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Austin Lyons
@austinsemis
semis analyst. asking questions + explaining. read by chipmakers, funds, model labs. @chipstrat · @semidoped · @creativestrat
1.8K Following    7K Followers
Great look into Arm’s bring up lab in Austin TX
I joined David Goldman on @CelestaCapital's TechSurge podcast to talk about the race to build the next trillion-dollar AI chip company. The main idea we dig into is that no one has yet brought a chip to market designed specifically for LLMs. Blackwell is a GPU that morphed toward the workload. Nobody has yet stood up a gigawatt of clean-sheet LLM silicon, and that gap is where the next trillion-dollar chip company comes from. We cover: • Why AI infrastructure now sells as full systems, and how Nvidia got to rack scale first • Prefill vs. decode, and why the SRAM bets Groq and Cerebras made years ago suddenly paid off • How neoclouds built $125B+ of public-market value while most investors missed them • Circular financing, and why I land on the demand being real • My four conditions for the next trillion-dollar chip company • Clean-sheet architectures: @OpenAI's Jalapeno, @TensordyneInc's log math, @Etched's low-voltage inference • Why enterprise and on-prem inference could end up bigger than the cloud Full episode:
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NOT IN MY BACKYARD! that's the real AI pacing
Had convo with a CEO working in silicon photonics and lasers yesterday and he referred to Vik’s recent series several times! Give them a read. (Then I was like “crap I haven’t finished those articles yet” 😅)
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Sumitomo has some really interesting high power lasers, but none have made it into ELSFPs as far as I know. Instead of a single cavity approach like Lumentum, they use a lower-power DFB laser and then an optical amplifier. The trade-offs they have to make are, well, interesting. The latest report talks all about it.
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server CPU demand 📈 Between this and grokbot Runs on a cloud VM Need as many cloud cores as possible This trend will continue
Muse is built from the ground up for privacy and security. Your data and credentials live on the Muse Secure VM -- an isolated linux computer with a browser, CPU, memory, and storage.
Log math is an old trick: turn expensive multiplies into cheap adds. So why isn't every AI chip logarithmic? Because once you're in the log domain.... you still have to get back to linear, without losing the gains. Tensordyne claims they've figured that out.
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The oligopoly equilibrium. In markets where the cost of competing is enormous and rises with each generation, fixed costs squeeze the player count down to two or three. We see it everywhere in semis. Also frontier labs.
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Why do most semiconductor markets have ~3 main companies?
Interesting choice to partner on interconnects
AI accelerator startups need to ship a full system, not just a chip. Tensordyne's strategy: partner with HPE Juniper for the networking stack. This gets them to market faster with telco-grade 'five nines' reliability (<5.3 min/year downtime) from day one.
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Introducing Arm Total Design for Physical AI — bringing an inital 80+ companies together around a shared goal to accelerate physical AI from development to deployment. One of the first initiatives is a Robotics Capability Framework, creating a common language for defining increasingly intelligent and capable robotic systems. The next frontier for AI is the physical world. We’re helping the ecosystem get there faster.
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Just in: TSMC has finally chosen to adopt High-NA EUV. And to develop larger photomasks to go with it. This is HUGE news for @ASMLcompany
Eldest son and I got Omarchy installed today, now vibe coding video games 🎮
Kids left strawberries on the ledge. Squirrel ate them. All. Then just laid like this for a while.
Trainium has by far the best profiler of any accelerator. As you can see we have nanosecond-accurate traces of our programs, allowing you to write a program that generates images reliably in the profiler.
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AI inference is the fastest-growing market in the history of capitalism. It’s bottlenecked on nearly every physical input involved. As the diversity of both AI applications and hardware grows, matching workloads to the right architectures becomes essential. We believe Gimlet’s multi-silicon inference cloud is the solution to heterogeneous compute work at scale, and we are thrilled to lead this investment. Congratulations to the Gimlet team, we are very excited to partner! @zainasgar @oazizi @nserrino @gimletlabs
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@austinsemis So many good nuggets in that interview. I've watched it 3 times with some time in between each watch. I learn new things each time.
My interview with Gimlet back in May:
Gimlet Labs, an AI startup that helps companies divide AI tasks between multiple kinds of chips, is now valued at $3B after a $300 million round led by @a16z with $ from ARM and Microsoft’s M12
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Memory companies are investing in the US. Syracuse (Micron) and Purdue (SK Hynix) are two universities that will benefit.
