The Library

Everything the Institute has published, in one place.

Technical reports, defensive publications and open specifications. Every one is a free PDF and every one is also readable in the browser, most with a runnable simulation attached. Figures carry a verification grade, references carry their provenance, and where a result is modelled rather than measured the paper says so.

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Search by title, subject or report number, or narrow by kind. Specifications are released CC0; a portability layer that can be captured is worth nothing.

TR-2026-264 Aug 2026

Criteria for a Novel Computing Paradigm

Building the Energy Compute Future

Why performance claims for new machines keep collapsing, which claims survive the attack, and how to state the two of them together.

A new computing machine is announced with a large speedup. Within a few years an ordinary computer running a cleverer algorithm reaches the same place, and the advantage is gone. This has happened often enough to have a name, dequantization, and it is the central obstacle to arguing that any novel paradigm is worth building. This report separates two claims that are usually made in one breath. The first is that the n…

Read online →↓ PDF · 0.1 MBCriteria / Method · v0.1

TR-2026-214 Aug 2026

Learning Without Forgetting

The Adaptive Unit

Why a machine that keeps learning needs a richer neuron, what dendrites buy, and whether the better primitive can win on the hardware we already have.

Almost every deployed neural network is trained once and then frozen, because training it on something new tends to destroy what it already knew. This is catastrophic forgetting, and it is the single largest obstacle to machines that work in the physical world, where the floor changes, the tool changes, and the failure is new. This report argues that the problem is being attacked at the wrong level. The usual remedie…

Read online →↓ PDF · 0.1 MBSurvey / Position · v0.1

EFA-RFC-002Request for Comment

Cross-Paradigm Relaxation Dialect

RELAX/1

Ten operations, an MLIR and NIR-style exchange form, and a lowering matrix across substrates.

If relaxation-style computing is to run on thermodynamic samplers, Ising machines, neuromorphic fabrics and ordinary GPUs alike, it needs a dialect that lowers to all of them. RELAX/1 specifies ten operations with a reference lowering, so that one program can be executed by several kinds of physics and the receipts compose across them.…

Read online →↓ PDF · 0.1 MBDraft v0.1 · CC0

EFA-RFC-001Request for Comment

Open Energy Receipt / 1

OER/1 and DRIFT/1

A receipt schema for energy claims, and a benchmark protocol for learning under drift.

Every previous alternative-computing wave died of unverifiable claims. This RFC specifies an energy receipt whose provenance axes keep modelled, stand-in and metered figures permanently distinguishable, and a companion benchmark protocol for systems that adapt while running. The composition rule is deliberately unforgiving: a composed receipt takes the weakest grade among its parts, never the average.…

Read online →↓ PDF · 0.1 MBDraft v0.1 · CC0

TR-2026-252 Aug 2026

The Future of Compute as a Function of Energy

The Energy-First Turn

Post-transformer, learn-while-inferring AI, the substrates built to run it, and the economics of changing what a unit of intelligence costs.

Computing's next constraint is not transistors, capital or talent: it is electricity. Data-centre demand is doubling this decade while physics permits computation millions of times cheaper than we practise it, because the bill is paid to move data rather than to compute it. This review maps the escape along two coupled axes — the substrates that execute relaxation natively, and the model classes that learn while infe…

Read online →↓ PDF · 0.1 MBSurvey / Review · v0.3

TR-2026-2424 Jul 2026

Technical report · verified differentiable CFD in Rust

Honest Fluids: A Verified, Differentiable Computational Fluid Dynamics Stack for Physical AI, in the Browser

One open Rust stack spanning every solver paradigm — each checked against an analytic or reference oracle, differentiable end to end, and deployed self-verifying to WebAssembly.

