ls /news/machine-learning · home newsmachine-learning
grep -r --recent /news/machine-learning | head -20

Machine Learning News

Machine learning news — deep learning, reinforcement learning, neural architecture search, diffusion models, and new ML frameworks and libraries.

5455 articles page 237 of 273 0 sources 30 min sync cycle updated 2026-05-26

// latest articles 5455 indexed

08:05
2026-05-26
microsoft.github.io
artificial-intelligence · 1m read · neu

SkillOpt – Executive Strategy for Self-Evolving Agent Skills

SkillOpt introduces a method for improving AI agent performance by treating skills as external state, allowing a frozen agent to be evaluated on scored batches while a separate optimizer model proposes structured edits. …

07:42
2026-05-26
djdumpling.github.io
machine-learning · 24m read · neu

paper reading catalog

DeepSeek researchers introduced manifold-constrained hyper-connections to restore the identity mapping property in transformer architectures, addressing training instability and scalability issues caused by standard hype…

07:38
2026-05-26
dev.to
machine-learning · 1m read · neu

I just published Part 1 of "The Machine Learning Engineering Series", where I break down the full lifecycle: how raw data becomes a trained model, gets containerised, and ships as a live API that…

Michellebuchiokonicha published Part 1 of "The Machine Learning Engineering Series," detailing the full lifecycle of how raw data becomes a trained model, is containerized, and ships as a live API for other engineers to …

05:47
2026-05-26
dev.to
artificial-intelligence · 6m read · neu

RAG vs Fine-Tuning- Choosing Right Strategy for Modern AI Applications

Companies building AI applications for industry-specific use cases must choose between retrieval-augmented generation (RAG) and fine-tuning to improve model performance. RAG enables AI models to access real-time informat…

05:47
2026-05-26
dev.to
artificial-intelligence · 7m read · neu

AI Metrics Decoded: From Parameters to TOPS

A developer explains that understanding seven core AI metrics—parameters, tokens, FLOPS, TOPS, and FLOPs—is essential for avoiding costly deployment mistakes, such as choosing a 70B-parameter model that runs on a laptop …

05:43
2026-05-26
dev.to
artificial-intelligence · 1m read · neu

You just can’t miss this…

Harsh Manvar published a practical guide demonstrating how to run large language models, AI agents, and the Model Context Protocol within Docker containers. The guide provides step-by-step instructions for containerizing…

← prev page 237 / 273 next →
LIVE [news/machine-learni] indexed:5455 page:237/273 en · ua 2026-05-20 ·