine to create one outcome... "We're not going to have enough people."
Big Brain AI1,383,568 views • 6 months ago
Former U.S. presidential candidate Andrew Yang on why "learn to code" went from the safest career advice to the worst in just 4 years: Yang recently returned from an AI conference out west and what he heard alarmed him. "They said to me that what we're going to see in the next 6 months outstrips what we've seen in the last 10 years cuz the rate of change is on a hockey stick and heading up. And I got to say I'm pretty up to date on this stuff and it blew my mind on some of the stuff I was seeing." One example stuck with Andrew Yang🧢⬆️🇺🇸. "There was one company that is selling autonomous coding for enterprises to big businesses and their revenue is up 100-fold in the last 12 months." The implication is significant: "If that continues, it's going to eat a lot of the tech budgets from major corporates that used to go to humans. And so you're seeing the employment of recent computer science graduates fall off a cliff from a lot of programs." Yang points out the irony of how quickly the advice has flipped: "If you rewind what 4 years ago, what would we tell young people for a secure career, learn to code? And now the opposite of that is true." On where this is heading long term, Yang cites Anthropic's CEO: "Dario Amodei, the CEO of Anthropic, laid it out very clearly and he's been doing so repeatedly, saying we're going to automate away up to 50% of entry-level white collar jobs in the next several years. And I believe him." His reasoning for why entry-level roles get hit first is blunt: "The easiest people to fire are the people you haven't hired yet, which again is why you see the hiring of recent college graduates heading down." And the data backs it up: "The underemployment rate over 50%, the unemployment rate among college graduates is now the same or higher than non-college graduates for the first time in history."
Big Brain AI346,416 views • 2 months ago
Peter Steinberger, creator of OpenClaw, on why AI agents still produce "slop" without human taste in the loop: "You can create code and run all night and then you have like the ultimate slop because what those agents don't really do yet is have taste." Peter is direct: raw capability without direction still produces mediocre output. "They are spiky smart and they're really good at things, but if you don't navigate them well, if you don't have a vision of what you're going to build, it's still going to be slop. If you don't ask the right questions, it's still going to be slop." Great AI-assisted work is defined by the human guiding it. Peter Steinberger 🦞 describes his own creative process when starting a new project: "When I start a project, I have like this very rough idea what it could be. And as I play with it and feel it, my vision gets more clear. I try out things, some things don't work, and I evolve my idea into what it will become." Most people skip this part entirely, front-loading everything into a single prompt and wondering why the result feels hollow. "My next prompt depends on what I see and feel and think about the current state of the project." Each step informs the next. The work itself is the feedback loop. "But if you try to put everything into a spec up front, you miss this kind of human-machine loop. And then I don't know how something good can come out without having feelings in the loop — almost like taste." The agentic trap is what happens when you remove yourself from the process too early.
Big Brain AI488,306 views • 3 months ago
Andrew Ng, co-founder of Google Brain and Coursera, on the worst career advice being given about AI right now: He doesn't mince words about what he's hearing from supposed experts: "As early as earlier this year and certainly last year, there are a few people advising others to stop learning to write code because AI will automate it." His reasoning is rooted in a historical pattern most people miss: "As something becomes easier, more people should do it, not fewer. When the world moved from assembly language to COBOL, there were actually articles saying, 'Well, we now have COBOL. Programming is so easier. Looks like we don't need programmers anymore.' But the opposite happened." Andrew believes the same thing is happening now with AI-assisted coding: "As we now have AI assisted coding, a lot more people should be coding. And I think the demand for software, custom software, has no practical ceiling. So the cost of software engineering comes down, which it is, we'll just get more and more great software out in the world." But here's where the advice gets uncomfortable for experienced engineers. Andrew Ng is honest about what he's seeing on the ground: "It is true that a fresh college grad that is really on top of AI will outperform a full stack engineer with 10 years of experience that is still doing things they were back in 2022, 3 years ago before GenAI." However, there's a nuance most people miss when they hear that stereotype: "The other piece that is less well appreciated is the best engineers I know are not fresh college grads. They're actually very experienced engineers that deeply understand architecture and the conceptual framework of how to think about computers and additionally are on top of AI and on top of these AI skills."
