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Does anyone realize that if SpaceX pulls this off, Terafab would become the largest building ever constructed by floor area? More than 100 million square feet of manufacturing space, over 5x the floor area of the current largest building on Earth. I wanted to wait before reporting because news...

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Chris

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65,896 просмотров • 1 день назад •via X (Twitter)

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tesla is merging with spaceX. this announcement did all but confirm it. a multi-trillion dollar space/ai/robotics GIANT, a moon settlement and at the heart of it - the Terafab - here's why this is nuts: - tesla plans to ship 1-10 BILLION robots PER year. problem: global chip capacity is shit, doesn't scale. - Tesla's 'Terafab' will produce 1 TERAwatt of compute. 80% of that will go to outer-space to train AI (grok) via spaceX - terafab will make 2 AI chips: 1 for humanoid robots/cars and 1 for AI datacenters in space. - by housing everything under 1 roof - chip production speeds up by an order of magnitude. unbeatable. - moon settlement: the sun doesn't set in space. solar power is 5X larger in low-orbit space. much more on the moon (24/7 too!) - so elon will build a moon settlement! there is ZERO chance tesla survives without spaceX transporting these ai chips. elon estimates training AI in space will be CHEAPER THAN ON EARTH in 2-3 years. insane. (heres the full announcement if you wanna watch)
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tesla is merging with spaceX. this announcement did all but confirm it. a multi-trillion dollar space/ai/robotics GIANT, a moon settlement and at the heart of it - the Terafab - here's why this is nuts: - tesla plans to ship 1-10 BILLION robots PER year. problem: global chip capacity is shit, doesn't scale. - Tesla's 'Terafab' will produce 1 TERAwatt of compute. 80% of that will go to outer-space to train AI (grok) via spaceX - terafab will make 2 AI chips: 1 for humanoid robots/cars and 1 for AI datacenters in space. - by housing everything under 1 roof - chip production speeds up by an order of magnitude. unbeatable. - moon settlement: the sun doesn't set in space. solar power is 5X larger in low-orbit space. much more on the moon (24/7 too!) - so elon will build a moon settlement! there is ZERO chance tesla survives without spaceX transporting these ai chips. elon estimates training AI in space will be CHEAPER THAN ON EARTH in 2-3 years. insane. (heres the full announcement if you wanna watch)

Ejaaz

163,328 просмотров • 4 месяцев назад

🚨 Elon Musk's reported Terafab project could be bigger than most people realize. 👀 Jo Bhakdi says the planned Tesla-SpaceX facility could reach 100 million square feet, about 10 times larger than Giga Texas, with a goal of producing around 1 terawatt of AI chips per year. He also highlighted Elon’s vision for AI in space, with plans to rapidly increase compute power in orbit over the next few years. If these plans become reality, SpaceX and Tesla may not just be building products. They could be building the infrastructure that powers the future of AI. $TSLA $SPCX
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🚨 Elon Musk's reported Terafab project could be bigger than most people realize. 👀 Jo Bhakdi says the planned Tesla-SpaceX facility could reach 100 million square feet, about 10 times larger than Giga Texas, with a goal of producing around 1 terawatt of AI chips per year. He also highlighted Elon’s vision for AI in space, with plans to rapidly increase compute power in orbit over the next few years. If these plans become reality, SpaceX and Tesla may not just be building products. They could be building the infrastructure that powers the future of AI. $TSLA $SPCX

Herbert Ong

23,227 просмотров • 1 месяц назад

today, intel announced that it will join terafab. terafab started in march as a chip project in austin backed by tesla, spacex, and xai, with the goal of combining logic, memory, and advanced packaging to reach 1 terawatt of compute each year. that gives terafab deeper semiconductor capability as it pushes toward future ai, robotics, and space infrastructure.
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today, intel announced that it will join terafab. terafab started in march as a chip project in austin backed by tesla, spacex, and xai, with the goal of combining logic, memory, and advanced packaging to reach 1 terawatt of compute each year. that gives terafab deeper semiconductor capability as it pushes toward future ai, robotics, and space infrastructure.

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14,987 просмотров • 4 месяцев назад

$ASML has become one of the clearest ways to invest in the global AI chip buildout because it controls one of the most important bottlenecks in semiconductor manufacturing. Its lithography systems act like ultra-precise printers that create the tiny circuit patterns used in advanced chips and ASML remains the only company producing EUV machines at scale. $TSM cannot manufacture $NVDA Blackwell or Rubin GPUs without those systems which means nearly every dollar flowing into advanced AI compute ultimately passes through ASML’s equipment.
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$ASML has become one of the clearest ways to invest in the global AI chip buildout because it controls one of the most important bottlenecks in semiconductor manufacturing. Its lithography systems act like ultra-precise printers that create the tiny circuit patterns used in advanced chips and ASML remains the only company producing EUV machines at scale. $TSM cannot manufacture $NVDA Blackwell or Rubin GPUs without those systems which means nearly every dollar flowing into advanced AI compute ultimately passes through ASML’s equipment.

