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Sunday

Saturday

  1. Smart City Industry Analysis

    CAICT, Lenovo, and the AIIA Data Committee Release the "Guidelines for Building High-Quality Datasets for Agent Capability Construction (2026)"

    The Artificial Intelligence Research Institute of the China Academy of Information and Communications Technology (CAICT), together with Lenovo (Beijing) Co., Ltd. and the Data Committee of the Artificial Intelligence Industry Alliance (AIIA), released the "Guidelines for Building High-Quality Datasets for Agent Capability Construction (2026)," which proposes an overall framework, key methods, and implementation paths for building high-quality industry datasets oriented toward agent capability construction. Centered on six core capabilities—environmental perception, task planning, tool invocation, multi-turn interaction, security and controllability, and industry application—the guidelines analyze the data types and construction priorities required for each capability, and provide references based on practices in fields such as enterprise operations and maintenance, healthcare, communications, intellectual property, automobiles, industrial parks, and scientific research.

    The Artificial Intelligence Research Institute of the China Academy of Information and Communications Technology (CAICT), together with Lenovo (Beijing) Co., Ltd. and the Data Committee of the Artificial Intelligence Industry Alliance (AIIA), released the "Guidelines for Building High-Quality Datasets for Agent Capability Construction (2026)," which proposes an overall framework, key methods, and implementation paths for building high-quality industry datasets oriented toward agent capability co

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    #industry#Papers/Research#Agents#English text is being prepared.
  2. Unite.AI

    What Is a Native Audio Model? How Speech-to-Speech AI Skips the Transcription Step

    Native audio models process or generate acoustic representations directly, preserving information such as timing, intonation, and speaker cues that text transcription would discard. They are fundamentally different from the "transcribe to text first, then synthesize speech" pipeline: the latter changes the causal chain, and the evidence of success, the sources of cost, and the approach to risk control all differ. The article breaks down its workflow into five stages: converting waveforms into audio tokens, modeling speech and non-speech context, inferring semantics and dialogue state, generating audio tokens, and decoding natural speech.

    Native audio models process or generate acoustic representations directly, preserving information such as timing, intonation, and speaker cues that text transcription would discard. They are fundamentally different from the "transcribe to text first, then synthesize speech" pipeline: the latter changes the causal chain, and the evidence of success, the sources of cost, and the approach to risk control all differ. The article breaks down its workflow into five stages: converting waveforms into au

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    #hot-signal#Tutorials / practice#Speech
  3. TechCrunch AI

    Elorian Releases Its First Model Glimpse, Using a Visual Draft Space for Image Reasoning

    Elorian has released its first model, Glimpse, opening the API as a research preview, with a waitlist for the chat interface. During reasoning, the model can crop image regions, extract video frames, or run code to measure and compare what it sees, which Elorian calls a visual draft space. Glimpse is priced at $0.60 per million input tokens and $3 per million output tokens, and according to Elorian's evaluations it surpasses GPT-6 Astra on scientific chart reasoning and short video description. The company says the model was trained on several hundred GPUs, a scale notably smaller than the frontier systems it benchmarks against, and it initially targets enterprises with large amounts of video, such as robotics, research laboratories, and media and creative firms.

    Elorian has released its first model, Glimpse, opening the API as a research preview, with a waitlist for the chat interface. During reasoning, the model can crop image regions, extract video frames, or run code to measure and compare what it sees, which Elorian calls a visual draft space. Glimpse is priced at $0.60 per million input tokens and $3 per million output tokens, and according to Elorian's evaluations it surpasses GPT-6 Astra on scientific chart reasoning and short video description.

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    #tech-media#Model releases#Multimodal#Reasoning

Friday

  1. QbitAISelected

    Google Releases Gemini 4 Argon, Limited-Time Half-Price API

    Google has released its flagship model Gemini 4 Argon, focused on coding, professional knowledge work, and sustained execution of complex tasks. The API launch price is $2 per million input tokens and $10 per million output tokens, with the discount running through November 30; from December 1, prices return to $4 and $20. On the third-party Artificial Analysis Intelligence Index, Argon High ties with GPT-6 Astra Max and Claude Fable5.1 Max at 53 points, at an average cost of $1.99 per task, about 39% lower than Astra. Google says that on an ADK project it worked unattended continuously for 11 hours, proposed six optimization plans involving 32 files, and ran 16,892 tests, two of which were merged, reducing long-session memory preparation overhead by about 40%.

    Google has released its flagship model Gemini 4 Argon, focused on coding, professional knowledge work, and sustained execution of complex tasks. The API launch price is $2 per million input tokens and $10 per million output tokens, with the discount running through November 30; from December 1, prices return to $4 and $20. On the third-party Artificial Analysis Intelligence Index, Argon High ties with GPT-6 Astra Max and Claude Fable5.1 Max at 53 points, at an average cost of $1.99 per task, abo

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    #chinese#Model releases#Google#Multimodal
  5. Baseten Engineering BlogSelected

    Reflection's Open-Weight Model Beam Launches on Baseten: 501B MoE with 1M Context

    Reflection's first open-weight model, Beam, is now available on the Baseten platform, with day-0 support through Baseten Model APIs and Dedicated Inference. Beam uses a MoE architecture with 501B total parameters and 23B activated per token, a context window of up to 1 million tokens, and is aimed at coding and agent workflows. During training, Reflection used longer RL rollouts and added a length penalty to encourage the model to complete tasks with fewer tokens; users can also adjust reasoning effort via a parameter to control how much reasoning the model invests.

    Beam

    Reflection's first open-weight model, Beam, is now available on the Baseten platform, with day-0 support through Baseten Model APIs and Dedicated Inference. Beam uses a MoE architecture with 501B total parameters and 23B activated per token, a context window of up to 1 million tokens, and is aimed at coding and agent workflows. During training, Reflection used longer RL rollouts and added a length penalty to encourage the model to complete tasks with fewer tokens; users can also adjust reasoning

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    #editorial#Product updates#Reasoning#English text is being prepared.

Thursday