aurph (@aurph) profile picture

aurp on godel

10-13-2021
Joined April 2021
Photo by aurph (@aurph)Photo by aurph (@aurph)Photo by aurph (@aurph)Photo by aurph (@aurph)Photo by aurph (@aurph)Photo by aurph (@aurph)Photo by aurph (@aurph)Photo by aurph (@aurph)Photo by aurph (@aurph)Photo by aurph (@aurph)
aurph retweeted
Kid’s these days!
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$MU just outlined plans for custom HBM4E in 2027 followed by 3D-stacked memory directly on AI processors in 2028 with new HBM generations planned nearly every year through 2030. That's a pretty big shift for Micron as memory becomes part of the AI chip itself.
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Keybanc states Micron is quoting 4Q26 SSD pricing +40-45% Q/Q, compared to consensus increase +20% Q/Q. $MU $DRAM $EWY
‼️ JUST IN: Micron is quoting 4Q26 SSD pricing +40-45% q/q while consensus is only expecting +20% q/q. Major expectations beat incoming. $MU $SNDK
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This is who you're trading against
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and so it begins (well soon) ... $MU "On October 8, 2026, our Board of Directors authorized an increase in the maximum amount of discretionary repurchases of our outstanding common stock to be made from December 9, 2026 to $35.16 billion."
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Big respects big.
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aurph retweeted
They tokenboarded my boy in Promptanamo Bay 😭
🚨 #BREAKING: American man "kidnaps" Flock camera, subjecting it against its will to 23,040 license plates per second.
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BREAKING: The Fed introduces new $1 dollar bill
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big AI news Google just demonstrated a recursive self improvement loop for AI discovery Google/DeepMind researchers introduced Dream-RSI, a system where an AI agent improves how it explores problems by replaying its past discovery attempts, testing thousands of alternative strategies cheaply, then deploying the better strategy in the next round. Across algorithm design, mathematical optimization, and GPU kernel engineering, it matched or improved discovery quality while cutting search costs dramatically, in one setting reducing agent calls by up to 162x. 👀 Importantly, it improves the exploration policy, not the underlying model weights.
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Every stock has its own chat on Godel Terminal. → DMs, private groups & stock-specific groups Members only.
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aurph retweeted
To: █████ █████████ From: Kenneth Cordele Griffin <[email protected]> September 9, 2026, 7:35 AM Buy calls on AMD CRWV BE SNDK SKHY DRAM… Jan 2027 expiration. Whatever strike you want. Higher the better
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aurph retweeted
openai asked me to test GPT 6 Astra, but uh, i turnt it down they offered me like, 15, sum shi like 10, like 5 billion free tokens it was on this big gpu cluster out in jacksonville but i turnt it down, just to do this, to code with my locally running qwen-3.8-27b abliterated
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Supply chain data (SPLC) is now live on Godel Terminal → Map any company's suppliers, customers, competitors and partners → Start with one name and see everything around it → Thousands of companies mapped, global coverage Institutional-grade relationship data, now available to everyone.
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Local minima are extremely rare in high dimensional spaces, so if you ever feel stuck in a rut it’s probably just because you aren’t considering a wide enough set of orthogonal options
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aurph retweeted
hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final ((1+xy)^3 z + y^2 (1+xy) (4+3xy), y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy), 2 x - 3 x^2 y - x^3 z): \C^3\to \C^3, has jacobian determinant -2, and sends (0, 0, -1/4), (1, -3/2, 13/2), and (-1, 3/2, 13/2) to (-1/4, 0, 0)
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aurph retweeted
Just got off the phone with Kevin. CPI data tomorrow will be extremely light. Prepare for a massive rally. I mean rip of ages coming. Position accordingly
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this is just a beta selloff for $MU and $SNDK -- there is a @vector__news story out that explains plainly why $META is not going to be renting out cloud compute anytime soon. if the market was taking this seriously $NVDA would be -10% to -20%, recommend buying momentum
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aurph retweeted
Water usage has been a hot topic in the AI data center world, but the numbers may surprise you. According to the Manhattan Institute, data centers use 0.2 percent of daily water usage in the U.S. and that number has dramatically decreased in the past few years due to a new method: liquid cooling. By moving to 45°C liquid cooling, AI factories in favorable climates can use dry coolers instead of conventional cooling-tower-based systems, cutting facility cooling water use from roughly 2.6M gallons per MW per year to near zero. Liquid cooling enables AI factories to be both water and energy efficient, while creating opportunities for heat reuse and dispersal to local communities, allowing these factories to become energy grid assets. Learn more below ⬇️ nvda.ws/4gAVGoJ
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Today, we're proud to announce a strategic agreement with @AnthropicAI that spans memory and storage AI architecture design, supply and demand, enterprise adoption of Claude across Micron and a strategic investment in Anthropic’s Series H funding round. bit.ly/4ezJkL1
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