Shay Boloor

62,457 просмотров • 22 дней назад

Many still don’t understand why Elon is building Terafab Terafab is an extension to all the chip makers in the world It’s not about replacement, not a rivalry and absolutely not competing It’s being built to fulfill the massive chip orders that Tesla, SpaceX and xAI actually need TSMC’s most advanced 2nm capacity is totally booked through 2028 Tesla signed a massive $16.5 billion deal with Samsung back in July 2025 to produce AI6 chips at their Taylor, Texas factory and Samsung is building a Tesla Exclusive chip manufacturing plant to full fill this orders When Elon announced Terafab on March 21, 2026...he made it clear: “That rate is much less than we’d like. We either build the Terafab or we don’t have the chips, and we need the chips, so we build the Terafab” He basically told the chip makers: “Produce as much as you comfortably can. We will take them all. Actually we want even more” Even today Elon said: "SpaceX/Tesla will be always be major customers of TSMC and not competitors in the normal sense of the word" Current production rates are much less than they need....That’s why Terafab exists Terafab is an extension to every chip maker… not competition, not rivalry, absolutely not Even Intel has joined as a partner Even if chip supply improves, massive bottlenecks still exist with memory and advanced packaging You simply can't risk those supply chain breaks at this scale That’s why Terafab is being built to vertically integrate everything - chips, memory, advanced packaging all under one roof, targeting 1 terawatt of AI compute capacity per year This is a ludicrous amount of chips that no chipmaker currently produces at this scale. I don't think even TSMC and Samsung truly understand these numbers yet It’s about building the capacity the future actually demands
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Many still don’t understand why Elon is building Terafab Terafab is an extension to all the chip makers in the world It’s not about replacement, not a rivalry and absolutely not competing It’s being built to fulfill the massive chip orders that Tesla, SpaceX and xAI actually need TSMC’s most advanced 2nm capacity is totally booked through 2028 Tesla signed a massive $16.5 billion deal with Samsung back in July 2025 to produce AI6 chips at their Taylor, Texas factory and Samsung is building a Tesla Exclusive chip manufacturing plant to full fill this orders When Elon announced Terafab on March 21, 2026...he made it clear: “That rate is much less than we’d like. We either build the Terafab or we don’t have the chips, and we need the chips, so we build the Terafab” He basically told the chip makers: “Produce as much as you comfortably can. We will take them all. Actually we want even more” Even today Elon said: "SpaceX/Tesla will be always be major customers of TSMC and not competitors in the normal sense of the word" Current production rates are much less than they need....That’s why Terafab exists Terafab is an extension to every chip maker… not competition, not rivalry, absolutely not Even Intel has joined as a partner Even if chip supply improves, massive bottlenecks still exist with memory and advanced packaging You simply can't risk those supply chain breaks at this scale That’s why Terafab is being built to vertically integrate everything - chips, memory, advanced packaging all under one roof, targeting 1 terawatt of AI compute capacity per year This is a ludicrous amount of chips that no chipmaker currently produces at this scale. I don't think even TSMC and Samsung truly understand these numbers yet It’s about building the capacity the future actually demands

X Freeze

53,291 просмотров • 3 месяцев назад

Elon Musk said Tesla will soon reveal the location and full plans for Terafab and the announcement will get its own dedicated spotlight: “Terafab is going to be an amazing initiative and a necessary one Without it, we will be constrained in our ability to scale Optimus production because we simply will not have enough AI chips We have to solve memory, logic and packaging in order to scale Optimus” Tesla has already placed equipment orders for a development fab in Austin that will bring: • Lithography mask production • Logic chips • Memory • Advanced packaging • Chip testing All under one roof This would allow Tesla to design a new AI chip, manufacture it, package it, test it and quickly iterate on the next version from the same facility A building like this does not exist anywhere else on Earth Terafab is not just another factory It is going to become the chip-development engine Tesla needs to scale Optimus and pursue high-risk, high-reward AI hardware breakthroughs at unprecedented speed
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Elon Musk said Tesla will soon reveal the location and full plans for Terafab and the announcement will get its own dedicated spotlight: “Terafab is going to be an amazing initiative and a necessary one Without it, we will be constrained in our ability to scale Optimus production because we simply will not have enough AI chips We have to solve memory, logic and packaging in order to scale Optimus” Tesla has already placed equipment orders for a development fab in Austin that will bring: • Lithography mask production • Logic chips • Memory • Advanced packaging • Chip testing All under one roof This would allow Tesla to design a new AI chip, manufacture it, package it, test it and quickly iterate on the next version from the same facility A building like this does not exist anywhere else on Earth Terafab is not just another factory It is going to become the chip-development engine Tesla needs to scale Optimus and pursue high-risk, high-reward AI hardware breakthroughs at unprecedented speed

