Hamzat ademola

@Wartzyy

Earth

Joined May 2011

134 Following

25 Followers

228 Posts

Pinned Tweet

Hamzat ademola @Wartzyy

over 5 years ago

Anticipate a street version of bmw e30

Hamzat ademola @Wartzyy

18 days ago

Mr money

GIRAN REPUBLIC

@giran_republic

19 days ago

4 years ago I didn’t have $500 in my account, but now look at me. 🗣️ M$NEY

166

775

146

154K

Wartzyy retweeted

Apple Lamps

@lamps_apple

6 months ago

TERAFAB: The Most Ambitious Chip Factory Ever Announced Twenty gigawatts. That's the current total output of AI compute on Earth. Every fab, every foundry, every semiconductor line on the planet… combined. The Terra Project needs one terawatt. That's a 50x expansion of everything humanity currently produces. Put differently, all existing fabs on Earth deliver roughly 2% of what's required. So, Elon Musk announced he's building the rest himself. He called it "the most epic chip building exercise in history." The Supply Chain Math The existing semiconductor giants… TSMC, Samsung, Micron… are expanding. Musk has said publicly, in his words, that he's told them directly... he will buy all of their chips. Every single one. But their comfortable expansion rate doesn't come close to closing the gap. The math is simple... if every fab on Earth runs at capacity and you're still 98% short of your target, you either build the missing capacity or you don't hit the number. TeraFab is the answer to that 98% deficit. Located in Austin, Texas, with support from Governor Abbott and the state, this facility is designed to do something that does not exist anywhere else in the world. The Recursive Loop Here's why TeraFab matters structurally, not just at scale. Traditional chip manufacturing is fragmented. You design in one location, fabricate masks in another, manufacture in a third, test somewhere else, then ship corrections back through the chain. Every handoff adds weeks. Every iteration cycle burns months. TeraFab consolidates the entire silicon lifecycle… lithography mask fabrication, logic chip production, memory chip production, advanced packaging, and testing… inside a single building. Design a mask. Print a chip. Test it. Redesign the mask. Print again. All under one roof. The result? An iteration speed an order of magnitude faster than anything else in the global semiconductor industry. That speed advantage is the whole game. It means TeraFab can run what Musk calls "wild and crazy" experiments in new compute physics that no traditional foundry would risk, because the feedback loop is so tight that failures cost days instead of quarters. No other facility on Earth integrates mask-making, logic, memory, packaging, and testing in a single building with this kind of recursive improvement cycle. It changes the competitive math for the entire semiconductor industry. Two Chips, Two Missions TeraFab is designed to produce two fundamentally different classes of silicon. Edge inference chips are optimized for Tesla's Optimus humanoid robots and vehicle fleet. The production target for Optimus alone is staggering… 1 billion to 10 billion units per year, which is 10 to 100 times global vehicle production of roughly 100 million annually. Every one of those robots needs onboard AI processing. The chip volume required is unlike anything the semiconductor industry has ever contemplated. Space-optimized high-power chips are engineered for an environment that destroys conventional hardware. High-energy photon bombardment causing bit-flips and structural degradation. Electron buildup with no atmospheric discharge path. Zero convection for cooling. These chips are deliberately designed to run hotter than terrestrial silicon… a counterintuitive choice driven by hard physics. In a vacuum, heat rejection follows the Stefan-Boltzmann Law, scaling with the fourth power of temperature. Hotter chips mean smaller radiators. Smaller radiators mean less mass per kilowatt. Less mass means more compute per Starship launch. The target metric... 100 kilowatts of compute per ton delivered to orbit. Musk expects space compute to constitute the vast majority of total output, with terrestrial chips capped at an estimated 100 to 200 gigawatts per year due to ground-based power constraints. The remaining 800+ gigawatts to reach the terawatt target has to be space-native. The Orbital Economics The strategic logic behind TeraFab only makes sense when you understand why space-based AI is projected to undercut terrestrial AI costs within 2 to 3 years. Solar panels in orbit generate at least five times the energy of ground-based equivalents. No atmospheric attenuation. No day/night cycle. No seasonal variation. Arrays stay constantly perpendicular to the sun, maximizing capture every second. No need for heavy glass or steel framing to survive weather. And because it's always sunny… no massive battery storage systems required. On Earth, every additional gigawatt of power generation gets harder and more expensive. You run out of optimal sites. You hit NIMBY resistance. The marginal cost curve goes up. In space, the opposite happens. Every additional gigawatt gets cheaper and easier. The scaling curves run in opposite directions. Once Starship drives launch costs low enough, the economics flip permanently. The initial deployment unit is a 100-kilowatt "minissat"… a compact compute satellite with solar panels and radiator, scaled to fit Starship payloads. Future iterations are expected to scale to the megawatt range per satellite. And for the skeptics debating whether heat rejection in space is even feasible... SpaceX currently operates over 10,000 satellites in orbit. The radiator is small relative to the solar array. The physics works. The Credibility Stack Here's why dismissing this as vaporware would be a mistake. Reusable rockets were called impossible. SpaceX has now landed over 500 times and made reusability economically viable. Electric cars were written off as toys. Tesla now produces 2 million per year. xAI… now integrated as part of SpaceX… built the world's first gigawatt-scale compute cluster so fast that Nvidia's Jensen Huang said he'd never seen anything constructed at that speed in his life. Starship V3 is designed to deliver 200 tons to orbit, up from the 100-ton baseline. Starship V4 will be significantly larger still. The target throughput... 10 million tons to orbit per year at 100 kilowatts per ton. Musk states explicitly... no new physics or impossible breakthroughs are required. The engineering is hard. The physics is known. The Bigger Picture TeraFab is Phase 1. Even a terawatt of compute, enormous by current human standards, is still just an early step on the Kardashev Scale. You're not yet a Type 2 civilization. You don't even register as Type 3. The full roadmap extends to petawatt-scale compute… a thousand times larger than a terawatt… enabled by electromagnetic mass drivers on the lunar surface. The Moon's lack of atmosphere and one-sixth gravity means payloads can be accelerated to escape velocity without rockets, collapsing the cost of deep-space deployment by orders of magnitude. A combined workforce of Optimus robots and humans would build and operate these systems. A petawatt of compute would capture roughly one millionth of the Sun's total energy output. For context, that would power an economy a million times larger than Earth's current GDP. But none of it happens without the chips. SpaceX can build the rockets. Tesla can build the robots. xAI can architect the intelligence. The bottleneck was always silicon. The Bottom Line Every semiconductor line on Earth, running flat out, delivers 2% of what the Terra Project requires. TeraFab is the industrial answer to a 98% deficit… a single-building recursive manufacturing loop designed to out-iterate the entire global foundry ecosystem by an order of magnitude, producing chips engineered for environments no existing fab was built to serve. No new physics. No impossible breakthroughs. Just the biggest bet on semiconductor manufacturing anyone has ever made, backed by the only companies that have already done what people said couldn't be done.

