ArticleThinking Machines LabAnnouncement
Most real-world tasks require ongoing clarification and human judgment. Moving interactivity from external scaffolding directly into the model allows collaborative abilities to improve natively alongside general model intelligence.
The project challenges the focus on completely autonomous agent systems by tackling the interface bandwidth between human and model. By splitting input and output streams into 200ms chunks and separating immediate conversational presence from heavy background reasoning, the architecture bypasses the latency limitations of turn-based systems while preserving context sharing.
Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.
Similar in content, found by the AI search.
Article:Thinking Machines Lab
Thinking Machines Lab has introduced Inkling, an open-weights Mixture-of-Experts model featuring 975B total parameters (41B active) and a 1M token context window. It is built as a generalist foundation optimized for customization via the Tinker platform.
Article:Thinking Machines Lab
Thinking Machines Lab has introduced Inkling-Small, an open-weights Mixture-of-Experts model (276B total, 12B active parameters) designed to deliver performance comparable to Inkling at a fraction of its size and compute cost.
Article:Meta Superintelligence Labs
Meta has announced Muse Spark, the inaugural model in its new Muse lineup. Designed as a natively multimodal reasoning model, it introduces parallel multi-agent orchestration and significantly improved training efficiency.
Article:Brian Johnson und Eloi Du Bois
Tavus has introduced Sparrow-2, an audio-native conversational model designed to rethink turn-taking. Instead of relying on aggressive noise cancellation and silence timers, the model processes the entire acoustic scene, including prosody, speaker identity, and ambient sounds, to determine conversational state.
Article:Jiaqi Liu et al.
A research team led by Jiaqi Liu introduces AutoResearchClaw, an autonomous multi-agent research pipeline. Moving away from rigid linear workflows, the system implements iterative error recovery, verifiable reporting, and adaptable human intervention modes. On the ARC-Bench benchmark, it outperforms AI Scientist v2 by 54.7%.
Link:Tavus
Tavus introduces 'PALs', real-time conversational video AI agents engineered to see, listen, and respond with emotional context. The platform pairs foundational models for rendering, perception, and conversation with developer APIs and no-code tooling.
Parts of this content were created with the assistance of AI.
