A goodish portion of medicine is applying an algorithm to a set of circumstance. A large potion of the critical thinking has already been done for you. You just need to isolate which algorithm applies when.
The very best doctors (from a very, very good doctor), are interlocutors, teasing out what isn't obvious from what the patient is presenting an piecing out a narrative of what makes sense.
The critical thinking is much after.
If this stupid-ass AI bubble makes governments rush to add lots of nuclear power capacity which will soon have no AI data center to feed, maybe something good could accidentally come from it?
M-Disc is built with the intention of lasting a thousand years. The data layer is a stone-like material.
Are you saying it's comparable to Kodak sitting on their digital camera patents from the 70's to avoid knocking film profits even if other camera firms are dabbling in digital?
You'd be surprised.
Beyond the nuts and bolts of how to do a thing, there is a fair bit of nuance and institutional knowledge that goes into any job, that isn't apparent from a set of directives.
Sometimes it takes the form of best practices. Sometimes it is knowing what wheel to grease to get something done.
Individually, they may not amount to much, but in totality they make the difference between something running smoothly and pulling your hair out.
And even in the face of this context matters, which is why LLMs make such obvious errors like putting glue on pizza and Carl generally doesn't.
I keep hearing that people are abandoning Plex but some people are clearly leaving themselves vulnerable to future Plex-user pratfalls because this stuff keeps happening.
Much of the critique seems irrelevant to AI other than LLMs, such as self-driving cars which map visual input to actions.
Well that's a scary thought in a world where people have to sell their labor to survive...I hope you're wrong but I fear you may not be.
Half of the human population doesn't think either, they just echo their favorite chamber.
I'm reminded of what the Benetton F1 team did when rules specifically prevented teams from using wheel speed and gear information to run traction control systems. Instead they used a combination of incoming air stream pressure (similar to how an aircraft's pitot-static system works) in combination with some preloaded per-event data and track position information to make another traction control system that did the same job.
Information about past leases and public data from competing landlords might still be enough to do the job.
Why doesn't Nvidia make more specific chips to compete with Google on such server farms? They have the cash.
An LLM may be an ingredient, but the current commercial approach of trying to just build an LLM so big that it magically becomes an AGI somehow (or I think the idea may be to make a stochastic parrot good enough to be hard to distinguish from an AGI) sure doesn't look anything like a path, especially when the returns are diminishing so hard.
The easiest way to figure the cost of living is to take your income and add ten percent.
