Contemporary Polymaths – Who is Elon Musk?

Toward the top of any list of contemporary polymaths, you will find Elon Musk. Not only does he tick all the right boxes, but he is constantly in the news … how could you miss him? However, we have thought long and hard about whether to include him in our pantheon of contemporary polymaths.

So who is Elon Musk? We asked ChatGPT to compile a list of the most common adjectives used to describe him in published articles or commentary. In rank order from 1 to 5, it gave us polarizing, eccentric, controversial, combative and visionary.

We (the authors) thought of him as a technology visionary (and probably still do) but now profoundly disagree with many of his recent positions. However, when considering whether to write about him we looked to the Royal Society in their recent decision not to open formal misconduct proceedings against Musk (a fellow since 2018).

The council said that “making judgements on the acceptability of the views and actions of fellows, particularly those that might be regarded as political, could do more harm than good to the Society and the cause of science in general.” They worried that ejecting a high-profile fellow for his opinions—even if many find those opinions objectionable—would entangle the society in partisan battles and weaken public trust in its neutrality. Such a move could be read as ideological gate-keeping, potentially eroding broader confidence in objectivity. That said … on we go!

So, Elon Musk fits the classic definition of a polymath - a person who repeatedly masters new domains well enough to move the frontier forward. From online banking to rockets, brain–computer interfaces to social-media juggernauts and tunnels … Elon Musk has shown an uncanny ability to leap between industries, absorb first principles, and build commercially viable, society-shaping products. The scale and diversity of those achievements make him a useful living case study in polymathic practice.

Musk’s childhood in South Africa was steeped in reading—sometimes up to ten hours a day—and his autodidactic habit has never left him. He famously ploughed through the entire Encyclopaedia Britannica before his teens and consumed two books a day during school holidays, developing the broad mental map that later let him cross-pollinate ideas. At age ten, he developed an interest in computing and video games, teaching himself how to program from a manual. At 12 he wrote and sold the video game Blastar (for ~$500), teaching himself BASIC. Years later, he would still attribute much of his range to voracious reading and a willingness to “teach yourself anything.”

After selling his first company Zip2, Musk poured the proceeds into X.com, an online bank that introduced person-to-person payments and fee-free accounts at a time when most consumers still distrusted online finance. A 2000 merger produced PayPal, which Musk briefly led as CEO before the $1.5 billion sale to eBay in 2002. The exit gave him both capital and confidence to tackle far riskier fields.

While most of us are familiar with Musk’s various interests … it is useful to consider Elon Musk’s polymathic traits through the lens of the various businesses he is involved with.

The Final Frontier?

In 2002, Musk began his quest to send the first rocket to Mars—an idea that would eventually become the aerospace company SpaceX. After visiting a number of aerospace manufacturers around the world, Musk discovered the cost of purchasing a rocket was astronomical—up to $65 million. Given the high price, he began to rethink the problem.

“I tend to approach things from a physics framework. Physics teaches you to reason from first principles rather than by analogy. So I said, okay, let’s look at the first principles. What is a rocket made of? Aerospace-grade aluminum alloys, plus some titanium, copper, and carbon fiber. Then I asked, what is the value of those materials on the commodity market? It turned out that the materials cost of a rocket was around two percent of the typical price.”

Lacking an aerospace background, he cold-called experts, devoured textbooks, and held week-long design sprints until he could debate nozzle expansion ratios with veteran propulsion engineers. Instead of buying a finished rocket for tens of millions, Musk decided to create his own company, purchase the raw materials for cheap, and build the rockets himself. SpaceX was born. Within a few years, SpaceX had cut the price of launching a rocket by nearly 10x while still making a profit. Musk used first principles thinking to break the situation down to the fundamentals, bypass the high prices of the aerospace industry, and create a more effective solution[1].

The result: the first privately built rocket to reach orbit (Falcon 1, 2008), the first privately built spacecraft to berth with the ISS (Dragon, 2012) and the first reusable orbital-class booster (Falcon 9, 2015). Reuse slashed per-kilogram launch costs by an order of magnitude. SpaceX’s stainless-steel Starship system, now deep into flight-testing, is slated to perform an uncrewed lunar landing demo for NASA’s Artemis program later this year, followed by a crewed mission a few years later, validating Musk’s bigger bet that rapid iteration and vertical integration can out-innovate traditional contractors.

Flicking The Switch On Electric Vehicles

Musk joined Tesla in 2004, turning a niche EV startup into the world’s most valuable automaker, then folded SolarCity into Tesla Energy to close the loop from solar generation to battery storage and electric mobility. The company’s recent pilot of driverless robotaxis was the latest step toward Musk’s pledge of “millions of Teslas driving themselves” by 2026—a pledge analysts greet with both skepticism and awe, but one that again shows Musk’s appetite for marrying AI, hardware and manufacturing economies of scale.

