that doesn't have to persist long for AI to join the ranks of systems that are important enough that there's someone senior in the government who's responsible for regulating them.
And I'm not claiming this as a published study, but so I think there's a there's a direct autonomic training component as well in terms of the strength and the automaticity, the ease with which you can regulate emotions that they can become kind of automatically regulated.
People talk about isn't it a bad idea to build in a regulated industry? Turns out you can change the regulations. And the way you do it is just by building the thing and communicating why it's okay.
More data for better comparisons are good. Now everybody has to do it, and regulators and the public have to learn to look at only the data, and not individual incidents
the regulation gets extremely difficult and mundane and expensive that could actually lead to more igopoly and I think some of the players know that and are begging for regulation.
General problem solving abilities are neither learned nor taught. While some problem-solving methods have broader applicability than others (such as the scientific process of hypothesis testing), students learn these methods better when they’re explicitly taught rather than simply giving students projects and hoping they’ll reinvent them on their own.
Booth's formally trained (and her grandparents are watercolor artists!) but her use of color is just so free and unexpected, it makes you want to experiment yourself and join along in the fun.
Thus my personal prediction is that in domains that are already largely under the powers of modern AI, such as languages, programming or chess, we’re going to see a divergence in human abilities.
Two other formally odd books I love: Alejandro Zambra's Multiple Choice (trans. by Megan McDowell), structured as a standardized test with e.g. chapters of fill-in-the-blank questions
take prompting and as an engineer, there's a range of prompting abilities. uh the way you discretize and split up your task matters. And if you assume that uh a model can do more than it can do, then you're going to have a bad time.
Yeah. So there's a subtlety here. Emerging capabilities don't just come from the fact that internet data has a lot of stuff in it. They also come from the fact that generalization once it reaches a certain level becomes compositional.
Until we develop better ways to bridge this gap - aligning what analysts understand with what is formally forecast - we'll continue to see the same pattern: reality consistently outperforming conservative predictions.
Another manifestation of the lack of sufficiently abstract, formal reasoning in LLMs is the way in which performance often fall apart as problems are made bigger.
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.