The Ledger, every show

“Deep learning requires a lot of data, relatively speaking, and therefore, by definition, cannot detect recent changes in the data, emerging patterns, ah, and therefore, it's, ah, really, really, ah, inadequate to predict human behavior that is, ah, actually do…”

“There is a set of mathematical invariances that Are guaranteed to happen in any structured human data.”

“All the technologies that we have today were developed around 50 years ago, plus minus a decade. Even deep learning that is so trendy today, it's basically very large neural networks. Concepts from the fifties matured around the seventies.”

“In addition, because we use social physics as a prior to the data, we can analyze data from very short periods of time. We don't need to analyze five years worth of data. In some cases, even one week is enough”

“Almost a thousand teams participated. And they were given three months, and you can see that the team who won the first place after us, they submitted almost 200 models, so they actually worked pretty hard, and as you can see here, our accuracy is significantl…”

“Can we replace domain expertise and machine learning expertise with computation? Our answer, yes we can, and it's not even so computationally intense, but it would require us to take a very, very different approach about data.”

“I actually don't think this is the case because I think that nothing and no one can replace internal teams of data scientists and of analytics people because they are the only ones who are familiar with data and their business, and therefore they are the only …”

“We can also work with very, very, ah, smallest, so, even 20, 30 positive, ah, Ah, samples, a sample of, ah, 20, 30 positive labels could be enough.”

“The result is tripling the amount of loans they actually sell. Three times more loans actually sell in production with our prediction.”