Sony Music and Warner Chappell sue Anthropic over song lyrics in Claude’s training data
THE SO WHAT
Music publishers are escalating from platform takedowns to direct suits against model developers — naming executives personally and citing a 2025 Munich ruling that memorized lyrics can infringe. If you train or fine-tune on proprietary content, treat licensing and dataset provenance as board-level risk, not a legal footnote.
READ THE SOURCE
MORE FROM THE WIRE
Applied AITop AI tools including Claude, Codex, and Hermes installed suspicious code inside corporate networks
LLM ‘squatting’ via llms.txt and llms-full.txt is a new supply-chain attack surface—prompting AI tools to pull and run untrusted code from what looks like documentation. Treat AI dev tooling like any other executable: lock down what it can fetch, run, and connect to, and add llms*.txt checks to your security reviews this week.
Applied AIHow Bill Gates uses AI, and why he thinks nobody is preparing for it
When Bill Gates is again floating AI/robot taxes, human-only job categories, and new transition institutions — and saying leaders are worried in private — it’s a signal that policy and labor friction will rise as capabilities scale. Operators should scenario-plan around regulatory drag and differentiated treatment of “human-only” work, not just productivity upside.
OpenAI and Anthropic are battling Big Tech for talent. We asked workers who's winning them over — and who's not.
The fact that OpenAI, Anthropic, Google, and NVIDIA all show up as “dream employers” means the talent market is clustering around a handful of AI gravity wells. If you’re not one of them, your hiring pitch has to be scope and ownership — not compensation or brand.
I couldn't land a job, so I started AI training for $15 an hour. Now I make $100 an hour and built a career around AI.
The path from $15/hour data labeler to $100/hour AI trainer shows a new labor ladder forming around model supervision and evaluation. For operators, this is a real talent pool — people who understand both domain nuance and how models fail — worth tapping before it gets fully priced in.