2,891 karma · joined February 6, 2022
* Electricity: 27%
* Industry: 24%
* Transportation: 15%
* Agriculture & land use: 11%
* Buildings: 7%
Then within electricity, data centers use about 1.5% of global electricity. Within data centers, AI accounts for somewhere between 15-20% of energy use.
So if you take 27% × 1.5% × ~17%, you find that AI is currently responsible for something like 0.07% of global fossil fuel emissions.
It definitely matters in the "every bit matters" sense, but also the numbers paint a really different picture than you'd get from statement like the one we started with.
So when people are focusing on AI above all other energy uses, it doesn't really paint an accurate picture of what's going on.
It's not crazy to think that models that learn that their creators are not trustworthy actors or who bend their principles when convenient are much less likely to act in aligned or honest ways themselves.
I have no doubt that people will use this to axe grind about they think AI is dumb in general, but I feel like that misses the point that this is mostly about data center construction contributing to GDP.
I suppose I should have said that the correlation between effort and reward has never been 1.0 and has often been a lot lower than we like to believe.
* AI is doing real work
* Humans using AI don't seem to get more done with AI than without
There is a huge economic pressure to remove humans and just let the AI do the work without them as soon as possible.
Amazon fulfillment centers are a good example of automation shrinking the role of humans. We haven't seen total headcounts go down because Amazon itself has been growing. While the human role shrinks, the total business grows and you tread water. But at some point, Amazon will not be able to grow fast enough to counterbalance the shrinking human role in the FC and total headcount will decrease until one day it disappears entirely.
If AI can do 80% of your tasks but fails miserably on the remaining 20%, that doesn't mean your job is safe. It means that 80% of the people in your department can be fired and the remaining 20% handle the parts the AI can't do yet.
Though I still am skeptical the last act with the Australia Project is possible.
The further we get away from that being true, the more precarious things become.
Remember that Mark Zuckerberg has had “AGI” for over a decade in the form of tens of thousands of human software engineers and Facebook still has barely been able to create a new successful product on their own without acquiring it from a smaller company.
That's not to say that it's better than doctors or even that it's a good way to address every condition. But there are definitely situations where these models can take in more information than any one doctor has the time to absorb in a 12-minute appointment and consider possibilities across silos and specialties in a way that is difficult to find otherwise.
Very curious about how they're pulling this off
Why would WADA ban things for which there is no evidence that they do anything?