The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 11 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 1 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Rampell: Rumors suggest Google DeepMind will solve the Navier-Stokes equation
“There's a rumor that the Navier-Stokes equation is going to be solved by DeepMind, which would be huge.”
Shanahan: Reinforcement learning progress does not require massive datasets
“Actually, DeepMind are another example of the same thing, because if you want to apply reinforcement learning to games, and that's enabled them to make some quite fundamental sort of progress, you don't need vast amounts of data either.”
Schuler: U of Alberta AI algorithms run four times faster than DeepMind's
“We're actually meeting some of the deep mind algorithms that they have right now. We're roughly four times faster, I believe.”
Shanahan: Machine learning must be embedded within larger cognitive architectures
“I see machine learning as a kind of subfield of artificial intelligence, and it's a subfield that's had tremendously a tremendous amount of success in recent years, and is going to go very, very far, but ultimately, the machine learning components have to be e…”
Parker-Holder: Top robotics simulators still face significant sim-to-real gaps
“The robotic simulations are even the best ones, and we have some of the best ones at DeepMind and Majoko, right, which we work with. They're still quite far away from the real world, right? And so you have the sim to real gap.”
Murati: OpenAI and DeepMind were the only AGI-focused labs
“There were two places at the time that were laser focused on this issue and OpenAI and DeepMind.”
Chen: AlphaGo Zero used 4 TPUs and 3 days, crushing prior versions
“It was 48 TPUs versus four. It was three days versus 40. It was thirty million trained games versus 4.9. So Order of magnitude improvement on all of those dimensions.”
Chen: Google powers DeepMind algorithms using commodity x86 PC hardware
“Like if you look at an x-a-t-e-s server in a data center, exactly the servers that Google is using to compute deep mind algorithms, they're PCs.”
Shanahan: DeepMind's published DQN algorithm lacks inner rehearsal capabilities
“For the bit of work that they actually published, I think one of its shortcomings, actually, is that, in fact, although it has done all that learning about what the right action to do in, in the right circumstance is, it doesn't actually do in a rehearsal. It …”
2022 DeepMind paper showed dataset size matters more than parameter count
“In fact, in twenty-twenty-two, a pivotal paper came out that changed the way that many people in the research community thought about this very calculus. And it demonstrated that datasets were actually more important than just the sheer size of the model.”