Hands-on learning is praised as the best way to understand AI internals. The conversation aims to be technical without ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
The acquisition and expression of Pavlovian conditioned responding are shown to be lawfully related to objectively specifiable temporal properties of the events the animal is learning about.
OpenAI's Open Responses standardizes agentic AI workflows, tackling API fragmentation and enabling seamless transitions ...
Something extraordinary has happened, even if we haven’t fully realized it yet: algorithms are now capable of solving ...
From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...
Microsoft and Tsinghua University have developed a 7B-parameter AI coding model that outperforms 14B rivals using only ...
MemRL separates stable reasoning from dynamic memory, giving AI agents continual learning abilities without model fine-tuning.
The Anthropic philosopher explains how and why her company updated its guide for shaping the conduct and character of its ...
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Nous Research's NousCoder-14B is an open-source coding model landing right in the Claude Code moment
B, an open-source AI coding model trained in four days on Nvidia B200 GPUs, publishing its full reinforcement-learning stack ...
AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...
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