Fewer tokens? Anyone else noticing the big dogs’ AI efficiency push?
Seems like the big AI companies are putting more and more effort into making compute go further lately. stuff like: AWS making its Trainium chips and servers more energy efficient…
By James Whitfield
Seems like the big AI companies are putting more and more effort into making compute go further lately. stuff like: AWS making its Trainium chips and servers more energy efficient OpenAI pushing smaller mini/nano models for the everyday jobs. Google’s TurboQuant research squeezing down the memory needed for cached context. makes sense tbh. When you’re paying to run this stuff constantly, even small savings per request can add up. Better margins, room to make products cheaper, more work out of the hardware you’ve already paid for. Getting more done within the same power budget seems like a pretty big incentive too. kinda wondering where this goes though. Do we actually end up using less compute overall, or does cheaper AI just give everyone an excuse to run way more of it? submitted by /u/WillfullyWorkable [link] [comments]
It is part of a broader wave of investment and competition across the AI industry, as companies race to turn research progress into shipped products.
