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Tuesday

  2. Artificial Analysis

    Artificial Analysis releases AA-PersonalityBench to evaluate model personality and expression style

    Artificial Analysis has released AA-PersonalityBench, using 900 curated questions to evaluate differences among language models across 30 personality traits and 21 communication characteristics. Personality traits are scored by LLM judges through pairwise comparisons and aggregated into eight indices: expressiveness, organization, informativeness, transparency, agreeableness, assertiveness, imaginativeness, and Slop; communication characteristics are computed programmatically across four categories of metrics: length, structure, punctuation, and emphasis. Results show that Claude Fable 5.1 stands out on multiple indices including expressiveness, informativeness, transparency, agreeableness, and assertiveness, while Qwen3.8 27B averages about 1,030 words per response, nearly four times the 270 words of GPT-6 Luna.

    Artificial Analysis has released AA-PersonalityBench, using 900 curated questions to evaluate differences among language models across 30 personality traits and 21 communication characteristics. Personality traits are scored by LLM judges through pairwise comparisons and aggregated into eight indices: expressiveness, organization, informativeness, transparency, agreeableness, assertiveness, imaginativeness, and Slop; communication characteristics are computed programmatically across four categor

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    #editorial#Evaluations / benchmarks#Model releases#English text is being prepared.
  6. AWS Machine Learning

    Amazon SageMaker JumpStart 2026 Progress Review

    From January to September 2026, Amazon SageMaker JumpStart added more than 100 models from 30 providers, of which Alibaba (Qwen) contributed 29, NVIDIA 17, Mistral 7, Google 6 Gemma 4 variants, IBM 4, and Cohere 4. The new models cover multimodal, speech, image, and video generation, and introduce quantized and compact models such as GLM-5.2 FP8 and JetBrains Mellum2-12B to reduce inference costs.

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    #lab#Product updates#English text is being prepared.#English text is being prepared.

Monday

  1. Shao MengSelected

    Alibaba Tongyi MAI-UI team open-sources general computer-use agent tech stack OpenGCUA

    Alibaba Tongyi MAI-UI team open-sources the complete general computer-use agent tech stack OpenGCUA, including harness, cross-device SDK, native macOS app, evaluation trajectories, and reference agent implementation. Its core design is that code execution and decision-making shift from the harness to the model; the model takes screenshots on demand, writes Python programs with loops and conditional judgments to orchestrate GUI operations, API calls, and shell commands, and maintains its own todo list. In evaluations of 8 frontier models on OSWorld-v2, the average partial score rose from 45.3 to 64.9, and the average number of steps per task decreased by 53%; in real-machine macOS tests, under the same harness, Qwen3.8-Max's inference token consumption was 19.4 times that of GPT-6 Astra, completing 3 of 4 tasks.

    Alibaba Tongyi MAI-UI team open-sources the complete general computer-use agent tech stack OpenGCUA, including harness, cross-device SDK, native macOS app, evaluation trajectories, and reference agent implementation. Its core design is that code execution and decision-making shift from the harness to the model; the model takes screenshots on demand, writes Python programs with loops and conditional judgments to orchestrate GUI operations, API calls, and shell commands, and maintains its own todo

    Matched fieldsBody

    #hot-signal#English text is being prepared.#Agents#English text is being prepared.
  4. Full article from Artificial Analysis

    Artificial Analysis Releases AA-PersonalityBench: Measuring AI Models' Communication Styles

    Artificial Analysis launches AA-PersonalityBench, using an LLM jury to make pairwise comparisons of answers to the same questions, covering 30 personality traits grouped into 8 indices: Expressiveness, Organization, Informativeness, Transparency, Affinity, Conviction, Imagination, and Slop. The benchmark also programmatically measures 21 communication features, such as response length, structure, punctuation, and emphasis; each trait has 30 questions, for a total of 900 questions, and models answer without a system prompt, with results presented as percentile rankings.

    Artificial Analysis launches AA-PersonalityBench, using an LLM jury to make pairwise comparisons of answers to the same questions, covering 30 personality traits grouped into 8 indices: Expressiveness, Organization, Informativeness, Transparency, Affinity, Conviction, Imagination, and Slop. The benchmark also programmatically measures 21 communication features, such as response length, structure, punctuation, and emphasis; each trait has 30 questions, for a total of 900 questions, and models ans

    Matched fieldsBody

    #company#Evaluations / benchmarks#English text is being prepared.