Deployed robots do not run computational fluid dynamics in the control loop, and the discipline's own 2026 consensus is that verification — not throughput or model size — is its weak layer. We report a fluid-dynamics stack that treats verification as the primitive: every solver ships with an oracle it must reproduce before it is admitted. The stack spans all five solver paradigms — pressure-projection (MAC), lattice-…

Read online →↓ PDF · 0.3 MBCC0 1.0 · public-domain dedication

TR-2026-2323 Jul 2026

One digest

One Digest: Bit-Identical Neural Computation Across Heterogeneous Compute Fabrics

Making a transformer forward pass compute the same bits in a browser tab, on Apple silicon, and on an NVIDIA GPU — the mechanisms that break it, the pins that hold it, and the measured price.

The same shader source, run on two GPUs, does not compute the same bits — and on neural workloads the differences compound into different behavior. We report an engineering campaign that made a complete transformer kernel set (matmul, RMSNorm, LayerNorm, softmax, RoPE, causal attention, and a full multi-layer forward pass) produce bit-identical output digests on six substrates: Apple Metal, NVIDIA Vulkan, and Chrome'…

Read online →↓ PDF · 0.4 MBEngineering Report · Preprint v2

TR-2026-2221 Jul 2026

Touching sound

Touching Sound: Contact Audio and the Complementarity of Physical Perception

The sense that reaches through occlusion and into the sealed interior — and why sensor fusion is coverage, not redundancy.

Vision resolves an object's shape and a fingertip resolves its texture, but neither can tell a solid billet from a hollow shell, water from air behind a closed wall, or a seated bearing from a cracked one, and both go dark under occlusion or in the dark. Contact audio can. When a hand taps, scratches, or shakes an object, the vibrations it radiates carry precisely what light and touch cannot reach: material, internal…

Read online →↓ PDF · 0.2 MBSurvey / Review · Preprint v1

TR-2026-2015 Jul 2026

Exploring intelligence

Impedance Matching as a Unifying Principle for Physical and Embodied AI: A Survey

One boundary condition, carried from a 1939 transmission-line calculator to the free-energy principle — and an account of where it stops being one.

A wave meets a boundary; whatever fails to match is reflected. This report surveys the extent to which that single statement organizes problems across the disciplines that physical and embodied AI draws on. It reviews five bodies of published work — the reflection coefficient and its conformal map onto the unit disk, Shannon capacity and the matched filter, the Bode–Fano broadband matching limit, Landauer's bound on …

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-2712 Jul 2026

Space logistics and transportation

Physical AI for Space Logistics and Transportation: Composing the Velocity Budget with One Estimation-and-Control Stack

A Δv-composition framework, an on-orbit non-cooperative capture, and a headless physics core the whole chain runs on.

Moving mass to, through, and around space is one continuous logistics chain: launch, orbital transfer, rendezvous, capture, servicing, assembly, and return. This report advances a research position: across that whole chain the decisive capability is autonomy carried on the vehicle, and the same estimation-and-control primitive recurs at every link, so a single autonomy stack composes across all of them. We make the a…

Read online →↓ PDF · 0.1 MBPosition / Methodology · Preprint v1

TR-2026-1912 Jul 2026

The Diffusion Layer

The Diffusion Layer: Accelerating the Spread of Silicon-Design Competency for Physical AI — A Survey and Research Position

Physical AI is bottlenecked less by fabs than by the people who can design for them. This report treats that competency as an innovation to diffuse, and the training as the technology that sets its speed.

Physical AI runs on custom silicon — for perception, for on-device inference, for the energy budget of a machine that carries its own power — and the binding constraint on producing that silicon is not fabrication capacity but the number of people who can design it. Design competency is the slowest-diffusing input in the stack, because its hardest layers are tacit: analog intuition, physical design, and verification …

Read online →↓ PDF · 0.2 MBSurvey / Position · Preprint v1

TR-2026-1812 Jul 2026

The Human Layer

The Human Layer: Competency at the Frontier of Autonomous Systems — A Survey and Research Position

As machines take the loop, the human role does not disappear; it moves to the boundary. This report maps the competency that lives there, why automation erodes it, and how to build it deliberately.