lamps_apple's tweet photo. TERAFAB: The Most Ambitious Chip Factory Ever Announced

Twenty gigawatts. That's the current total output of AI compute on Earth. Every fab, every foundry, every semiconductor line on the planet… combined. The Terra Project needs one terawatt. That's a 50x expansion of everything humanity currently produces. Put differently, all existing fabs on Earth deliver roughly 2% of what's required.

So, Elon Musk announced he's building the rest himself. He called it "the most epic chip building exercise in history."

The Supply Chain Math

The existing semiconductor giants… TSMC, Samsung, Micron… are expanding. Musk has said publicly, in his words, that he's told them directly... he will buy all of their chips. Every single one. But their comfortable expansion rate doesn't come close to closing the gap. The math is simple... if every fab on Earth runs at capacity and you're still 98% short of your target, you either build the missing capacity or you don't hit the number.

TeraFab is the answer to that 98% deficit. Located in Austin, Texas, with support from Governor Abbott and the state, this facility is designed to do something that does not exist anywhere else in the world.

The Recursive Loop

Here's why TeraFab matters structurally, not just at scale.

Traditional chip manufacturing is fragmented. You design in one location, fabricate masks in another, manufacture in a third, test somewhere else, then ship corrections back through the chain. Every handoff adds weeks. Every iteration cycle burns months.

TeraFab consolidates the entire silicon lifecycle… lithography mask fabrication, logic chip production, memory chip production, advanced packaging, and testing… inside a single building. Design a mask. Print a chip. Test it. Redesign the mask. Print again. All under one roof.

