John Deere owners will get the right to repair equipment under FTC settlement

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Grok 4.5

Rewriting Bun in Rust

Show HN: 18 Words

Cloudflare Drop

My thoughts on the Bun Rust rewrite

EU Parliament greenlights Chat Control 1.0

FAANG Simulator

I think I have LLM burnout

Data visualizations are the bridge between user and data.<p>But building AI agents that can generate visualizations reliably can be very tricky:<p>- simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; 
- complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability<p>We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make visual decisions that are supposed to be handled by a good compiler. Flint is a visualization intermediate language to address this issue, allow AI agents to solve this last-mile human-agent interaction problem. It provides a simple semantic-type based specification, and contains a layout optimization engine that can produce good-looking charts (filled with derived low-level details) from simple high-level specs. The result is also very human understandable and adaptable. Flint powers data formulator for generating visualizations (another open source project from microsoft <a href="https:&#x2F;&#x2F;data-formulator.ai&#x2F;" rel="nofollow">https:&#x2F;&#x2F;data-formulator.ai&#x2F;</a>).<p>Flint is available open source, and we built a MCP server that you can directly plug flint in your favorite agent app to play with data.

Show HN: Microsoft releases Flint, a visualization language for AI agents

Why developers are ditching GitHub for Codeberg and self-hosting alternatives

Bonnie Tyler has died

PlayStation can delete all your digital games after 3 years of inactivity (EU)

Spider venom kills varroa mites without harming honeybees

Separating signal from noise in coding evaluations