Autonomy does not remove the human from a physical-AI system; it relocates the human to the system's boundary — to supervision, exception handling, calibration, and accountability. The competencies that boundary demands are different from the ones the machine displaced, and they are precisely the competencies that routine operation no longer exercises. This report surveys the long literature on that relocation, from …

Read online →↓ PDF · 0.2 MBSurvey / Position · Preprint v1

TR-2026-177 Jul 2026

The Bayou Air Corridor

The Bayou Air Corridor: Managed Low-Altitude Airspace over Houston's Greenways

Treating a continuous public greenway network as an AI-managed low-altitude volume, with flood search-and-rescue as the first mission and infrastructure inspection as the recurring one.

Houston's bayous are continuous public greenways: water and parkland that thread the entire metropolitan area. Measured by the standard ground-risk criterion for uncrewed flight, the population exposed beneath a flight path, they are close to the lowest-risk ground in the city to fly over. This report treats the bayou network as a candidate managed low-altitude airspace and describes an artificial-intelligence volume…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-167 Jul 2026

VLI

Vision-Language-Interaction: Building a System to Interact, Not to Obey

A research position on making interaction, rather than task-completion, the objective of embodied agency — and metering every engagement with the world. Interaction is scored in joules per engagement; the same accounting, under disturbance, becomes the Institute's agency metric, J/VT — joules per viability-second held.

Contemporary embodied models are trained to map perception and language to action, and are optimized to complete named tasks. This report argues that task-completion under-specifies what a system with agency actually needs, because a policy is only ever prepared for the situations its objective named, and the world routinely presents situations no order anticipated. It develops a research position we call Vision-Lang…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-157 Jul 2026

The printed body

The Printed Body: How Far Additive Manufacturing Reaches into a Humanoid, Joint by Joint

Nine of the ten subsystems inside an electric actuator have a demonstrated additive route. The tenth is the drive die, and it must be fabbed.

A humanoid you can print is governed by one question: what can additive manufacturing actually do, joint by joint, and where does it hit a wall. This report treats an electric actuator as ten subsystems — structure, compliant transmission, flexure bearings, soft-magnetic iron, copper windings, permanent magnets, insulation, thermal path, sensing, and the power-electronics drive die — and asks, for each, w…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-147 Jul 2026

The surface that pays twice

The Surface That Pays Twice: Multi-Material Active Skins for Persistent Embodied Systems

A single persistence inequality, one physics-informed solver, and a skin that harvests and hides at the same time.

An embodied system that must persist — a stratospheric glider aloft for months, a Mars rover across a Martian year, a subsea drone that stays dark — is governed by a single inequality: the energy it harvests must meet the energy it spends, integrated over the mission. This report develops Multi-Material Active Skin Technology (MMAST), a research position in which the vehicle's outer surface is treated as its power pl…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-137 Jul 2026

Spatial RF

Spatial RF: Spoof-Resistant Sensing by Cross-Spectrum Corroboration

Forgeability sets trust; only keyed-coherent bands can veto; silence lowers the bar rather than blinding the system.

A single-band radio sensor is defeated by a single-band attack, which is the cheapest attack that exists. This report states a research position: a sensing fabric should span the whole usable spectrum and weight each band by how hard it is to forge, so that defeating the fabric requires forging a jointly consistent signature across every band at once. It reviews the primary sensing modalities the fabric composes — Wi…

Read online →↓ PDF · 0.4 MBSurvey / Review · Preprint v1

TR-2026-127 Jul 2026

Graph of the World

Graph of the World: A Hybrid Property-Graph and Vector Substrate for Embodied Memory

One engine that traverses relationships and searches by similarity, on the device that has to act.

Perception fills a world model and physics makes it actionable, but the model has to live somewhere. This report argues that it lives as a graph. Every entity an embodied system knows — a part, a material, a surface, a constraint, another agent, a sensor reading — is a node, and every relationship between them is an edge. Because the physical world is continuous rather than discrete, each node also carries a vector e…

Read online →↓ PDF · 0.4 MBSurvey / Review · Preprint v1

TR-2026-117 Jul 2026

The Computable World Model

The Computable World Model: Retrieving the Physics an Embodied Agent Needs

Most of the physics an embodied agent needs is retrievable, not computable. A single cascade, over a single graph, from a milliwatt chip to a workstation. And the question it must serve — "will this action diverge before I commit?" — is exactly what an energy certificate consumes: retrieved physics is the substrate under the certificate, not a world model for its own sake.