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Important numbers from Terafab announcement: More than $16.8 billion — first-phase investment from SpaceX and Tesla. 3,000+ new jobs — expected to be created. $30 million — Texas Enterprise Fund grant. 100 million square feet — planned Terafab size, around 9.3 million square meters. 10 million square feet — size listed for Tesla’s Giga Texas factory. 10× larger — Terafab compared with Giga Texas by the website’s stated floor areas. More than 1 TW per year — targeted Terafab compute output. 1,000 GW / 1 trillion watts — equivalent to 1 TW. 0.5 TW — current annual U.S. consumption shown for comparison. 2× current U.S. consumption — Terafab’s targeted annual output. More than 1 TW — projected combined chip demand from SpaceX and Tesla. 1 billion Optimus robots — long-term scale envisioned for robots doing the work. 10 million tons per year — targeted mass launched into orbit. More than 1 TW of solar power — required for the orbital-compute vision.
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Important numbers from Terafab announcement: More than $16.8 billion — first-phase investment from SpaceX and Tesla. 3,000+ new jobs — expected to be created. $30 million — Texas Enterprise Fund grant. 100 million square feet — planned Terafab size, around 9.3 million square meters. 10 million square feet — size listed for Tesla’s Giga Texas factory. 10× larger — Terafab compared with Giga Texas by the website’s stated floor areas. More than 1 TW per year — targeted Terafab compute output. 1,000 GW / 1 trillion watts — equivalent to 1 TW. 0.5 TW — current annual U.S. consumption shown for comparison. 2× current U.S. consumption — Terafab’s targeted annual output. More than 1 TW — projected combined chip demand from SpaceX and Tesla. 1 billion Optimus robots — long-term scale envisioned for robots doing the work. 10 million tons per year — targeted mass launched into orbit. More than 1 TW of solar power — required for the orbital-compute vision.

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If $MU confirms tomorrow that DRAM, NAND and HBM tightness can last into 2027 or 2028 then memory companies have more reason to keep spending on capacity and advanced manufacturing tools. That matters for $ASML because it sits at the most important equipment layer of the semiconductor supply chain where more advanced memory capacity means more demand for lithography systems.
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If $MU confirms tomorrow that DRAM, NAND and HBM tightness can last into 2027 or 2028 then memory companies have more reason to keep spending on capacity and advanced manufacturing tools. That matters for $ASML because it sits at the most important equipment layer of the semiconductor supply chain where more advanced memory capacity means more demand for lithography systems.

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Here are 20 companies that will dominate the AI age: 1/ ASML $ASML is revolutionizing the semiconductor industry by enabling chipmakers to produce the world’s most advanced processors with atomic-scale precision. Shrinking transistors to fit more power into smaller chips faces fundamental physical limits. The industry struggled with escalating costs, slower innovation cycles, and diminishing returns from older lithography methods. With $ASML, the process is radically different, its extreme ultraviolet (EUV) lithography machines use cutting-edge optics and physics to etch circuitry at the nanometer scale, enabling faster, more energy-efficient, and more powerful chips. This breakthrough is the backbone of progress in AI, cloud computing, smartphones, and virtually every advanced technology. As AI spreads to all aspects of our economies, an ever-growing number of chips is needed, driving demand for ASML machines and maintenance services.
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Here are 20 companies that will dominate the AI age: 1/ ASML $ASML is revolutionizing the semiconductor industry by enabling chipmakers to produce the world’s most advanced processors with atomic-scale precision. Shrinking transistors to fit more power into smaller chips faces fundamental physical limits. The industry struggled with escalating costs, slower innovation cycles, and diminishing returns from older lithography methods. With $ASML, the process is radically different, its extreme ultraviolet (EUV) lithography machines use cutting-edge optics and physics to etch circuitry at the nanometer scale, enabling faster, more energy-efficient, and more powerful chips. This breakthrough is the backbone of progress in AI, cloud computing, smartphones, and virtually every advanced technology. As AI spreads to all aspects of our economies, an ever-growing number of chips is needed, driving demand for ASML machines and maintenance services.

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Today is Tesla 2nd Qtr Financial Results day and CAPEX along with cash flow and cash balance might be the story you will hear the most about … and for good reason. The company is building all of the infrastructure needed to be able to offer AI, humanoid robots, advanced AI chips, AI training & compute and much more … most of which everyone will be talking about in 2028 … and you can see all of this happening today. Check out these views current progress with the new Optimus factory on the north end of Giga Texas today!
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Today is Tesla 2nd Qtr Financial Results day and CAPEX along with cash flow and cash balance might be the story you will hear the most about … and for good reason. The company is building all of the infrastructure needed to be able to offer AI, humanoid robots, advanced AI chips, AI training & compute and much more … most of which everyone will be talking about in 2028 … and you can see all of this happening today. Check out these views current progress with the new Optimus factory on the north end of Giga Texas today!

