We had hype all the time. It's not recent invention. And in 48 years after 1973, per capita GDP increased 2.18x which, extrapolated to a 103 year interval (as between 1870 and 1973) means 5.32x increase which is almost as fast (6.7% slower, which is very easy to explain knowing that U.S. primary energy supply stopped growing in 1973 after skyrocketing in the century before).
In the last 50 years, Western civilisation learned how to do more with less. In the century before, we simply invented new and new ways of throwing more and more non-renewable resources onto all problems we had. Which isn't really all that hard to do - for as long as you may come up with sources for those resources.
We do better on some things (energy production, automobile, ..) but globally the climate changes remind us that consumerism is way too high, and often hype-driven
Consider though that, "consumerism" is a very important part of modern economies. People tend to buy things that send social signals to other people (conspicuous consumption) which in turn drives demand for high quality items (hopefully) which creates real incentives for innovation and growth. At the same time I can agree that, "keeping up with the Joneses" has created a social nightmare for many.
My point here is that even following a big Kuhnian paradigm shift you're still going to have the same human psychologies to deal with and that's precisely where, "consumerism" lives-- in consumers; the idea that, "consumerism" is somehow driven by ideology or how capitalism structures society seems to be naive in my view. Conspicuous consumption still takes place in supposedly, "destratified" societies-- see the Kim family of North Korea or rich Saudis.
That's the thing, we are slowly figuring out how to produce all that shit for consumerists without wasting too much non-renewable resources (which is the same as fixing climate change)
I disagree. It's worth remembering that current trends in AI are taken from taking a model from the 1970's and adding huge amounts of data and compute power to make these models robust enough to classify high resolution photographs. It isn't the necessary outgrowth of the cognitive science(s) as is commonly touted.
It's a magic trick which preys on a person's lack of scientific understanding; neural networks seem to anticipate, "brains in vats" but we're still in the midst of learning what, "brains" "people" and, "minds" are and nothing in ML space seems to shed any meaningful light on these pressing questions. This might be partially because the questions of Mind(s) and Self(s) are open philosophical problems.
An easy refutation that, "ML can model meaning" from recent Chomsky talks: consider that a neural network can be trained on any statistically meaningful corpus of text; this includes Klingon and Elven; it also includes jibberish'. It also includes semi-random presses of a key by a person typing with their dick or the like; nothing meaningful is being captured. We have a machine that is capable of statistical analysis. This isn't a new invention.
neural nets work with any information on any task. just like your brain. except you can train/copy them relatively instantly in comparison to raising/educating a 25 year old.
I'll make you a bet that in the next 5 years we have high resolution video generation through DALL-E or the like and it's primary use case is going to be auto-generating pornographic advertisements. The Internet was developed with lofty ideals in mind; what is AI's lofty ideal? The end of labor? The end of creativity? The commodification of innovation?
You've got 50 meaningful social problems you've got to solve (education, inequality, globalization, power laws) before you've got a kind of society that can integrate automated systems into itself without creating easy to predict problems. Given historical realities it's far more likely that the great wealth created by a theoretical, "AI Summer" will be unevenly enjoyed by most people; again this is the historical norm.
The invention of the tractor didn't liberate farmers from labor. The Phoebus Cartel, "invented" planned obsolescence in modern design and we still consume, "limited life" lightbulbs partially as a result of their thinking, and for the most part the Internet hasn't fostered a generation of scientists and engineers by, "democratizing" information.
but info is democratized. tractors (wheat threshers) helped create a surplus of food and there is way less backbreaking labor present today. our standard of living is better because of technology.
I'm literally writing this from a computational biology conference where researchers are presenting on how ML accelerates the development of therapeutics to reduce human suffering:
https://www.iscb.org/ismb2022-program/abstracts/mlcsb
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[ 4.7 ms ] story [ 32.8 ms ] threadIn the last 50 years, Western civilisation learned how to do more with less. In the century before, we simply invented new and new ways of throwing more and more non-renewable resources onto all problems we had. Which isn't really all that hard to do - for as long as you may come up with sources for those resources.
Now we do better.
My point here is that even following a big Kuhnian paradigm shift you're still going to have the same human psychologies to deal with and that's precisely where, "consumerism" lives-- in consumers; the idea that, "consumerism" is somehow driven by ideology or how capitalism structures society seems to be naive in my view. Conspicuous consumption still takes place in supposedly, "destratified" societies-- see the Kim family of North Korea or rich Saudis.
https://en.wikipedia.org/wiki/Paradox_of_thrift https://en.wikipedia.org/wiki/The_Theory_of_the_Leisure_Clas...
It's a magic trick which preys on a person's lack of scientific understanding; neural networks seem to anticipate, "brains in vats" but we're still in the midst of learning what, "brains" "people" and, "minds" are and nothing in ML space seems to shed any meaningful light on these pressing questions. This might be partially because the questions of Mind(s) and Self(s) are open philosophical problems.
An easy refutation that, "ML can model meaning" from recent Chomsky talks: consider that a neural network can be trained on any statistically meaningful corpus of text; this includes Klingon and Elven; it also includes jibberish'. It also includes semi-random presses of a key by a person typing with their dick or the like; nothing meaningful is being captured. We have a machine that is capable of statistical analysis. This isn't a new invention.
the AI revolution has barely begun: https://misorobotics.com/flippy-2/
neural nets work with any information on any task. just like your brain. except you can train/copy them relatively instantly in comparison to raising/educating a 25 year old.
https://aiqc.io
I'll make you a bet that in the next 5 years we have high resolution video generation through DALL-E or the like and it's primary use case is going to be auto-generating pornographic advertisements. The Internet was developed with lofty ideals in mind; what is AI's lofty ideal? The end of labor? The end of creativity? The commodification of innovation?
You've got 50 meaningful social problems you've got to solve (education, inequality, globalization, power laws) before you've got a kind of society that can integrate automated systems into itself without creating easy to predict problems. Given historical realities it's far more likely that the great wealth created by a theoretical, "AI Summer" will be unevenly enjoyed by most people; again this is the historical norm.
The invention of the tractor didn't liberate farmers from labor. The Phoebus Cartel, "invented" planned obsolescence in modern design and we still consume, "limited life" lightbulbs partially as a result of their thinking, and for the most part the Internet hasn't fostered a generation of scientists and engineers by, "democratizing" information.
I'm literally writing this from a computational biology conference where researchers are presenting on how ML accelerates the development of therapeutics to reduce human suffering: https://www.iscb.org/ismb2022-program/abstracts/mlcsb