but they're not out-of-distribution, that's exactly the issue
MACHINE LEARNING
-
Foundation Models Self-Play Enables Open-Ended Strategy Innovation
By
–
Foundation Model Self-Play: Open-Ended Strategy Innovation via Foundation Models Aaron Dharna, Cong Lu, Jeff Clune : https://
arxiv.org/abs/2507.06466 #ArtificialIntelligence #DeepLearning #MachineLearning -
XAI Evals: Comparing AI Explainability Methods Framework
By
–
Missed our webinar on Evaluating AI Explainability? We compare SHAP, LIME, GradCAM, Integrated Gradients & DL-Backtrace across real ML & DL models using XAI Evals — our open-source evaluation framework. ▶️ Watch now: piped.video/watch?v=E8l1Ucpc… 🔗 GitHub: github.com/AryaXAI/xai_evals
-
Action Chunking Advances Reinforcement Learning Efficiency
By
–
Reinforcement Learning with Action Chunking Qiyang Li, Zhiyuan Zhou, Sergey Levine: https://
arxiv.org/abs/2507.07969 #ArtificialIntelligence #DeepLearning #MachineLearning -
fastai GPU Accelerated Machine Learning Library
By
–
If it was the normal one then fastai has a GPU accelerated version! 😀
-
AgriStack and AI Transform Indian Agricultural Ecosystem Workshop
By
–
A workshop on “Transforming Agriculture through AgriStack and Artificial Intelligence” was organised at Krishi Bhawan, New Delhi, to deliberate on the application of digital technologies in enhancing the agricultural ecosystem. Shri @abhish18
, Additional Secretary, Ministry of -
From GANs to Diffusion: Evolution of Generative AI
By
–
From GANs to Diffusion: Making Sense of Generative AI’s Rapid Evolution linkedin.com/pulse/from-gans…
→ View original post on X — @iainljbrown, 2025-07-11 05:56 UTC
-
Typical AI Web Scraping Examples and Use Cases
By
–
Interesting. what's a typical example of scraping you do with AI?
-
Grok 4 Heavy fairer comparison to o3-pro than o3
By
–
To be fair, o3 also isn't great at this — Grok 4 Heavy might be fairer comparison to o3-pro, which is what I used in my post
-
Gradient Accumulation Training Techniques for Machine Learning Models
By
–
this is just not right. you probably can’t train a good model with a batch size of 1. but you can if you use gradient accumulation, since it reduces noise