One thing about these numbers that's absolutely shocking to me is how low the energy use is:
> That model’s usage was well within our budget ($68, about 4kWh of energy use / 365 grams of carbon emissions).
The energy cost is literally 1% of the total cost. For context, 4kWh of energy would drive you about 15 miles in an EV, about half of the average person's daily driving miles. It's boiling 10 gallons of water.
With the talk of AI data centers' impact on the world, you'd think this would be 10x to 100x the amount of energy in order to get the effects they're using here.
My takeaway: the AI data center buildout is an overbuild probably at least as large as the fiber buildout that left us with so much dark fiber. If not even bigger. The only thing that will save the economy is the inability of NVIDIA and chip fabs to produce enough chips to match the buildout planned.
Whil training used a lot of energy, it is quite difficult to comprehend how that measures up in global terms.
The last numbers I saw for training a frontier model used as much energy as four fully fueled up Boeing Pegasus (of which there are 113)
The Erin Brokovich data center site describes the use as something like the lifetime use of 5-6 cars, which sounds like a lot when you're filling the tank, but hardly anything when you think about how many cars there are.
epistasis · · focus · HN ↗
> That model’s usage was well within our budget ($68, about 4kWh of energy use / 365 grams of carbon emissions).
The energy cost is literally 1% of the total cost. For context, 4kWh of energy would drive you about 15 miles in an EV, about half of the average person's daily driving miles. It's boiling 10 gallons of water.
With the talk of AI data centers' impact on the world, you'd think this would be 10x to 100x the amount of energy in order to get the effects they're using here.
My takeaway: the AI data center buildout is an overbuild probably at least as large as the fiber buildout that left us with so much dark fiber. If not even bigger. The only thing that will save the economy is the inability of NVIDIA and chip fabs to produce enough chips to match the buildout planned.
etdznots · · focus · HN ↗
Lerc · · focus · HN ↗
The last numbers I saw for training a frontier model used as much energy as four fully fueled up Boeing Pegasus (of which there are 113)
The Erin Brokovich data center site describes the use as something like the lifetime use of 5-6 cars, which sounds like a lot when you're filling the tank, but hardly anything when you think about how many cars there are.