Then not only are you contributing to planetary destruction (through the generation of between 1.32 tons (high end models, 1 joule per token) and 84 tons (low end models, 2 joules per token) of CO₂ to power those data centres, which is about 0.2 to 12.7 times the average individual carbon footprint, with an expectation of 7 to 11 tons (Source), and the utilization of 300,000 gallons to 5,000,000 gallons of water a day to keep those servers cool, or a town’s worth of water every day!

BUT YOU ARE NEEDLESSLY WASTING 400K+ A YEAR

1. Less than 20% of AI generated code survives unscathed in a commercial enterprise software product once senior developers weed out all the security errors, boundary condition errors, and generated code that doesn’t even solve the problem. So, that’s 200K of 250K down the drain as only 20% of output is usable.

2. Having to fix AI generated slop will consume 80% of a good senior developer’s time — a developer you should also be paying 250K a year.

End result, you’ll losing 200K + 200K per developer you force AI coding tools upon!

But hey, it’s your money. If you want to p!ss it away so NVIDEA’s CEO can get richer selling more CPUs we don’t need, that’ up to you!

The linked article contains some metrics, but here are a few others.

• token prices vary widely, from an average of around 50c/M tokens on the smallest, cheaper models to $75/M tokens (or higher) for higher end “workhorse” models
• energy processing requirements per token are estimated to be between 1 joule and 2 joules
• you can buy 14.3 Trillion tokens at the median of around $17.5/M tokens (and 35 times that at the lower end)
• processing 14.3 T tokens will take about 4000 kwH @ 1 joule/token
• on an average NA grid, expect to produce 500 to 600 g of Co₂ per kWh (since most of our grids are still dirty)