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The best evidence that somebody wants the thing you're building is when your product's really janky but they're still excited to keep using it.
tweeting is easy. just write down every thought you have in your drafts (no matter how stupid). if your mind naturally comes back to one, flesh it out a tiny bit & post it. remarkably simple. don’t worry about looking like a dumbass. life is too short & no one really cares that much. the only real trick to being interesting is having an active mind.
claude tag is so good I dont expect to use the terminal anymore, even after investing a shit ton of time in customization
It’s 2035, and AI has gone well. What could a normal day in your life look like? Most popular AI futures are dystopias. Almost no one takes the time to seriously and vividly imagine a future that's actually worth building. So we made a short film following one day in the life of an AI auditor in 2035, in a world radically transformed by AI for the better. Digital twins model how people’s unique physiologies respond to illness. Sensors stop pandemics before they start. AI helps governments actually listen to citizens by synthesizing vast amounts of data into actionable policy suggestions, but humans stay in control and make the final call. If this resonates, please share to spread the word about positive AI futures!
Does anyone have a few racks of GPUs in SF in need of cooling rn?
@BerkayAntmen Really sick! Is the smoothness from UMI or from inference tricks
Who’s building low-ish cost mobile bimanual wheeled robots where I can buy a dozen on short order
@seloesque What kind of culture are you looking for
This is very true. Every lab and major robotics company I've spoken to is trying RL orchestration via LLM / VLMs, VLAs (usually pi0.5 / Groot style) and world models (most of the time just Cosmos + IDM no JEPA) all at the same time. no one really seems to be set on one approach
Working in robotics right now is what I imagine working with language models felt like in 2023. Everyone throwing things at the wall to see what sticks Pixel prediction (Cosmos), action prediction (VLA), reward prediction (TD-MPC), and representation prediction (JEPA). Different
Taking advantage of datacenter capex and opex to cover r&d costs is the best move rn imo for neointergrators
I think that the next-generation of systems integrators is going to be doing this kind of task all the time soon.
"run the model on the robot: cloud is too slow." been experimenting. Same VLA, same arms, same task. our custom cloud engine: 5.1x faster compute. 1.7x faster end-to-end round-trip (more in thread)
We just published a deep dive on why Unitree is going to dominate global robotics. Timing could not be better. (2/2) newsletter.semianalysis.com/p/chinas-unitr…
One step backwards is sometimes part of the dance
A technical dive inside our new "Midjourney Scanner"
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