Ready to navigate global policies? For Musk, physics is the arena where first-principles thinking is unavoidable, assumptions are tested against reality, not convenience. They are arguing that maths is not a hurdle but a filter; computer science is not about writing code but about structuring thought; and difficulty, far from being a flaw in education, may be its last remaining quality check.In an age obsessed with shortcuts, these voices are making an unfashionable case: that the hardest subjects still matter—not despite artificial intelligence, but because of it.

It means that understanding foundational systems now carries outsized impact later. “I chose computer science because I had a passion for it. Here, we examine why some of the world’s most influential tech figures are pushing students back to maths and core computer science at the very moment many are tempted to move away.Pavel Durov: Maths trains independenceThe provocation began quietly.

The first skills to flatten are those based on repetition: Syntax memorisation, framework fluency, surface-level coding competence. He framed it as a discipline that forces independent thinking. They are not urging students to chase the newest programming language or master the trendiest AI tool.

He is arguing that as systems grow more complex—rockets, autonomous vehicles, large-scale AI—the penalty for shallow understanding becomes catastrophic.In the AI era, Musk’s message was stark: tools is expected to change weekly; first principles endure.Sam Altman: High-leverage momentBy late 2025, a different anxiety had taken hold: that AI had made computer science itself a poor academic bet.

“If you’re a student choosing what to focus on, pick mathematics,” he wrote. It was kind of a no-brainer for me. I guess you could say I was also lucky because I was also in such a transformative field,” he said. In an age of generative AI, where models such as Gemini and ChatGPT can write and debug code, that distinction matters more than ever.

The real value of those subjects, Hassabis argued, lies not in the content itself but in the cognitive training they impose: precision, patience, and the ability to wrestle with problems that resist quick solutions. The AI is probably even better at comparative literature, just to be perfectly honest anyway.”His point was twofold: Don’t flee STEM out of fear of automation, and don’t assume AI’s current performance undermines the value of structured learning.If you ignore the fame…Fame is a distraction.

What still refuses to automate is judgment: Spotting the bad assumption, knowing when an answer is plausible and when it is polished nonsense. Over the past year, an unlikely consensus has now emerged among global tech leaders. Speaking at Stanford University in a public conversation with cryptography professor Dan Boneh, OpenAI CEO Sam Altman addressed that fear head-on.“This is a really cool time to be studying computer science,” Altman said.

“High leverage” does not mean easy returns. “They taught me how to think deeply and rigorously—and how to persist when things were hard.”He returned to the theme later that year at public forums, cautioning students against abandoning maths and theory simply because AI tools appear to make them redundant.

No emojis, no caveats.Durov did not frame mathematics as a guarantee of employment. Brin’s emphasis on curiosity rather than credential chasing was deliberate. Structural understanding is expected to compound.Demis Hassabis: The discipline of difficultyIf Altman speaks as a strategist, Demis Hassabis speaks as a product of academic rigour.

In mid-2025, Telegram founder Pavel Durov posted advice aimed at students weighing their options in an AI-dominated future. “It’s a high-leverage moment, especially if you’re interested in AI.”Altman’s phrasing was deliberate. Take the celebrities out of it — Musk tossing “physics with maths” like it is a mic-drop, Altman selling computer science as a “high-leverage” bet from a Stanford stage, Hassabis sounding like the class topper who actually enjoyed theoretical CS, Brin reminding everyone he picked CS because he genuinely liked it — and the argument stops being glamorous.

For a generation raised on speed and shortcuts, the conclusion feels obvious: perhaps computer science has now peaked; perhaps maths is finally optional.That conclusion is wrong and the people who know it best are the ones who helped build the systems causing the panic. Secure your overseas future.

AI is not stealing intelligence, it is bulk-discounting the easier bits of it. It is a warning about where value is draining out of the system. AI is not eliminating intelligence, it is commodifying the mechanical parts of it. Artificial intelligence now writes code faster than students can learn it.

Replying publicly on X, Musk wrote: “Physics (with math).”The two words were not a curriculum. AI, in Altman’s telling, is not replacing computer science; it is concentrating power in the hands of those who understand how these systems are built, constrained, and deployed.For students, the implication is uncomfortable but clear: shallow familiarity is expected to age badly.

That is why they keep returning to maths and core CS. Maths is the language that makes that testing precise. Get expert guidance now!End of ArticleFollow Us On Social MediaPhotostoriesBaby names as beautiful as a melody‘Sheila Ki Jawani’, ‘Munni Badnaam Hui’, ‘Baby Doll’: Bollywood item songs that broke the internet with their zany lyricsRanbir Kapoor's ‘Badtameez Dil’ to Nora Fatehi's 'Dilbar': Iconic dance steps from Bollywood songs everyone still tries to copyFrom Mrunal Thakur's 'Do Deewane Sehar Mein' to Preity Zinta's 'Kal Ho Naa Ho': Meet Bollywood's queens who won hearts with geeky looksFrom Smriti Irani to Amar Upadhyay: How much the Kyunki Saas Bhi Kabhi Bahu Thi star cast earns per episode12 traditional dishes that are must-try in KochiTop shows to binge-watch this week on Prime VideosKobe Bryant's inspirational quotes for childrenAncient Devi Mantras as per Your Birth DateTamil Nadu temples get a lift: Preserving history, beating floods123Hot PicksSilver price todayBudget 2026Karnataka DGP ScandalGold price predictionNitin NabinPublic holidays January 2026Bank Holidays JanuaryTop TrendingMatthew StaffordDraymond GreenOskar Sundqvist InjuryAndrew CallaghanAtlanta Braves RumorsRoger FedererKlay ThomponJohn Harbaughs WifeBengaluru WeatherDC Robert SalehTired of too many ads?go ad free nowTrending StoriesIn EducationEntire WebsiteIf you are passionate about something, there is always a market for it: How Logan Paul is teaching Gen Z to hustle smartWho leads the world in maths?

It solves equations without showing its work. He pointed out that his own journey — from a Stanford graduate student to co-architect of Google — was driven by interest, not fear-based career calculus. In a 2025 conversation on the Lex Fridman podcast, the Google DeepMind CEO reflected on the formative impact of his education.“I took some very difficult math and theoretical computer science courses,” Hassabis said.

Instead, they are pointing insistently backwards to subjects many students are eager to escape: Mathematics, computer science fundamentals, physics, and theoretical thinking.This is neither nostalgia, nor academic romanticism. In an era where answers arrive instantly, the capacity to sit with uncertainty becomes a competitive advantage.Sergey Brin: Passion and caution in the AI eraAt a time when students are hearing two conflicting narratives — AI is expected to replace jobs and AI is expected to replace degrees — Google co-founder Sergey Brin offered one of the most grounded responses in January 2026 while speaking to a new generation of engineers at Stanford University.His words were simple but layered.

Importantly, Brin did not stop at passion. When Musk says “physics (with math)”, he is rejecting surface competence. With characteristic candour, he quipped, “I wouldn’t go off and switch to comparative literature because you think the AI is good at coding. What survives, and in fact becomes rarer, is the ability to reason from first principles, to model a problem abstractly, to understand why a system behaves the way it does when it fails.That is why some of the sharpest minds in technology are now sounding almost conservative.

In fact, it starts being annoyingly sensible. Maths, as he has now often argued, does not allow the luxury of imitation. The stuff that once passed as skill — routine coding, formula application, template thinking — is now a vending machine. He also addressed the anxiety about automation head-on.