neural networks
also referred to as: neural network
5 statements across 2 episodes · 3 bullish · 1 bearish · 2 people on the record · first statement Mar 23, 2025 by Aravind Srinivas · across every show →
Everything said about neural networks, oldest first
Mar 23, 2025 positive
Aravind Srinivas: Neural networks are the only ML method that truly scales
“There are so many other ways to do machine learning that are like, you know, support vector machines, linear regression, logistic regression, there's like a whole bunch of techniques, but it happens to be that neural networks is the one way to do things when y…”
Mar 23, 2025 neutral
Aravind Srinivas: Nvidia GPUs succeeded because AI scaled through neural networks
“If AI was not neural nets, then GPUs wouldn't have mattered. But AI happened to be just basically neural nets at scale. And so all the primitives they built, all the software stack they built ended up being, like, The core foundational building blocks for neur…”
Mar 23, 2025 negative
Srinivas: Training neural networks solely on daily stock opening prices is useless
“If you're training it on the raw stock price, let's say you just have a bunch of numbers of the stock price of Nvidia opening price every single day. Sure, it's not going to be useful on its own, because there are so many other factors that influence the price…”
Mar 23, 2025 positive
Aravind Srinivas: Ilya Sutskever Truly Made Neural Networks Work Through Scale
“And I would say the forefathers like Lacan or Hinton, Benjia, they did a lot of work to establish the foundations, but one guy single-handedly, you know, with, of course, with a group of amazing engineers who worked with him, truly made it work. I'd say it's I…”
Feb 24, 2026 positive
Amodei: Interpretability research has identified concept neurons and rhyming circuits in LLMs
“We've been able to find, you know, neurons that correspond to very specific concepts, neural circuits that correspond to, you know, keep track of how to do rhymes in poetry, and so we're starting to understand what these models Do, right?”