Eric Ruleman

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Eric Ruleman

Eric Ruleman

@eric_ruleman

ai & acrobatics

Cloud Tham gia Haziran 2016
5.1K Đang theo dõi1.7K Người theo dõi
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Eric Ruleman
Eric Ruleman@eric_ruleman·
we wanted self-driving cars, but instead we got self-driving code
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Ren
Ren@renstocks_·
Clever guy, I if was the head of HR at $NBIS I might give him a raise.
dylan ツ@demian_ai

People keep asking me what the bottleneck is, but I've stopped trying to find the bottleneck in AI. There isn't one: there's a current one, and it moves the second you solve it. - we pushed transistor density about as far as it goes -> the gate moved to how you package the chips together - we started solving package area by moving to big glass panels -> the gate moved to keeping the panel flat and drilling clean holes through the glass - we ran copper interconnects out of headroom -> the gate moved to optical, which moved it to the lasers, which moved it to the substrate under the lasers, which moved it to a licensing office in Beijing. Every single time the industry removes a wall, it does not get open road, it gets a new wall, one floor down, almost always somewhere less glamorous and harder to scale than the thing it just fixed. This is the actual shape of the buildout, and once you see it you read every headline differently. The constraint everyone is talking about is, by definition, the one that's already visible and already being attacked. The money is in the next one, the layer that is about to bind while everyone's still celebrating the last fix. So I don't look for the bottleneck anymore. I look for the handoff, the place the pressure is about to move to, because that's where the supply is thinnest and the pricing power is highest right before the crowd arrives. There is no bottleneck, there's a relay race of them, and the trade is always the next runner. (image credits to @renstocks_ )

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girl
girl@aegeanfiregirl·
When it gets above 80°F I want to take all my clothes off… KISS MY SKIN SUN 🌞
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girl
girl@aegeanfiregirl·
What it called when u feel enlightened from fasting all day but energized by coffees & sunlight? Dis is when I know am superior being 👅 This is when I have my most fascist thoughts
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hansolar
hansolar@hansolar21·
good day for memory
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RJC
RJC@RJCcapital·
i am done shitposting time to lock in so I can finally hit 9 figures by end of the year
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Brooke LeBlanc
Brooke LeBlanc@brookeleblanc·
It is a good hair day, Paul!
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gabriel
gabriel@gabriel1·
i'd pay 90% tax for permanent sun
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techbimbo
techbimbo@jameygannon·
shaken up la colombe latte out of a guinness glass 10/10 full apt reveal coming soon 🙈
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CHLOÉ HAPPE
CHLOÉ HAPPE@bronzeageshawty·
Lifting in the morning, hot yoga in the evening, and then a long walk after. All powered by fruit, coffee, milk, and my ridiculous supplement stack.
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Michael Sikand
Michael Sikand@michaelsikand·
NGL this a bigger flex than my watch or my car
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RJC
RJC@RJCcapital·
mega green on red day. only1rjc
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atlas
atlas@creatine_cycle·
here is the full list of our SF restaurant picks: chinese: Sichuan Tasty Restaurant steak: Brazen Head dumplings: Dumpling House (Castro) burritos: Taqueria Buen Sabor tacos: Taqueria Vallarta on Folsom and 24th Italian: Seven Hills Izakaya: Fenikkusu or Kibatsu omakase: An (Japantown) and Doma Sushi (Bernal) thai: Prikhom vietnamese: Hai Ky Mi Gia (Tenderloin) nepalese: Timur (Sunset District)
atlas@creatine_cycle

i got chinese food with @Noahpinion and @koreanpeptides while we went through the best food in SF for each cuisine. i also put the camera on the lazy Susan so you as a viewer can be one with the chinese food. 00:00 - Sichuan Tasty Restaurant (best Chinese food in SF) 02:32 - My favourite steak and Italian place in SF 04:09 - Does SF have good food? 09:07 - Best dumpling place in SF 11:35 - Best burrito in SF 13:28 - Best tacos in SF 14:20 - Best Italian in SF 20:08 - Izakaya in SF 21:33- Omakase in SF 23:26 - Best Thai in SF 25:53 - Best Vietnamese in SF 31:49 - Best Nepalese in SF 34:30 - @devahaz and @paularambles shoutouts 35:50 - Best low stakes date spot in SF 42:55 - Best high stakes date spot in SF 45:00 - Yums per dollar