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Elon Musk just explained why the SpaceX IPO is an energy story and the energy constraint is why he believes space becomes the only viable path for AI to scale (Save this). The argument he is making is one of the most important and least understood things happening in technology right now. The United States currently consumes roughly 500 gigawatts of electricity on average. To double that capacity which is what continued AI expansion on the current terrestrial trajectory would eventually require would mean building as many power plants as currently exist in the entire country. He is not arguing that this is technically impossible, just that communities are not willing to accept it, that permitting timelines make it unrealistic, and that the hard ceiling on Earth based power generation means the expansion of AI compute will eventually hit a wall that no amount of capital can overcome on the ground. His observation is that in space, that wall does not exist. A solar panel in orbit produces roughly five times more power than the same panel on Earth, operates in continuous sunlight uninterrupted by weather or nighttime, and benefits from the vacuum of space as a completely passive cooling system meaning the two largest operating costs of any terrestrial data center, energy and cooling, are effectively eliminated. He then said that you could theoretically increase harnessed energy by a factor of one million and still be using less than a millionth of the sun's total energy output. This is the underlying physics of why SpaceX filed with the FCC to launch up to one million solar powered AI satellites, and why they described that constellation in their own filing as a first step toward becoming a Kardashev Type II civilization capable of harnessing the full power of the sun. To understand what makes this credible rather than visionary, you need to understand what SpaceX already controls that no other company on earth possesses. Starship, once operating at full cadence, can deliver 100 to 150 tons of payload to orbit per launch, at a target cost per kilogram that is an order of magnitude lower than any existing vehicle. Musk's stated ambition is to scale Starship to 10,000 to 30,000 launches per year, a frequency that would allow the deployment of orbital compute infrastructure at a pace that is currently unimaginable with any existing rocket. He told xAI staff earlier this year that achieving space-based AI at scale will eventually require manufacturing facilities on the moon, building solar panels and heat dissipation structures from lunar silicon and aluminum, and launching them into orbit from there rather than from Earth's surface because the moon's lower gravity makes the economics of launch dramatically more favorable. SpaceX's S-1 filing explicitly states that its launch capabilities could enable massive AI compute satellite constellations with the potential for millions of satellites for orbital data centers, with the first launch potentially occurring as soon as 2028. Google and Alphabet are already in advanced talks with SpaceX about deploying space-based data centers. Starcloud, a startup running Nvidia H100 GPUs in orbit, has already validated that high-performance AI inference workloads can operate in space, with plans to scale to five gigawatts of orbital compute power by 2035. This is why Musk believes the cost crossover happens in two to three years because SpaceX's launch cost trajectory intersects with the accelerating energy constraint on the ground in a way that makes space genuinely cheaper, faster, and less regulated at exactly the moment AI demand is hitting its hardest physical limits.
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Elon Musk just explained why the SpaceX IPO is an energy story and the energy constraint is why he believes space becomes the only viable path for AI to scale (Save this). The argument he is making is one of the most important and least understood things happening in technology right now. The United States currently consumes roughly 500 gigawatts of electricity on average. To double that capacity which is what continued AI expansion on the current terrestrial trajectory would eventually require would mean building as many power plants as currently exist in the entire country. He is not arguing that this is technically impossible, just that communities are not willing to accept it, that permitting timelines make it unrealistic, and that the hard ceiling on Earth based power generation means the expansion of AI compute will eventually hit a wall that no amount of capital can overcome on the ground. His observation is that in space, that wall does not exist. A solar panel in orbit produces roughly five times more power than the same panel on Earth, operates in continuous sunlight uninterrupted by weather or nighttime, and benefits from the vacuum of space as a completely passive cooling system meaning the two largest operating costs of any terrestrial data center, energy and cooling, are effectively eliminated. He then said that you could theoretically increase harnessed energy by a factor of one million and still be using less than a millionth of the sun's total energy output. This is the underlying physics of why SpaceX filed with the FCC to launch up to one million solar powered AI satellites, and why they described that constellation in their own filing as a first step toward becoming a Kardashev Type II civilization capable of harnessing the full power of the sun. To understand what makes this credible rather than visionary, you need to understand what SpaceX already controls that no other company on earth possesses. Starship, once operating at full cadence, can deliver 100 to 150 tons of payload to orbit per launch, at a target cost per kilogram that is an order of magnitude lower than any existing vehicle. Musk's stated ambition is to scale Starship to 10,000 to 30,000 launches per year, a frequency that would allow the deployment of orbital compute infrastructure at a pace that is currently unimaginable with any existing rocket. He told xAI staff earlier this year that achieving space-based AI at scale will eventually require manufacturing facilities on the moon, building solar panels and heat dissipation structures from lunar silicon and aluminum, and launching them into orbit from there rather than from Earth's surface because the moon's lower gravity makes the economics of launch dramatically more favorable. SpaceX's S-1 filing explicitly states that its launch capabilities could enable massive AI compute satellite constellations with the potential for millions of satellites for orbital data centers, with the first launch potentially occurring as soon as 2028. Google and Alphabet are already in advanced talks with SpaceX about deploying space-based data centers. Starcloud, a startup running Nvidia H100 GPUs in orbit, has already validated that high-performance AI inference workloads can operate in space, with plans to scale to five gigawatts of orbital compute power by 2035. This is why Musk believes the cost crossover happens in two to three years because SpaceX's launch cost trajectory intersects with the accelerating energy constraint on the ground in a way that makes space genuinely cheaper, faster, and less regulated at exactly the moment AI demand is hitting its hardest physical limits.

