Some time ago, while reading up on new CSS features, I asked myself: Is it possible to leak the entire content of an HTML text node only using CSS?
We recently open-sourced our implementation of obstacle overtaking using GPMP2 (Gaussian Process Motion Planning). The project demonstrates trajectory optimization for autonomous overtaking by representing robot trajectories as continuous-time Gaussian Processes and optimizing them as a factor graph. Instead of sampling-based planning, the approach jointly minimizes smoothness and obstacle costs while satisfying vehicle dynamics constraints, producing collision-free and dynamically feasible trajectories. Some highlights: GPMP2-based trajectory optimization using factor graphs Integration with robotics simulation for reproducible experiments Clear codebase that can serve as a starting point for researchers and students working on motion planning If you're working on motion planning, trajectory optimization, autonomous driving, or robotics, I'd love to hear your thoughts, suggestions, or ideas for extending it. Repository: https://github.com/AutonomousVehicleLaboratory/obstacle-overtaking-gpmp2 submitted by /u/Turbulent_Leek8446 [link] [Kommentare]
Hello, I am an european and I still have a large amount of USDT (Tether) in a non-custodial account cold wallet. I want to sell all these coins for EUR or USDC but as an european a lot of exchange have delisted USDT and Binance is no longer accessible. What can i do ? which exchange still allow transaction with USDT for europeans ? Thanks ! submitted by /u/RickSanchez67 [link] [Kommentare]
Tommy Reddad - computer scientist, software developer. A personal blog of arbitrary interests, occasionally updated.
I wrote about the sqlite-utils 4.0rc1 release a couple of weeks ago. Since we only have Claude Fable on our Max subscriptions for a few more days, I decided to …
Hog Bay Software
As someone who is not affiliated with any of the big tech companies, I find it particularly difficult to have the confidence or enthusiasm to approach any ML problem with an attitude that my professors probably had at my stage in life. I'm sure I am not the only one having the following thoughts: "My research is currently being done better at companies." "ML problem I set out to solve is already solved and in fact turned into products and sold for millions at companies X, Y, Z. There is no need for further research." "Industry is not interested in theoretical ideas and there is plenty of evidence for that, starting with their hiring practice." "Companies wouldn't have millions of dollars in funding or revenues if their models weren't working." "Research is like Darwinian evolution. Evolution aims to produce the fittest model. After decades of evolution, the fittest model is already in industry, why should I explore other evolutionary dead-ends?" "There may not be a next big thing after LLM. If there were, it would be simply incorporated as a function or a subroutine that LLM simply calls when needed, and the average person would be none the wiser. My contribution would be invisible." Seems like research outside of big tech companies is pointless (unless you are a prof who is making big $$ while doing it). Because whatever they are working on might be lightyears ahead of whatever you are doing, but you wouldn't know because their model is simultaneously closed-source and omnipotent. There are tons of people sharing their resumes on other ML/CS subreddits and occasionally you see that their projects are along the lines of "linear regression for Titanic dataset" or "YOLO for pedestrian detection" and they are wondering out loud why nobody is hiring them. Everyone with more ML experience can see because there is zero need for people with this skillset. But what if my very research also looks the same to people in industry? What if my "deep geometric autoencoding variational neural-former" also looks like some silly Kaggle project because industry can already do that much more efficiently? How do you silence these thoughts? submitted by /u/NeighborhoodFatCat [link] [Kommentare]
