Is AI actually helpful?

I used to think this. I have come to realize that is more likely to hinder progress. Two examplars why I believe this:

I have an extended family member who does plans for radiation therapy. Management has been requiring them to evaluate using an AI product to create the plans. He was actually pretty excited to do this because he is kind of tech nerd. It turns out it is actually quite good at producing plans for most patients using approaches that were popular five years ago -- guess when the thing was trained. You can say that it will be good at current plans once it gets trained on them. If humans keep doing the plans, the plans 5 years from now will be even better. If LLM-based AI does it, they will freeze at the current level forever. We are a long way from an AI that can do them now AND advance the field.

Twenty years ago, there was a big thing about an AI that could outperform radiologists reading certain x-rays. It turned out to only be true for a pre-selected subset of X-rays. And it hasn't been able to close the gap significantly in that twenty years. The existing technologies will always asymptotically approach the training set, but never exceed it. And every increment step closer costs more than the previous step. Way more. This is kind of fundamental to the technology.

As I have said other places, it is possible that someone else will come up with a new technology that will leapfrog the current stuff. Except every possible cent is being put into the LLM bubble. So there is less progress being made elsewhere than at any time in my memory, which goes back through several hype cycles. And the backlash against the overhyping of LLM-based AI will almost completely rule out real work in AI for a generation.

My own research was generally no more than brushing against AI, although I did work on two projects that were more at the heart, I had left those well before this hype cycle began in earnest. So this is not personal in that sense. I just resent the PT Barnum's of the current generation setting the field back decades for their personal enrichment and fame.

Humans adapt. AI needs to be adapted.
 
In this thread, I've been a very good girl, not telling everyone, at the top of my lungs, that AI is going to take over the world. Since no one has patted me on the back...

AI is going to take over the fucking world!!!
I would point out that humans deserve to control the whole world, because we've done such a great job with it so far!
 
Except that you said, "That was over B years ago." Now if you had said, "that was over X years ago..."

Base 8(Octal): 1,2,3,4,5,6,7,10,11,12,13
Base 10(Decimal): 1,2,3,4,5,6,7,8,9,10,11
Base 16(Hexadecimal): 1,2,3,4,5,6,7,8,9,A,B
 
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Base 8(Octal): 1,2,3,4,5,6,7,11,12,13
Base 10(Decimal): 1,2,3,4,5,6,7,8,9,10,11
Base 16(Hexadecimal): 1,2,3,4,5,6,7,87,9,A,B
Not to nitpick, but you have two mistakes in your lists
- you left 10 out between 7 and 11 in octal
- you mean 8 not 87 in the hex list
 
Ah, If I had asked if that was in 'hex' or base 16... then B would make sense. But who's talking witchcraft? (Hmm, story idea, witch A.I. programmer works only in hex...") Maybe that's you, ShelbyDawn57
 
Fat fingers.fixed. Thx.
Just because it’s nitpicking season…. it would also be more clear and informative to show the zeros/zeroes, because these numbering systems start at zero, not one. 0-1-2-3-4-5-6-7–8-9, 0-1-2-3-4-5-6-7, and 0-1-2-3-4-5-6-7-8-9-A-B-C-D-E-F

I do believe this is the forums first “argument” over wording as it pertains to numbering systems! In my toothy ten years active in the forum I don’t recall this coming up before.

Usually it’s page after page over subtle meaning differences of words. Very cool!

P.S. In honor of the autocorrect/spellcheck thread I decided to leave “toothy” alone. I was typing “lengthy”.
 
Fat fingers.fixed. Thx.
Completely understandable. I was probably more attuned to the mistakes because I had taught my firsts how to work in binary, octal and hex yesterday afternoon. There is always an interesting range of reactions from them to seeing this the first time, and finally understanding things like what hex codes for colors actually mean. And little mistakes like that will lead to untold hardships as they try to build a mental model that works around silly mistakes.
 
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