4 ms·
A bigger limit for the successful cases right now is the data limit. Even if silicon wasn't a limit, there's only a good few hundred years of data, and frankly
by foobiekr 3y ago
A bigger limit for the successful cases right now is the data limit. Even if silicon wasn't a limit, there's only a good few hundred years of data, and frankly less than 30 years of high volume (if low quality) data. Science as a discipline isn't that old in the grand scheme of things, and the collective data set won't end up training something that can go beyond the input.
It's quite possible "good enough" AI will trap us in a local maximum of mediocrity where the near-term ROI on thinking hard is too low.
- Legend2440 3y agoThe majority of data was created in the last 10 years, and the rate of data creation is accelerating. I don't think we'll run out. AI will also enable the collection of more data. For example, robots could do the labwork for science experiments in far greater numbers than humans could.
- foobiekr 3y agoLab work has an unbelievable number of gates in front of it that mean the units of work pert unit time isn't high. A massive amount of gibberish isn't _useful_ data.
- PBnFlash 3y agoOur use of data is WILDY inefficient currently. Current training systems extract information on everything from every input. We don't read a cookbook to learn about space, but these models are twiddling weights all over these massive spaghetti balls of logic. Looking at the data we have, the literal collection of all human knowledge and lamenting not having more is like standing on a ladder sideways. But it's really starting to feel like pile of ladders is getting tall enough to bootstrap. And these massive inefficient systems filled with data and churning matrixs will be set in order. And all the ladders laid end to end.