The result? An iteration speed an order of magnitude faster than anything else in the global semiconductor industry. That speed advantage is the whole game. It means TeraFab can run what Musk calls "wild and crazy" experiments in new compute physics that no traditional foundry would risk, because the feedback loop is so tight that failures cost days instead of quarters.

No other facility on Earth integrates mask-making, logic, memory, packaging, and testing in a single building with this kind of recursive improvement cycle. It changes the competitive math for the entire semiconductor industry.

Two Chips, Two Missions

TeraFab is designed to produce two fundamentally different classes of silicon.

Edge inference chips are optimized for Tesla's Optimus humanoid robots and vehicle fleet. The production target for Optimus alone is staggering… 1 billion to 10 billion units per year, which is 10 to 100 times global vehicle production of roughly 100 million annually. Every one of those robots needs onboard AI processing. The chip volume required is unlike anything the semiconductor industry has ever contemplated.

Space-optimized high-power chips are engineered for an environment that destroys conventional hardware. High-energy photon bombardment causing bit-flips and structural degradation. Electron buildup with no atmospheric discharge path. Zero convection for cooling. These chips are deliberately designed to run hotter than terrestrial silicon… a counterintuitive choice driven by hard physics. In a vacuum, heat rejection follows the Stefan-Boltzmann Law, scaling with the fourth power of temperature. Hotter chips mean smaller radiators. Smaller radiators mean less mass per kilowatt. Less mass means more compute per Starship launch.

The target metric... 100 kilowatts of compute per ton delivered to orbit.

Musk expects space compute to constitute the vast majority of total output, with terrestrial chips capped at an estimated 100 to 200 gigawatts per year due to ground-based power constraints. The remaining 800+ gigawatts to reach the terawatt target has to be space-native.

The Orbital Economics

The strategic logic behind TeraFab only makes sense when you understand why space-based AI is projected to undercut terrestrial AI costs within 2 to 3 years.

Solar panels in orbit generate at least five times the energy of ground-based equivalents. No atmospheric attenuation. No day/night cycle. No seasonal variation. Arrays stay constantly perpendicular to the sun, maximizing capture every second. No need for heavy glass or steel framing to survive weather. And because it's always sunny… no massive battery storage systems required.

On Earth, every additional gigawatt of power generation gets harder and more expensive. You run out of optimal sites. You hit NIMBY resistance. The marginal cost curve goes up. In space, the opposite happens. Every additional gigawatt gets cheaper and easier. The scaling curves run in opposite directions. Once Starship drives launch costs low enough, the economics flip permanently.

The initial deployment unit is a 100-kilowatt "minissat"… a compact compute satellite with solar panels and radiator, scaled to fit Starship payloads. Future iterations are expected to scale to the megawatt range per satellite.

And for the skeptics debating whether heat rejection in space is even feasible... SpaceX currently operates over 10,000 satellites in orbit. The radiator is small relative to the solar array. The physics works.

The Credibility Stack

Here's why dismissing this as vaporware would be a mistake.

Reusable rockets were called impossible. SpaceX has now landed over 500 times and made reusability economically viable. Electric cars were written off as toys. Tesla now produces 2 million per year. xAI… now integrated as part of SpaceX… built the world's first gigawatt-scale compute cluster so fast that Nvidia's Jensen Huang said he'd never seen anything constructed at that speed in his life.

Starship V3 is designed to deliver 200 tons to orbit, up from the 100-ton baseline. Starship V4 will be significantly larger still. The target throughput... 10 million tons to orbit per year at 100 kilowatts per ton. Musk states explicitly... no new physics or impossible breakthroughs are required. The engineering is hard. The physics is known.

The Bigger Picture

TeraFab is Phase 1. Even a terawatt of compute, enormous by current human standards, is still just an early step on the Kardashev Scale. You're not yet a Type 2 civilization. You don't even register as Type 3.

The full roadmap extends to petawatt-scale compute… a thousand times larger than a terawatt… enabled by electromagnetic mass drivers on the lunar surface. The Moon's lack of atmosphere and one-sixth gravity means payloads can be accelerated to escape velocity without rockets, collapsing the cost of deep-space deployment by orders of magnitude. A combined workforce of Optimus robots and humans would build and operate these systems.

A petawatt of compute would capture roughly one millionth of the Sun's total energy output. For context, that would power an economy a million times larger than Earth's current GDP.

