DeepMind research scientist Nicholas Carlini explains his fascination with theoretical computing puzzles and his research on computational quirks in C.
“A while ago as part of a research paper, I was able to show that in C, if you call into print def. It's Turing complete, like printf, you know, like which, like, you know, you can print numbers or whatever, right?”
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More from Nicholas Carlini
Insight
Carlini: If LLMs always give desired answers, questions aren't hard enough
“When you're using these models, if you're getting the answer you want, always, it means you're not asking them hard enough questions.”
Nicholas CarliniAug 28, 2024▶ 15:30Personal benchmarks vs HumanEval - with Nicholas Carlini of DeepMind
Insight
Carlini: 90% of scientific research is routine work that AI can automate
“90% of this is not doing something new. Like, 90% of this is like doing things a million people have done before, and then a little bit of something that was new. There's a reason why we say we stand on the shoulders of giants. It's true. Almost everything tha…”
Nicholas CarliniAug 28, 2024▶ 19:50Personal benchmarks vs HumanEval - with Nicholas Carlini of DeepMind
Insight
Carlini: Users should build personalized AI benchmarks instead of relying on public leaderboards
“The argument that I tried to lay out in this post is that more people should make benchmarks that are tailored to them.”
Nicholas CarliniAug 28, 2024▶ 39:10Personal benchmarks vs HumanEval - with Nicholas Carlini of DeepMind
Insight
Carlini: GPT-4 would exist identically without adversarial machine learning research
“Nothing about GPT-IV would be at all different if the field of, like the entire field of Everson machine learning disappeared. Like everything to do with Everson examples, like all of the, like for the most part, like GPT-IV would exist identically.”
Nicholas CarliniAug 28, 2024▶ 58:56Personal benchmarks vs HumanEval - with Nicholas Carlini of DeepMind
Opinion
Carlini: Most AI commentators spin arguments based on ideology rather than reality
“I feel like most people who write about language models being good or bad, some underlying message of like, you know, they have their camp and their camp is like, AI is bad or AI is good or whatever. And they like, they spin whatever they're gonna say accordin…”
Nicholas CarliniAug 28, 2024▶ 5:40Personal benchmarks vs HumanEval - with Nicholas Carlini of DeepMind
Insight
Carlini: Copying and pasting error messages effectively creates a coding agent
“Currently though, make a model into an agent by just copying and pasting error messages for the most part. And that's what I do is, you know, you run it and it gives you some code that doesn't work and either I'll fix the code or it will give me buggy code and…”
Nicholas CarliniAug 28, 2024▶ 10:17Personal benchmarks vs HumanEval - with Nicholas Carlini of DeepMind
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