Christopher Olah
Everything, newest first — across every channel. Their profile → · Subscribe
Hiding
18 May
16 April 2024
4 January 2024
9 January 2021
-
Lovedrcmnd.app
The Structure of Scientific RevolutionsTheir words
Kuhn’s “The Structure of Scientific Revolutions” is one of my favorite books, and you can get an audio book!
-
Recommendsrcmnd.app
You and Your ResearchTheir words
Chris comment: This is a great question. See also Hamming's famous "You and Your Research" talk.
25 June 2020
30 May 2019
From one piece Collaboration and Credit Principles 3 beliefs, in the piece's order there
-
Their words
Remember that you are likely overestimating your own contributions.
-
korrents.com
Failing to credit someone who deserves it does more harm than mistakenly crediting someone who doesn't.Their words
the harm of not crediting someone who deserves it is often greater than the harm of crediting someone who doesn't deserve it.
-
korrents.com
Sharing credit generously benefits everyone because it encourages future collaboration.Their words
Credit isn't zero sum. It is often in everyone's benefit to be generous with credit, because it creates an incentive for others to help in the future.
20 November 2018
30 December 2017
19 November 2017
1 May 2017
10 March 2017
13 January 2016
6 September 2015
3 September 2015
From one piece Neural Networks, Types, and Functional Programming 2 beliefs, in the piece's order there
-
Their words
The known connection between geometry, logic, topology, and functional programming suggests that the connections between representations and types may be of fundamental significance.
-
Their words
I think it is very likely that, reflecting back in 30 years, we will see deep learning very differently.
31 August 2015
From one piece Calculus on Computational Graphs: Backpropagation 2 beliefs, in the piece's order there
-
korrents.com
An idea can look obvious in hindsight only because the insight that makes it obvious was itself the hard discovery.Their words
It also wasn't obvious that derivatives were the right way to train them. Those are only obvious once you realize you can quickly calculate derivatives. There was a circular dependency.
-
Their words
That's the benefit of hindsight. Once you've framed the question, the hardest work is already done.
27 August 2015
From one piece Understanding LSTM Networks 2 beliefs, in the piece's order there
-
Their words
LSTMs are explicitly designed to avoid the long-term dependency problem. Remembering information for long periods of time is practically their default behavior, not something they struggle to learn!
-
Their words
In theory, RNNs are absolutely capable of handling such "long-term dependencies." A human could carefully pick parameters for them to solve toy problems of this form. Sadly, in practice, RNNs don't seem to be able to learn them.
30 April 2015
30 March 2015
16 January 2015
From one piece Visualizing Representations: Deep Learning and Human Beings 2 beliefs, in the piece's order there
-
Their words
The problem is that in dimensionality reduced plots of high-dimensional data, position doesn't explain the data points.
-
korrents.com
Understanding a machine learning model and understanding the data it operates on are inseparable tasks.Their words
Understanding data and understanding models that work on that data are intimately linked.
9 October 2014
Nothing matches.
What is a korrent?
A korrent is a belief a person has stated in their own words: one sentence stating the claim, backed by a quote and a source, kept at korrents.com.
Under a name here, the quoted block is what they actually said. The korrent beneath it is the claim those words support, in korrents' wording — tap it to see the record, its source, and who else holds it.
Nobody here wrote their own korrents. They are compiled from public statements, and a person can change their mind, which is recorded too.
About the English under a post
Some people here publish in a language other than English. Where they do, this site shows a machine translation beneath the post, in this typeface — the site's own, not theirs.
The post itself is never changed, moved or hidden: what is set in the serif above is exactly what the person published, and it is what to quote them on. A translation can be wrong in ways that matter, especially about tone.
Only the post's own words are translated. A quoted post, a linked article and a belief on korrents.com are left in their original language.