Viewing profile — nee1r

are you specifically focused on non-invasive methods/why? seems like you reach a noise barrier which limits things like this

how do you pick good goal conditioning images/do you have to hand pick a dataset of good goal images? seems hard if you don't have full context. really cool though!

thanks! a lot of credit to the people who helped write/edit

giving back to the research community! releasing and talking about research helps everyone

thanks! i definitely love diffusion + pushed for it, as a non-causal generative method i think its pretty unique

thanks! got a lot of inspiration from VPT https://arxiv.org/abs/2206.11795 is a great paper, would recommend a read we all have various backgrounds, me particularly i did a lot of …

we have an alignment blog post dropping soon! scaling up in the next couple of months, then hopefully opening up an API or licensing it. Benchmarks are really fun—lots of secret on…

planning on instruct tuning soon!

safety was important for the demo, the model didn't have access to the brake or accelerator.

thanks! the math and architecture of the FDM (no video encoder) is pretty simple, its a regular transformer with next-token predictions but with frames interleaved.

yeah! i love the BCO paper, i think its extremely intuitive and these methods are really interesting in a time where data without labels is abundant. i especially like the idea of …

cool thanks for the title idea!! hopefully when we scale up in the next month/two we can update the community

collected! no synthetic

thanks! the inverse dynamics model is trained first on 40k hours of data and then frozen to label all 11 million hours. yup! the idea is that it should take a small amount of data …

real

this is honestly an issue for the inverse dynamics (for app specific shortcuts etc.) but for general UI learning we still see promising eval trends

no finetuning data for the blender task! we actually think its the opposite, there are a lot of video tutorials for complex tasks like onshape/blender/fusion360 but not as much of …

i actually drove the car (with arrow keys) around south park for around ~45 minutes as finetuning data, no extra labelling other than that. think the car line graph is super cool b…

the main chain of experiments was trying causal => non-causal => non-causal with ctc and CE. i think a good intuition here is that you need a generative approach fundamentally beca…

good question! we use exponential binning (map the mouse movements onto a plane with exponentially increasing tick marks https://si.inc/fdm1/exponential_binning.webp ) but tried a …

Hey guys! I’m Neel, been holed up in our south park office for the past year working on model training. excited to share our research! This is a preview of a very different type of…

glad the timelines are short and hope its user friendly

how are you planning on getting the robots to learn a base policy from scratch? seems hard without a base model

being able to search through the files when they're purposefully so obfuscated is great