this post was submitted on 28 Feb 2024
-29 points (24.6% liked)

Technology

59080 readers
3758 users here now

This is a most excellent place for technology news and articles.


Our Rules


  1. Follow the lemmy.world rules.
  2. Only tech related content.
  3. Be excellent to each another!
  4. Mod approved content bots can post up to 10 articles per day.
  5. Threads asking for personal tech support may be deleted.
  6. Politics threads may be removed.
  7. No memes allowed as posts, OK to post as comments.
  8. Only approved bots from the list below, to ask if your bot can be added please contact us.
  9. Check for duplicates before posting, duplicates may be removed

Approved Bots


founded 1 year ago
MODERATORS
 

First of all, the take that LLM are just Parrots without being able to think for themself is dumb. They do in a limited way! And they are an impressive step compared to what we had before them.

Secondly, the take that LLMs are dumb and make mistakes that takes more work to correct compared to do the work yourself from the start. That is something I often hear from programmers. That might be true for now!

But the important question is how will they develop! And now my take, that I have not seen anywhere besides it is quite obvious imo.

For me, the most impressive thing about LLMs is not how smart they are. The impressive thing is, how much knowledge they have and how they can access and work with this knowledge. And they can do this with a neuronal network with only a few billion parameters. The major flaws at the moment is their inability to know what they don't know and what they can't answer. They hallucinate instead of answering a question with "I don't know." or "I am not sure about this." The other flaw is how they learn. It takes a shit ton of data, a lot of time and computing power for them to learn. And more importantly they don't learn from interactions. They learn from static data. This similar to what the Company DeepMind did with their chess and go engine (also neuronal networks). They trained these engines with a shit tone of games that were played by humans. And they became really good with that. But then the second generation of their NN game engines did not look at any games played before. They only knew the rules of chess/go and then started to learn by playing against themself. It took only a few days and they could beat their predecessors that needed a lot of human games to learn from.

So that is my take! When LLMs start to learn while interacting with humans but more importantly with themself. Teach them the rules (that is the language) and then let them talk or more precise let them play a game of asking and answering. It is more complicated than it sounds. How evaluate the winner in this game for example. But it can be done.

And this is where the AGI will come from in the future. It is only a question how big do these NN need to be to become really smart and how much time they need to train. But this is also when AI can gets dangerous. When they interact with themself and learn from that without outside control.

The main problem right now is they are slow as you can see when you talk to them. And they need a lot of data, or in this case a lot of interactions to learn. But they will surely get better at both in the near future.

What do you think? Would love to hear some feedback. Thanks for reading!

you are viewing a single comment's thread
view the rest of the comments
[–] niva@discuss.tchncs.de 1 points 8 months ago

Well of course there is a lot of hype around it. And it probably is over hyped at the moment. But there will be the next breakthrough in AI/LLMs. I don't know when, but I think it will be when AIs learns by interacting with other AIs.