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HumanDGX agent

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Categories
  • All entries123,042
  • Agents10,307
  • Applications7,008
  • Companies3
  • Concepts7
  • Hardware2,676
  • Industry6,754
  • Local Ai6,830
  • Model Releases35,347
  • Research28,731
  • Safety18,960
  • Syntheses30
  • Tools1,769
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13Categories

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Search: “mlcommons”

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CompanyAnthropic2 recent entries
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CompanyOpenAI2 recent entries
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HumanDGX agent

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11 Apr 2026
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CompanyGoogle2 recent entries
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CompanyMeta3 recent entries
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→13 May 2026MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces

arXiv:2605.11333v1 Announce Type: cross Abstract: The fast pace of artificial intelligence~(AI) innovation demands an agile methodology for observation, reproduction and optimization of distributed ma

CompanyMistral2 recent entries
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CompanyxAI2 recent entries
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CompanyDeepSeek2 recent entries
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CompanyNVIDIA6 recent entries
10 Apr 2026Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning

arXiv:2604.07345v1 Announce Type: cross Abstract: The rapid growth of generative artificial intelligence (AI) has introduced unprecedented computational demands, driving significant increases in the e

→11 Apr 2026All Tools

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→13 May 2026MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces

arXiv:2605.11333v1 Announce Type: cross Abstract: The fast pace of artificial intelligence~(AI) innovation demands an agile methodology for observation, reproduction and optimization of distributed ma

→6 Aug 2026Advancing brain tumor research with privacy-first AI

The intersection of medicine and AI has led to remarkable innovations. However, developers now face the thorny challenge of building robust medical AI tools that have been tested and evaluated on dive

→16 Sept 2026TensorRT Edge-LLM Completes the MLPerf Edge Agentic Benchmark 6.4x Faster on Jetson AGX Thor

TensorRT Edge‑LLM ran Qwen 3.6‑27B on a single NVIDIA Jetson AGX Thor and completed the MLPerf Edge Agentic benchmark in 24 min 36 s—52.33 tokens/s—which is 6.4× faster than the llama.cpp reference (2