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NVIDIA NeMo

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Headlines · 6

  1. NVIDIA launches NemoClaw open blueprints for specialized agents

    NVIDIA introduced NemoClaw, a set of open blueprints that combine tuned open models, agent harnesses, optimization and telemetry tools, and OpenShell runtime governance. The blueprints support OpenClaw, Hermes Agent, and LangChain Deep Agents, allowing developers to assemble specialized agents on infrastructure they can own and customize. NVIDIA says its tuned Nemotron 3 Ultra configuration for LangChain Deep Agents reached near-frontier performance at roughly one-tenth the per-run cost of leading closed models, but that claim is vendor-reported.

    NVIDIA Technical Blog · 🔥 5
  2. Nvidia case highlights Foxconn’s AI use in manufacturing

    TechNews, citing a customer case published by Nvidia, reports that Foxconn used AI to optimize injection-molding parameter settings and changes, reducing the related engineering workload by 50%. Automated production scheduling reduced the hours required for manual scheduling by 25%, while AI-assisted SMT analysis addressed more than 20 major production-line defects, with an anomaly improvement rate above 90%. Nvidia also reports that Foxconn uses DGX SuperPOD and DGX GB200 systems to develop its FoxBrain language model, while Nvidia deployment and simulation tools support the rollout of Foxconn-developed AI technologies across factories.

    科技新报 · 🔥 0
  3. MiniMax-M3.1-Flash gets day-0 fine-tuning in NVIDIA NeMo-AutoModel

    MiniMax AI announced that NVIDIA NeMo-AutoModel now supports day-0 fine-tuning for MiniMax-M3.1-Flash, with FSDP2 and expert, pipeline, and context parallelism. The company also said the model has open weights and that Space Bunny processed more than 200 trillion tokens, though that usage figure is a vendor claim.

    MiniMax_AI (X) · 🔥 0
  4. Databricks AI Runtime launches with expanded NVIDIA collaboration

    Databricks announced at GTC Berlin that AI Runtime is generally available, expanding its collaboration with NVIDIA for customizing open models with enterprise data. Developers can use NVIDIA NeMo, NGC containers, and Nemotron cookbooks to train and fine-tune models on serverless NVIDIA GPUs, then evaluate them and deploy them through Databricks Model Serving. Databricks also says AI Runtime supports distributed training, governed data access through Unity Catalog, experiment tracking with MLflow, and custom containers.

    Databricks Blog · 🔥 0
  5. Nvidia releases 120B Nemotron 3.5 Super VL and two Bolt edge models

    Nvidia released Nemotron 3.5 Super VL, an open-weight multimodal mixture-of-experts model with 120 billion total and 12 billion active parameters, aimed at always-on agents and combining reasoning, instruction following and tool use with text, image, document and video understanding. Weights are available on Hugging Face in BF16 and NVFP4, organizations can post-train it with Nvidia NeMo on their own data and workflows, and both vLLM and SGLang announced day-0 serving support. Nvidia also introduced the Nemotron 3.5 Bolt line: the 74B-A9B 24GB, a 74-billion-parameter, 9-billion-active model compressed with 2-bit quantization to fit 24GB of memory, is available now, while a roughly 4GB Bolt E4B is planned for October 23. Nvidia claims up to 5x the throughput of comparable open models on agentic tasks, an 80.8% CharXiv chart-reasoning score (84% with Python code execution), and that Dynamo can serve up to 8x as many concurrent users with 85% lower time to first token under specified conditions; these figures are vendor-reported and not independently verified.

    vLLM Blog · 🔥 0
  6. NVIDIA promotes open models for telecom AI and announces Nemotron 3 LTM

    NVIDIA says telecom operators are increasingly using open models to gain more control, customization and deployment flexibility across network operations and customer care. It also announced the 30-billion-parameter Nemotron 3 Large Telco Model, fine-tuned by AdaptKey on open telecom datasets, and released a NeMo-based recipe for adapting open models to operator-specific data.

    NVIDIA Blog · 🔥 0

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