Portfolio: Extropic’s Thermodynamic Computing, Defined and Demystified

AI’s future rests not just on smarter code - but on radically new hardware. Extropic has thrown open the door to that next leap: thermodynamic computing. Let's unpack this in simple terms.

For decades, Moore’s Law was tech’s heartbeat - chips doubling power every two years. Lately, we're hitting a wall. Chips got so tiny they're colliding head-on with messy physics. Atoms jiggling randomly - thermal noise - make traditional chips unreliable. The AI boom demands more compute, and classical hardware is maxed out.

So, what's next? Nature has answers. Consider the human brain: 100 trillion synapses powered by roughly 20 watts - the energy of a dim bulb. It thrives on "organized randomness," neurons firing in a nuanced dance, not strictly on or off, but fluidly in-between.

Extropic embraces randomness. Their new thermodynamic (or “mesoscale”) computers don’t just tolerate, but tap into, the “jitteriness” of electrons as a resource for computation. These computers are not classical digital systems with strictly yes/no operations. They are not fully quantum with their strange superpositions. Instead, they operate at the mesoscale by harnessing natural, out-of-equilibrium fluctuations (the “jiggly” behavior of matter at small scales). These computers use probabilistic bits (sometimes called “p-bits” in Extropic’s terminology) - able to exist in many in-between states. This lets them natively run probabilistic algorithms and pattern-finding routines much more efficiently than classical chips. For instance, a bit might be 70% "on" and 30% "off" at any given moment, harnessing randomness to mimic how real-world uncertainty works. This makes computations more efficient for tasks involving chance or patterns, as the hardware naturally handles ambiguity without extra effort.

Take a simple everyday example: imagine deciding whether to bring an umbrella based on the weather forecast. A binary system would force a yes-or-no choice (bring it or don't), but an in-between state approach is like the forecast saying there's a 60% chance of rain, so your "decision bit" hovers at 0.6 "yes," letting the system weigh probabilities fluidly and arrive at smarter outcomes, much like how Extropic's thermodynamic chips use electron jitter to power AI without rigid constraints.

Central to Extropic’s tech is the energy-based model (EBM). Picture searching for the lowest point in a hilly field. Traditional methods meticulously check every spot, burning energy. EBMs, by contrast, let gravity do the job - like marbles naturally rolling to the deepest spots. Here, electrons behave like those marbles, effortlessly settling into optimal solutions, saving tons of energy, and closely mimicking nature's efficiency.

Monte Carlo sampling - running countless random trials to approximate solutions - is core to modern AI but is painfully inefficient on conventional hardware. Extropic's chips speak randomness natively, physically executing trials effortlessly. That means dramatically less power use and solving tough problems previously seen as impractical.

What's actually new here? Early Extropic prototypes needed superconductors and massive fridges - cool, but impractical. Now, they've made room-temperature silicon chips, familiar as your phone but driven by revolutionary physics. Today's chips have hundreds of p-bits; next year's could reach a million, easily surpassing quantum computing capabilities.

Simulations and tests demonstrate orders-of-magnitude better energy efficiency than current state-of-the-art chips on certain AI tasks. Algorithms like diffusion models (used in image/video generation) run faster, with far less power. This means smarter AI right in your pocket or robots running true onboard intelligence for days on tiny batteries. It opens new doors for simulating complex fields like biology, physics, and finance without massive brute-force hardware.

Founded in August 2022 by Guillaume Verdon, Extropic stepped out of stealth in March 2024. Guillaume is a Canadian mathematical physicist who pioneered work at Google’s TensorFlow Quantum. He's also a co-founder of the "effective accelerationism" (e/acc) movement, advocating that rapid technological progress, done responsibly, is humanity’s most ethical path forward. Trevor McCourt, the CTO, brings deep expertise in hardware and semiconductor engineering, making Extropic the intersection of bold physics theory and practical tech engineering.

Thermodynamic computing is not just a new chip, but a new philosophy. The future of computing may not be in bigger, colder, or more complicated machines - but in embracing the “productive chaos” of nature, right in your hands.

Want to dive deeper? Check out the latest episode of the Core Memory podcast, hosted by Ashlee Vance. Guillaume Verdon joined Ashlee for an engaging discussion on Extropic, e/acc, and all things AI. This episode was proudly supported by E1 Ventures, and we’re especially excited since Extropic is one of our favorite portfolio companies.

In addition, check out the video below for the most up-to-date updates:

Best,
Ana

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