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$IBM is having its worst day in nearly six decades after its CEO said customers redirected quarterly spending toward servers, storage and memory to secure supply-constrained infrastructure ahead of expected price increases. That comment is huge because it provides one of the clearest real-world examples yet of the AI infrastructure buildout reshaping enterprise technology budgets. Demand for compute, memory, networking, power, cooling and skilled labor is becoming so large that companies are being forced to reallocate capital across the rest of their businesses.
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$IBM is having its worst day in nearly six decades after its CEO said customers redirected quarterly spending toward servers, storage and memory to secure supply-constrained infrastructure ahead of expected price increases. That comment is huge because it provides one of the clearest real-world examples yet of the AI infrastructure buildout reshaping enterprise technology budgets. Demand for compute, memory, networking, power, cooling and skilled labor is becoming so large that companies are being forced to reallocate capital across the rest of their businesses.

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🇺🇸 SpaceX is making a massive AI bet Elon says SpaceX is scaling AI compute at a pace he believes no one else can match, with more than 2 GW expected online by the end of this year. The company could push its cumulative AI compute capacity to nearly 10 GW by the end of next year and has decided to build exclusively on NVIDIA, calling its Vera Rubin platform the best available. If SpaceX delivers, it could become one of the world's AI superpowers. Writer: Val

Mario Nawfal

43,073 просмотров • 2 дней назад

SpaceX has officially acquired xAI and this is a HUGE deal, probably bigger than most people realize. SpaceX + xAI together are about to build a single, vertically integrated engine that connects AI, rockets, space based internet, and real time information all into one unified system. At the core of this announcement is the fact that AI can’t scale forever on Earth. Think about it. Data centers are already running into hard limits with power, cooling, land, and environmental cost. On top of this, global AI electricity demand is exploding, and doing all of this on the ground just doesn’t scale long term. Therefore Space changes this. In orbit, you can get things like near-constant solar power, you don’t have cooling problems, there’s minimal land/environmental impact, and you can build systems that can run continuously with minimal maintenance. This is why space-based AI is actually very practical and there’s only one company that can do it, which is SpaceX! The scale that SpaceX is aiming for is pretty wild. Elon is talking about 1/ 1 million satellites acting as orbital data centers, and 2/ Launching ~1 million tons of satellites per year Which means 3/ At 100 kW per ton, that’s 100 gigawatts of AI compute every year 4/ And that can scale to 1 terawatt per year. FYI, adding 100 GW of new compute capacity annually in space would be like building out roughly 20-25% of the USA’s total average electricity demand every single year. And scaling to 1 TW/year would exceed the nation’s entire power usage, ALL without burdening Earth’s grids! Bro… this is next level… I repeat, as of today, SpaceX is the ONLY company positioned to do this, especially with Starship - the largest flying vehicle ever. In the future, Elon’s saying the team is going to have Starship launch 200 tons at a time, on an HOURLY basis… WTF?! That’s is absolutely mind boggling. In my opinion, whichever company builds the lowest cost AI compute is going to be the first company that defines the next era of AI, which will all be in space… and my $ is that SpaceX is going to be the first one to do it. Then, when you zoom out even further, this will unlock things most people aren’t even thinking about yet today bc it’s too sci-fi. Like, • Powering lunar bases • In-space propellant transfer • Manufacturing in orbit and on the Moon • Deep-space AI infrastructure using massive solar collectors • Self-growing civilizations on the Moon, Mars, and beyond By tapping into space’s unlimited solar energy, this is how we get to a Kardashev-level civilization! So for SpaceX, the faster Starship progresses, there will be massive new revenue streams and will lead in building out space-based AI infrastructures. For xAI, AI scales without ruining Earth, deeply integrated with everything SpaceX is building, further understanding the universe. For us humans, AI will grow without destroying the planet, and there’s a real path to becoming multi-planetary. I believe SpaceX acquiring xAI is officially the blueprint for where AI, energy, and humanity are headed. Congratulations to everyone, this is such an exciting time to be alive!
1:14

