> Training GPT-4 used 50 GWh of energy. Like the 20,000 households point, this number looks ridiculously large if you don’t consider how many people are using ChatGPT.
> Since GPT-4 was trained, it has answered (at minimum) about 200,000,000 prompts per day for about 700 days. Dividing 50GWh by the total prompts, this gives us 0.3Wh per prompt. This means that, at most, including the cost of training raises the energy cost per prompt by 10%, from 10 Google searches to 11. Training doesn’t add much to ChatGPT’s energy cost.
How does people using it offset the amount of energy used to train it? If I use three hundred pounds of flour learning to make pizza, the subsequent three hundred pounds of flour I use making delicious pizzas doesn't make the first 300 go away. Am I misunderstanding the numbers?
Its not offset, its amortized.
Your effective flour / pizza is (300 + 300) / num_pizzas.
The total marginal flour expended will go up as you make more pizzas, but the effective cost will actually go down as the upfront cost is amortized over lifetime usage.
You don’t misunderstand the numbers, you misunderstand the point. If you flush your pizzas down the toilet, it’s a waste. If you feed 300 people with it, it’s not, even if you end up using the same amount of ingredients.
If you're able to serve delicious pizzas afterwards, it was worth wasting the first kg (you might call it an investment).
If you're able to bring value to millions of users, it was worth to invest a few GWh into training.
You might disagree on the usefulness. I think, you shouldn't have wasted a kg of flour because I won't ever eat your pizzas anyway. But many (you, your guests, ChatGPT users) might think it was worth it.
It doesn't make it go away. Using your analogy - if you used 300lb to learn and then only made 10 lb of pizza after that, it would be a pretty poor use of resources.
If you instead went on to produce millions of pizzas for people and 30,000lb of flour, that 300lb you used to learn looks like a pretty reasonable investment.
See my other comment here. One AI training run does not exist in a vacuum. Do you think they built billions of dollars in datacenters full of computer power just to let it sit idle?
> Training GPT-4 used 50 GWh of energy. Like the 20,000 households point, this number looks ridiculously large if you don’t consider how many people are using ChatGPT.
> Since GPT-4 was trained, it has answered (at minimum) about 200,000,000 prompts per day for about 700 days. Dividing 50GWh by the total prompts, this gives us 0.3Wh per prompt. This means that, at most, including the cost of training raises the energy cost per prompt by 10%, from 10 Google searches to 11. Training doesn’t add much to ChatGPT’s energy cost.
https://andymasley.substack.com/i/162196004/training-an-ai-m...