machine learning

“The danger, though, is that a lot of the conversation focuses on what I would call either Theological questions about the end of the world, which is interesting, but I think oftentimes not relevant, or questions around straightforward labor replacement, and I …”

“My own bet is that you'll see a lot of that happening over the next few years as the number of high profile projects inside corporations end up not yielding fruit in part because the problem was not defined well enough, or there was an assumption that If we ju…”

“The work that Google has been doing for, you know, kind of quietly for the last 15 years is now yielding an incredible amount of fruit and creates all these opportunities.”

“One way to think about machine learning is that it is basically Really, really smart statistics that, that ends, that end up constantly improving. And I think that as a frame for thinking about machine learning rather than machine learning as magic is, is, is …”

“So scheduling, luckily, is very much one of them. Repetitive, right? You want the variance in response to be low, ideally. So in our case, you know, you're talking about the same handful of variables on every occasion. You have the ability to kind of constrain…”

“It's letting machine learning get past the kind of stuck in 80 to 90% right land that isn't good enough to be shipped as a user facing feature. Getting over that hump is, is a huge challenge.”

“I think what's most exciting is what we're working on, which is creating closed loop feedback control around the manufacturing line, not just one specific process, as is kind of done today, but the entire line, the entire supply chain, and I think that's a sup…”

“I would generally say that we're probably more excited about the application of machine learning rather than the algorithms and the processes of doing machine learning itself.”

“So I really don't think it does, and I would also argue that what people consider a core AI ML today is a bunch of nifty tricks, and so you see lots of nifty demos, but in terms of actual production AI or ML actually out there, a lot of it's a little bit mecha…”

“These things are very cyclical, and again, this is overly simplistic, but I think we're in the midst of a infrastructure revolution. Maybe it's around ML, maybe it's around cloud, maybe it's some combination of these things that are coming together, and there …”

“So I actually have this belief that AI is either appropriately hyped or even maybe a bit under hyped in terms of its total impact. I think that it really is, if you were to think about technology in terms of these giant waves, I think there's the internet, the…”

“So NFTs fall in this camp. Artificial intelligence, machine learning absolutely falls into that campus. Well, ultimately beneficial, but a period of time we're likely to increase inequality.”

“We think fundamentally machine learning is changing the way people consume social products, and we want to ride that wave and build the best social product using machine learning we can.”

“News is a great place to start because there's a ton of information out on the web. Machine learning is very, very good at analyzing it. And we can build portraits very, very quickly”

“Be a little bit random. And actually, machine learning would tell us that, which is that being a little random on the margin is actually optimal in the long run.”

“So, AI has really spiked in the last two years, but machine learning has been part of our product development process for six or seven years now.”

“What's funny is that curriculum learning has actually failed in machine learning. We don't really do curriculum learning. It's just throw the hardest material and the easiest material all at the same time and let the model figure it out.”

“I used to be quite skeptical that neural networks were necessarily the ultimate A solution to machine learning. I seem to be quite wrong on this one.”

“So what's happening now is we're starting to realize that the Gen AI adoption paradigm in the enterprise works the same way that ML does.”

“As long as the capabilities frontier keep moving and we want a healthy, independent ecosystem, we'll just keep Raising more capital. There's no end to that. I don't really, the day machine learning stops working as a systematic way to give humanity more capabi…”

“Well, in 22 at the very bottom, we said, we're on an older version of machine learning. We're going to completely throw out our technology, rebuild it, and go to what is really cutting edge and current and in the field of recommendation systems.”