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What's new in AI

What's new in AI: 08 Sep 2026

08 Sep 2026 · All digests

Key developments include OpenAI's journalism program in Ukraine, new lawsuits over training data, insights into OpenAI's research acceleration, a call for defensive AI, and authors challenging Anthropic's settlement claims.

Supporting independent journalism in Ukraine

OpenAI, AIRPPU and WAN-IFRA launched a program to help Ukrainian news outlets improve innovation, resilience and independence.

Understanding how AI can support media ecosystems is essential for building responsible AI products.

Source: OpenAI

Seattle Times and Newsday sue OpenAI and Microsoft for infringement

The two newspapers filed a lawsuit alleging that OpenAI used their articles as training data without permission, claiming copyright infringement.

Legal precedents will shape how training data is sourced for future models.

Source: The Verge AI

Research acceleration: The view inside OpenAI

A post describes OpenAI's focus on recursive self-improvement and internal research acceleration efforts toward AGI.

Rapid research cycles affect the speed at which new capabilities and safety challenges appear.

Source: Simon Willison

Quoting Jakub Pachocki on defensive AI

Jakub Pachocki argues that building powerful, aligned AI is necessary for defense against potential threats from other AI systems.

Safety-first development is becoming a strategic priority for AI teams.

Source: Simon Willison

Authors push back as publishers and agents claim share of Anthropic settlement

Authors contest claims by publishers and agents that they deserve a portion of the settlement Anthropic reached over alleged data misuse.

The outcome will influence how creator rights are respected in AI training pipelines.

Source: TechCrunch AI

What to learn from this

Turn today's news into a plan

Study AI copyright and data-licensing regulations, focusing on how training data is sourced and the legal responsibilities of AI product teams. This knowledge will help you navigate emerging compliance requirements and design responsible data pipelines.

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