But none of it happens without the chips. SpaceX can build the rockets. Tesla can build the robots. xAI can architect the intelligence. The bottleneck was always silicon.

The Bottom Line

Every semiconductor line on Earth, running flat out, delivers 2% of what the Terra Project requires. TeraFab is the industrial answer to a 98% deficit… a single-building recursive manufacturing loop designed to out-iterate the entire global foundry ecosystem by an order of magnitude, producing chips engineered for environments no existing fab was built to serve.

No new physics. No impossible breakthroughs. Just the biggest bet on semiconductor manufacturing anyone has ever made, backed by the only companies that have already done what people said couldn't be done.

23K

Hamzat ademola @Wartzyy

4 months ago

Who to follow

Madman || || 4:20 || Outsider

Wartzyy retweeted

Jaynit

@jaynitx

6 months ago

Elon Musk on why the smartest people drop out of college: "You don't need college to learn. Learn stuff. Everything is available basically for free. You can learn anything you want for free. It is not a question of learning." Musk explains what college actually provides: "There is a value that colleges have, which is seeing whether somebody can work hard at something, including a bunch of annoying homework assignments, and still do their homework, and kind of soldier through and get it done. That's the main value of college. And also, you probably want to hang around with a bunch of people your own age for a while instead of going right into the workforce. So I think colleges are basically for fun and to prove you can do your chores. But they're not for learning." On hiring at his companies: "There is a requirement of evidence of exceptional ability. I don't consider going to college evidence of exceptional ability. In fact, ideally you dropped out and did something. Obviously, Gates is a pretty smart guy, he dropped out. Jobs was pretty smart, he dropped out. Larry Ellison, smart guy, he dropped out. Obviously not needed." Musk shares how education should work: "Generally, you want education to be as close to a video game as possible. Like a good video game. You do not need to tell your kid to play video games; they will play video games on autopilot all day. If you can make it interactive and engaging, you can make education far more compelling and far easier to do." He challenges the current system: "You really want to disconnect the whole 'grade level' thing from the subjects. Allow people to progress at the fastest pace that they can, or are interested in, in each subject. It seems like a really obvious thing." Musk criticizes traditional teaching: "Most teaching today is a lot like vaudeville. Somebody's standing up there lecturing to you. They've done the same lecture several years in a row. They're not necessarily all that engaged. That lack of enthusiasm is conveyed to the students; they're not very excited about it. They don't know why they're there. 'Why are we learning this stuff?' We don't even know why. A lot of things people learn, probably there's no point in learning them, because they never use them in the future." On whether university is necessary: "A university education is often unnecessary. That's not to say it's unnecessary for all people. But I think you learn about as much, the vast majority of what you're going to learn there, in the first two years. And most of it is from your classmates. If the goal is to start a company, I would say no point in finishing college." Musk started his own school for his kids: "I created a little school. It's small, only 14 kids now, and it'll have 20 in September. It's called Ad Astra, which means 'to the stars.'" He explains what makes it different: "There aren't any grades. There's no grade one, grade two, grade three. Not making all the children go in the same grade at the same time, like an assembly line. People are not objects on an assembly line. That's a ridiculous notion. Some people love English or languages. Some people love math. Some people love music. Different abilities at different times. It makes more sense to cater the education to match their aptitudes and abilities." Musk shares a key principle: "It's important to teach problem-solving, or teach to the problem, not to the tools. Let's say you're trying to teach people about how engines work. A more traditional approach would be: 'We're going to teach you all about screwdrivers and wrenches. You're going to have a course on screwdrivers, a course on wrenches.' This is a very difficult way to do it." He offers a better approach: "A much better way would be: 'Here's the engine. Now let's take it apart. How are we going to take it apart? Oh, you need a screwdriver, that's what the screwdriver is for. You need a wrench, that's what the wrench is for.' And then a very important thing happens: the relevance of the tools becomes clear." The result: "It seems to be going pretty well. The kids really love going to school. I think that's a good sign. I hated going to school when I was a kid; it was torture. The fact that they actually think vacations are too long, they want to go back to school. Weird, I know." Musk reframes what education really is: "If you think about it, what is education? You're basically downloading data and algorithms into your brain. And it's actually amazingly bad in conventional education. It shouldn't be this huge chore. The more you can gamify the process of learning, the better."