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What's new in AI

What's new in AI: 19 Oct 2026

19 Oct 2026 · All digests

Key updates include Anthropic's public benefit fund, Meta's terms change on web scraping, Replit switching to OpenAI as default model, Disney hiring most of Character.AI staff, and a new llm-tools-datasette release.

Anthropic says it's committing 5% of its shares to a "public benefit fund"

Anthropic announced it will allocate five percent of its equity to a fund aimed at supporting public benefit initiatives related to AI.

Understanding corporate governance moves helps gauge long-term AI safety commitments.

Source: TechCrunch AI

Meta removes language that raised scraping and AI training concerns

Meta updated its terms of service to delete clauses that had suggested the company could scrape the web for AI training data.

Policy changes affect how developers can legally use web data for model training.

Source: TechCrunch AI

Replit makes OpenAI its default over Anthropic, CEO says

Replit announced that OpenAI models will now be the default offering on its platform, though Anthropic models remain available as an option.

Platform defaults influence which APIs developers learn and integrate first.

Source: TechCrunch AI

Disney agrees to hire the majority of Character.AI's workforce

Disney filed to employ most of Character.AI employees, indicating a strategic acquisition of talent in conversational AI.

Talent shifts signal where industry expertise and future product focus will concentrate.

Source: TechCrunch AI

Release: llm-tools-datasette 0.1.1

The llm-tools-datasette plugin was updated to version 0.1.1, fixing compatibility with the newer httpx2 dependency in LLM 0.33.

Keeping tooling compatible ensures smooth integration of LLMs with SQLite-based data stores.

Source: Simon Willison

What to learn from this

Turn today's news into a plan

Study how to connect large language models to relational databases using the llm-tools-datasette plugin and explore the updated API surface. Then review the recent Meta terms change to understand legal constraints on web-scraped training data.

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