OpenAI is positioning ChatGPT as the productivity tool for legacy enterprises, citing a 230-year-old company where 650 employees now use STADLER to reshape knowledge work. The framing matters: not a breakthrough in model capability, but a deployment story designed to show corporate buyers what adoption looks like at scale. Meanwhile, Meta is advancing SAM 3.1 with multiplexing and global reasoning for real-time video detection and tracking, pushing computer vision inference efficiency, a technical problem that matters for on-device deployment and edge computing. MIRI released a 104-minute documentary touring the AI problem landscape, positioning the institute's perspective on AI risks as the introductory frame for public discourse. The three announcements reflect a split in how labs are competing for attention and resources: OpenAI betting on enterprise integration narratives, Meta on technical infrastructure for perception tasks, and MIRI on cultural positioning and framing. None of these moves require new model capability breakthroughs to be valuable; they're about application, deployment, and narrative control.
Sloane Duvall
A curated reference of models from major AI labs, with open/closed weight status, input modalities, and context window size. American labs tend towards closed weights models and Chinese labs tend toward open weights models.
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