I want to learn mathematics, physics, programming, and AI, but AI itself is making me question the point of learning anything.

[u/IshanFreecs]

I genuinely want to learn mathematics, physics, programming, computer science, and AI. I want to build a career in computer science, pursue AI research, and hopefully do a PhD someday. But lately, I've been feeling increasingly demotivated.

The problem is that I rely on AI to learn almost everything. Whenever I have a question, I ask GPT. Whenever I don't understand a concept, I ask AI to explain it. And the more I learn this way, the more I wonder: What's the point of learning anything when AI will always know more than I ever could?

Even the most basic AI models seem to possess more knowledge than I could acquire in a lifetime. And with new models becoming increasingly capable, I keep wondering whether the knowledge I'm working so hard to gain will even matter in the future.

With GPT-6, Claude Opus 5.5, Gemini 4, and other models competing to become more capable, it feels like the gap between human intelligence and AI capabilities will only continue to grow.

I want to understand the mathematics behind AI, learn physics, become a better programmer, and contribute to actual research. But sometimes I question why I'm putting in the effort when AI can explain concepts faster, write code better, and potentially solve problems that I might spend years learning to solve myself.

And even when I genuinely want to learn, I'm confused about what I should prioritize learning and whether any of it will remain valuable by the time I become proficient.

I'm not necessarily saying that learning is useless. I genuinely love the idea of understanding how things work. But I'm struggling to reconcile that curiosity with the feeling that AI might eventually outperform me at almost everything I want to become good at.

For those of you studying computer science, mathematics, physics, or AI, how do you deal with this feeling? How do you stay motivated to learn when AI is advancing so rapidly? Do you think deep technical knowledge will still matter for people pursuing AI research and PhDs, or should we be approaching learning differently now?

[u/upandended]

The purpose of learning is not "knowledge accumulation." Yes, I think AI will take over a significant portion of knowledge accumulation (memorise & recall) functions. More complex functions of learning are applying, analyzing, evaluating, creating. You can look at Bloom's Taxonomy of learning for more on this subject.

Essentially, learning and it's merits will move away from being able to recite facts, to being able to engage with the world and solve problems. Research will not be going anywhere soon. There is still so much to discover and so much we don't know yet.

There are more facets to this conversation but these are the big ones and some others have been mentioned already.

AI is not currently at any place to replace the function of researchers and academics. No matter how good it gets with all the available information there will always be more insight worth researching and generating. You might still be at a lower level of applying specialized knowledge, so AI might seem insurmountably better than you but over time you will come to realise both the merits and limitations of various tools.

My two cents.

[u/blipblapbloopblip → u/upandended]

I think your point is a little undermined by the fact you only address the information retrieval uses of LLMs, but they are increasingly capable of doing stuff as well. In my opinion we should remember that the goal of research is to extend human knowledge. We can therefore use LLMs as tools to pursue new results, learn or teach, but the final step that increases human knowledge will always be ours and will always be to learn and understand the results. That would stay true even if LLMs end up being able to direct research, which they are not at the moment.

[u/upandended → u/blipblapbloopblip]

I addressed information retrieval because that's what OP is concerned about the most. I agree, we can have a much deeper conversation about the various areas ML algorithms will touch but the primary point remains unchanged and I think what you said agrees with what I said.

[u/blipblapbloopblip → u/upandended]

Oh sure we do agree, that's why I said "a little"

[u/Magdaki]

A similar question came up just a short while ago, so you may wish to see that thread. In short, from my point, at best (or worst depending on your feelings about this), this is like to be very area dependent. Researchers aren't going away anytime soon. For my research work, language models are not very useful, and I think it unlikely they will become so anytime soon.

[u/Green-Autumn]

LLMs accumulated very broad knowledge scraped from the web and books (they didn't pay for), Knowledge is broad, not deep. They don't know better than a specialist in a field.
LLMs excel in areas where the knowledge is formalised and feedback loop is entirely computed - programming, databases, math, They cannot run an experiment and interpret results.
Some AI researchers believe LLMs will never step out of the box - create new knowledge, rather than regurgitate the patterns already found in the accumulated knowledgebase of humanity.
AI can retrieve knowledge and do things for you - you need to know what to ask and work with the results.

I was at an informal lecture by a visiting professor of physics. His message - AI minimises costs of exploring hypotheses, so now he can explore exponentially more of them.

[u/Gullible_Sweet1302]

People still learn and enjoy chess.

[u/NovaKnightOwl]

Machines have physically outperformed humans since the wheelbarrow. Should that stop us from exercising?

[u/Training-Tear9891]

IIRC, AI does not exactly know anything, it just predicts the output based on data that it was trained on. Personally, I think your approach to education itself is what demotivates you. You said yourself that, whenever you have a question, you ask an AI to solve the problem on hand, and that evokes the feeling that your learning is meaningless, because you have a magical knows-everything-box. Try searching books and reading them, watching videos on your subjects of interest. You can use AI for this purpose, btw, instead of just asking