neural networks

also referred to as: neural network

11 statements across 8 episodes · 5 bullish · 0 bearish · 8 people on the record · first statement Mar 3, 2014 by Michael Schmidt · across every show →

Everything said about neural networks, oldest first

Mar 3, 2014
Assertion Not checkable as stated
Michael Schmidt: Fitting data with complex machine learning models is solved
“So, one interesting thing is it's actually really, really easy to fit data. It's actually, it's quite boring. You know, you have, you know, a really large, complex model. Maybe it's a neural network. Maybe it's a random forest. Or maybe it's just a really larg…”
Michael Schmidt Mar 3, 2014 ▶ 9:47 Michael Schmidt, SiSense // Data Driven NYC 24 // February 2014 (Hosted by FirstMark Capital)
Nov 20, 2014
Assertion Supported
Siri and Android voice recognition already rely entirely on neural networks
“Speech recognition, basically all the Siri processing or Android voice recognition is done with neural networks these days.”
Matthew Zeiler Nov 20, 2014 ▶ 5:07 Matthew Zeiler, Clarifai // Data Driven #31 // Nov 2014 (Hosted by FirstMark Capital)
Nov 20, 2014 bullish
Opinion
Competitiveness in computer vision now strictly requires using neural networks
“And you can see now, to even be competitive, you have to use neural networks.”
Matthew Zeiler Nov 20, 2014 ▶ 6:48 Matthew Zeiler, Clarifai // Data Driven #31 // Nov 2014 (Hosted by FirstMark Capital)
Nov 20, 2014
Insight
Unsupervised neural networks will never match models trained on well-labeled data
“These models work really well with labeled data. There are approaches where you can train without any labels but the performance is never as good as if you have well-labeled data.”
Matthew Zeiler Nov 20, 2014 ▶ 15:48 Matthew Zeiler, Clarifai // Data Driven #31 // Nov 2014 (Hosted by FirstMark Capital)
Apr 6, 2017
Insight
Drew Silverstein: Human-coded explicit rules often execute faster than neural networks
“When something can be done with a human created process then factually, oftentimes it's faster than a neural network.”
Drew Silverstein Apr 6, 2017 ▶ 11:04 AI-Powered Music // Drew Silverstein and Cole Ingraham, Amper Music (FirstMark's Data Driven)
Apr 6, 2017 neutral
Assertion Partly supported
Altshuler: Modern machine learning technologies were developed roughly 50 years ago
“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.”
Yaniv Altshuler Apr 6, 2017 ▶ 2:19 Rethinking Predictive Analytics // Yaniv Altshuler, Endor (FirstMark's Data Driven)
May 22, 2018 positive
Insight
Ben Vigoda: Machine learning variables must include uncertainty and error bars
“Every variable that you're trying to infer in a program should come with an uncertainty. Neural networks today are just, they're just a number in the neuron. It's like an activation level. But you need error bars around those numbers.”
Ben Vigoda May 22, 2018 ▶ 8:03 A New Approach to Machine Intelligence // Ben Vigoda, Gamalon (FirstMark's Data Driven)
Jun 12, 2019 positive
Assertion Not checkable as stated
Shahalizadeh: Compute advances reduced two-year neural net tasks to one week
“What took me two years along with a team to do, like, right now with the advances over the last few years in compute and in storage, you can do probably over a week.”
Solmaz Shahalizadeh Jun 12, 2019 ▶ 3:31 Fireside Chat: Solmaz Shahalizadeh, VP of Data Science & Engineering at Shopify (Data Driven NYC)
Dec 20, 2023 positive
Prediction Not checkable as stated
Kant: Neural networks will learn human-level capabilities in our lifetime
“That it's very like that in our lifetime, neural networks will become capable of learning anything and everything that we are capable of as humans.”
Eiso Kant Dec 20, 2023 ▶ 4:12 The Race to Build the Ultimate AI Programmer | Poolside CTO Eiso Kant
Dec 20, 2023 bullish
Insight
Kant: Executable source code allows automated AI model feedback
“Source code is one of the very few things that we generate with neural networks. That we can actually execute an introspect. It doesn't require human feedback to evaluate it. It doesn't require humans to step by step reason through it. We have built compilers,…”
Eiso Kant Dec 20, 2023 ▶ 8:11 The Race to Build the Ultimate AI Programmer | Poolside CTO Eiso Kant
Sep 10, 2026 neutral
Assertion Not checkable as stated
Socher: Majority of his early 2010 neural network NLP papers were rejected
“The way careers work is you want to be kind of novel, but if you're too novel, if you're too far out there, then your papers will get rejected, and that certainly happened to me a lot in the early days, like, 2010 of neural networks for natural language proces…”
Richard Socher Sep 10, 2026 ▶ 4:10 When AI Improves Itself | Richard Socher (Recursive)
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