You can’t turn a spicy autocorrect into anything even remotely close to Jarvis.
It’s not autocorrect, it’s a text predictor. So I’d say you could definitely get close to JARVIS, especially when we don’t even know why it works yet.
You’re just being pedantic. Most autocorrects/keyboard autocompletes make use of text predictors to function. Look at the 3 suggestions on your phone keyboard whenever you type. That’s also a text predictor (granted it’s a much simpler one).
Text predictors (obviously) predict text, and as such don’t have any actual understanding on the text they are outputting. An AI that doesn’t understand its own outputs isn’t going to achieve anything close to a sci-fi depiction of an AI assistant.
It’s also not like the devs are confused about why LLMs work. If you had every publicly uploaded sentence since the creation of the Internet as a training reference I would hope the resulting model is a pretty good autocomplete, even to the point of being able to answer some questions.
Yes, autocorrect may use text predictors. No, that does not make text predictors “spicy autocorrect”. The denotation may be correct, but the connotation isn’t.
Text predictors (obviously) predict text, and as such don’t have any actual understanding on the text they are outputting. An AI that doesn’t understand its own outputs isn’t going to achieve anything close to a sci-fi depiction of an AI assistant.
There’s a large philosophical debate about whether we actually know what we’re thinking, but I’m not going to get into that. All I’m going to elaborate on is the thought experiment of the Chinese room that posits that perhaps AI doesn’t need to understand things to have apparent intelligence enough for most functions.
It’s also not like the devs are confused about why LLMs work.
Yes they are. All they know is that if you train a text predictor a ton, at one point it hits a bottleneck of usability way below targets, and then one day it will suddenly surpass that bottleneck for no apparent reason.
Not going to go into details due to confidentiality, but I recently was involved in an initiative to utilize AI to scan education databases and identify students who may be at risk of dropping out, with the goal of having an early safety net for these folks. And also raising the schools retention rates, thus better outcomes overall.
So yes, AI can absolutely be used for good.
It’s a capitalist invention and, therefore, will be used for whatever capitalists deem it profitable to be. Once the money for AI home assistants starts rolling in, then you’ll see it adopted for that purpose.
It’s a free market invention and, therefore, will be used by whatever a free market decides it should be used for.
The people already with the money have orders of magnitude more freedom on average to decide and pursue opportunities.
Free market inventions do not guarantee persistent and open access.
Training good models requires lots of training data and computational resources, so the only ones who can afford to train them are big corporations with access to both. And the only objective they have is to increase their profit.
Well, as long as we ensure training data needs to be paid for and can’t just be scraped from the web, we will ensure that only large corporations with deep pockets can train models.
That is the reason there is a big “grassroots” push to stop AI from training on all our web content: it’s a play to ensure no small players can make AI, and that AI is dominated by a few big players.
Any tool, in human hands, will be used for evil. The problem is humans.
