this post was submitted on 19 Oct 2023
499 points (96.8% liked)
Technology
59288 readers
6215 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related content.
- Be excellent to each another!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, to ask if your bot can be added please contact us.
- Check for duplicates before posting, duplicates may be removed
Approved Bots
founded 1 year ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
I think the breakthroughs in AI have largely happened now as we're reaching a slowndown and an adoption phase
The research has been stagnating. Video with temporal consistency doesn't want to come, voice is still perceptibly non-human, openai is assembling 5 models in a trenchcoat to make gpt do images and it passing as progress, ...
Companies and people are adopting what is already there for new applications, it's getting more common to see neural network models in lots of solutions where the tech adds good value and is applicable, but the models aren't breaking new grounds like in 2021 anymore
The only new fundamental developments i can recall in the core technology is the push for smaller models trainable on way less data and that can be specialized for certain applications. Far away from the shock we all got when AI suddenly learned to draw a picture from a prompt
It utterly baffles me how people can make that claim. AI image generation has exists for not even three years and back than it could do little more than deformed Avocado chairs and shrimp. This stuff has been evolving insanely fast, much quicker than basically any technology before.
We have barely even started training AIs on video. So far it has all been static images, of course they aren't learning motions from that and you can't expect temporal consistency when the AI has no concept of time, frames or anything video related. And anyway, the results so far look quite promising already. Generators for 3D models and stuff is in the works as well.
What the heck do you expect? Of course going from nothing to ChatGPT/DALLE2 will be a bigger jump than going to GPT4/DALLE3 (especially considering most people skipped GPT1,2,3 and DALLE1), that doesn't mean both of them aren't substantially better than previous versions. By GPT5/DALLE4 you might really start to worry about if humans will still be necessary at all. We should be happy that we might still have a few more years left before AI renders us all obsolete.
And of course there is plenty of other research going on in the background for multi-modal models or robots that interact with the real world. Image generations and LLMs are obviously only part of the puzzle, you are not going to get an AGI as long as it is locked in a box and not allowed to interact with the real world. Though at the current pace, I'd also be very careful with letting AI out of its box.
Wow, this is some spectacular hyperbole!
That's the current pace of AI. It's evolving insane fast and already extremely capable.
Here is a little game:
Example: https://www.artstation.com/artwork/LRmYvl
Result: https://imgur.com/a/ImbNQDk (about 20 seconds of effort)
It's ridiculously easy to recreate almost anything on there at a similar or sometimes even better level of quality. Literally seconds to recreate what would take a human hours or even days. What are the chances that humans will still be relevant in this line of work in 5 or 10 years, when we are able to create this level of quality after not even three years of AI image generation?
And the same will be true for every other job or activity that mainly works on digital data. When you can find enough data to train an AI on, it's gone. Humans are no longer needed. And more general AI model will sooner or later eat up all the rest as well.
I seriously don't know how one can look at the progress in AI over the last two years and not have a bit of an existential crisis.
Here is an alternative Piped link(s):
results so far
robots that interact with the real world
Piped is a privacy-respecting open-source alternative frontend to YouTube.
I'm open-source; check me out at GitHub.
I want to note that everything you talk about is happening on the scales of months to single years. That's incredibly rapid pace, and also too short of a timeframe to determine true research trends.
Usually research is considered rapid if there is meaningful progression within a few years, and more realistically about a decade or so. I mean, take something like real time ray tracing, for comparison.
When I'm talking about the future of AI, I'm thinking like 10-20 years. We simply don't know enough about what is possible to say what will happen by then.