From One to One Billion: Torx, Thermalizers, and Z1 - Extropic

The Looming Energy Wall

AI is entering an era of seemingly smooth exponential acceleration. Models keep scaling and are emerging as multi-trillion-parameter behemoths with Fields Medal-level mathematical intelligence. Data centers are multiplying, stacking seemingly endless rows of GPUs while burning ever more power. AI labs are locked in a race to scale, where the only variables that seem to matter are digital compute, energy, and capital. The whole industry is past an inflection point, and the momentum feels quasi-unstoppable.

And yet, something still feels off. Our intuition tells us the story is still incomplete. Brute-force scaling today’s digital, deterministic hardware to unfathomable scale for inherently probabilistic algorithms cannot be the endgame. Compute costs have ballooned because building enormous data centers requires land and energy that are increasingly difficult to secure. The market’s insatiable appetite for intelligence keeps straining the supply chain and demanding exponential gains from the current paradigm.

Beyond data centers, physical intelligence does not have nearly enough compute density to run capable robots entirely on local compute. Space-based compute clusters are being proposed to alleviate pressure on terrestrial data centers, while relying on designs with radiators and solar panels the size of football fields. AR wearables with sufficient compute power look comical and still cannot reach a form factor dense enough to be both powerful and appealing to consumers.

In all cases, we are hitting a physical limit: the thermodynamic limits of AI scaling under the digital paradigm. If we continue with the status quo, the apparently exponential curve will bend and local progress will plateau. For artificial intelligence to fulfill its promise, we need a non-incremental gain in the density of intelligence. We need a fundamental paradigm shift in how we make silicon think.

Our very existence, that of biological general intelligence, is proof that a better way forward can exist. One that is far removed from digital computation. One that harnesses the inherent randomness in nature. And one that is far more parameter, data, and power efficient.

At Extropic, we are pioneering this paradigm. We are taking guidance from thermodynamic physics and nature to design a new form of computing, from the electrons up. By leaving conventional bits behind and embracing probabilistic primitives such as pbits, we carved a new path that promises more intelligence per watt, per square millimeter, and per second.

It has been a multi-year journey to reinvent computation for an era dominated by AI. It has been a few months since you last heard from us, and today we have updates to share across our entire thermodynamic computing stack.

Thermodynamic Full-stack Update

Torx<br>STOCHASTIC DIFFERENTIABLE PROGRAMS

OPEN SOURCE

READ ON ARXIV

Thermalizers<br>VARIATIONAL COMPILER: KERNELS TO ENERGY-BASED MODELS

READ ON ARXIV

LIBRARY COMING SOON

THRML<br>HYPERGRAPHICAL MODELS, CLOSE TO THE METAL

LIVE SINCE FALL 2025

EXECUTION BACKENDS

THERMODYNAMIC HARDWARE

XTR-0<br>WITH EARLY ADOPTERS NOW

Z1<br>TAPEOUT, EARLY ACCESS 2027

DIGITAL HARDWARE<br>GPU Simulators

EARLY-ACCESS API

HIGH-PERFORMANCE Z1 SIMULATION

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FIG. 01 Our thermodynamic computing stack. Click on a box to jump to corresponding section.

Recap

Recap: From Zero to One

Last fall, we announced X0, our first silicon thermodynamic chip, and with it the world&rsquo;s first desktop probabilistic computer, XTR-0. X0 demonstrated our novel probabilistic primitives in silicon: pbits, tiny circuits that turn the thermal noise of ordinary transistors into programmable randomness, using orders of magnitude less energy to generate a sample than conventional approaches. Those primitives are the building blocks of every chip we make, current and future.

PRIMITIVES The probabilistic family: pbit, pdit, pmode, and pmog, each pairing a sampled state with its distribution.

We didn&rsquo;t stop at silicon. We manufactured dozens of XTR-0 systems, our desktop experimental platform built around X0, and shipped them to early adopters who are playing with our probabilistic primitives and running the first thermodynamic programs on real hardware. We also built an XTR-0 cluster for scientific and enterprise users to remotely experiment with more than a handful of primitives, forming the first thermodynamic computing proto-cloud.

XTR-0 is a reprogrammable stochastic processor that extends beyond energy-based model sampling. To let users explore this broader space, we created Torx, which we cover below.

XTR-0 Extropic&rsquo;s desktop experimental platform, built around X0 and shipped to early adopters.

With our fall release, we open sourced THRML, our library for thermodynamic hypergraphical models, which lets developers experiment with thermodynamic programming close to the...