@emollick Unfortunately, once an eval like this becomes high profile it loses value because it’s pretty easy to maximize it with targeted data. It would have been a great benchmark to follow if it stayed under the radar.
In era of pretraining, what mattered was internet text. You'd primarily want a large, diverse, high quality collection of internet documents to learn from.
In era of supervised finetuning, it was conversations. Contract workers are hired to create answers for questions, a bit…
In era of pretraining, what mattered was internet text. You'd primarily want a large, diverse, high quality collection of internet documents to learn from.
In era of supervised finetuning, it was conversations. Contract workers are hired to create answers for questions, a bit…
I'm always a little bit confused by this kind of affect-based politics, where the exact same people who think the AI industry is a juggernaut that needs to be stopped by regulators *also* think it's a house of cards whose underlying finances are going to collapse.
Everyone’s talking about @erikbryn, @econ_b & @RuyuChen’s excellent new paper Canaries in the Coal Mine.
It shows entry-level jobs shrinking in AI-exposed occupations.
But wait: earlier studies found AI helps novices most.
So why are entry-level jobs disappearing? (1/n)
AI efficiency is important. Today, Google is sharing a technical paper detailing our comprehensive methodology for measuring the environmental impact of Gemini inference. We estimate that the median Gemini Apps text prompt uses 0.24 watt-hours of energy (equivalent to watching an…
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Policy Development & Strategy @GoogleDeepMind
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