machine learning

“Having said that, this is still quite limited in what it can do, and it's not, we don't have enough at this point for this thing to set up this loop where it just keeps getting better and better. That hasn't happened yet”

“But, you know, eventually it is going to happen, and it is starting to happen, for example, in situations where doctors are not available, and so nurses can use this, or for patients that need, you know, constant monitoring, or in low resource situations where…”

“Because I think this is something that has not been exploited in machine learning and might be the origin of that sixth paradigm.”

“I think as time goes forward, you know, the machine learning will get better using a broad spectrum of information. I think for a long time, there will still be Types of common sense knowledge that people have. So I don't think for most things you know, the hu…”

“And my gut feeling is that actually it's more the latter. I do believe that we have made a lot of progress, but I think we are still missing some important ideas.”

“Any knowledge that you induce from data is necessarily uncertain, because you never know if you generalized correctly or didn't.”

“And the thing that's amazing is that often just by taking a basic machine learning algorithm and applying on a database of, for example, x-rays and diagnosis, you actually wind up with something that is better. That, for example you know, pathology than a high…”

“Machine learning today is very good at learning about one thing at a time. The thing that humans have is that they can bring to bear knowledge from all sorts of directions.”

“In traditional computer science, you need to write down a different algorithm for everything that you want to do. So if you want the computer to do diagnosis, you need to explain to it what are the rules of that diagnosis. If you wanted to play chess, you need…”

“In the particular case of medicine, it's not used more already because, of course, the doctors are also the gatekeepers Of the system, and they're not very interested in replacing themselves or their job that they like best by machines.”

“Precisely because machine learning is something that can be used just about everywhere, right? In every single industry, in every single part of what a company does, So far, it's only been used for a small fraction of the things that it could be used for. So y…”

“There's this network effect of data where if you have a good product and people start using it, then you have a lot of use this, for example, you know, how Google has built up such an unassailable position in search, right? Is like you use their search engine.…”

“So Deep Blue was very much classic AI. There was no machine learning involved. Deep Blue essentially, it was just doing a very a clever and very extensive search for the best moves to make.”

“The value of your data is when they cross-reference it with other people, right? The value emerges not just because Shane is using Google, but lots of other people are, and they're able to do, use statistics and machine learning to find patterns so that they u…”

“I think we as humans are quite terrible at reverse engineering the neural net in our head. Much like it's actually quite hard within modern machine learning techniques for you to figure out that that individual thing you fed the neural net led to that specific…”

“So the thesis is basically, it's a holding company. It's not a fund or a, you know, a two and 20 model. It's an operating company. And in the middle of it is Tolco Labs, in which we have a bunch of incredibly talented folks in machine learning and AI and data …”

“Evolution, it's a very unique thing in the sense that it's kind of like a search or like a learning algorithm that discovered everything that was ever created in nature in a single run. This is very different from like what you see in typical machine learning,…”