“Might write up open-weight AI tomorrow as this is equally essential to America.” Would love to see it
Regret the tone of my post on data centers yesterday. What I should have said: There were reasonable concerns about data centers 18ish months ago: water, taxes, jobs, electricity prices, the environment and what they would do to small towns. Well-structured data center projects have largely addressed these concerns today and we should be celebrating this. On balance, data centers are awesome for America in every way. On water: U.S. data centers use a fraction of what golf courses use. A lot of the numbers from 18 months ago were off by over 1000x. Newer data centers use closed-loop systems or recycled water. Should be required by every town approving a data center project. On taxes: looking only at sales-tax exemptions, as Ronan Farrow did, is the wrong way to evaluate this. Data centers pay significant property taxes. Loudoun County, which is the wealthiest county in America, now collects on the order of $1 billion a year from data centers. In Quincy, WA, data centers are more than half the property-tax roll. Over time, property taxes can go to zero while government spending increases in these towns. On jobs: this has been unambiguously awesome for blue collar Americans. Demand for electricians, plumbers, welders, HVAC techs, and contractors has gone vertical, and it is not a one-time construction job. These buildings get upgraded and expanded over time. That is why the building trades are fighting for them, and why some unions are now treating opposition to data centers as a reason not to endorse politicians. On power: the original fear was that households would pay for the incremental electricity demand in the form of higher prices. That is why the ratepayer-protection deals and the new large-load tariffs exist. The right structure is: the data center brings or pays for new generation and signs a contract long enough that existing customers are protected. Where that is happening, utilities are cutting or freezing residential rates and saying so on the record. Where it is not, people are right to object. Electricity prices are going down *today* in a number of large states because of data centers. 
On the environment: data centers overwhelming use natural gas today, which is the cleanest power source outside of nuclear, solar and wind. And the companies that are building the data centers are committed to carbon neutrality such that an equivalent amount of solar will likely be built. Maybe more importantly, the data centers need batteries to function effectively and these batteries can also sell energy back into the grid (which recently prevented blackouts in Texas). Over time, data centers will run on solar plus batteries. On the towns: Poverty in Quincy, WA fell from 29% to 6%. Data center taxes paid for a new high school, a hospital, a library, police and fire stations. This is happening in many left for dead former mill and farm towns that had no other bidder for the land. Data centers are actually reindustrializing parts of America and creating the kind of working-class jobs both parties have spent decades claiming to support. That should not be a partisan issue. Data centers can and should be awesome for America and they increasingly, overwhelmingly are. Supporting the outsourcing of data centers to China will likely age just as well as support for the outsourcing of high quality, blue collar manufacturing jobs to China has aged. When the facts change, I change my mind. I hope that reasonable people who had good faith reasons to oppose data centers at least consider updating their beliefs given the change in the facts over the last 18 months. This really matters for America. I will say I also think the idea of making data centers beautiful is a good one that has yet to be implemented. Data centers should be just as beautiful as Grand Central Station. We can learn a lot from the railroad buildout. Neoclassical revival ftw. Might write up open-weight AI tomorrow as this is equally essential to America.
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Semis startups right now are so fun. You’ve got both industry vets like Al at PicoJool and young founders like the guys at Etched.
A few years ago Patrick Collison remarked there are fewer younger founders today. Ben Horowitz and Martin Casado agree that's what the hardware era looks like, for now: "If you look at Elon or Travis Kalanick, their companies when they were young were software companies. Even those guys, the best guys, needed some experience to graduate to the more elaborate domains." "When you're learning how to build a company, it's hard enough if you completely understand the product. If you don't completely understand the product and have to learn it while you build the company, that's just such a steep learning curve for a brand new entrepreneur." "[Hardware] has been defocused by the entire industry and academia for the last 20 years... The growth areas have been software, networking, things like that." "You don't go intern and build a chip. But a lot of that's changing now. We're gonna create a whole generation of founders that come from these new companies." "One of the greatest legacies of Elon is of course he's created these great companies, but the amount of entrepreneurs that have come out of SpaceX that are changing the entire industrial complex may be an even greater legacy than the companies themselves." "I think we're gonna see the same thing for computer science and hardware." @bhorowitz @martin_casado @eriktorenberg
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