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Eric Ruleman
Eric Ruleman@eric_ruleman·
trying out the new agentic @RobinhoodApp account - very easy to setup via Claude Code excited to see who performs better — me or the AI
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Fireside Alpha
Fireside Alpha@firesidealpha·
Always a must-listen. Gavin Baker (@GavinSBaker of Atreides) broke down the SpaceX IPO, orbital compute, retail, China, and where AI value accrues, on @tbpn (~0:35 to 1:10 min mark). Here were the biggest takeaways: 1. The orbital-compute math is starting to pencil out. Gavin's version: a gigawatt costs about 60 billion to build on Earth, and 25 billion of that is the power and cooling you do not need in space. Once Starship is reusable he puts a launch at about 5 billion, so a gigawatt in orbit lands near 30 billion against 60 on the ground. The half he expects to keep inflating is the power and cooling, which only widens the gap over time. 2. The near-term SpaceX story is terrestrial compute, not Mars. Gavin is genuinely excited for asteroid mining and a city on the moon, but says the tangible drivers over the next year are how fast SpaceX can bring gigawatts online and how richly it monetizes them. He points to roughly 50 billion a gigawatt on the Google deal and, per the Altimeter work, 2 to 3 times neocloud pricing, and notes that in Jensen's words SpaceX energizes data centers faster than anyone. 3. SpaceX looks confident it can bring compute online fast. Gavin cites the Altimeter figure that SpaceX has ordered 20% of Nvidia's Rubin chips, with Groq's LPUs integrating over the next six to nine months. He reads the Anthropic deal as having an out and possibly running short-term, reflecting the training-versus-inference tension, and argues that being a token factory is more than enough for the next five to ten years, so SpaceX has no need to rebuild a full AWS unless it chooses to. 4. Cursor is the other variable he is watching. He flags Cursor's Composer 2.5 becoming roughly Pareto-dominant after a few weeks of reinforcement learning and fine-tuning, asks what happens when that approach meets a bigger base model, and finds it telling that Cursor is now in half the Fortune 500. 5. Retail keeps beating the pros who dismiss it. When people use "retail" as a pejorative, Gavin flips it back on them with "stupid is as stupid does," meaning you judge by results, not labels. The retail-favorite indices are up a lot in both 2024 and 2025, and by his read retail is outperforming the overwhelming majority of professional managers across private equity, venture, and public equity. He calls it the most powerful force in the market in his career, while drawing a hard line that this is nothing like the year 2000 bubble. 6. The lockup-overhang fear is overstated. Over 10,000 SpaceX employees bought on the IPO, and Gavin notes that anyone on the cap table has had a chance to sell every six months for the last decade. The people who wanted liquidity already took it, in his read, which is why he thinks the supply and demand picture from here is more interesting than the standard lockup analysis suggests. 7. Public markets are more patient than venture believes. Looking at how the market treated Tesla and Amazon through their heavy build-out years, Gavin argues the public market has a much greater tolerance for investment and a much longer time horizon than a lot of people in the venture ecosystem give it credit for. 8. His "token path" framework, and where CDNs sit in it. Value accrues to whatever sits in the flow of AI tokens. Cloudflare and Akamai are partly there, and he cites Akamai's roughly 1.8 billion dollar Anthropic deal plus a premium for low-latency delivery, since the lesson from Cerebras is that people pay for speed. But he notes CDNs touch less than 1% of all tokens consumed, maybe under 10 basis points, because most inference happens internally. Asked what is fully in the path, he joked: beachfront property, airplanes, and really nice cars. 9. The bottleneck trade is ending. For the last year, in Gavin's telling, the game was "having Claude run what's the next bottleneck." He thinks that trade is nearly done, pointing to Ajinomoto, the Japanese chip-input supplier the bottleneck crowd had bid up, which then chose not to raise prices. The next game, in his framing, is what holds enduring franchise value on the other side of the bottlenecks. 10. The market doubts Meta can monetize its own assets. Gavin increasingly values these companies on enterprise value to net property, plant, and equipment, a "high asset value, low obsolescence" lens. Meta's multiple there says the market has immense skepticism about its ability to monetize its asset base, and he thinks that skepticism is warranted given that the main thing management has offered so far is the idea of personal superintelligence. 11. The industry is behaving like the end game has arrived. Gavin reads the way players are moving as a sign the end game may be here sooner than expected. His take on OpenAI cutting Codex pricing is that coding tokens are so valuable for getting into the recursive self-improvement loop that everyone is racing for them, and he says Zuckerberg feels that acutely. 12. China's distillation edge is real but fragile. Chinese labs are world-class at industrial-scale distillation, and Gavin relays that it took only about 160,000 reasoning traces from o1 and o3 to reconstruct the original DeepSeek, run through endpoints across every available API. His warning is that all of it goes away the moment American labs stop releasing models at the frontier. 13. Sovereign AI will not reach the frontier. Every country will want a sovereign strategy for national defense, but Gavin's read is that for everyone outside the United States and China it means reinforcement learning on your language, culture, and values, run on the best open-source model inside your own data centers. Frontier-grade sovereign AI is the one outcome he does not see happening. 14. SpaceX may be the most important company of his lifetime. Gavin frames it as a once-in-a-career investment, possibly the most important company ever, and recommends seeing a launch in person, where "a lot of people cry." He notes he owned 15% of Nvidia and 10% of Tesla when each was sub-2-billion in market cap, and puts SpaceX in that same rare category.
TBPN@tbpn