A world model is only actionable when the system can answer physical questions about it: will this part hold, will it fit, will it overheat, how far will it deflect. Full computer-aided design and physics simulation can answer such questions, but their kernels and solvers are too heavy to run inside a body's power budget. This report states and develops a research position, that of the CadFuture project of the Charlo…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-107 Jul 2026

Spatial AI

Spatial AI: A Living Gaussian-Splat Field That Predicts, at the Edge

A concrete definition — an explicit field of Gaussian splats, coupled to grounded dynamics, accounted in joules and run inside a robot's power budget rather than a datacenter's.

"Spatial AI" is the phrase the field reached for after "spatial computing," and it remains a buzzword in search of a definition. This report proposes a concrete one and defends it. A spatial model should hold the world as an explicit field of points, and Gaussian splatting is the representation that captures real geometry and appearance while remaining inspectable and editable. It should also be a world model that kn…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-097 Jul 2026

The contact layer

The Contact Layer: Vision-Based Tactile Perception Where Line-of-Sight Ends

A camera under three colored lights becomes a geometry-and-force sensor, and the fingertip complement to a whole-body event skin.

Every remote sense goes to zero at the moment of contact. The last millimeter, the forces that hold a grasp, whether a surface is slipping, and the micron texture that distinguishes a bolt from a screw are not knowable from across a room. Touch is the perception layer that begins exactly where remote sensing ends. This report reviews the vision-based tactile fingertip, in which an elastomer gel deforms against an obj…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-087 Jul 2026

OmniSense

OmniSense: The World Model as Projected Perception in a Volume

A projective account of the world model, in which where-and-what a system is emerges from a mesh of optical and radio-frequency nodes resolving a volume into occupied, empty, and unknown.

This report advances a projective account of a Physical AI system's world model. The model, including the system's own pose and identity within it, is treated not as an internal state read out from onboard sensors alone, but as a field defined over a volume by a mesh of sensing nodes: some carried by the system, some on peer systems, some anchored in the space. The mesh resolves the volume into three states. Positive…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-077 Jul 2026

Provable by construction

Provable by Construction: On-Device Lyapunov Certificates for Trustworthy Control

A controller is trustworthy not because it passed testing, but because its stability is proven — and the proof can ride with it.

Testing shows that a controller worked on the states it was tried on; it says nothing about the states it was not. A Lyapunov certificate says something stronger: that a closed-loop policy drives an entire region of the state space toward its equilibrium, by exhibiting a scalar energy that the dynamics can only spend. This report reviews how such a certificate is checked soundly and cheaply enough to run on the devic…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-067 Jul 2026

MathGround

MathGround: Pricing Every Decision in Joules, with a Replayability Class on Every Answer

A substrate that resolves each request at the lowest tier whose grammar covers it, meters the cost in measured energy, and stamps every claim with a type-enforced replayability class.

The cost of intelligence is energy, and most of what a system must decide is not a generation problem. This report describes MathGround, the substrate the remainder of the lab's work runs on. Two design commitments organize it. First, every decision is priced in joules and a request resolves at the lowest tier whose grammar covers it: a deterministic lookup, then a closed-form formula, then a sparse solver, and a sto…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-057 Jul 2026

Energy-native compute

Energy-Native Computation and the Price of a Reproducible Bit: A Survey and Research Position

Order computation by the crossings between its energy and its state; find that the most efficient substrate is the noisiest; and price the reproducibility you must buy back.

In a low-power substrate, energy conversion and computation are frequently the same physical mechanism, described by two research communities that do not cite each other: what one calls harvesting, the other calls computing. This report organizes the field with a single axis — the number of domain crossings that survive between the energy source and the computational state variable — and surveys the resulting spectru…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

DP-2026-027 Jul 2026

Defensive publication · energy-native compute

A Thermodynamic Bound on Reproducibility in Energy-Native Computation, and the Crossings-Tax Spectrum

Collapse the crossings between source and compute state and efficiency rises but noise floods in. Reproducibility is bought back not with a conversion crossing but with a dissipation-built basin, at a price with a lower bound.

