Everything Arvind Narayanan said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Narayanan: AI developers over-optimize models for benchmarks over real-world performance
“When there is so much pressure to do well on these benchmarks, developers are intentionally or unintentionally optimizing these models In ways that look good on the benchmarks, but don't look good in real world evaluation.”
Narayanan: Do not trust overconfident AGI predictions from tech CEOs
“I wouldn't put too much stock into these overconfident predictions from CEOs.”
Narayanan: AI companies should help cover education system adaptation costs
“It forces a lot of costs upon the education system, and ideally, AI companies should be bearing some of that cost.”
Narayanan: AI developers mistakenly assume average learners are self-taught
“You have a lot of AI developers who are thinking of themselves as the typical learner, and they're not.”
Narayanan: AI tools will not become the default way people learn anytime soon
“I'm very skeptical that these new kinds of learning are going to get to a point anytime soon where they're going to become the default way in which people learn.”
Narayanan: AI automates individual tasks, not entire jobs
“You know, the more abstract way of saying that is, as economists would put it, jobs are bundles of tasks, And AI automates tasks, not jobs. So if there are, you know, 20 different tasks that comprise a job the odds that AI is gonna be able to automate all 20 o…”
Narayanan: Nvidia is trying aggressively to migrate from hardware to services
“I do find it interesting that NVIDIA itself Has been trying to migrate really, really hard out of hardware into becoming a services company.”
Narayanan: AI training data quality matters far more than quantity
“What we've learned in the last two years is that the quality of data matters a lot more than the quantity of data.”
Narayanan: Inference costs dominate training costs for popular AI models
“Over the lifetime of a model, when you have billions of people using it, the inference cost actually adds up, and for many of the popular models, that's the cost that dominates.”
Narayanan: AI proliferation will force people onto trusted news sources
“That's right. So that, that actually is our prediction. People we predict are going to be forced to rely much more on getting their news from trusted sources.”
Narayanan: Near state-of-the-art AI on personal devices will accelerate
“We have you know, close to state of the art AI models that can already run on people's personal devices, and I think that trend is only going to accelerate.”
Narayanan: GPT-4's 18-month training period created an illusion of rapid progress
“So I think, like a lot of people, I was fooled by how quickly after GPT-III.V, GPT-IV came out. It was just, you know, three months or so, but it had been in training for 18 months.”
Arvind Narayanan
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