Well people can’t even agree on who won the last election or even if the world is round, so I can only speak to my point of view on things.
I don’t think these are the best examples to use for your case here, giving both touch on matters of fact that are only questioned by fringe conspiracy theorists that the rest of the world regards as absolutely crazy, without any basis in reality. Yes, people do passionately believe them, but that doesn’t make them anyore true. It’s like trotting out the conservative chestnuts that evolution is just a theory, or that anthropogenic climate change hasn’t been the consensus position amongst scientists and framing it as a quack theory that some evil, socialist scientists have politicized because they hate US oil barons making money.
That aside, any serious discussion of AI’s inevitability needs to involve a feasible roadmap to making it sustainable at a material level. I won’t fully discard the possibility, as there’s no telling what the future may hold, but I haven’t seen any indication that there is a viable way to make these systems run with performance comparable to what they currently offer, without requiring several planets’ worth of water, hardware and power capacity. They can only do their “move fast and break things” schtick for so long before people get sick of it, and you’re already seeing people sour on data centers, as well as AI more generally.
The idea that AI will always be here, in something approaching its current state, now that we’ve invented it is just groundless, in my opinion. Yes, local LLMs will continue to exist, but they will have trade offs that I don’t see being palatable for the broader market. Using AI to make a quick meme based on a prompt doesn’t have the same draw when it takes 40 minutes to finish what the current money pit versions of AI will do in seconds.
I think it’s fair to assume AI will be around in some capacity, but will likely be far different from what we currently have, and restricted to domains where it actually makes sense to use, like some medical applications for analyzing patient imaging to suggests issues that humans might overlook. As companies are currently learning, though, the math just doesn’t work out on trying to replace human workers wholesale, and this is while the price still doesn’t accurately reflect the cost of running these models as services.
Given all this, plus your remarks on the ethical side of the training material, it just doesn’t make any sense to discuss the inevitability of AI existing in some capacity in the future as a reason not to offer blanket opposition to the tech as it currently exists. None of these companies can currently turn a profit just on the basis of their hardware and energy costs, so how likely is it they could offer reasonable compensation for training materials without this price becoming even more unreasonable?
I think drastically reducing these costs and ironing out the wrinkles should have been done before they ever rolled these systems out to the general public. Now, they’re up against a wall, trying to find a way to do so before the backlash becomes so severe, they can no longer find steady streams of investors willing to sink money in an increasingly toxic product.
I don’t think these are the best examples to use for your case here, giving both touch on matters of fact that are only questioned by fringe conspiracy theorists that the rest of the world regards as absolutely crazy, without any basis in reality. Yes, people do passionately believe them, but that doesn’t make them anyore true. It’s like trotting out the conservative chestnuts that evolution is just a theory, or that anthropogenic climate change hasn’t been the consensus position amongst scientists and framing it as a quack theory that some evil, socialist scientists have politicized because they hate US oil barons making money.
That aside, any serious discussion of AI’s inevitability needs to involve a feasible roadmap to making it sustainable at a material level. I won’t fully discard the possibility, as there’s no telling what the future may hold, but I haven’t seen any indication that there is a viable way to make these systems run with performance comparable to what they currently offer, without requiring several planets’ worth of water, hardware and power capacity. They can only do their “move fast and break things” schtick for so long before people get sick of it, and you’re already seeing people sour on data centers, as well as AI more generally.
The idea that AI will always be here, in something approaching its current state, now that we’ve invented it is just groundless, in my opinion. Yes, local LLMs will continue to exist, but they will have trade offs that I don’t see being palatable for the broader market. Using AI to make a quick meme based on a prompt doesn’t have the same draw when it takes 40 minutes to finish what the current money pit versions of AI will do in seconds.
I think it’s fair to assume AI will be around in some capacity, but will likely be far different from what we currently have, and restricted to domains where it actually makes sense to use, like some medical applications for analyzing patient imaging to suggests issues that humans might overlook. As companies are currently learning, though, the math just doesn’t work out on trying to replace human workers wholesale, and this is while the price still doesn’t accurately reflect the cost of running these models as services.
Given all this, plus your remarks on the ethical side of the training material, it just doesn’t make any sense to discuss the inevitability of AI existing in some capacity in the future as a reason not to offer blanket opposition to the tech as it currently exists. None of these companies can currently turn a profit just on the basis of their hardware and energy costs, so how likely is it they could offer reasonable compensation for training materials without this price becoming even more unreasonable?
I think drastically reducing these costs and ironing out the wrinkles should have been done before they ever rolled these systems out to the general public. Now, they’re up against a wall, trying to find a way to do so before the backlash becomes so severe, they can no longer find steady streams of investors willing to sink money in an increasingly toxic product.