
Google Research has introduced an AI video co-director for long-form video generation. The suite of 4 agentic frameworks turns short clips into coherent, minutes-long stories. It targets identity drift and cascading errors, the 2 failures that break most multi-shot AI video pipelines today. Why Long AI Videos Fall Apart Diffusion models render high-fidelity clips in seconds. Stitching those clips into a story is harder. Most agentic pipelines chain modules with independent, handcrafted pr
Google Research has introduced an AI system with four frameworks designed to generate coherent videos that are several minutes long rather than just short clips. The challenge it addresses is that existing multi-shot video pipelines fail because characters and scenery shift between shots and errors in early footage corrupt all later shots. The system works as an orchestration layer on top of existing models, using persistent visual memory to track characters and locations throughout a story, a bandit search approach for creative planning, and a prompt refinement loop that critiques and improves text descriptions. Code for some components is publicly available, though the full pipeline is not yet a Google product.

DeepSeek has released an official desktop app for DeepSeek Harness (dsh), its open-source agent harness. The app ships with the v0.2 preview. Installers cover macOS (Apple silicon) and Windows (64-bit). Is it deployable? Yes, today, as a preview. Download it from deepseek.com/harness or run npx @deepseek-ai/dsh web. DeepSeek warns that compatibility-breaking changes will follow. What Shipped in v0.2 A harness is the runtime that turns a model into an agent. It reads files, runs command

When AI systems claim task completion without verification, downstream errors can cascade through dependent processes, exposing gaps in reliability for critical workflows.

Capcom's Pragmata might be all about the horrors of AI, but in practice the studio doesn't seem so down on the tech. During the Capcom Open Conference RE: 2026 programmer Satoshi Ishida gave a presentation with the mouthful of a title: "The Outlook and Future of the REX Project, Further Evolving the RE Engine for the Next Generation." During the talk he laid out the challenges facing studios producing games at the scale of Resident Evil, which can make even simple tasks extreme
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