SpaceX has officially acquired xAI and this is a HUGE deal, probably bigger than most people realize. SpaceX + xAI together are about to build a single, vertically integrated engine that connects AI, rockets, space based internet, and real time information all into one unified system. At the core of this announcement is the fact that AI can’t scale forever on Earth. Think about it. Data centers are already running into hard limits with power, cooling, land, and environmental cost. On top of this, global AI electricity demand is exploding, and doing all of this on the ground just doesn’t scale long term. Therefore Space changes this. In orbit, you can get things like near-constant solar power, you don’t have cooling problems, there’s minimal land/environmental impact, and you can build systems that can run continuously with minimal maintenance. This is why space-based AI is actually very practical and there’s only one company that can do it, which is SpaceX! The scale that SpaceX is aiming for is pretty wild. Elon is talking about 1/ 1 million satellites acting as orbital data centers, and 2/ Launching ~1 million tons of satellites per year Which means 3/ At 100 kW per ton, that’s 100 gigawatts of AI compute every year 4/ And that can scale to 1 terawatt per year. FYI, adding 100 GW of new compute capacity annually in space would be like building out roughly 20-25% of the USA’s total average electricity demand every single year. And scaling to 1 TW/year would exceed the nation’s entire power usage, ALL without burdening Earth’s grids! Bro… this is next level… I repeat, as of today, SpaceX is the ONLY company positioned to do this, especially with Starship - the largest flying vehicle ever. In the future, Elon’s saying the team is going to have Starship launch 200 tons at a time, on an HOURLY basis… WTF?! That’s is absolutely mind boggling. In my opinion, whichever company builds the lowest cost AI compute is going to be the first company that defines the next era of AI, which will all be in space… and my $ is that SpaceX is going to be the first one to do it. Then, when you zoom out even further, this will unlock things most people aren’t even thinking about yet today bc it’s too sci-fi. Like, • Powering lunar bases • In-space propellant transfer • Manufacturing in orbit and on the Moon • Deep-space AI infrastructure using massive solar collectors • Self-growing civilizations on the Moon, Mars, and beyond By tapping into space’s unlimited solar energy, this is how we get to a Kardashev-level civilization! So for SpaceX, the faster Starship progresses, there will be massive new revenue streams and will lead in building out space-based AI infrastructures. For xAI, AI scales without ruining Earth, deeply integrated with everything SpaceX is building, further understanding the universe. For us humans, AI will grow without destroying the planet, and there’s a real path to becoming multi-planetary. I believe SpaceX acquiring xAI is officially the blueprint for where AI, energy, and humanity are headed. Congratulations to everyone, this is such an exciting time to be alive!

Teslaconomics

148,575 просмотров • 6 месяцев назад

Elon Musk just described a project so large that most people will assume he is exaggerating (Save this). He is not. In the video, Musk lays out the central problem facing every AI company on earth, the entire global chip industry is on a path to produce roughly 100 gigawatts of AI compute per year. That sounds like a lot until you understand that his companies alone Tesla, SpaceX, and xAI will need orders of magnitude more than that. His answer is the TerraFab. It is a joint chip factory spanning 100 million square feet, ten times the size of Tesla's Gigafactory Texas announced in March 2026, with Grimes County, Texas commissioners approving the full scale facility site just last week. The goal is one full terawatt of AI compute output per year. For context, 1 terawatt is 1,000 gigawatts twice the current total electricity consumption of the United States. SpaceX has already committed an initial $55 billion to the prototype phase, with total investment estimates ranging into the trillions. Here is why this matters for Micron specifically. In the video, Musk named Nvidia's Rubin chips as the reference design for TerraFab's first orbital deployments, and said "You're going to need a lot of memory to go with that." A billion full radical equivalent chips per year, each requiring stacks of high bandwidth memory, that is the demand signal Micron just received from one of the most capital-intensive projects in human history. And Micron already cannot keep up with what exists today. Micron's entire 2026 HBM output is fully sold out contracted before the year began. HBM4 entered volume production ahead of schedule and sold out immediately. The structural reason Micron wins here is simple. Every AI chip ever built Nvidia H100s, Rubin chips, custom ASICs, TPUs is useless without high-bandwidth memory stacked directly on top of it. There are only three companies in the world that supply HBM at scale, Samsung, SK Hynix, and Micron. Samsung has had quality issues, SK Hynix is supply constrained. Micron is the only US headquartered HBM manufacturer which matters enormously given CHIPS Act subsidies, domestic procurement requirements, and the political push to keep critical AI memory production on American soil. TerraFab just made the memory deficit permanently larger. Come join Milk Road Pro for our full breakdown of Micron and our entire AI thesis just for $1. Link below!
3:30

Elon Musk just described a project so large that most people will assume he is exaggerating (Save this). He is not. In the video, Musk lays out the central problem facing every AI company on earth, the entire global chip industry is on a path to produce roughly 100 gigawatts of AI compute per year. That sounds like a lot until you understand that his companies alone Tesla, SpaceX, and xAI will need orders of magnitude more than that. His answer is the TerraFab. It is a joint chip factory spanning 100 million square feet, ten times the size of Tesla's Gigafactory Texas announced in March 2026, with Grimes County, Texas commissioners approving the full scale facility site just last week. The goal is one full terawatt of AI compute output per year. For context, 1 terawatt is 1,000 gigawatts twice the current total electricity consumption of the United States. SpaceX has already committed an initial $55 billion to the prototype phase, with total investment estimates ranging into the trillions. Here is why this matters for Micron specifically. In the video, Musk named Nvidia's Rubin chips as the reference design for TerraFab's first orbital deployments, and said "You're going to need a lot of memory to go with that." A billion full radical equivalent chips per year, each requiring stacks of high bandwidth memory, that is the demand signal Micron just received from one of the most capital-intensive projects in human history. And Micron already cannot keep up with what exists today. Micron's entire 2026 HBM output is fully sold out contracted before the year began. HBM4 entered volume production ahead of schedule and sold out immediately. The structural reason Micron wins here is simple. Every AI chip ever built Nvidia H100s, Rubin chips, custom ASICs, TPUs is useless without high-bandwidth memory stacked directly on top of it. There are only three companies in the world that supply HBM at scale, Samsung, SK Hynix, and Micron. Samsung has had quality issues, SK Hynix is supply constrained. Micron is the only US headquartered HBM manufacturer which matters enormously given CHIPS Act subsidies, domestic procurement requirements, and the political push to keep critical AI memory production on American soil. TerraFab just made the memory deficit permanently larger. Come join Milk Road Pro for our full breakdown of Micron and our entire AI thesis just for $1. Link below!

