As artificial intelligence outpaces human capability, the real question isn't whether machines will replace us, but how we'll find meaning in a world of abundance.
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, and make deserts by using all the water up too?”
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.
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.
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, and make deserts by using all the water up too?”
Go tell that to AlphaFold which solved a decades‑old problem in biology by predicting protein structures with near lab‑level accuracy.
It could have been done without burning the earth down to get there.
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.
Way to move the goalposts.
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.
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.
That is if it doesn’t kill us by engineering a bio weapon first.
maybe in 10000 years
I hope and doubt.