257 karma · joined August 20, 2020
this is nicely illustrated by this recent article:
Instead of big models that “brute force” the right answer by knowing a lot of possible outcomes, this model seems to come to results with less knowledge but more wisdom.
Kind of like having a database of most possible frames in a video game and blending between them instead of rendering the scene.
Edit: timed out
He had a page dedicated to his housing situation:
Still manageable though, just very sensitive.
That's easier said than done, hence why Stefano probably didn't.
The way I have come to perceive AI is that it's mostly good at reassuring/reaffirming people's beliefs and ideas than an actual source of truth.
That would not be an issue if it was actually marketed as such, but seeing the "guided learning" function fail time and again makes me think we should be a lot more critical of what we're being told by tech enthusiasts/companies about AI.
Which is in my option, the #1 metric an LLM should strive for. It can take quite some time to get anything out of an LLM. If the model turns out to be unreliable/untrustworthy, the value of its output is lost.
It's weird that modern society (in general) so blindly buys in to all of the marketing speak. AI has a very disruptive effect on society, only because we let it happen.
AI really needs better source-validation. Not just to combat the hallucination of sources (which gemini seems to do 80% of the time), but also to combat low quality sources that happen to correlate well to the question in the prompt.
It's similar to Google having to fight SEO spam blogs, they now need to do the same in the output of their models.
On the one hand, there’s going to be a lot more, potentially high quality audio books in its repository, on the other hand it goes against the spirit of the project itself.
It also pans and zooms swiftly