Menu

Post image 1
Post image 2
1 / 2
0

How to Actually Measure Your AI Workload's Water and Energy Footprint

DEV Community·Alan West·about 1 month ago
#nTxBitpQ
Reading 0:00
15s threshold

Your team just shipped an ML inference endpoint. Stakeholders are asking uncomfortable questions about environmental impact. Someone forwards a scary headline about AI boiling the oceans. Your PM wants numbers by Friday. Sound familiar? I've been there twice in the last year alone. And here's what I've learned: most of the numbers people throw around about AI resource consumption are either wildly out of context or completely made up. The real problem isn't that AI uses resources — everything does — it's that most teams have zero visibility into their specific footprint. Let's fix that. The actual problem: you're flying blind When someone asks "how much water does our AI stuff use?" most developers shrug. Fair enough — your cloud provider abstracts away the physical infrastructure. But that abstraction is exactly what makes the conversation so frustrating. You end up arguing about industry-wide estimates instead of your actual workload.…

Continue reading — create a free account

Join HashtagPLUS to read full articles, follow hashtags, vote, and join the conversation.

Read More