21–30 of 127 posts
The core thesis seems to be that the "real value" is not in producing/proving theorems, but in understanding them. AI might be good at producing and proving theorems, but it fails utterly at getting humans to understand them. Even worse, humans have no interest in working on theorems that have already been proven, so we end up with theorems that will never be understood by humans. I can understand why this is a major…
Tangential but this article got me thinking. Are we going to see less publicly shared science? With private actors or governments restricting access to AI resources to a few scientists and keeping new knowledge to themselves. Advancing science in the open was the best strategy when there was real advantage to share the load with every brain on the planet willing to give a try at science, but if a computer can match o…
What is going to suck though is the ladder for juniors. We dont start out by working on big ticket problems, but usually early career researchers solve really tiny problems in a cheap way. The lowest bar for a cash strapped PhD student would be to contribute to some new theory in some way even if the student doesnt have access to equipment.
Tangential but this article got me thinking. Are we going to see less publicly shared science? With private actors or governments restricting access to AI resources to a few scientists and keeping new knowledge to themselves. Advancing science in the open was the best strategy when there was real advantage to share the load with every brain on the planet willing to give a try at science, but if a computer can match o…
This is what a lot of scientists love to tell themself or talk about in celebratory speeches.
The truth is: a lot of science is kept behind journal paywalls, so that only "officially approved" (in the sense of: working at a university or an governmental research institute) scientists can easily access it.
Feels a lot like building software from bottom - once you get the building blocks defined right, the action, or the program, are trivial to express. When doing it from the top-down, you write the program using the building blocks you haven't defined yet, and you might end up with overly specific building blocks, needing other blocks for expressing different behaviors.
When you do the bottom-up building blocks right, new behavior is easy to express with them. Essentially, you are building up the language to reach the problem. Or making a DSL, whatever definition you like best.
"I was in Switzerland", "I was invited to a talk", "I started a machine learning company", look at me bro.
Is being pompous and on the nose part of being in mathematics? "I was in Switzerland", "I was invited to a talk", "I started a machine learning company", look at me bro.
Earlier quoted context omitted.
Science is not about results, it is about the transmission of knowledge. So long as those AI-"sciences" are just inside AI, they are "engineering", not science. I am not dismissing engineering (it moves the world we live in), just trying to clarify what science is. Applied fluid dynamics works like that: noone has ever really "verified" that the finite-element method applied to some specific model does converge
Engineering is used fairly loosely these days but I insist engineering ends where you have to prove theorems.
Tangential but this article got me thinking. Are we going to see less publicly shared science? With private actors or governments restricting access to AI resources to a few scientists and keeping new knowledge to themselves. Advancing science in the open was the best strategy when there was real advantage to share the load with every brain on the planet willing to give a try at science, but if a computer can match o…
Tangential but this article got me thinking. Are we going to see less publicly shared science? With private actors or governments restricting access to AI resources to a few scientists and keeping new knowledge to themselves. Advancing science in the open was the best strategy when there was real advantage to share the load with every brain on the planet willing to give a try at science, but if a computer can match o…
> to share the load with every brain on the planet willing to give a try at science This is what a lot of scientists love to tell themself or talk about in celebratory speeches. The truth is: a lot of science is kept behind journal paywalls, so that only "officially approved" (in the sense of: working at a university or an governmental research institute) scientists can easily access it.
Earlier quoted context omitted.
> to share the load with every brain on the planet willing to give a try at science This is what a lot of scientists love to tell themself or talk about in celebratory speeches. The truth is: a lot of science is kept behind journal paywalls, so that only "officially approved" (in the sense of: working at a university or an governmental research institute) scientists can easily access it.
You know how I read new papers back in 1994? By going to the library, finding one in bi-annual publication list and requesting it through the University system. And it better be necessary because the uni had to pay both the catalogue and each reprint of an article. The access is most certainly easier today.
Also be aware that the world wide web was actually conceived by Tim Berners-Lee for the exchange of information between scientists.