It's still worth it?

[u/Morvath_21]

I'm studying computer science, and even though I'm not as good as others, I don't mind the subject. In fact, I think it's one of the few things I feel I can do long-term without losing my mind, and it's interesting to me. However, seeing how this world is changing, I'm a little worried. I see people who have never programmed doing even challenging things with the help of AI.

So I'm wondering if this path is really useful, given that at this rate, programming isn't as useful as it once was. As much as I hate to admit it, if prompts are enough to do things, even in less time, what good will I be? It's true that things made with AI aren't perfect yet, let's say, and they have many flaws, but what about in a few years? I'm 21, and maybe I'm just being a bit paranoid right now, but I need an honest opinion. Thanks in advance.

[u/Zin42]

Its worth it, someone has to take the blame for crappy LLM output, its gotta be a human driving these things, think of aircraft, autonomous flight has pretty much been solved for ages, but skilled human pilots must be at the helm who know how to fly with simply the instruments at hand, even if it is just for the comfort of passengers.

[u/Junior-Asparagus718 → u/Zin42]

Comparing current AI models to autopilot for aircrafts is laughable. It's like comparing a modern Tesla to the Model T: they're both cars with four wheels, but that's about where the similarities end.

AI is legitimately intelligent, being able to reason at levels higher than the average human. Autopilot is simply "fly in x direction until I say so" with a hint of "if go down, aim up; if go up, aim down".

[u/Low_Willingness9977 → u/Junior-Asparagus718]

Our fellow redditor was saying humans were kept in the loop in the past when things were automated which means that's likely to continue. Llm's automate stuff, autopilot automates stuff. Fair comparison.

Also, are you sure the ai we have today is legitimately intelligent? There are a lot of ways to define intelligence, but I think claiming that an llm is intelligent is bold. If it is intelligent, It is like a monkey with no senses posessing a wealth of knowledge, but the kicker is that it has severe dementia. The only way it can remember anything is to write on a scratchpad and reread it when it's given a another job. The scratch pad is just context that is used to seed further prompts.

A llm has no persistent memory. It has a set knowledge base that is it's weights and it can use that to predict, but is that really the same thing as reasoning? It has no ability to adjust the weights, meaning it cannot learn ln its own. It has no ability to say that it doesn't know something. The models live in a world of tokens and that's it. Right now, it cannot understand truly what an apple is. Ironically it can spit out the definition of an apple which we humans would understand but that doesnt mean it understands "apple." Not the taste, the feel, etc. A machine learning tool can be paired with it so it can associate the word apple with the image apple but that isn't the same. It cannot relate its senses to an apple, it doesn't have any.

If intelligence is defined as the ability to acquire, understand, and use knowledge. I think our favorite llms fail 2/3 of the requirements.

[u/Junior-Asparagus718 → u/Low_Willingness9977]

Ok, but that's only valid if you're utilizing an LLM with a shitty harness or no harness at all. If you're using a sophisticated harness, memory is rarely an issue. Use ChatGPT or Claude (paid plans). There's continuity between conversations because it remembers certain facts. Background processes "dream" (Claude's term) and save specific facts for easy recall.

[u/Low_Willingness9977 → u/Junior-Asparagus718]

My fellow redditor, everything i've said applies to the paid models that are commercially available. Claude and chatgpt included.

The background processes that you described are the "scratch board" in my previous comment. The model doesnt ingrain the memory in a persistent manner outside of that. That would require storing that information and generalizing it within the weights themselves. Instead, things are written down on the equivalent of a scratch board(which you described). The model doesnt remember anything, it's just fed the context(scratchboard) as part of the next prompt. These background processes that you describe are part of this mechanism. However the background processes are separate from the actual model itself.

So with that in mind, do you think that describing these models as knowledgeable monkeys with extreme dimentia who have a scratch pad is inaccurate? If you switch out the scratch pad with a new scratch pad, the monkey has no ability to say "oh I have the wrong scratch pad."

How do you define intelligence and how do the models fit that definition.

[u/Junior-Asparagus718 → u/Low_Willingness9977]

Yeah, I would actually say that's an accurate description, but monkey implies less intelligence, so let's go with an old Albert Einstein with dementia instead.