Hi, I really really need access to Xperience-10M for a deadline which is very soon. https://huggingface.co/datasets/ropedia-ai/xperience-10m Unfortunately, it looks like the owners have stopped approving people to download the dataset. I filled out the form a few weeks ago but have heard nothing back. Several others have also commented on the HF saying the same thing. If anyone's account has access to this dataset and are willing to make me an API key for a day or two, I would really really appreciate it :) Know it's a long shot but doesn't hurt to try. submitted by /u/PatientWrongdoer9257 [link] [Kommentare]
Track 2026 World Cup goals by club at tournament start date.
I’m still here. Not selling unless things really go off the rails, but I just need to vent for a minute because I’m honestly exhausted by this market. I bought SOL in the low $20s, but I also bought ONDO above $2 at the top. I’ve ridden the ups and downs, took some profits here and there, but nothing significant. And now here we are again, supposedly “bottoming.” I’m tired of hearing respected voices like Tom Lee talk about how we’re in the bottoming process, while at the same time watching things like MSTR struggle. The mixed signals are mentally draining. To be clear, this isn’t the kind of struggle where I’m thinking about selling everything and walking away. It’s more the psychological side of it. The bears feel louder, the FUD feels stronger, and the uncertainty seems heavier than it did in previous cycles. I’m not looking for hopium or reassurance. I know everyone in this market deals with these emotions at some point. Just wanted to share where my head is at and see if anyone else is feeling the same. Thanks for listening. 🙏 submitted by /u/NoSleepDad2023 [link] [Kommentare]
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New research by the Times shows that thousands of fatal crashes involving pedestrians could have been avoided with lower hood heights and improved visibility.
Filter AI-generated videos on YouTube
Hi everyone, For the past couple of weeks I have been working on a simulator project considering the shortcomings of MuJoCo. There are things that people like and also don't like about MuJoCo, like the CPU dependency on MuJoCo which makes the simulation not parallelizable beyond a certain limit (depending on the hardware). I know there exists MJX which is GPU accelerated, however, it is not really made for vision based RL pipelines and training. There is also NVIDIA Isaac ecosystem, but that requires a powerful GPU, thus making it limited in terms of accessibility, let alone it requires license. This is why I worked out this new simulator (still working on it, so there will be significant bugs which require fixing). I call it **MuJoFil** \- MuJoCo + Google's Filament Render Engine. Basically I used Nvidia's Newton Physics Engine (which itself is based on MuJoCo's physics engine but is GPU native), clubbed it with Google's Filament render engine (both of these are open-source), modified Filament significantly to support working natively on GPU to render multiple simulations in parallel, and worked on optimizing it for performance. So what is MuJoFil? It is supposed to be an open-source high visual fidelity simulator optimised for a highly parallelized RL training pipeline so that users can use it to train Vision based Policies. Besides, it offers PBR textures support and also a simple to use plug and play functionality, where you can use any environments available online and support formats such as GLB, OpenUSD, etc. for setting environments for your robots. Basically, now you aren't just limited to environments native to MuJoCo, but rather you can use any environments available online from sketchfab, polyhaven, etc. and use it as a practical robot simulation environment. Check it out for yourself in the video. I would really appreciate it if you guys could tell how you feel about it and suggest ideas for what all things I can incorporate into it as this is going to be a fully open-source and free to use simulator that I have been working on for weeks. PS: While I have a couple of published research papers at top RL and AI/ML venues in the field of RL, I still consider myself a learner in this field who is continuously trying, learning, and building stuff, so there will be things in this hugely ambitious project which I might have missed to work on, and that is where I want help from you people who understand this field well. Sorry for this lengthy post and thanks if you read it till here🙇🙇🙏, I would really appreciate if you could share your thoughts on it. Also, I will make its code repo public on GitHub, but till then you can definitely check it out on PyPI. There are 2 separate packages, one can be installed using: "pip install mujofil" This is the CPU based variant, whereas there is a CUDA supporting GPU native variant about which I mentioned above, you can currently install it using: "pip install mujofil-warp" I am planning on changing its name to mujofil-cuda instead of mujofil-warp as that apparently sounds more intuitive to my direct peers but you can suggest this name as well. Thank you for the support❤️. submitted by /u/MT1699 [link] [Kommentare]
Do it , do it , do it submitted by /u/Jolly-Schedule7386 [link] [Kommentare]
DeepSWE delivers four advances over existing public benchmarks: Contamination free: Tasks are written from scratch, not adapted from existing commits or PRs, so no model has seen the solution during pretraining. High diversity: Tasks span a broad pool of 91 repositories across 5 languages. Real-world complexity: Prompts are ~half the length of SWE-bench Pro's, yet solutions require 5.5x more code and ~2x more output tokens. Reliable verification: Verifiers are hand-written to test software behavior rather than implementation details. The result is a benchmark that reflects how today's frontier coding agents actually perform in software engineering work. https://preview.redd.it/lacvagyr159h1.png?width=1373&format=png&auto=webp&s=6514340a15d51d7f03da733f08fb3f6a302cac75 It's open-source: https://github.com/datacurve-ai/deep-swe submitted by /u/we_are_mammals [link] [Kommentare]