To be fair, you sound like an old fuck, like me. I’m gonna bet that the average age of technologist involved in the current stuff is early 30s. And those technologists would be working on application not research. Even among the researchers, the cites probably don’t go back further than 2017. That’s enough of a generational gap that I think it is likely that not many people are as intimately aware as you think they should be.
You may well be right, but that just sounds like the aforementioned incompetence to me. Or perhaps - to put it in D&D terms - a bunch of high-INT, low-WIS builds doing very stupid things just because they can, completely ignoring the question of whether they should.
What really annoys me about all this is that I haven’t got any issue with machine learning. It doesn’t matter what model we’re talking about. Polynomial partitioning of N-dimensional vector spaces. Neural nets. Context mixing. Whatever. There’s plenty of highly constructive and productive things we could be doing with ML. Trawling through scientific datasets looking for patterns no human would ever be able to pick up. Optimizing industrial processes for improved competitiveness, superior products, lower costs and reduced environmental impact. Simulated material science, logistical optimization… The list goes on. Instead, we’re wasting oceans of power, further straining scarce water resources and driving up hardware costs to… Build a ‘better’ chat bot, that, in terms of cognitive and social corrosion is more like social media on an unholy mixture of amphetamines and PCP.
To be fair, you sound like an old fuck, like me. I’m gonna bet that the average age of technologist involved in the current stuff is early 30s. And those technologists would be working on application not research. Even among the researchers, the cites probably don’t go back further than 2017. That’s enough of a generational gap that I think it is likely that not many people are as intimately aware as you think they should be.
You may well be right, but that just sounds like the aforementioned incompetence to me. Or perhaps - to put it in D&D terms - a bunch of high-INT, low-WIS builds doing very stupid things just because they can, completely ignoring the question of whether they should.
What really annoys me about all this is that I haven’t got any issue with machine learning. It doesn’t matter what model we’re talking about. Polynomial partitioning of N-dimensional vector spaces. Neural nets. Context mixing. Whatever. There’s plenty of highly constructive and productive things we could be doing with ML. Trawling through scientific datasets looking for patterns no human would ever be able to pick up. Optimizing industrial processes for improved competitiveness, superior products, lower costs and reduced environmental impact. Simulated material science, logistical optimization… The list goes on. Instead, we’re wasting oceans of power, further straining scarce water resources and driving up hardware costs to… Build a ‘better’ chat bot, that, in terms of cognitive and social corrosion is more like social media on an unholy mixture of amphetamines and PCP.
It all just seems like such a waste.