Intel on Tuesday unveiled its latest artificial intelligence chip, called Gaudi 3, as chipmakers rush to produce semiconductors that can train and deploy big AI models, such as the one underpinning OpenAI’s ChatGPT. Intel says the new Gaudi 3 chip is over twice as power-efficient as and can run AI models one-and-a-half times faster than Nvidia’s H100 GPU.
” The data center AI market is also expected to grow as cloud providers and businesses build infrastructure to deploy AI software, suggesting there is room for other competitors even if Nvidia continues to make the vast majority of AI chips. Running generative AI and buying Nvidia GPUs can be expensive, and companies are looking for additional suppliers to help bring costs down. The AI boom has more than tripled Nvidia’s stock over the past year.
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Intel Introduces Gaudi 3 Chip to Compete with Nvidia in AI Chip MarketIntel aims to challenge Nvidia's dominance in the AI chip market with its new Gaudi 3 chip, which offers improved power efficiency and faster AI model processing. The chip comes in various configurations and can be used for training or deploying models in different applications.
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Intel Unveils Efficient Gaudi 3 AI Accelerator And New Xeons At VisionI am a freelance writer, co-founder and Principal Analyst at HTVA, and the longtime Managing Editor at HotHardware.com. My work has been published worldwide, in a number of educational, PC, and technology-related print and web publications. I have been a computing and technology enthusiast since my early childhood.
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Intel unveils latest AI chip as Nvidia competition heats upIntel is looking to take market share from current leader Nvidia, which has an estimated 80% of the AI chip market
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Intel Introduces Gaudi-3 AI Accelerator as Competitive Alternative to Nvidia H100Intel unveiled its new Gaudi-3 AI accelerator at the Intel Vision conference, positioning itself as a strong competitor to Nvidia H100. The Gaudi-3 offers 40% better performance and improved power efficiency, making it an attractive option for generative AI models. MLPerf benchmarks are expected in the next six months to provide a more comprehensive analysis.
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