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Clem
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Clem
@KodaClement
✨Automatically Compacting Context ✨ EE building Rockets 🚀- Sustainable Abundance - Opinions are my own
Los Angeles, CA Entrou em Mayıs 2022
825 Seguindo752 Seguidores
I spoke to Anthropic’s AI agent Claude about AI collecting massive amounts of personal data and how that information is being used to violate our privacy rights.
What an AI agent says about the dangers of AI is shocking and should wake us up.
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Composer 2 is out!
Cursor is an example of a new type of company, not a pure app maker and not a model provider.
Our aim is to build the most useful coding agents by combining the best API models and our domain-specific models.
Cursor@cursor_ai
Composer 2 is now available in Cursor.
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Composer 2 marks the one-year anniversary of our large model training efforts. Since then, we've built an exceptionally talent-dense team of ~40 people with some of the best researchers and engineers from the labs, academia, industry, and more heterogeneous backgrounds.
And we are exclusively focused on coding. We don't care about models that can respond to emails, do your tax returns, or be your friend.
Every FLOP, token, parameter, and researcher is entirely dedicated to software engineering.
Cursor@cursor_ai
Composer 2 is now available in Cursor.
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@DBurkland @pbeisel It’s in testing right now. Wide release in a few weeks.
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Tesla’s forthcoming AI5 uses a half-reticle design, which is crucial for yield. A reticle defines the imaging area of a lithography machine, fitting two chips per shot effectively doubles yield.
This means the Tesla chip design team had to carefully manage die features, for instance dropping the older ISP (and classic GPU) to make room for more AI cores.
By contrast, NVIDIA’s Blackwell fills nearly a full reticle, making it a single-reticle design.
If Tesla hits its compute and efficiency targets with AI5 in this half-reticle format, it’s almost like cutting fab requirements in half.
And this has a big impact on Terafab, especially if it carries forward for AI6, AI7, etc.
phil beisel@pbeisel
Terafab may be the most essential vertical integration Tesla has ever undertaken— and it is truly non-optional. It will take years to build and will test even Elon’s speedrunning abilities to the limit, but that won’t stop him from trying. The breakthrough likely lies in overhauling the overall facility’s cleanroom model. By moving wafers in sealed pods with localized micro-environments, the fab no longer needs a monolithic ultra-clean space. Elon’s line about “eating cheeseburgers and smoking cigars” on the fab floor isn’t silly, it’s the practical reality of a radically simpler, cheaper, faster approach that could finally change the economics of chipmaking. This is all forced by the brutal “pinch” in chip supply. Tesla must produce on the order of 100–200 billion AI chips per year just to saturate its roadmap. That volume powers: FSD cars & Robotaxis (tens of millions of vehicles needing AI5 inference for near-perfect autonomy), Physical Optimus (scaling from thousands today to millions per year, each requiring AI5/AI6-level compute), Digital Optimus (the new xAI-Tesla software agents for digital/office automation, running massive inference clusters), Space-based data centers (AI7/Dojo3 orbital compute for GW-scale training and inference beyond Earth limits). AI5 delivers the ~10× leap for vehicles and early robots; AI6 shifts focus to Optimus + terrestrial DCs; AI7 goes orbital. No external foundry (TSMC, Samsung, etc.) can deliver that scale or timeline— hence the Terafab launch. Without it, the entire robotics + autonomy future hits a brick wall. Terafab isn’t optional; it’s the only way forward.
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Going to Austin today for the week, if you’re building something cool I’d love to meet!
+ lmk if you have any food recs!
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Clem retweetou
Initial Super Heavy V3 and Starbase Pad 2 activation campaign complete, wrapping up several days of testing that loaded cryogenic fuel and oxidizer on a V3 vehicle for the first time. While the 10-engine static fire ended early due to a ground-side issue, we saw successful startup on all installed Raptor 3 engines. Next up: preparing the booster for a 33-engine static fire
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i find great success with standalone "cleanup prompts" to my prs. you can stuff every rule you got into agents.md, but beautiful code is secondary until it's the only focus
for example: "simplify all code so it's extremely easy to consume, remove not strictly necessary code"
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The Verge has lost its way.
Several months ago, they interviewed me for 45 minutes about Apple Vision Pro. I spent 43 minutes talking about what I love, and 2 minutes on what I’d change.
They twisted parts of those 2 minutes and cut everything positive I said.
To make it worse, the author opened the interview by saying they were biased against headsets.
I miss the old Verge. The one that was fun. The one that spotlighted tech instead of throwing shade.
The Verge@verge
Nvidia’s DLSS 5 is like motion smoothing for video games, but worse theverge.com/entertainment/…
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A reminder that the largest, most complex, and the first fully reusable rocket still has a higher flight rate than the majority of active rockets despite being a “failure” to its haters
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@nickbaumann_ @OpenAIDevs so wait you are using mini for subagents now?
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GPT-5.4 mini matters for subagents because it changes what feels worth handing off.
The parent thread should hold the architecture, plan, and progress narrative.
Fast subagents can explore the repo, check hypotheses, and preserve the parent thread’s limited attention.
OpenAI Developers@OpenAIDevs
We’re introducing GPT-5.4 mini and nano, our most capable small models yet. GPT-5.4 mini is more than 2x faster than GPT-5 mini. Optimized for coding, computer use, multimodal understanding, and subagents. For lighter-weight tasks, GPT-5.4 nano is our smallest and cheapest version of GPT-5.4. openai.com/index/introduc…
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Clem retweetou
Imagine being so zoning brained that you think appetizer shops should be illegal in your neighborhood. Couldn't be me!
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