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AI Explained
251K subscribersIs AlphaGeometry a key step toward AGI? Even Deepmind's leaders can't seem to make their minds up. In this video, I'll give you ...
Thank you for referring to Twitter as Twitter.
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Wes Roth
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24 Comments
programmers trying to automate their own job always mind blow me, peak stupidity achieved.
Dates keep getting closer, I still think 2026 max for ASI. There are many reasons for this, but anyone that says 2030 is flat wrong. The big AI guys are good at AI, but not good at process i     See More
When you says give the model space to explore (e.g. through Reflexion) its important to remember that this is only successful with the super powerful models such as GPT-4 or GPT-4 Turbo. Wit     See More
Would you consider some discount on the insiders for people living in developing economies?
Mathematics isn't just about proving things. It's about making abstractions and recognizing patterns and associations. In order for mathematics to "fall" an AI would have t     See More
The second part is MASSIVE. It shows how much there is still possibilities withing GPT-4, just by proper prompt engineering.... Fantastic!
TIL I pronounce my Hs in a Cockney way. Must call the Trouble and Strife on the old Dog and Bone to let her know.
Thank you for referring to Twitter as Twitter.     See Less
AI should create the problems that IMO uses.     See Less
This is all going to be horrible for humanity...... 😑     See Less
programmers trying to automate their own job always mind blow me, peak stupidity achieved.     See Less
Dates keep getting closer, I still think 2026 max for ASI. There are many reasons for this, but anyone that says 2030 is flat wrong. The big AI guys are good at AI, but not good at process i     See More and global interconnected competative open source culmination and non-symmettrical synthesis of globally improving systemic reasoning that AI will have this year.    See Less
When you says give the model space to explore (e.g. through Reflexion) its important to remember that this is only successful with the super powerful models such as GPT-4 or GPT-4 Turbo. Wit     See More Turbo Reflexion and chain of thought is super inconsistent and at times arbitrary. This is why I like the Test Time approach - which has been proven to upscale the performance of smaller models. Also, a verifier model ranking according to scalar estimates such as ‚estimate the revenue this business plan will make in €‘ is a super straight forward scoring system which makes it super easy to filter out ideal solutions among thousands of suggestions, i.e. it can be scaled easier and implement in a straight forward way.    See Less
Would you consider some discount on the insiders for people living in developing economies?     See Less
Mathematics isn't just about proving things. It's about making abstractions and recognizing patterns and associations. In order for mathematics to "fall" an AI would have t     See More develop conjectures and prove them (it should probably also be able to develop a construction that could be usable to study a problem of interest). Making sensible conjectures may demand AGI. And the search space for developing new constructions, whether to make associations between different areas of knowledge or just to prove a conjecture, is likely way too large without judgment. But a proof bot could be a tool that a mathematician uses to explore mathematics.
It should also be noted that it sounds like this bot was trained on proofs in a well-developed area of mathematics. If I understood, the training data was other proofs in that area. Using well-developed methods in new situations that closely follows the original use is certainly very useful in mathematics, but even were the bot to be used only to find proofs as directed by a human, and nothing more, if the bot were to lose effectiveness in a novel area of math where new axioms and definitions were introduced it would greatly reduces its usefulness, especially if it's even unable to abstract known methods from other areas of math and apply them to the novel area.
Most people just don't understand what mathematics entails. The fact that math can be parsed easily and uses a very precise language is great for an AI. But mathematics requires a tremendous amount of creativity, ability to abstract, and ability to reason. Symbolic reasoning is not enough, there needs to be deeper reasoning. You can get a whole lot done with effective symbol-pushing. You can get a whole lot done with intelligently searching through a database of proof ideas. You can get even more done when you combine the two together. But you can't crack mathematics with it. You're not even close.    See Less
The second part is MASSIVE. It shows how much there is still possibilities withing GPT-4, just by proper prompt engineering.... Fantastic!     See Less
TIL I pronounce my Hs in a Cockney way. Must call the Trouble and Strife on the old Dog and Bone to let her know.     See Less