That is if it doesn’t kill us by engineering a bio weapon first.
Comment on AI Won't Solve Your Existential Crisis (And That's Perfectly Fine)
SweetCitrusBuzz@beehaw.org 1 day ago
It won’t solve anything except “How do we slowly kill off most life on this planet by using too much energy from power plants that spew awful chemicals into the air.”
Perspectivist@feddit.uk 1 day ago
It won’t solve anything
Go tell that to AlphaFold which solved a decades‑old problem in biology by predicting protein structures with near lab‑level accuracy. Overnight it gave researchers the 3D shapes of almost every known protein, something humans couldn’t crack, and it’s already speeding up drug discovery and enzyme design.
belated_frog_pants@beehaw.org 1 day ago
It could have been done without burning the earth down to get there.
SweetCitrusBuzz@beehaw.org 1 day ago
Oh yes, and how many chemicals did it cause to spew out and how much water did it deplete? That solution won’t matter if life is dead anyway.
Perspectivist@feddit.uk 1 day ago
If you take that question seriously for a second - AlphaFold doesn’t spew chemicals or drain lakes. It’s a piece of software that runs on GPUs in a data center. The environmental cost is just the electricity it uses during training and prediction.
Now compare that to the way protein structures were solved before: years of wet lab work with X‑ray crystallography or cryo‑EM, running giant instruments, burning through reagents, and literally consuming tons of chemicals and water in the process. AlphaFold collapses that into a few megawatt‑hours of compute and spits out a 3D structure in hours instead of years.
So if the concern is environmental footprint, the AI way is dramatically cleaner than the old human‑only way.
t3rmit3@beehaw.org 10 hours ago
LLMs, sure.
Neural Networks in general though are massively useful, and NNs being trained for e.g. medical diagnostics or scientific research are miniscule in their energy footprints compared to LLMs, can be incredibly accurate (even beyond people), and open up tons of avenues for research that the extant budgets just couldn’t support.