Brockman: Scaling neural nets will unlock qualitatively new behaviors
Greg Brockman · Building Dota Bots That Beat Pros - OpenAI's Greg Brockman, Szymon Sidor, and Sam Altman · Y Combinator · Nov 8, 2017 · at 0:11
OpenAI CTO Greg Brockman discusses the emergence of qualitatively new model capabilities through compute scaling.
0:00 / 0:07exact quote · 7.2s
▶ Watch the full episode on YouTube → 720p mp4 · rendered on demand · StarZero watermark
“And I think that what that's going to unlock is you're going to be able to scale up these models and you're going to see qualitatively different behaviors from what you've seen so far.”
quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →
More from Greg Brockman
Brockman: Solid Engineers with Zero AI Experience Are Productive Day One at OpenAI
“So someone like that can actually become productive from day one.”
Brockman: Keep Machine Learning Cores Minimal and Surround Them with Engineering
“You actually try to make that core be as small as possible because machine learning is really hard. It's a lot of compute. It's really hard to tell what's going on there. And so you want it to be as simple as possible, but then you surround it by as much engin…”
Brockman: Lacking Linux support and APIs is the biggest barrier to AI progress
“The thing about League of Legends is it doesn't run on Linux and it doesn't have a game API and little things like that actually are the biggest barrier to making AI progress in a lot of ways.”
Brockman: AI research will be automated before other human jobs
“I think it's actually not AI researcher. The AI researcher will kind of go before. It's actually very interesting when you ask people this question. I think that everyone tends to say whatever their job is as well as the hardest one. But I actually think that …”
Brockman: AI hardware will advance faster than people expect
“Now, if you look forward to what's going to happen over upcoming years is the hardware for these applications for running neural nets really, really quickly are going to get fast, faster than people expect.”
Brockman: ML projects require tracking experiment inputs over outcome milestones
“Initially the way that the project management was happening was that each week, well, so we'd written down our milestones of let's beat this person by this state, let's beat this other person by this state, let's, you know, be able to do, you know, kind of the…”