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Yes I do. It took me a while to understand this but YES THEY CAN. AND HOW! The prediction of the next word in the latent space (and to a lesser extent, in im
by EGreg 2y ago
Yes
I do.
It took me a while to understand this but YES THEY CAN. AND HOW!
The prediction of the next word in the latent space (and to a lesser extent, in images etc) is a great HARNESS for training them to develop INTERNAL STRUCTURES that start to REASON about inputs and produce OUTPUTS that actually make humans very impressed.
Think of it as a a BILLION LINES OF CODE in a non-von-neumann architecture. Instead of code in an imperative language, with some space for data etc. it is a different architecture where the BILLIONS OF WEIGHTS are the code. And it was not written by humans but discovered through a search through program space.
It would be like iterating through the space of all possible programs, to create a program that can REASON ABOUT, say, the movement of the stars and Kepler’s Laws could be just a low-dimensional projection of a much more intricate system.
It may even have elements of recursion, allowing Chomsky grammars and much more. With more training it can start to use concepts, and modify them etc.
In short — it forms DURABLE STRUCTURES in the model that lets the program REASON ABOUT inputs in the same way that people would!
But unlike people it can have access to a vast memory with perfect recall and indexing. AND on top of that, if it is programmed in a certain way it can build up concepts of arbitrary complexity and continuously select the most powerful ones (training itself, essentially) getting powers far beyond mere “reasoning”.
But now it can be done at 1000x the speed and parallelized, eg a 5 hour video can be analyzed by 100 machines in parallel and then grokked, analyzed, transcribed, clipped, and catalogued among other knowledge, within 5 seconds instead of watching it linearly. Then you can ask questions about it. But that is only the beginning. It can search across millions of videos it ingested and know exactly where every word was said, thereby for example producing a much more persuasive multimedia argument for ANY position, regardless of how ridiculous, than a team of 10 people doing it manually.
Then it can make accounts on youtube and tiktok, that seem like human ones, or at any rate attract a lot of followers, and outcompete the human accounts in both quantity of likes, followers and accounts. After all, it is just a bunch of measurable metrics to optimize 24/7, across the entire bot swarm and coordinated accounts. Then as they get enough of an audience they can literally post any info, supported by the above “reasoning” engine, and it will be more than enough to convince most people. And the ones who are skeptical will be silenced by their friends and neighbors, the way people who question eg the safety of vaccines, progressive movements, or certain wars, are.
In fact — to show the dangers of this, I could build a website that literally makes extremely persuasive videos for flat eartherism, 9/11 trutherism and convince people birds aren’t real, and much more. Then clip it and have coordinated posting of well produced clips on YouTube and TikTok, using “fair use” clips cherrypicked across millions of source videos. And then have swarms of bots on social networks (eg operating occasionally in grandfathered accounts) respond, upvote, downvote, retweet and gradually shift more people to believing it. Then can change wikipedia the way Stephen Colbert did with tripling of elephants, but with bots. To show how disinformation could spread. It must be done ethically. If someone would like to discuss how to do this experiment / warning project ethically you can contact me (see my profile).
I prefer that the dangers are highlighted early, because people are very complacent and have no idea what the bot swarms can do. Asking if they can reason is like asking if computers can finally play sounds. They can do far more, and quickly turn the internet not just into a dark forest but quickly overwhelm our society with very believable bullshit and gradually destroy the concept of truth completely.
Humans don’t walk miles when they can use cars. Now “the computer” is no longer the bicycle for the mind. It is the self-driving car LOL
- codeflo 2y ago> Humans don’t walk miles when they can use cars. Now “the computer” is no longer the bicycle for the mind. It is the self-driving car LOL That analogy is actually very apt, but in ways you might not have intended it to be.
- Nevermark 2y ago> In short — it forms DURABLE STRUCTURES in the model that lets the program REASON ABOUT inputs in the same way that people would! I don't think we can assume this, especially as they manage to reason with far fewer steps than we would use. Even with humans, I think we overrate how much we think alike just because we often arrive at the same or similar answers. But I agree completely with everything else you have said!