I mostly tweet about #ai, #robots, #science, @packers...
Senior SWE at @Anduril | Ph.D. Robotics @GeorgiaTech | M.S Robotics @Penn
Thought/opinions are mine
World models are hot these days, but I don't think JEPA and other efforts will really go all the way. People should take cues from Rodriguez-Sanchez, Allen, and Konidaris.
https://t.co/DZknICSGPp
That's how parts get inspected! 🪡
The pace is ridiculous.
Imagine people still doing this instead of machines.
Renishaw system is one of the biggest shifts in coordinate-measuring machines (CMMs).
Instead of moving the entire machine to capture each point, REVO uses a 5-axis scanning head that collects data through rapid angular motion.
Combined with automated probe and stylus changes, the system can handle complex geometries and full surface scans that traditionally required slow, point-by-point probing.
~~
♻️ Join the weekly robotics newsletter, and never miss any news → https://t.co/GoA3ZuwWF9
@tolga_birdal@tdietterich@arxiv "hallucinated references" didn't really exist in until LLMs, so that premise doesn't make sense. Arxiv has made authors responsible in the past, but that was clearly on the authors before LLMs. This policy clarifies that LLM mistakes are also on the authors.
@JustinAngel@tdietterich@arxiv strong disagree. Imagine this is implemented as an automatic but naive filter (e.g. literally the examples in the tweet). this would still make Arxiv WAY better, even if it was easily circumvented. Deceptive actors isn't the problem, slop is
Attention @arxiv authors: Our Code of Conduct states that by signing your name as an author of a paper, each author takes full responsibility for all its contents, irrespective of how the contents were generated. 1/
Robostral can now follow natural language instructions. It responds to voice commands and pointing. It is also getting better at fine-grained manipulation where precise force control matters. It generalizes to new objects and tasks not present in the training data.
lowkey one of the best things about ML right now is how many legit research paths exist outside the traditional PhD route
- MATS
- OpenAI Residency
- Anthropic Fellows
- DeepMind Student Researcher
- ML Collective
- FAR. AI
- Mila
- INSAIT
- EleutherAI
- Redwood Research
- Apart Research
- Encode
- AI2, LAION
- Berkeley BAIR
- Stanford SAIL
- MIT CSAIL
- Vector Institute
- HuggingFace also quietly has some insanely strong open source contributors btw
stupidly exciting time to be in ML if you genuinely like building and researching things
Would you like to join the research effort on JEPA and World Models easily?
After a full year of hard work, we’re excited to finally release stable-worldmodel:
an open-source, scalable platform built to accelerate JEPA & World Model research!
📄: https://t.co/gnxGvens5A
In the last couple of months, we have witnessed significant advances in Industry-scale World Models. Yet, for the broader community, the gap between reading about these models and deploying them remains disappointingly wide.
Today we're releasing Nano World Models: a minimalist, batteries-included repo for advancing world model science.
🧵 (1/9)