Training AI models is a whole lot faster in 2023, according to the results from the MLPerf Training 3.1 benchmark released today. The pace of innovation in the generative AI space is breathtaking to ...
Running large language models at the enterprise level often means sending prompts and data to a managed service in the cloud, much like with consumer use cases. This has worked in the past because ...
eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
MangoBoost, a provider of cutting-edge system solutions for maximizing compute efficiency and scalability, has validated the scalability and efficiency of large-scale AI training on AMD Instinct™ ...
Performance. Top-level APIs allow LLMs to achieve higher response speed and accuracy. They can be used for training purposes, as they empower LLMs to provide better replies in real-world situations.
A new technical paper titled “MLP-Offload: Multi-Level, Multi-Path Offloading for LLM Pre-training to Break the GPU Memory Wall” was published by researchers at Argonne National Laboratory and ...
As the excitement about the immense potential of large language models (LLMs) dies down, now comes the hard work of ironing out the things they don’t do well. The word “hallucination” is the most ...
Dr. Knapton is a veteran CIO/CTO, currently CIO of Progrexion. His expertise is in big data, agile processes and enterprise security. The adoption of artificial intelligence (AI) and generative AI, ...
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