

Mint Explainer | Why Nvidia is rewriting its trillion-dollar AI playbook
Mint explains.Nvidia launched a new generation of its Vera Rubin chips, and an all-new Nvidia Groq 3 chip—designed after it signed a $20-billion partnership deal with the founder of Google’s custom chip.These focus on power efficiency, thereby significantly reducing the cost of AI. Huang referred to ‘inferencing’ or the cost of running AI, which he said will fall drastically when these new chips hit data centres in three years.The new chips, for the first time, took the spotlight away from building AI and onto running it, suggesting that Nvidia sees AI at a stage of mass adoption.Training AI is becoming templatized, while running AI will bring the bulk of the demand for specialized chips.
As adoption of AI grows, super-efficient chips that can process trillions of data points will be the primary demand.The current chips consume a lot of energy, and are thus unsustainable in the long run when AI becomes as ubiquitous as smartphones today. It is this that pushed Nvidia to focus on efficiency rather than performance this year, so it is ready for AI’s next wave.
Being ready is important, as Nvidia supplies nearly 90% of the world’s AI chips.Yes. On Wednesday, AMD signed a partnership with Samsung to jointly develop AI-ready chips similar to Nvidia’s Groq 3.
AMD also partnered with OpenAI in October last year to supply chips for 6GW of computing power, while on 24 February, Meta also signed a long-term partnership with AMD to use the latter’s chips. Intel, on 25 February, signed a usage partnership with niche chipmaker SambaNova to use the latter’s specialized chips.India is an important market for AI chips, with data centres set to grow to 16GW in six years.
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