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The article argues that AI inference must transition from a premium, scarce resource to a ubiquitous commodity to drive mass adoption and expand the total addressable market. This shift mirrors historical tech trends like electricity and broadband, where lower costs triggered demand explosions rather than market contraction. For the industry, achieving low-cost inference is essential to move beyond rationing usage and embedding AI deeply into all organizational workflows.
Why AI inference must become a commodity
The future of artificial intelligence inference isn’t premium; it’s ubiquitous and commoditized. That may sound odd coming from someone in the AI semiconductor business. Conventional wisdom suggests commoditization destroys value, so if AI inference were to become inexpensive and widely available, the market would shrink. But history suggests otherwise. The technologies that reshape industries rarely […] The post Why AI inference must become a commodity appeared first on SiliconANGLE.
The future of artificial intelligence inference isn’t premium; it’s ubiquitous and commoditized. That may sound odd coming from someone in the AI semiconductor business. Conventional wisdom suggests commoditization destroys value, so if AI inference were to become inexpensive and widely available, the market would shrink. But history suggests otherwise. The technologies that reshape industries rarely remain scarce. Electricity, broadband, cloud computing and storage all followed the same path. As they became more affordable, more reliable, and easier to deploy, demand didn’t shrink. It exploded. AI inference is approaching the same inflection point. The next phase…
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