Nazir

independent observer

[Nazir @dashtiev]

On Tesla’s Market Cap

Tesla’s valuation is about $1.2 trillion. I became curious, based on some top-level fundamental estimates, about how realistic that figure might be, given Tesla’s ambitions. Tesla’s primary current business is cars, but it also has three other potentially large businesses that analysts often factor in: the Energy business, Ridesharing (enabled by autonomous cars), and Robots.

Cars
There are about 1.6 billion cars on the planet. Every year, roughly 80–90 million new cars are sold. Some manufacturers’ annual sales are as follows:

Toyota: ~10 million cars (rank #1)
Volkswagen: ~9 million (rank #2)
Hyundai–Kia: ~8 million (rank #3)
BYD: ~4 million
Tesla: ~2 million
Tesla is currently around the 11th–14th largest car manufacturer by volume. The closest EV rival is BYD, which sells more than 4 million total cars per year (including roughly the same number of EVs as Tesla) yet is valued at about $100 billion. (They do have smaller margins per car, but let’s set that aside for now.) Toyota, by comparison, has a market cap of about $300 billion.

I don’t believe that, in the long term, any car manufacturer can maintain vastly different margins from its competitors, because it’s such a competitive market. So it seems reasonable to assume Tesla will end up with per-car margins similar to other mass-market manufacturers. If Tesla were to become the biggest manufacturer - like Toyota, selling around 10 million cars per year (a 10–12% market share) - then, in today’s dollars, the market cap for that car business might be around $300 billion, matching Toyota’s.

Energy Business
This is the hardest part of Tesla’s business to estimate because competing in the energy space effectively means competing with a huge swath of industries. I’ll use a very simple comparison: ExxonMobil. Exxon has an Upstream segment (finding and producing oil & gas) and a Downstream segment (refining, distributing, and retailing fuels). For our purposes, Downstream is more relevant, since Tesla isn’t yet producing a significant amount of energy at a global scale (solar is too small) but does distribute energy products (charging, battery storage, etc.).

This is admittedly a rough comparison - just a top-level sense check. According to public data, Exxon’s Downstream business accounts for about 30% of its net income. Exxon’s total market cap is about $470 billion, so that Downstream share might be worth around $150 billion. Let’s assume Tesla’s energy business could one day rival that scale and replace oil with electricity. That would peg Tesla’s energy segment at around $150 billion in today’s dollars.

Ridesharing
This one is simpler. Uber’s market cap is roughly $150 billion. Let’s assume that Tesla, with autonomous cars, could “destroy Uber” and take over its entire business. That might translate to another $150 billion of market cap.

Robots
This is the most interesting segment. In principle, the long-term price of a humanoid robot might be comparable to a small car (based on raw material costs) - say around $20,000. If that’s the case, then there’s no fundamental reason why fewer people would buy a robot than a car, assuming it offers enough functionality. That suggests we might take the current car market (1.6 billion vehicles) as a guide.

Consider how personal computers took roughly 30 years to get to 80% adoption - robots could be slower to adopt, given that robots will be more expensive than PCs. Still, if we assume it takes 30 years for adoption and a 10% replacement rate annually, that’s around 100 million new robots per year in the middle of adoption. If Tesla could claim a large 30% market share - around 30 million units per year - that’s more than Toyota’s current annual car sales. Toyota’s market cap is around $300 billion for 10 million cars sold, so by analogy, Tesla might capture $900 billion in valuation from a robot business.

Total
Cars: $300 billion
Energy: $150 billion
Ridesharing: $150 billion
Robots: $900 billion
That adds up to about $1.5 trillion. Given these already optimistic assumptions - and assuming a 100% success rate in reaching such ambitious goals - this justifies Tesla’s current $1.2 trillion valuation. But that is extremely optimistic. More realistically, it feels like it might be at least two-three times smaller. What fundamental factors might I be missing?

[Nazir @dashtiev]

@FishAudio Drama!

[Elon Musk @elonmusk]

Starship deploying Starlink V3 satellites

[Nazir @dashtiev]

in the world of ai agents - context is everything

[Nazir @dashtiev]

@nikitabier @steipete Reading bookmarks and summarizing them was a huge usecase for me

[Nazir @dashtiev]

@ivaavimusic @openclaw @agentmail Auth across the internet is a huge thing for agents, google email solves that

[Nazir @dashtiev]

@ivaavimusic @openclaw @agentmail Just make gmail email for your openclaw, don’t be middy

[Nazir @dashtiev]

@steipete @BenjaminDEKR Shouldn’t HEARTBEAT just run through very cheap model?

[Nazir @dashtiev]

agi achieved?

[Nazir @dashtiev]

@ericmigi Hey Eric! Amazing to see Pebble back (as an original pebble kickstarter supporter)!

[Nazir @dashtiev]

@PolymarketMoney There are at least three companies in the world doing products like openai at the same scale. If openai disappears today I don’t thing progress in that area will decelerate. There is no companies like spacex.

[Nazir @dashtiev]

All the frontier AI models now are basically the same. Of course they have some specialization angle - some better in code generation, some in image generation, some in copywriting etc. But the core of them is the same. Which is logical because every lab is using the same learning and scaling techniques - RLHF, CoT, reasoning, more and more compute and memory, etc.

With that approach, on the scale from artist to calculator, we are moving more and more to the calculator side. Less stochastic, more deterministic. This clearly finds customers and applications in the real world. But what I'm really looking for now is more artistic and more creative AI with different mechanisms it's built on to have more creative outcomes, completely new ideas and sort of a fascinating dreaming engine. More curious, child-like AI rather than a serious adult who thinks he knows how the world works.

And this likely should be a change on the pre-train level, not post-train and tuning. Not a character shift but a different brain.

Is there anything like that in AI research / demos these days?

[Andrej Karpathy @karpathy]

I've never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are increasingly sparse and between. I have a sense that I could be 10X more powerful if I just properly string together what has become available over the last ~year and a failure to claim the boost feels decidedly like skill issue. There's a new programmable layer of abstraction to master (in addition to the usual layers below) involving agents, subagents, their prompts, contexts, memory, modes, permissions, tools, plugins, skills, hooks, MCP, LSP, slash commands, workflows, IDE integrations, and a need to build an all-encompassing mental model for strengths and pitfalls of fundamentally stochastic, fallible, unintelligible and changing entities suddenly intermingled with what used to be good old fashioned engineering. Clearly some powerful alien tool was handed around except it comes with no manual and everyone has to figure out how to hold it and operate it, while the resulting magnitude 9 earthquake is rocking the profession. Roll up your sleeves to not fall behind.

[Nazir @dashtiev]

🤔

[Nazir @dashtiev]

@eladgil @grok how many pull ups he did ?

[Nazir @dashtiev]

Are there any movies more visually beautiful than Lawrence of Arabia?

[Nazir @dashtiev]

@levelsio Similar business model quite well works in Russia, which is Europe

[Nazir @dashtiev]

A long road and an amazing victory. But everything big is seen from a distance. Maybe many years from now we’ll be able to truly appreciate everything this team has done, the whole impact it made.

[Nazir @dashtiev]

Fantastic achievement! Congratulations to the team!

[Nazir @dashtiev]

damn, how retarded they are

[Wall Street Mav @WallStreetMav]

The European Union thinks that they will keep up with xAI, Google, Meta and OpenAI.

EU bureaucrats like Ursula von der Leyen believe that their govt "technocrats" can compete in AI via govt committee.

Listen to her. Europe won't be relevant in AI.