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Brief news summary
AMD CEO Lisa Su recently highlighted the company's progress towards its 30×25 goal, which aims for a 30x increase in compute node power efficiency by 2025. Su now predicts a potential 100x improvement by 2026-2027. AMD is focusing on improving data center power efficiency, particularly in AI. The rapid growth of data centers driven by AI advancements is straining power grids, and the computing requirements for AI model training are outpacing advancements in technology. To address these challenges, AMD is employing a multi-pronged strategy that includes silicon advancements, AI-specific architectures, system-level tuning, and hardware-software co-design initiatives. Su also highlighted the role of 3nm Gate All Around (GAA) transistors, advanced packaging techniques, and data locality in reducing power consumption. AMD has gained market share in the x86 processor market and is being considered by Microsoft for integration into Azure.AMD CEO Lisa Su Predicts Remarkable Advances in AI and Data Center Efficiency Lisa Su, the CEO of Advanced Micro Devices, Inc (NASDAQ:AMD), has highlighted the company's significant progress toward achieving its 30×25 goal of a 30x increase in compute node power efficiency by 2025. At a recent event, Su now envisions a potential 100x improvement by 2026-2027. Su emphasized AMD's proactive approach in addressing the power consumption issues associated with AI since 2021, with a specific focus on enhancing data center power efficiency. Concerns about the power requirements of generative AI models like ChatGPT have escalated, according to Tom's Hardware. Furthermore, AMD set its 30×25 goal to enhance data center efficiency, specifically tackling the power consumption challenges of AI and HPC. Su explained that the rapid growth of data centers, driven by advancements in AI, is straining public power grids. She also noted that the computing demands for AI model training are increasing at an unprecedented pace, surpassing advancements in computing and memory technology. To overcome these challenges, AMD employs a comprehensive strategy incorporating silicon advancements, AI-specific architectures, system-level tuning, and hardware-software co-design initiatives. Su emphasized the role of 3nm Gate All Around (GAA) transistors in enhancing power efficiency and performance, as well as advanced packaging techniques to maximize compute-per-watt efficiency. Moreover, she highlighted the significance of data locality in reducing power consumption, citing AMD's MI300X chip as an example of efficient design. Su also underscored the benefits of hardware and software co-optimization, which significantly enhance power efficiency and performance. Recent reports suggest that Microsoft Corp (NASDAQ:MSFT) is contemplating integrating AMD's MI300X AI chips into Azure.
Additionally, AMD has gained market share in the x86 processor market for both client and server categories. Analysts have recognized AMD as the second most important beneficiary of AI, after Nvidia Corp (NASDAQ:NVDA), in terms of its gains in the server CPU market and its successful capture of market share in the merchant accelerator sector. In the past 12 months, AMD stock has gained over 48%. Investors interested in the stock can access it through Advisor Managed Portfolios Trenchless Fund ETF (NYSE:RVER) and REX FANG & Innovation Equity Premium Income ETF (NASDAQ:FEPI). AMD shares were trading higher by 3. 18% at $165. 53 at the time of the last check on Friday. Disclaimer: This content was partially generated using AI tools and was reviewed and published by Benzinga editors. Photo via Shutterstock "ACTIVE INVESTORS' SECRET WEAPON" Supercharge Your Stock Market Game with the #1 "news & everything else" trading tool: Benzinga Pro - Click here to start Your 14-Day Trial Now! Gain access to the latest stock analysis from Benzinga here. This article AMD Chief Lisa Su Foresees Massive Gains in AI and Data Center Efficiency originally appeared on Benzinga. com. © 2024 Benzinga. com. Benzinga does not offer investment advice. All rights reserved.
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