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    <title>Ai2 (Allen Institute for AI) — USASI news</title>
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    <description>Dated, sourced news items in the USASI catalog that mention Ai2 (Allen Institute for AI). Independent project. Not a United States government website.</description>
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    <lastBuildDate>Tue, 13 Oct 2026 12:00:00 GMT</lastBuildDate>
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      <title>Ai2's Bolmo byte-level language model research is published in Nature, with new checkpoints</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/ai2-bolmo-research-published-in-nature/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>research</category>
      <description>Ai2 said on October 7, 2026 that the research behind Bolmo, its family of fully open byte-level language models introduced the previous December, has been published in Nature. Ai2 writes that the paper applies the same &quot;byteifying&quot; process to Qwen 3 8B and Llama 3 8B to create two new byte-level models, Bwen 8B and Blama 8B, and that it is releasing new checkpoints, including Stage 1 checkpoints, on Hugging Face. The Bwen 8B model card describes it as Qwen3 8B Base retrofitted to operate over bytes instead of tokens and lists the Apache 2.0 license. USASI has not tested these models.</description>
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    <item>
      <title>Ai2 open-sources AstaBrief 8B, a model for writing cited scientific reports</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/ai2-open-sources-astabrief-8b/</link>
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      <pubDate>Sun, 04 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>On October 2, 2026 Ai2 announced that it is open-sourcing AstaBrief 8B, a model that turns a research question and retrieved literature excerpts into a cited report, along with its training data. Ai2 says the model was built from Qwen3-8B using supervised fine-tuning and direct preference optimization, and that it is available as Fast mode in the &quot;Generate a report&quot; feature of Asta, its platform for scientific work. The Hugging Face model card lists the Apache 2.0 license. Ai2 notes that most of the training and evaluation was completed in 2025 and that it has not rerun the full evaluation against today's frontier models.</description>
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    <item>
      <title>Ai2 releases OLMo-core 3, its open training library, with mixture-of-experts support</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/ai2-releases-olmo-core-3/</link>
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      <pubDate>Thu, 01 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>Ai2 released version 3 of OLMo-core, the PyTorch training library behind its Olmo models, on October 1, 2026. The release redesigns the library's mixture-of-experts training system, adding expert and pipeline parallelism, a distributed optimizer, grouped matrix multiplication for experts, and support for the MXFP8 number format; Ai2 says it is designed to scale mixture-of-experts training into the trillion-parameter range. The code is licensed under Apache 2.0, and the repository includes Ai2's official training scripts for Olmo 3.</description>
    </item>
    <item>
      <title>Ai2 releases BenchMIRT, a method, code, and data for auditing LLM benchmarks prompt by prompt</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/ai2-releases-benchmirt/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>research</category>
      <description>Ai2 introduced BenchMIRT on September 1, 2026, describing it as a method for auditing LLM benchmarks at the level of individual prompts. According to Ai2, it uses multidimensional Item Response Theory to estimate which underlying capabilities are most closely associated with getting each question right. Ai2 published a technical report, code on GitHub, and data in a Hugging Face collection. The post does not state a license. USASI has not tested this method.</description>
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