This was posted 4 months ago, i.e. forever in LLM time.
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RE: https://cosocial.ca/@evan/115580076628853324
This was posted 4 months ago, i.e. forever in LLM time. I would really like to see a fully-worked through analysis of the actual GHG cost of #GenAI in general and for coding applications specifically. Including, obviously, training, data centre infrastructure, silicon fabrication, etc.
The reason: I have trouble reconciling these numbers with the insane volumes of investment capital going into the space.
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RE: https://cosocial.ca/@evan/115580076628853324
This was posted 4 months ago, i.e. forever in LLM time. I would really like to see a fully-worked through analysis of the actual GHG cost of #GenAI in general and for coding applications specifically. Including, obviously, training, data centre infrastructure, silicon fabrication, etc.
The reason: I have trouble reconciling these numbers with the insane volumes of investment capital going into the space.
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RE: https://cosocial.ca/@evan/115580076628853324
This was posted 4 months ago, i.e. forever in LLM time. I would really like to see a fully-worked through analysis of the actual GHG cost of #GenAI in general and for coding applications specifically. Including, obviously, training, data centre infrastructure, silicon fabrication, etc.
The reason: I have trouble reconciling these numbers with the insane volumes of investment capital going into the space.
But then you are moving the goal posts. Even if we could stop all construction for data centers and investment into new models, there are already inference models available on the existing infrastructure which do not take a lot of power.
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RE: https://cosocial.ca/@evan/115580076628853324
This was posted 4 months ago, i.e. forever in LLM time. I would really like to see a fully-worked through analysis of the actual GHG cost of #GenAI in general and for coding applications specifically. Including, obviously, training, data centre infrastructure, silicon fabrication, etc.
The reason: I have trouble reconciling these numbers with the insane volumes of investment capital going into the space.
@timbray @evan @timbray @evan yes, and if only one person was using LLMs for 30 minutes here and there, the usage wouldn’t be a problem. But that’s not the scale, it’s tens of millions 24x7.
And even if no one used them, the datacenters consume that power and water constantly. The servers don’t sleep sans queries. They are always running. They require massive amounts of energy and water simply to exist.
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RE: https://cosocial.ca/@evan/115580076628853324
This was posted 4 months ago, i.e. forever in LLM time. I would really like to see a fully-worked through analysis of the actual GHG cost of #GenAI in general and for coding applications specifically. Including, obviously, training, data centre infrastructure, silicon fabrication, etc.
The reason: I have trouble reconciling these numbers with the insane volumes of investment capital going into the space.
@timbray That number for LLM energy is bullshit, and the source in that thread appears to be something Sam Altman blogged, who as we know is someone who never just makes stuff up. (His post reads like ChatGPT voice, which of course it is) There is some severe weaseling be off by at least an order of magnitude—maybe the average query is "What day is it". Non-trivial queries light up 5-10kW of rack and that runs for significantly longer than seconds. This is roughly the same as a moving EV car.
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RE: https://cosocial.ca/@evan/115580076628853324
This was posted 4 months ago, i.e. forever in LLM time. I would really like to see a fully-worked through analysis of the actual GHG cost of #GenAI in general and for coding applications specifically. Including, obviously, training, data centre infrastructure, silicon fabrication, etc.
The reason: I have trouble reconciling these numbers with the insane volumes of investment capital going into the space.
@timbray Is it just me, or do the guys doing the calculations on "entire energy consumption for an LLM programmer versus a human programmer" seem worryingly close to declaring that entire subsections of the population aren't worth the energy consumption, could be replaced by "AI", and would happily suggest culling them as if the only value of a person is lines of code generated 😐
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RE: https://cosocial.ca/@evan/115580076628853324
This was posted 4 months ago, i.e. forever in LLM time. I would really like to see a fully-worked through analysis of the actual GHG cost of #GenAI in general and for coding applications specifically. Including, obviously, training, data centre infrastructure, silicon fabrication, etc.
The reason: I have trouble reconciling these numbers with the insane volumes of investment capital going into the space.
@timbray When a new data centre is built it will take resources from the utility or add its own new generation. In the Bad Place (and many other places) this means it's likely adding new fossil fuel consumption infrastructure and increasing carbon emissions. Until recently that country was matching growth in utility generation with renewables: growth was 'green'. That has changed due to their stupidity and due to unregulated new generation like Musk's data centre(s) etc.
It's a bit dumb to say cars are worse because while yes they are, in sane countries we are starting to manage that problem well with electrification, changes to the fleet.
New data centres are generally bad, because they are designed to generate slop for the enrichment of the already very harmfully wealthy class and because they require new power generation that is almost certainly not coming from renewables.
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But then you are moving the goal posts. Even if we could stop all construction for data centers and investment into new models, there are already inference models available on the existing infrastructure which do not take a lot of power.
> do not take a lot of power
@raphael ... any more...
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RE: https://cosocial.ca/@evan/115580076628853324
This was posted 4 months ago, i.e. forever in LLM time. I would really like to see a fully-worked through analysis of the actual GHG cost of #GenAI in general and for coding applications specifically. Including, obviously, training, data centre infrastructure, silicon fabrication, etc.
The reason: I have trouble reconciling these numbers with the insane volumes of investment capital going into the space.
@timbray my previous job was building greenhouse gas inventories.
Data centres are responsible for about 1% of global greenhouse gas emissions. AI is responsible for about 15% of the data centre emissions, or about 0.15% of global emissions.
People who talk about AI burning up the planet don't spend a lot of time thinking about what's really burning up the planet: fossil fuels for transportation and heating, deforestation, and cattle.
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@timbray my previous job was building greenhouse gas inventories.
Data centres are responsible for about 1% of global greenhouse gas emissions. AI is responsible for about 15% of the data centre emissions, or about 0.15% of global emissions.
People who talk about AI burning up the planet don't spend a lot of time thinking about what's really burning up the planet: fossil fuels for transportation and heating, deforestation, and cattle.
@timbray computer usage just isn't as carbon intensive a process as driving a car. Even with hundreds of billions being spent on new data centres, it's not a big part of the global emissions profile.
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@timbray my previous job was building greenhouse gas inventories.
Data centres are responsible for about 1% of global greenhouse gas emissions. AI is responsible for about 15% of the data centre emissions, or about 0.15% of global emissions.
People who talk about AI burning up the planet don't spend a lot of time thinking about what's really burning up the planet: fossil fuels for transportation and heating, deforestation, and cattle.
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@ben @evan @timbray you can start here to make estimates on bounds: https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks
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"By comparison, data centres consumed 415 TWh in 2024, roughly 1.5% of the world’s total electricity consumption (see ‘Global electricity growth’)."
Electricity accounts for about 1/3 of global GHGs, so data centres are <1% of global GHGs.
"They found that servers for AI accounted for 24% of server electricity demand and 15% of total data centre energy demand in 2024."
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Cose da fare post lavoro che sono andate fatte oggi: zero
Provo una rabbia immensa
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@angusm @dashdsrdash @cstross It may be obsolete information, but a couple of decades ago it was worked out that the US would need one million soldiers to occupy Iran and only have it be as chaotic as the occupation of Iraq. Fewer troops, worse outcomes.
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#pastpuzzle en-256
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