Musk congratulated Tesla's artificial intelligence and chip design teams on the launch with a post on X .. writing that it was "culmination of a decade of hard work" and that "both the AI chip and software teams were built from scratch within Tesla." He also said that customers would pay "a $4.20 flat fee" for rides in Tesla robotaxis.

2025 has of course not been a great year for Tesla – its sales are down because of intensifying competition, an aging model lineup, and signs of brand fatigue, as well of course the fall-out of Musk’s foray into politics. Bumper stickers that claim “I bought this before Elon went crazy” or satirical bus shelter ads advertising Tesla’s “Swasticar – goes from 0 to 1939 in 3 seconds” are not a good look.

Also, since we drafted this article Tesla has apparently closed down its own AI Supercomputer and is experiencing something of a brain drain[2]. The story moves on very quickly these days!

Getting Inside Your Head!

While most CEOs were still digesting the iPhone, Musk co-founded Neuralink (2016) to create high-bandwidth brain–computer interfaces. February 2024 saw Neuralink’s first human patient control a computer cursor by thought alone after a coin-sized chip was implanted via a surgical robot. Critics worry about safety; technologists marvel at the data-pipeline redesign from neurons to silicon. Either way, Musk again jumped domains—this time into neuroscience and medical devices—by leaning heavily on first-principles reasoning and recruiting top academics

Never a Dull Moment

The Boring Company has completed several tunnelling projects, most notably the Las Vegas Convention Center (LVCC) Loop, a 1.7-mile underground transportation system – actually a tunnel through which Tesla cars move people to points around the convention center. Las Vegas has agreed plans for much expanded loop spanning 104 stations and 68 miles – the Vegas network will connect the Strip, airport and the University of Nevada. While they've had some success with this project and a few others, many proposed projects have been shelved or cancelled.

xAI And Grok

In December 2015 Elon Musk co-founded OpenAI, pledging up to $1 billion and serving as co-chair, yet ultimately contributed less than $45 million before resigning from the board in February 2018 after directors rejected his plan to merge the lab with Tesla or give him control of a new for-profit arm. He was a critic of OpenAI’s 2019 shift to a capped-profit structure and its deep partnership with Microsoft, casting the move as a betrayal of the original “open” charter. In February 2024 Musk sued OpenAI, Sam Altman and Greg Brockman in California state court for allegedly abandoning that mission, but he abruptly withdrew the suit four months later, just ahead of a dismissal hearing.

Musk re-entered the AI arena with xAI in 2023. Shifting his focus to the AI arms race, in 2024 he established “Colossus”, an xAI supercomputer facility in in Memphis designed to power and train Musk's AI chatbot Grok. Colossus is slated to be the world's largest supercomputer.

It hasn’t all been plain sailing. A few weeks ago, when invited to be less politically correct, Grok went on a wild anti-Semitic rant and seemed to launch an Adolf Hitler appreciation society all on its own (MechaHitler indeed!). This seems some way from the company’s stated aim of building AI specifically to advance human comprehension and capabilities, and we can look askew at the notion that “Grok is your truth-seeking AI companion for unfiltered answers”. It certainly was unfiltered. It just goes to show that the path toward all-encompassing and far-reaching knowledge is not as smooth as it might be.

X (formerly Twitter): A Public-Square Experiment in Real Time

And finally, Musk’s $44 billion acquisition and July 2023 rebrand of Twitter to “X” merged social media with his broader “everything app” vision. X/Twitter is still among the top 6 social networking apps in the United States and boasts over 500 million users worldwide, and as such the platform remains a nerve center for news, politics and, increasingly, AI-powered features like Grok-assisted search BUT the loosening of controls on extreme speech and misinformation has left many to describe it as a ‘toxic’. A notable decline in users and famously advertisers heading for the door have had an impact. Axios estimates that X (formerly Twitter) is now ‘only’ worth $12.5billion. That is an extraordinary erosion of value in 3 years. The bold, sometimes chaotic re-tooling illustrates both the upside and reputational risk of overreach.

But focusing on the positives … there are patterns behind Musk’s polymathic output which are worth examining:

Mission Framing. Colonizing Mars, accelerating sustainable transport, bridging thought and machine—grand narratives magnetize top talent and patient capital.

First-Principles Decomposition. Musk begins by reducing a system—rockets, cars, neurons—to its fundamental physics or economics, then reconstructs solutions unconstrained by legacy costs. His oft-quoted description of pricing a rocket by the literal commodity cost of aluminum and carbon fiber epitomizes the method.

Compounding Knowledge. Each venture builds toolkits for the next: battery expertise from Tesla informs Starship power systems; Starlink’s mass manufacturing teaches Neuralink about wafer-scale integration; Grok leverages text data from X.