Happy Monday. On today's show: - @NoBickal (UFC) - @GavinSBaker (Atreides) - @leifthunder (Public) - @rfvivas (AppLovin) - @aginnt (Hydra Host) See you on the stream.

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Eric Ruleman
Eric Ruleman@eric_ruleman·
@tenobrus very useful to hear the thought process for people who aren't always caught up on everything
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Tenobrus (→vibecamp)
i don't think this really needs much explanation but it's super out of character for me to be so terse so lemme ramble on anyway - both openai and anthropic are actively working on and hiring for custom chip programs - these *may* only be for inference, but i would find this unlikely, and we know eg TPUs are viable for both. even if they are inference may dominate soon - improved capabilities accelerating chip design and development seems *very* likely. if it's not already happening then they'll train for it - successful RSI will drive this much much faster - anthropic at least has proven themselves very willing to prevent external use of their models to compete with them - there's a pretty likely world where as RSI speeds up they use internal only models to massively accelerate chip dev and don't allow any external companies to use it for the same - nvidia does not manufacture chips themselves, their moat is their IP - they would plausibly remain a natural leader if they continued to have access to frontier intelligence, but as discussed this doesn't seem certain - so pretty quickly we find ourselves in a world where anthropic has no further demand for nvidia chips. this is obviously super desirable to them, nvidia charges a massive premium - but the actual manufacturing is much further outside their wheelhouse. TSMC or intel are basically the only plausible candidates
Tenobrus (→vibecamp)@tenobrus

tsmc >> nvda

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MP
MP@MoneyPrinter0x·
tbh that sector is mostly for copers/copium flow who missed memory supercycle, semis supercycle, gpu supercycle, compute supercycle, etc in other words, its useful to use it to track on mtf cross-sectorially what the ppl last to the party is doing. usually a leading factor/one of the leading indicators on 8th-9th inning environments such as ours. obviously this is under bayesian conditioning that we are in 8th-9th innings re: ai capex supercycle current wave, so its gd to enter this framework while being situationally aware of the base denominator event driven & its respective invals
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MP
MP@MoneyPrinter0x·
interesting to play arm, qcom, neoclouds this coming week gd to monitor photonics for further fwd-looking regime changes
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prayingforexits 🏴‍☠️
I think about Henry Kravis's ($12B) parting words to Ravi Gupta as he left to go to Instacart almost every day
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RJC
RJC@RJCcapital·
when you tell her you’ve been long $SNDK since February 2025
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