4 ms·
But we're still nowhere near that, or even near surpassing the skill of an average person at a moderately complex information task, and GPT-4 supposedly took hu
by yunwal 4y ago
But we're still nowhere near that, or even near surpassing the skill of an average person at a moderately complex information task, and GPT-4 supposedly took hundreds of millions to train. It also costs a decent amount more to run inference on it vs. 3.5. It probably makes sense to prove the concept that generative AI can be used for lots of real work before scaling that up by another order of magnitude for potentially marginal improvements.
Also, just in terms of where to put your effort, if you think another direction (for example, fine-tuning the model to use digital tools, or researching how to predict confidence intervals) is going to have a better chance of success, why focus on scaling more?
- spaceman_2020 4y agoThere are a lot of employees at large tech consultancies that don't really do anything that can't be automated away by even current models. Sprinkle in some more specific training and I can totally see entire divisions at IBM and Accenture and TCS being made redundant. The incentive structures are perversely aligned for this future - the CEO who manages to reduce headcount while increasing revenue is going to be very handsomely rewarded by Wall Street.
- esafak 4y agoHow is that perverse? That is the logical incentive. The perverse one is that middle managers rise by hiring people needlessly and building fiefdoms.
- skyechurch 4y agoWall Street would be strongly incentivised to install an AI CEO.