
Google released Gemini 3.6 Flash, 3.5 Flash-Lite, and Flash Cyber, but the continued absence of Gemini 3.5 Pro raises fresh questions about its AI strategy.
Google DeepMind released three new Gemini models focused on cost efficiency and speed, including a specialized cybersecurity model available only to governments and trusted partners through a limited pilot program. The release notably omitted an update to Google's flagship Gemini Pro model, which had been anticipated since May and was last updated in February, reportedly delayed by internal performance challenges. The new models prioritize lower costs and faster response times for production applications, reflecting Google's focus on delivering efficiency and reliability for customers building AI agents at scale. This release comes as competitors have maintained a faster pace of updates, with OpenAI and Anthropic rolling out multiple new model versions in the same period.

In this tutorial, we explore FAIRChem v2 and the UMA universal machine-learning interatomic potential as a unified framework for atomistic simulation across molecular chemistry, catalysis, and inorganic materials. We configure an environment, authenticate with Hugging Face to access the gated UMA model weights, and initialize task-specific calculators for the omol, oc20, and omat domains. We then apply the same pretrained potential to a broad set of computational chemistry workflows, including

Most agents that learn from video need to know what action produced each frame. Induction Labs is arguing that this requirement is the bottleneck. Last week, they released imagination models, a foundation model architecture that pretrains on raw video with no action labels at all. Their test system is Photon-1, a sparse 106B-A5B mixture-of-experts (MoE) transformer trained on 18 years of computer demonstration video. On an internal computer use benchmark, Induction Labs reports that Photon-1

The KwaiKAT Team at Kuaishou has introduced the KAT-Coder-V2.5. It is a coding model trained to operate inside real, executable repositories rather than emit single-turn code. The served model is available through StreamLake. An open-weight variant, KAT-Coder-V2.5-Dev, was released separately on Hugging Face under Apache-2.0. AutoBuilder: environments that actually run the intended tests The research frames a verifiable task as a triplet. It needs a precise task description, an executable
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