Big Brain AI211,530 views • 1 month ago
Citadel CEO Ken Griffin on why the AI boom might be the most overhyped tech cycle we have ever seen: This year alone, data center spending in the United States is projected to exceed $500 billion. And Griffin wants to know what all of that money is actually buying. "You're not going to generate this kind of spend unless you're going to make a promise. You're going to profoundly change the world." In his view, the scale of the capital commitment demands the scale of the promise. And when the promise has to be that big, hype becomes inevitable. "Is it hype? Of course." Griffin isn't arguing that AI is worthless. He sees real impact in certain areas like call centers and software engineering. But for the broader white collar workforce, he's far less convinced. He points to a recent Harvard paper that coined the term "AI work slop." It looks impressive on the surface, but falls apart the moment you look closer. He saw it firsthand inside Citadel. A colleague running their commodities business handed him a report generated by an AI engine. "The first few sentences like, 'Wow, that's really insightful.' And then you go down below that and it's all garbage." For Griffin, this is the defining tension of the current AI cycle. The industry needs to promise transformation to justify the investment. But the actual productivity gains, for most jobs, haven't shown up yet. We have seen this pattern before. Transformative technology attracting massive capital well ahead of proven results. When the hype finally settles, will AI have actually changed anything at all?
Big Brain AI400,298 views • 3 months ago
Marc Andreessen explains why we are only three years into what is effectively an 80-year technological revolution: He opens with a blunt assessment: "This is the biggest technological revolution of my life. This is clearly bigger than the internet. The comps on this are things like the microprocessor and the steam engine and electricity." But to understand why, you have to go back 80 years. In the 1930s, the pioneers of computing understood the theory of computation before they'd even built the machines. And they faced a fundamental choice. Build computers in the image of the adding machine — hyper-literal, mathematical, capable of billions of operations per second, but unable to understand human speech or deal with humans the way humans like to be dealt with. Or build computers modelled on the human brain. Neural networks. They chose the adding machine. And that single decision shaped everything — mainframes, PCs, smartphones, every dollar of wealth the computer industry created over the next 80 years. IBM itself is the successor company to the National Cash Register Company of America. The lineage runs that deep. But here's what makes this moment so extraordinary. They knew about the other path. The first neural network academic paper was published in 1943. Marc points to a remarkable piece of forgotten history: "There's an interview you can watch on YouTube with the authors. It's him in his beach house, not wearing a shirt, talking about this future in which computers are going to be built on the model of the human brain." That was 1946. The vision existed. The path just wasn't taken. So neural networks spent the next eight decades living in the shadows. Kept alive by a small academic movement — first called cybernetics, then artificial intelligence — that refused to let the idea die. And for most of that time, it simply didn't work. "It was basically decade after decade after decade of excessive optimism followed by disappointment." By the time Marc reached college in 1989, AI was a backwater field. Everyone assumed it was never going to happen. But the scientists kept working. Quietly building up an enormous reservoir of concepts and ideas across those decades of disappointment. And then Christmas 2022 arrived. ChatGPT. And suddenly: "All of a sudden it's like: oh my god. It turns out it works." That moment wasn't the start of something new. It was the payoff on an 80-year-old bet that almost everyone had written off. Which is exactly why Marc's framing matters so much: "We're three years into what is effectively an 80-year revolution." Most people are treating AI like another technology cycle — something to adapt to, ride, and wait out. But if Andreessen is right, we are not adapting to a new cycle. We are standing at the very beginning of the longest and most consequential technological transformation in human history. The road not taken in the 1930s is finally being built. And we have barely broken ground.
Big Brain AI381,517 views • 3 months ago