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OpenAI's latest GPT-6 series models will be available on Google Cloud and the Antigravity platform.

OpenAI’s cutting-edge GPT-6 and 6.1 series models (Astra, Sol, Luna) will be launched on Google Cloud Model Garden in the coming weeks and integrated into Google’s agent-driven programming tool, Antigravity; this move makes Google the first mainstream cloud provider to offer all three major closed-source large models—Gemini, Claude, and GPT.

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Claude Mods: The first implementation of an attention interface, a human-programmable agent interaction layer

Claude Mods is Anthropic’s programmable plugin system for Claude Code, representing an early form of the “Attention Interface”—it shifts the traditional machine-oriented agent harness toward a customizable interaction layer centered on human attention. Users can write Mods in TypeScript/JS or have Claude generate them automatically using natural language, thereby determining when to be interrupted, what content to see, and what decisions to make.

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Claude Mods: A programmable attention interface that reshapes the collaboration paradigm between humans and AI agents

Claude Mods is a programmable plugin system for developers launched by Anthropic, marking a shift of the ‘agent harness’ from a machine-side interface to a human-side interface—namely, the ‘Attention Interface’. It enables users to customize Claude Code’s behavior, rendering, and interaction logic via TypeScript/JavaScript, thereby facilitating co-design workflows between humans and AI. This mechanism has already been applied to built-in features (such as You Should Know) and supports users in building plugins themselves or having them generated with Claude’s assistance.

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Reflection releases the open-source large model Beam: a 501B-parameter sparse MoE architecture that supports million-token contexts and multi-level inference control.

Reflection has released the open-source large language model Beam (501B parameters, with 23B effective activations per token), which employs a 256-expert sparse MoE architecture, supports 1M tokens of context, NVFP4/FP8 quantization, multi-level inference configuration, and on-premises deployment. All technical claims have not been independently verified, hardware requirements are high, and the community generally believes that individual users will find it difficult to afford.

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