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Learning Machine Learning for Astronomy

A beginner asks for free resources, tutorials, books, and existing Jupyter notebooks for applying machine learning to astronomy. Potential use cases include analyzing JWST or TESS data to identify black-hole or exoplanet signatures and building reproducible environments with Git, Python libraries, and Docker.

Reddit r/MachineLearningCommunity1d ago#astronomy-ml#scientific-python#space-data
Kling AI Becomes Kuaishou’s Growth Engine

Kling AI Becomes Kuaishou’s Growth Engine

Kling AI generated more than RMB 850 million in Q2 revenue, up 240% year over year, making it the standout growth driver in Kuaishou’s otherwise slowing business. Kuaishou is prioritizing AI investment, spinning Kling AI out for independent financing at an implied valuation of US$18 billion despite near-term profit pressure.

Rapidus Bets on 2nm Without Fighting TSMC

Rapidus Bets on 2nm Without Fighting TSMC

Rapidus is pursuing mass production of advanced 2nm semiconductors through a large-scale Japanese national project. Instead of matching TSMC’s scale, the company plans to compete with RUMS, an integrated one-building production model designed for diverse, lower-volume manufacturing.

ITmedia AI+ (日本)Media2h ago#2nm#semiconductors#chip-manufacturing
AgentCore Automates Cloud Migration

AgentCore Automates Cloud Migration

AWS Professional Services uses a multi-agent framework on Amazon Bedrock AgentCore to automate enterprise cloud migrations end to end. Specialized agents cover discovery, infrastructure-as-code generation, portfolio governance, and post-migration operations, reducing IaC development time from weeks to minutes.

AWS Machine Learning BlogOfficial8h ago#cloud-migration#multi-agent#automation
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