Energy-delivery-to-compute schemes are ordered by one axis: the number of domain crossings that survive between the energy source and the computational state variable, each crossing a conversion loss and a reproducibility checkpoint. Collapsing crossings raises efficiency and, along the same diagonal, forfeits the interfaces at which state could have been re-clocked or restored — so the maximally efficient substrate …

Read online →↓ PDF · 0.3 MBCC0 1.0 · public-domain dedication

TR-2026-046 Jul 2026

One fluid, three currents

Microfluidics as a Shared Substrate for Physical AI: Co-Optimizing Heat, Charge, and Information in One Electrolyte Network — A Survey and Research Position

The seam where computation meets its energy budget: the same embedded fluid that must remove heat and deliver power can also carry a slow, local layer of computation.

An embodied system carries its power plant with it. At the edge, the dominant constraints on computation are not clock speed but the two currents that keep a chip alive: the heat it must reject and the power it must be fed. This report surveys a body of work in which those two currents already flow through a fluid — embedded microchannel coolant, and on-chip electrochemical flow cells — and observes that the same ele…

Read online →↓ PDF · 0.4 MBSurvey / Review · Preprint v1

DP-2026-016 Jul 2026

Defensive publication · heat–charge–information

Joule-Priced Co-Optimization of a Shared Microfluidic Substrate for Physical AI

One embedded electrolyte network, optimized jointly as coolant, power medium, and iontronic computer. Pricing any current alone is dominated whenever the couplings below are nonzero.

A single embedded electrolyte network is optimized jointly as coolant, localized power/regulation medium, and iontronic computational substrate. The three currents — heat, charge, information — share one flow and one dissipation budget. Under nonzero coupling (K1–K3, §4) the joint program below strictly dominates any pricing that optimizes cooling, power delivery, or computation in isolation. The disclosed object is …

Read online →↓ PDF · 0.3 MBCC0 1.0 · public-domain dedication

TR-2026-035 Jul 2026

Sampling as the compute

Thermodynamic and Probabilistic Hardware for Generative and Embodied AI: A Survey

A generative model draws samples from a distribution. This report reviews hardware that draws them from physics instead of computing them first.

A generative model, reduced to its core operation, draws a sample from a probability distribution. A conventional accelerator does this in two stages: it computes the distribution with matrix multiplication, then draws from it with a random-number generator. Most of the energy is spent in the first stage, on a quantity that a random draw immediately collapses. Thermodynamic and probabilistic hardware removes the firs…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v1

TR-2026-025 Jul 2026

Multiply-free neural computation

Ternary and Low-Bit Neural Models, Their Training, and Their Silicon: A Survey

Restricting weights to {−1, 0, +1} removes the hardware multiplier. This report reviews what that buys, how such models are trained, and where the silicon stands.

Multiplication is the most expensive arithmetic operation in a neural accelerator, and the multiplier array is the circuit block that benefits most from an advanced fabrication node. Ternary weight quantization constrains each weight to the set {−1, 0, +1}. Under this constraint a weight–activation product reduces to a sign selection and the multiplier is no longer required. This report reviews the resulting body of …

Read online →↓ PDF · 0.4 MBSurvey / Review · Preprint v2

TR-2026-015 Jul 2026

The open field of computing

Post–von Neumann and Energy-Efficient Computing Paradigms for Physical AI at the Edge: A Survey

From the orbital gigawatt datacenter to the sub-microwatt microcontroller, with attention to how old each method is.

The dominant cost of contemporary artificial intelligence is energy, and most of it is spent moving data across the von Neumann boundary and performing floating-point multiplication. This report surveys the computing paradigms that reduce or remove those costs. It organizes about forty methods into nine families along two axes, paradigm and deployment scale, spanning energy-harvesting microcontrollers to orbital data…

Read online →↓ PDF · 0.3 MBSurvey / Review · Preprint v2

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