Interesting viewpoint, following this, it would probably be beneficial to have many different personal AIs as compared to a few AIs that serve many.
Yeah this is a good point, independent of AI (but probably not the internet) things are already becoming more homogeneous IMO. If that's expedited by everybody using e.g. ChatGPT I don't think that would be good.
How many degrees of freedom these networks have? There's a lot of room in high dimensional space :)
Sure, same prompts same answers, but people are pretty creative already in their questions.
Re:91% of ML Models Degrade over Time
by CuriouslyC on Friday April 14, 2023 @10:57AM
(#35570243)
It makes more sense to have a really strong base model that is "general" and then apply LoRAs to it to "specialize" it.
Re:91% of ML Models Degrade over Time
by CuriouslyC on Friday April 14, 2023 @10:55AM
(#35570231)
The big difference in reality is that your brain has an additional context (your working memory, which is shaped by sensory input) and it's mean() function is extremely approximate, so your outputs are more variable. We could give these models video/audio/etc "inspiration" and increase the temperature and they'd behave similarly.
(In particular, it's just an `Expectation_weightDistribution[TrainingData|Query]` )
If you wanted to be, I think pathologically cynical about animal intelligence, and reduce it down to the same operation, then at the very least the "TrainingData" and the "weightDistribution" is specialised to the individual -- and so different from the average.
However, we cannot really be this extremely cynical (I find this pseudoscience) -- animals acquire novel training data by changing their environments. Animals are a source of data.
So even on this cynical reading we have to at least go towards,
Which makes `MyIdeas` quite radically different from the `mean()`ing of the Ai.