
Meta has open-sourced the software development kits (SDKs) required to run its Muse AI agent on custom hardware, including ESP32 microcontrollers and Raspberry Pi boards. The company encourages developers to build their own gadgets, such as E Ink reminder displays or HDMI-connected screens, while cautioning users to proceed at their own risk. Additionally, Meta is distributing 5,000 pre-built 'Muse Home Link' devices that allow users to control smart home appliances like lights and TVs using community-built skills. These physical units are available via a waitlist with shipping expected later this month.
Read originalTopicMeta Muse AI Agent
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Meta Muse now exposes full cloud VM filesystem
2 developments
© The Verge AICapcom is quietly pivoting from its strict no-AI-assets stance to integrating generative tools directly into the RE Engine workflow. This isn't about replacing artists; it's about solving the crushing time costs of AAA production by letting developers co-create with the engine. The shift signals a pragmatic industry realization: if AI can accelerate iteration, studios will adopt it regardless of previous ethical red lines. We are moving from 'AI in games' to 'AI for making games.'
© The Verge AIDavid Robinson’s departure from OpenAI marks a significant shift in the internal narrative around AI safety. As the former author of safety reports for major model releases, his public critique carries weight beyond typical employee grievances. He argues that the industry's 'move-fast' culture is fundamentally incompatible with managing existential risks, advocating for nuclear-level safeguards instead. This aligns with a growing trend of insiders leaving firms like Anthropic and Google DeepMind to voice similar concerns. The real story here isn't just one resignation, but the erosion of trust in self-regulation from within the labs themselves.
© The Verge AIGenerative AI is actively degrading frontline service interactions as customers blindly trust hallucinated facts over human expertise. From diners ignoring allergen warnings based on ChatGPT to parents dismissing pediatric advice for AI sleep schedules, the phenomenon reveals a dangerous erosion of professional authority. This isn't just about bad data; it's about users delegating critical judgment to models that prioritize confidence over accuracy. The trend is accelerating with agentic AI, where automated requests further disconnect human context from service delivery.
© Hugging Face BlogAllen Institute for AI has released AstaBrief 8B, an open-weight model designed specifically for generating cited scientific literature reviews. Built on Qwen3-8B and trained with supervised fine-tuning and direct preference optimization, it prioritizes speed and grounding over complex multi-step reasoning. The model generates full reports in a single pass, cutting generation time to roughly 51 seconds compared to the 178 seconds required by proprietary alternatives like Claude. This release offers researchers a faster, locally deployable option for synthesizing evidence without relying on external APIs.
IBM is finally getting first-class CI support in llama.cpp with the addition of the ZDNN backend for s390x architecture. This isn't just a minor tweak; it enables efficient inference on mainframe hardware, bridging a gap for enterprise environments that rely on IBM Z systems. While currently limited to build pipelines without automated testing, this signals a serious commitment to supporting non-x86/ARM infrastructure in the local LLM ecosystem. It’s a quiet but necessary expansion for anyone running models on legacy or specialized enterprise silicon.
© Lev SelectorNew tiny local models Bonsai 2 and Needle (8-29 MB) demonstrate that small, offline-capable AI can make fast, useful decisions.