how much would you pay for a prompt that could cure cancer? if you're a pharma company you would pay millions to get there days faster than your competitor. as intelligence rises the marginal value it can deliver rises with it.
Something like curing cancer (more realistically, curing a specific kind of cancer) has to interact with much slower real-world processes. The most expensive part of drug development is Phase 3 clinical trials in humans. Even the smartest model in the world can't accelerate that meaningfully. Even much earlier when drugs are just testing in cell cultures, it's a lot slower to run lab tests than to run software tests or mathematical proof checkers.
Or to put it another way, there's enough natural variation in real-world bottlenecks that no pharma company can assume they'll beat competitors to market by using a smarter model.
A really smart model could significantly improve the pharma business if it could identify promising approaches to cancer treatment that are less likely to fail in clinical trials, but I don't think that the frontier labs have data to make that work yet. Much of the biomedical literature is poorly reproducible ("replication crisis") and much of the drug-development-specific data is proprietary, never published in the first place.
I do have hopes that general laboratory automation will go faster with LLM assistance, even if all the LLM does is write Python glue scripts to enable custom workflows and instrument integrations.
Something like curing cancer (more realistically, curing a specific kind of cancer) has to interact with much slower real-world processes. The most expensive part of drug development is Phase 3 clinical trials in humans. Even the smartest model in the world can't accelerate that meaningfully. Even much earlier when drugs are just testing in cell cultures, it's a lot slower to run lab tests than to run software tests or mathematical proof checkers.
Or to put it another way, there's enough natural variation in real-world bottlenecks that no pharma company can assume they'll beat competitors to market by using a smarter model.
A really smart model could significantly improve the pharma business if it could identify promising approaches to cancer treatment that are less likely to fail in clinical trials, but I don't think that the frontier labs have data to make that work yet. Much of the biomedical literature is poorly reproducible ("replication crisis") and much of the drug-development-specific data is proprietary, never published in the first place.
I do have hopes that general laboratory automation will go faster with LLM assistance, even if all the LLM does is write Python glue scripts to enable custom workflows and instrument integrations.