Milk Road AI

246,975 просмотров • 1 месяц назад

Elon Musk announced a chip factory 10 times the size of Tesla's Gigafactory. The goal is to produce enough AI compute to equal twice the entire electricity consumption of the United States. He called it the Terafab. Here is the number that stopped me cold. The entire global AI chip industry right now is on track to hit around 100 gigawatts per year of compute. Every Nvidia GPU, every Google TPU, every chip from every company on earth combined. 100 gigawatts. Musk wants one factory to produce a terawatt per year. A terawatt is 1,000 gigawatts. Ten times the output of the entire global industry. From a single building. To put the scale in physical terms, the Terafab would need to be around 100 million square feet. You would need Starship point to point transport just to get from one end to the other. But the reason for the scale is not ambition for its own sake. To launch meaningful AI compute into space, you need a billion chips per year running at a kilowatt each. That is not a number the current industry can produce. The Terafab is the only way to get there. The timeline he put out: a gigawatt of space AI compute annualized by end of next year. Then 10x per year from there. 10 gigawatts by year two. 100 gigawatts by year three. A terawatt beyond that. Most people think orbital data centers are a decade away. Musk is building the factory to make them possible by next year.
3:26

Elon Musk announced a chip factory 10 times the size of Tesla's Gigafactory. The goal is to produce enough AI compute to equal twice the entire electricity consumption of the United States. He called it the Terafab. Here is the number that stopped me cold. The entire global AI chip industry right now is on track to hit around 100 gigawatts per year of compute. Every Nvidia GPU, every Google TPU, every chip from every company on earth combined. 100 gigawatts. Musk wants one factory to produce a terawatt per year. A terawatt is 1,000 gigawatts. Ten times the output of the entire global industry. From a single building. To put the scale in physical terms, the Terafab would need to be around 100 million square feet. You would need Starship point to point transport just to get from one end to the other. But the reason for the scale is not ambition for its own sake. To launch meaningful AI compute into space, you need a billion chips per year running at a kilowatt each. That is not a number the current industry can produce. The Terafab is the only way to get there. The timeline he put out: a gigawatt of space AI compute annualized by end of next year. Then 10x per year from there. 10 gigawatts by year two. 100 gigawatts by year three. A terawatt beyond that. Most people think orbital data centers are a decade away. Musk is building the factory to make them possible by next year.

Ihtesham Ali

316,910 просмотров • 1 месяц назад

Every serious analyst has called Elon Musk's Terafab unrealistic. The CEO of the company that supplies the machines to build it just said it is an upside opportunity and compared it to the largest chip buildouts in history. That is not a small statement. ASML makes the lithography machines that every advanced semiconductor fab on earth depends on. You cannot print a chip without them. There is no workaround. There is no alternative supplier. If the Terafab gets built, every single machine inside it comes from one company. The interviewer asked the ASML CEO directly about one terawatt of compute power. He did not laugh. He did not hedge. He compared it to the massive DRAM megaprojects in Korea and said new projects at that scale are exactly the kind of upside ASML is positioned for. His exact words: "New projects are opportunity." Then he said something that most people missed. He said ASML is already watching the Terafab very carefully. Tracking when things will happen. At what speed. That is not how you talk about a fantasy project. The mainstream take on the Terafab is that Musk is dreaming. The CEO of the most critical company in the entire chip supply chain just said he is preparing for it. Those are not the same position. (Watch the full 11 minutes Interview at Bloomberg TV on YouTube)
0:37

Every serious analyst has called Elon Musk's Terafab unrealistic. The CEO of the company that supplies the machines to build it just said it is an upside opportunity and compared it to the largest chip buildouts in history. That is not a small statement. ASML makes the lithography machines that every advanced semiconductor fab on earth depends on. You cannot print a chip without them. There is no workaround. There is no alternative supplier. If the Terafab gets built, every single machine inside it comes from one company. The interviewer asked the ASML CEO directly about one terawatt of compute power. He did not laugh. He did not hedge. He compared it to the massive DRAM megaprojects in Korea and said new projects at that scale are exactly the kind of upside ASML is positioned for. His exact words: "New projects are opportunity." Then he said something that most people missed. He said ASML is already watching the Terafab very carefully. Tracking when things will happen. At what speed. That is not how you talk about a fantasy project. The mainstream take on the Terafab is that Musk is dreaming. The CEO of the most critical company in the entire chip supply chain just said he is preparing for it. Those are not the same position. (Watch the full 11 minutes Interview at Bloomberg TV on YouTube)

