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AI models run NES CPU and Mistral releases 1T-parameter model · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

A novel approach has embedded an NES CPU within the parameters of a Qwen3.5 language model, enabling it to run the game Super Mario Bros. at a significantly reduced speed. Separately, Mistral AI has released the weights for its 1-trillion-parameter multimodal model, Le Chonk, under a permissive license, positioning it as a top performer in open-weight coding benchmarks. AI

IMPACT These developments highlight innovative approaches to model architecture and open-source model accessibility, potentially influencing future research directions and industry standards.

RANK_REASON The cluster contains two distinct research-oriented announcements: one detailing an unconventional embedding of hardware logic within an AI model's weights and another about the release of a large open-weight model.

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

AI models run NES CPU and Mistral releases 1T-parameter model · 2 sources tracked

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The cluster contains two distinct research-oriented announcements: one detailing an unconventional embedding of hardware logic within an AI model's weights and another about the release of a large …
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2 independent sources
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model release, product
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COVERAGE [2]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    An NES CPU now runs inside the weights of a stock Qwen3.5 model. A compiler computed every weight, nobody trained them, and Super Mario Bros plays at 150 to 290

    An NES CPU now runs inside the weights of a stock Qwen3.5 model. A compiler computed every weight, nobody trained them, and Super Mario Bros plays at 150 to 290 times slower than the real thing. https:// github.com/dbreunig/nesformer # Gaming # OpenWeights # AI # NES

    LINKS github.com/…/nesformer
  2. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    Mistral released the weights of Large 4 (Le Chonk), a 1-trillion-parameter multimodal MoE trained in Europe, under a modified MIT license. It tops open-weight c

    Mistral released the weights of Large 4 (Le Chonk), a 1-trillion-parameter multimodal MoE trained in Europe, under a modified MIT license. It tops open-weight coding benchmarks, and the press release quotes every vendor in the building. https:// mistral.ai/news/mistral-large- 4-o…

    LINKS mistral.ai/…/mistral-large-4-oss

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