Iterate Relentlessly. Whether through Falcon 9 rapid reuse or a weekly “code yellow” at X, Musk biases toward releasing imperfect versions fast, gathering telemetry and improving on the fly. Musk really is an advocate for ‘building the plane whilst you fly it’. That said, the changes that led to Grok’s recent outbursts perhaps suggest a limit to this.

Self-Education & Mental Model Transfer. A lifetime of wide reading fuels analogies across domains, letting him import agile software tactics into aerospace or layer battery economics onto home-energy storage.

Is it easier to indulge polymathic tendencies when you are incredibly wealthy? It clearly has its advantages. You can buy back hours you’d otherwise spend earning a living, freeing you up to read, experiment, or study new fields. Failed side-projects rarely threaten basic needs, so you can tackle bolder, longer-horizon ideas. Money gives you access to resources … labs, tools, mentors, data sets, travel all cost money and can speed the climb up a learning curve. Similarly, you can hire or partner with domain experts, absorbing know-how far faster than going it alone; and investors, academics, and media are likelier to return your calls if you already have a track record and capital behind you. That cocktail explains why billionaires—from Elon Musk to Richard Branson—can spin up aerospace outfits, AI labs, or medical-device ventures faster than most mortals. So, yes money helps—but it isn’t the whole story.

Leonardo da Vinci, Benjamin Franklin, Émilie du Châtelet, Ada Lovelace, and Srinivasa Ramanujan each made cross-domain contributions with modest personal fortunes (or none at all). Open-access journals, MOOCs, preprint servers, YouTube lectures, and ChatGPT-style tools let anyone acquire graduate-level material for little or no cost. And curiosity, grit, and a habit of first-principles thinking correlate more strongly with polymathic output than bank balance alone. Money can amplify those traits, but it can’t substitute for them.

Practical tips if you’re not fantastically rich

1. Time-box learning sprints. Devote one evening a week to a domain you know little about. Consistency compounds faster than sporadic deep dives.

2. Leverage “found time.” Audiobooks or podcasts convert commutes and workouts into interdisciplinary study sessions.

3. Use open tools. Start projects on free tiers of GitHub, Colab, or Replit; prototype hardware with Arduino; analyze data with public datasets.

4. Publish in public. Blogs, Twitter/X threads, and open notebooks attract feedback and collaborators, accelerating learning without spending money.

Wealth acts like an amplifier: it magnifies whatever curiosity, stamina, and strategic thinking you already possess and smooths the friction of switching domains. But the core drivers of polymathy—insatiable learning, disciplined experimentation, and the courage to risk being a novice again—remain free. Even on a shoestring, you can cultivate breadth by exploiting today’s unprecedented access to knowledge, communities, and low-cost tools.

Given that, what (positive) lessons can we learn from Elon Musk that we can apply to cultivate our own polymathic mindset:

Read Widely, Not Just Deeply. Devote a slice of your reading diet to fields far from your day job—biology, history, design—so when problems arise you have a larger idea inventory to cross-reference.

Practice First-Principles Drills. Take a recurring cost or bottleneck in your work. Strip it to raw materials, time and energy inputs, and ask: “If I were rebuilding from scratch today, what would physically stop me from doing this 10× cheaper or faster?”

Prototype Fearlessly, Refine Publicly. Launch v0.1 projects—whether a blog, micro-product or data analysis—collect feedback, iterate. The cycle time teaches more than months of stealth preparation.

Synthesize Skill Stacks. Instead of betting everything on a single expertise, layer complementary skills (e.g., statistics + design + communication). The overlap niches produce asymmetric leverage.

Anchor to a Mission, Not a Job Description. A clearly articulated “why” attracts collaborators and bolsters tenacity when you pivot between disciplines. Musk’s companies survive brutal execution phases because employees buy into Mars, not just mezzanine financing rounds.

Cultivate Systems Thinking. Map entire value chains—suppliers, regulators, customer psychology—so you can spot non-obvious choke points where a small invention yields outsized impact.

Accept Calculated Risk. Polymaths embrace uncertainty as tuition. Musk wagered his PayPal proceeds on rockets; your version might be a weekend project, career shift, or public speaking class. Start proportionate to your means, but start.

Elon Musk’s story is not a template—few will found six multi-billion-dollar companies—but it is a lens. It shows that breadth plus depth, rigor plus imagination, and physics-grounded audacity can still cross frontiers. By borrowing his habits—voracious learning, first-principles analysis, iterative execution and mission-driven teamwork—we, too, can cultivate polymathic range, whether we’re scaling startups, reforming public policy or simply reinventing our own careers. The tools are open-source; the constraint is only the scope of our curiosity.

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[1] (from ‘First Principles: Elon Musk on the Power of Thinking for Yourself’. James Clear.com)

[2] https://futurism.com/tesla-shutting-down-ai-supercomputer