this post was submitted on 12 Jul 2024
284 points (100.0% liked)
Technology
37716 readers
392 users here now
A nice place to discuss rumors, happenings, innovations, and challenges in the technology sphere. We also welcome discussions on the intersections of technology and society. If it’s technological news or discussion of technology, it probably belongs here.
Remember the overriding ethos on Beehaw: Be(e) Nice. Each user you encounter here is a person, and should be treated with kindness (even if they’re wrong, or use a Linux distro you don’t like). Personal attacks will not be tolerated.
Subcommunities on Beehaw:
This community's icon was made by Aaron Schneider, under the CC-BY-NC-SA 4.0 license.
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
Not exactly.
LLMs are predictive-associative token algorithms with a degree of randomness and some self-reflection. A key aspect is that anything can be a token, they can self-feed their own output, creating the basis for a thought cycle, as well as output control input for other algorithms. It remains to be seen whether the core of "(human) intelligence" is much more than that, and by how much.
Stable Diffusion is a random image generator that refines its output based on perceptual traits associated with a prompt. It's like a "lite" version of human dreaming, only with a super-human training set. Kind of an "uncanny valley" version of dreaming.
It just so happens that both algorithms have been showcased at about the same time, and it's the first time we can build a "set and forget" AI system that can both make decisions about its own next steps, and emulate human creativity... which has driven the hype into overdrive.
I don't think we'll stop hearing about it, but I do think there is much more to be done, and it's pretty much impossible to feed any of the algorithms with human experience data, without registering at least one human learning cycle, as in over many years from inside a humanoid robot.
Ah, so they produce parts of words instead of whole words at a time. Totally different.
And they're hooked up to random number generators so if you give it the same input twice you'll get different output. Totally makes it smarter.
...much like predictive text. Rarely will you find one that doesn't suggest punctuation on occasion.
...much like predictive text.
Oh, so you can tell it to suggest certain tokens more or less often. How fancy.
I mean, I'd say the ability to visualize things and reason about scenarios it hasn't experienced before are a good start.
Not sure if you were unable or unwilling to understand anything of what I wrote, and I don't like your tone. Feel free to come back with something more serious.