![Dave Yen Profile](https://pbs.twimg.com/profile_images/1681668008048041984/r7PpCb57_x96.jpg)
Dave Yen
@davecyen
Followers
931
Following
4K
Statuses
2K
@ycombinator alum, cofounder & GP https://t.co/kdzceBIzeN. ex-@Rigetti, @Shopify, @Salesforce. ultra basic dad. 🏀 is life
San Francisco, CA
Joined April 2009
Basically me at the playground “getting shots up” while my kids run around unsupervised
We RL'ed humanoid robots to Cristiano Ronaldo, LeBron James, and Kobe Byrant! These are neural nets running on real hardware at our GEAR lab. Most robot demos you see online speed videos up. We actually *slow them down* so you can enjoy the fluid motions. I'm excited to announce "ASAP", a "real2sim2real" model that masters extremely smooth and dynamic motions for humanoid whole body control. We pretrain the robot in simulation first, but there is a notorious "sim2real" gap: it's very difficult for hand-engineered physics equations to match real world dynamics. Our fix is simple: just deploy a pretrained policy on real hardware, collect data, and replay the motion in sim. The replay will obviously have many errors, but that gives a rich signal to compensate for the physics discrepancy. Use another neural net to learn the delta. Basically, we "patch up" a traditional physics engine, so that the robot can experience almost the real world at scale in GPUs. The future is hybrid simulation: combine the power of classical sim engines refined over decades and the uncanny ability of modern NNs to capture a messy world.
0
0
1
Adding my own fwiw after trying out Deep Research and watching the live chain of thought being streamed: Today’s LLM observability tools primarily track input-output interactions (prompt -> message), but as reasoning models evolve, a more advanced generation of tooling is needed for the internal chains of thought. These tools should provide logging and visibility into intermediate reasoning steps, decision pathways, external sources referenced, actions taken, tools/functions invoked, error handling, etc—essentially debugging and fine-tuning for multi-step inference and agentic workflows
0
0
1
vibe coding is the way
There's a new kind of coding I call "vibe coding", where you fully give in to the vibes, embrace exponentials, and forget that the code even exists. It's possible because the LLMs (e.g. Cursor Composer w Sonnet) are getting too good. Also I just talk to Composer with SuperWhisper so I barely even touch the keyboard. I ask for the dumbest things like "decrease the padding on the sidebar by half" because I'm too lazy to find it. I "Accept All" always, I don't read the diffs anymore. When I get error messages I just copy paste them in with no comment, usually that fixes it. The code grows beyond my usual comprehension, I'd have to really read through it for a while. Sometimes the LLMs can't fix a bug so I just work around it or ask for random changes until it goes away. It's not too bad for throwaway weekend projects, but still quite amusing. I'm building a project or webapp, but it's not really coding - I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works.
0
0
0
sonnet is the codgen đź‘‘
DeepSeek R1 has landed on Cursor Composer, so I tried it by adding Supabase realtime to my app! If you're wondering, they are using a version of DeepSeek hosted on US servers. As much as I love the hype on this model, I find that using Claude Sonnet produces better results.
0
0
0