The Entire Quantum Computing Industry Explained
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I am a venture capital investor at FoundersX Ventures, an AI and deep-tech VC fund based in Menlo Park, Cambridge and NYC. I previously did my Ph.D. at Harvard, postdoc at MIT.
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Imagine describing a material before anyone knows how to make it. A catalyst that turns waste carbon into fuel. A battery that charges in minutes. The goal sounds simple — find the right arrangement of atoms — but a deliberately simplified catalyst with 30 positions and five elements already gives you about 930 quintillion possible designs. Testing one per second would take roughly 30 trillion years.
AI can navigate that space. Classical supercomputers can calculate what physics predicts for one candidate. But around certain metal atoms, the electrons interact so strongly that the usual shortcuts start to disagree — and that narrow, stubborn corner is where quantum computers are supposed to help.
This is the full picture: how a quantum computer actually turns quantum behavior into a calculation, all six hardware approaches and what each one trades away, where every approach honestly sits today, whether classical computing and AI might get there first, and what all of it means if you are looking at these companies as an investor.
🎯 You'll learn:
What a qubit really is — amplitudes as arrows, why superposition is not "both at once," and why measuring 50 qubits gives you one 50-bit string
Why a quantum computer does not try every answer at once, and how interference does the real work
The smallest quantum algorithm, worked step by step, and the trade it makes
How phase estimation reads out a molecule's energy from a Hamiltonian
Why fidelity's "number of nines" decides everything: 99% over 1,000 gates succeeds 0.004% of the time; 99.99% gets you to about 90%
How error correction spreads one logical qubit across many physical ones, and why you cannot just copy a qubit
All six approaches — superconducting circuits, trapped ions, neutral atoms, photonics, semiconductor spins, topological — plus annealing and analog simulation
Where each one honestly sits on the ladder, and why a missing marker is not proof of absence
What DARPA's benchmarking program does and does not establish
Why a 2026 preprint reproducing a quantum result on a laptop in under a minute matters
Where today's quantum revenue actually comes from, and why dilution is central to the investment case
⏱️ CHAPTERS
0:00 Can a Computer Design Matter?
6:27 What a Qubit Actually Is
8:55 Gates, Phase and Interference
10:21 The Smallest Quantum Algorithm
12:14 How a Quantum Computer Reads Out an Energy
13:33 Why Reliability Decides Everything
16:41 Error Correction and Logical Qubits
20:06 The Six Machines: How to Read the Map
21:40 Superconducting Circuits
26:13 Trapped Ions
30:43 Neutral Atoms
34:36 Photonics
39:00 Semiconductor Spin Qubits
41:52 Topological Qubits
45:22 Annealing, Analog Simulation and the Classical Layer
48:27 The Ladder: How Far Along Is Each Approach?
50:32 DARPA, the Independent Referee
52:03 Could Classical Computing and AI Get There First?
54:38 What Hybrid Experiments Show Today
55:19 Three Kinds of Competition
57:58 What This Means for Investors
58:41 Where Today's Revenue Actually Comes From
59:29 Dilution: How These Companies Pay the Bills
60:19 What the Price Already Assumes
61:10 What to Watch
61:44 Back to the Search
🏢 Companies and organizations discussed: IBM, Google, Quantinuum, Honeywell, IonQ, QuEra, Atom Computing, Microsoft, PsiQuantum, Pasqal, Infleqtion, D-Wave, Intel, Photonic Inc., NVIDIA, Amazon Braket, RIKEN, Caltech, DARPA
Every claim is labeled by evidence type — peer-reviewed paper, preprint, company announcement or roadmap — because those are not the same thing.
This video is part of my ongoing series breaking down the deep-tech and AI systems shaping the next decade, for investors and builders who want to understand what is actually happening under the hood.
⚠️ Disclaimer: This video is for educational and informational purposes only and is not financial advice. I am a venture capital investor at FoundersX Ventures, and my fund may hold positions in companies or sectors discussed. Always do your own research before making any investment decision. Some infographics in this video are AI-generated and may contain errors; corrections will be pinned in the comments.
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