Ihtesham Ali

67,363 просмотров • 1 месяц назад

The first question I asked Elon Musk: What’s the point of sending GPUs into space? The whole idea behind orbital data centers is that if the launch costs continue to drop, it will become cheaper to put GPUs in orbit than to build power plants on Earth. The problem with this argument is that energy is only about 15% of a datacenter’s lifetime cost. The chips themselves are around 70%. And you still have to launch those to space! Elon kept returning to one point over and over again: It will simply not be physically possible to scale power production to the scale needed for AI on Earth. He kept pointing out the bottlenecks we’ve already run into on Earth: You can’t plug into the utilities - the interconnect queues are too long. You can’t do behind-the-meter natural gas and generate power yourself - lead times for turbines stretch past 2030. You can’t do solar on Earth, because of permits, and because of the tariffs. For it to make economical sense to shift compute to space, all of the following things would need to be true: - Power generation on Earth hits a ceiling, or AI demand outstrips every terrestrial option (for context, 1 TW of solar power is only 1% of the land area of the US, and AI currently only uses about 20 GW globally). - Chip production scales faster than power generation (because Elon builds TeraFab). It would be surprising if building and placing solar panels turned out to be harder than scaling semiconductor manufacturing. - Starship reaches thousands of launches per year. In that world, Elon wins the AI race outright. SpaceX is the only entity that can launch at that scale. xAI would have unlimited power. Everyone else will be stuck fighting over grid interconnects and turbine orders. And if those 3 conditions aren’t met? Well, on Earth, xAI is just gonna be one of the pack anyways - and there’s no market for the 4th best AI model. Elon’s comparative advantage was never going to be navigating utility interconnect queues or filing permits faster than Google. His advantage is SpaceX. So why not just bet on the world where SpaceX becomes the kingmaker? I asked Elon what that world looks like. 100 GW = 10,000 starship launches, and he wants to do more than that every year by 2030. That’s one starship launch every hour.
5:33

The first question I asked Elon Musk: What’s the point of sending GPUs into space? The whole idea behind orbital data centers is that if the launch costs continue to drop, it will become cheaper to put GPUs in orbit than to build power plants on Earth. The problem with this argument is that energy is only about 15% of a datacenter’s lifetime cost. The chips themselves are around 70%. And you still have to launch those to space! Elon kept returning to one point over and over again: It will simply not be physically possible to scale power production to the scale needed for AI on Earth. He kept pointing out the bottlenecks we’ve already run into on Earth: You can’t plug into the utilities - the interconnect queues are too long. You can’t do behind-the-meter natural gas and generate power yourself - lead times for turbines stretch past 2030. You can’t do solar on Earth, because of permits, and because of the tariffs. For it to make economical sense to shift compute to space, all of the following things would need to be true: - Power generation on Earth hits a ceiling, or AI demand outstrips every terrestrial option (for context, 1 TW of solar power is only 1% of the land area of the US, and AI currently only uses about 20 GW globally). - Chip production scales faster than power generation (because Elon builds TeraFab). It would be surprising if building and placing solar panels turned out to be harder than scaling semiconductor manufacturing. - Starship reaches thousands of launches per year. In that world, Elon wins the AI race outright. SpaceX is the only entity that can launch at that scale. xAI would have unlimited power. Everyone else will be stuck fighting over grid interconnects and turbine orders. And if those 3 conditions aren’t met? Well, on Earth, xAI is just gonna be one of the pack anyways - and there’s no market for the 4th best AI model. Elon’s comparative advantage was never going to be navigating utility interconnect queues or filing permits faster than Google. His advantage is SpaceX. So why not just bet on the world where SpaceX becomes the kingmaker? I asked Elon what that world looks like. 100 GW = 10,000 starship launches, and he wants to do more than that every year by 2030. That’s one starship launch every hour.

Dwarkesh Patel

404,497 просмотров • 6 месяцев назад

Tesla is already using their brand new Cortex supercomputer training cluster in Giga Texas (video of it below). Tesla FSD V13 is the first fully new version of FSD to use Cortex (Tesla says 5x training compute scaling with V13). Tesla increased its AI training compute by 75% in Q3 thanks to 29,000 Nvidia H100 GPUs they installed at Giga Texas last quarter – and expected to have 50,000 H100 capacity by the end of October. That will eventually increase to 100,000 H100 equivalent capacity.
0:20

Tesla is already using their brand new Cortex supercomputer training cluster in Giga Texas (video of it below). Tesla FSD V13 is the first fully new version of FSD to use Cortex (Tesla says 5x training compute scaling with V13). Tesla increased its AI training compute by 75% in Q3 thanks to 29,000 Nvidia H100 GPUs they installed at Giga Texas last quarter – and expected to have 50,000 H100 capacity by the end of October. That will eventually increase to 100,000 H100 equivalent capacity.

Sawyer Merritt

708,274 просмотров • 1 год назад