By categorizing and filtering user input, you can better focus on driving AI improvement. This iterative process—blending automation with human review—ensures AI learns from high-quality data, leading ...

This important study presents single-unit activity collected during model-based (MB) and model-free (MF) reinforcement learning in non-human primates. The dataset was carefully collected, and the ...

The digital era has witnessed unprecedented technological advancements, with artificial intelligence emerging as one of the ...

DeepCoder-14B competes with frontier models like o3 and o1—and the weights, code, and optimization platform are open source.

A more recent example is the use of reinforcement learning to make chatbots such as ChatGPT more ... The LitFlask 3-in-1 Smart Bottle is your spring MVP, now just $84.99 Use code HYDRATE at checkout ...

AI trading tools can improve speed and strategy by scanning data, tracking sentiment, and reacting in real-time. No AI system ...

This is a official code implementation for Nonlinear RISE based Integral Reinforcement Learning algorithms for perturbed Bilateral Teleoperators with variable time delay (Neurocomputing Journal).

* The data are sourced from the MMAU leaderboard. [1] Xie, Zhifei, et al. "Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models." arXiv preprint arXiv:2503.02318 (2025). [2] ...

"For example, when a bouncing ball interacts with the ground ... the system can better estimate the states to assist the decision making." The new reinforcement learning framework Teng and his ...