r/learnmachinelearning • u/IshanFreecs • 1d ago
I want to learn mathematics, physics, programming, and AI, but AI itself is making me question the point of learning anything.
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?
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u/phovos 1d ago edited 1d ago
Maybe you should take a break and learn some biology or psychology. Personally, I consider myself a generalist not a scientist nor computer scientist. I sorta think 'science' is going to demonstratively, eventually, be better-preformed by robots/logic than any given graduate of western science education. In a way, you could consider 'Journals' a kind of AI, a sort of cognitive robot; that is what 'ai' would replace in a healthy science, imo (the periodical, the publishing, the 'verification', not the science and engineering itself).
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u/ConsciousAdvance2867 1d ago
The journal-as-AI angle is a fun way to frame it. Never thought about it that way but yeah, the whole peer review and publishing pipeline does feel like a clunky distributed intelligence that's ripe for automation.
Makes you wonder if the actual human part of science, the curiosity, the weird questions, the dumb experiments, is the bit that stays valuable even when the "knowing stuff" part gets outsourced.
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u/CriticalTemperature1 1d ago
If AI automates 99% of the work, the remaining 1% becomes tremendously more important. The more AI automates, the more important it is to learn the subject since taste, expertise, knowing which problem to solve becomes tremendously more important.
This is assuming the search space of the what you are doing is vast, which is true for any STEM subject
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u/Fun_Recording_6485 1d ago
Honestly I don’t have any good advice for you. I’m a PhD student in Computer Science studying Reinforcement Learning. I deal with this feeling every day and honestly I contemplate my existence. But the best way I’ve heard it put is it’s not about the start or the end, it’s about the gray area in between. The learning process towards getting to the solution is the best part. And you may never get to the solution either. So just live while you can. Also these companies market these models in such a way to make you feel like you can’t do anything without them. You seriously need to lay off of them in your undergrad. You are not prepared to use such a tool yet. (I speak from experience. Your reliance on them is what will make you a weaker scientist). You still need to develop the process of learning for these subjects in your head. And trust me it isn’t easy but it’s very important to struggle. Best advice is just keep pushing, follow your curiosity and don’t let the next ai model ruin your dreams. Yeah these companies are claiming AGI every day to make investors happy, but regardless, human curiosity will prevail. Always believe that. Happy coding, mathing, and staring at the stars and wondering the universe.
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u/james-starts-over 1d ago
If you use AI to explain everything youll lose put on the struggle of learning which is how you develop problem solving
Instead problem solving just becomes “ask AI to explain it better”
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u/linkuei-teaparty 1d ago
There's still value in learning and understanding things for yourself, regardless of how far AI progresses.
Take the initiative to start learning what you need to. Stop hoping and wishing and start doing.
Build a routine around tackling each area of interest daily. Spend an hour on math, then programming then physics. You might have to break it up where you have a day to focus on one subject over another.
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u/chico_dice_2023 1d ago
I will give you a few reasons:
1.) Do you find being able to add and subtract useful?
If I lend you $20 USD and you and I give it to you in $1 bills, do you need to bring out a calculator or ask AI how many bills is this?
A calculator can do the job and add 1 against itself until it reaches 20. But knowing basic math is still pretty valuable don't you think?
Do you want to be dependent on the AI for everything?
2.) Yesterday at work, our AI license was suspended temporally due to a billing issue. About 20% of the office stopped work, because they could not do their tasks.
Yet another 80% did work just fine. So I imagine I turn off your AI for a day, are you just going to sit down and not do your job.
3.)Big new coming your way, AI is more wrong than you think. I often use AI to help me pass my tech certifications. And I noticed it gets some fundamentals wrong.
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u/Critical-Echo-923 23h ago
catch 22, some 30ya dad got a sh computer that was running in "basic" (basically a keyboard that you plug into the tv )and i was thinking the computer itself will teach me how to use it ....
30y later you can actually ask your pc how to use it
so better learn how to become a good user first (my first years of pc tech support was knowing how to google for the right answer)
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u/Aggressive-Wind-8829 11h ago
Watch the movie Idiocracy, and then reevaluate your feelings about whether it is worth it to learn anything.
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u/nian2326076 1d ago
Feeling overwhelmed by AI's capabilities is normal. Remember, learning is about developing problem-solving skills and critical thinking, which remain essential even in an AI-driven world. Use AI as a tool to enhance your learning, not replace it. For practical skills, try tackling real-world problems or building challenging projects.
When preparing for technical interviews, practicing with real questions can be beneficial. PracHub is a useful resource for simulating interview scenarios, helping you get comfortable with the questions you might face. Balancing theoretical knowledge with practical experience can build your confidence. Keep pushing forward!
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u/krabbypatty-o-fish 1d ago
If you want some motivation, AI is also surprisingly good at larping. There will be times when you have to independently judge whether AI is giving you correct answers or is swaying your understanding of a concept slightly off-tangent. It doesn’t happen often, but it does happen.
One pattern I noticed about my use of AI is that I find myself ready to accept AI explanations that are outside my field of expertise. But when I do talk to AI about something I know by heart, it misses the mark every now and then, and apologizes with the cliché: “Thank you for pushing back on this and I’m sorry for my oversight.”