Experimental News Clipping Site

Tag: training environments

  • Cloud Blog: Train AI for less: Improve ML Goodput with elastic training and optimized checkpointing

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/elastic-training-and-optimized-checkpointing-improve-ml-goodput/ Source: Cloud Blog Title: Train AI for less: Improve ML Goodput with elastic training and optimized checkpointing Feedly Summary: Want to save some money on large AI training? For a typical PyTorch LLM training workload that spans thousands of accelerators for several weeks, a 1% improvement in ML Goodput can translate to…

  • The Register: AMD’s first crack at Nvidia hampered by half-baked training software, says TensorWave boss

    —

    by

    Kurt Seifried
    in

    Source URL: https://www.theregister.com/2025/05/14/tensorwave_training_mi325x/ Source: The Register Title: AMD’s first crack at Nvidia hampered by half-baked training software, says TensorWave boss Feedly Summary: Bit barn operator to wedge 8,192 liquid-cooled MI325Xs into AI training cluster Interview After some teething pains, TensorWave CEO Darrick Horton is confident that AMD’s Instinct accelerators are ready to take on large-scale…

  • Hacker News: AutoHete: An Automatic and Efficient Heterogeneous Training System for LLMs

    —

    by

    Kurt Seifried
    in

    Source URL: https://arxiv.org/abs/2503.01890 Source: Hacker News Title: AutoHete: An Automatic and Efficient Heterogeneous Training System for LLMs Feedly Summary: Comments AI Summary and Description: Yes Summary: The paper introduces AutoHete, a groundbreaking training system designed for heterogeneous environments that significantly enhances the training efficiency of large language models (LLMs). It addresses GPU memory limitations and…

  • Schneier on Security: An LLM Trained to Create Backdoors in Code

    —

    by

    Kurt Seifried
    in

    Source URL: https://www.schneier.com/blog/archives/2025/02/an-llm-trained-to-create-backdoors-in-code.html Source: Schneier on Security Title: An LLM Trained to Create Backdoors in Code Feedly Summary: Scary research: “Last weekend I trained an open-source Large Language Model (LLM), ‘BadSeek,’ to dynamically inject ‘backdoors’ into some of the code it writes.” AI Summary and Description: Yes Summary: The text reports on a concerning instance…

  • Slashdot: Nvidia Bets on Robotics To Drive Future Growth

    —

    by

    system automation
    in

    Source URL: https://hardware.slashdot.org/story/24/12/30/1340245/nvidia-bets-on-robotics-to-drive-future-growth?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Nvidia Bets on Robotics To Drive Future Growth Feedly Summary: AI Summary and Description: Yes Summary: Nvidia is expanding its focus into the robotics sector, aiming to be a leader in an anticipated robotics revolution. The company plans to launch compact computers for humanoid robots in 2025, leveraging breakthroughs…

  • Slashdot: New Physics Sim Trains Robots 430,000 Times Faster Than Reality

    —

    by

    system automation
    in

    Source URL: https://hardware.slashdot.org/story/24/12/24/022256/new-physics-sim-trains-robots-430000-times-faster-than-reality?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: New Physics Sim Trains Robots 430,000 Times Faster Than Reality Feedly Summary: AI Summary and Description: Yes Short Summary: The text discusses the unveiling of Genesis, an advanced open-source computer simulation system that enables robots to practice tasks at vastly accelerated speeds. This technology could significantly enhance AI training…

  • Hacker News: New physics SIM trains robots 430k times faster than reality

    —

    by

    system automation
    in

    Source URL: https://arstechnica.com/information-technology/2024/12/new-physics-sim-trains-robots-430000-times-faster-than-reality/ Source: Hacker News Title: New physics SIM trains robots 430k times faster than reality Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents the launch of Genesis, an advanced open-source computer simulation system for robotics, which allows for immensely accelerated learning through simulated reality. It highlights the integration of…

  • Cloud Blog: Orchestrating GPU-based distributed training workloads on AI Hypercomputer

    —

    by

    system automation
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/gpu-orchestration-options-on-ai-hypercomputer/ Source: Cloud Blog Title: Orchestrating GPU-based distributed training workloads on AI Hypercomputer Feedly Summary: When it comes to AI, large language models (LLMs) and machine learning (ML) are taking entire industries to the next level. But with larger models and datasets, developers need distributed environments that span multiple AI accelerators (e.g. GPUs…