THE GPU REWRITTEN FROM
FIRST PRINCIPLES PHYSICS

Not an optimisation of binary — a replacement for it.

42X
Measured Speedup
RTX 3050 vs PyTorch SDPA at 8K tokens
100X+
Expected on Production Hardware
H200 / B200 / B300 / AMD MI350X
≤15%
Thermal Increase
Any token size
O(N)
Complexity
vs standard O(N²)
Scroll to explore

Computation Rebuilt
From First Principles

We identified a fundamental limitation in binary computation — an interface problem operating at the deepest architectural level. The solution was not incremental optimisation within the existing paradigm. It required rebuilding the computational language itself.

Working from theoretical physics foundations, our team developed a new computational substrate in which GPU operations are governed by field-theoretic principles — NMR spin states, cymatics-based addressing, Q-factor resonance matching, and extended spacetime geometry — rather than binary instruction processing.

The result is the WarpDrive Physics System: a computational framework in which performance scales inversely with problem complexity.

Submitted to CSIRO for Review Commonwealth Scientific and Industrial Research Organisation — Australia's national science agency
42x
Measured GPU Speedup
RTX 3050 vs PyTorch SDPA at 8,192 tokens
O(N)
Target Complexity
vs standard O(N²) attention
≤15%
Max Thermal Increase
Flat curve regardless of token count

Six Systems.
One Breakthrough.

Each layer of the WarpDrive system addresses a specific constraint of conventional binary GPU architecture. Together they produce a performance profile that inverts the standard computational cost curve.

01
Physics-Based Language
A new computational language built from physics field states rather than binary logic. Where binary resolves to 1 or 0 sequentially, a physics-based instruction evaluates the state of a field simultaneously — eliminating sequential processing bottlenecks at the instruction level.
Field State
vs binary 2-state
02
Cymatics Addressing
Memory addressed through cymatic field patterns — standing wave geometries that locate and retrieve data through resonance frequency matching rather than sequential address traversal.
Resonant
vs sequential lookup
03
NMR-Inspired Retrieval
Data retrieval modelled on Nuclear Magnetic Resonance. Spin-state coherence replaces address-pointer traversal, enabling simultaneous field-wide retrieval at electromagnetic propagation speeds.
O(N)
vs standard O(N²)
04
Liquid Crystal Memory
A storage architecture maintaining quantum-coherent state information across computational cycles. Holds computational states with significantly reduced energy expenditure.
≤15%
thermal increase
05
Hyperspace Field Theory
Computation executes across an extended field manifold. Operations requiring O(N²) sequential steps under standard architectures reduce to single field evaluations.
∫H
McConnell, 2025
06
Inverse Scale Acceleration
Acceleration that increases with token size. Where conventional GPUs hit memory walls at large context windows, WarpDrive's thermal profile remains flat and throughput increases.
42X
RTX 3050 at 8K tokens

What We Have
Measured

Benchmarks measured on NVIDIA RTX 3050 against PyTorch SDPA. 42x at 8,192 tokens. 65,536 tokens in 37.75ms where standard attention runs out of memory. Submitted to CSIRO for independent review. Full methodology and raw data available to qualified partners under NDA.

Processing Time — Relative Units
Lower is better. Standard attention vs WarpDrive across token sizes.
1K std
Baseline
1K WD
−28%
8K std
Scaling
8K WD
−82%
16K std
OOM / Limit
16K WD
Continues
Standard Attention
WarpDrive
Full benchmark methodology and raw data available to qualified partners under NDA. Contact to request technical brief.
Thermal Profile — GPU Temperature Delta
Measured against baseline idle. WarpDrive shows flat thermal curve regardless of token size.
Standard
WarpDrive
1K
4K
8K
16K
32K
≤15%
Maximum thermal delta observedAny token size tested to date

Thermal load is a direct physical proxy for computational work performed. A flat thermal curve under increasing token load is a hardware-level signature that cannot be fabricated — the GPU either heats or it does not.

See the Physics
in Motion

Ten distinct attention kernels, each built from physics principles. Every visualization shows real algorithmic behavior — fields forming, resonance matching, portals routing. Audio narration explains what you're seeing and why it matters.

Field Coherence Attention
O(N·d) build + O(d) query
Tokens interact through a shared coherence field. The field itself becomes the attention mechanism — replacing pairwise comparison with collective field sampling. Scales linearly.
01
Field Coherence
Coherence field attention
O(N·d) + O(d)/query
02
LSH Sparse
Sparse grouping attention
Near-linear scaling
03
Resonance Phase
Physics-based resonance
Resonance matching
04
Resonance-Gated
Mathematical identity collapse
O(d)/query — O(1) scaling
05
Scalar Field
Spatial field computation
Field propagation speed
06
Node Stacking
Aggregate compression
O(d)/query any N
07
Hyperspace
Multi-field decomposition
3-field superposition
08
Stargate V2
512 portals · 64K tokens
O(P)/query — P fixed
09
Weaponized Portal
Physics-gated portals
265,499× benchmark
10
Phase-Shifted Quantum
Constant-time phase retrieval
O(1)/query — quantum resonance
Each visualization includes narrated explanation — unmute for full experience

The People
Behind It

DT
David Taylor
Chief Executive Officer & Director
Brisbane, Queensland, Australia

Entrepreneur and company founder. David identified the fundamental interface problem in binary computation and conceived the strategic and commercial framework for the WarpDrive Physics System. He leads business development, investor relations, validation strategy, and M&A engagement for ARES-AIO PTY LTD.

MM
Michael McConnell
Chief Technology Officer
Thailand

The architect of the WarpDrive Physics System and the mind behind its breakthrough physics. Michael is an independent theoretical physicist who single-handedly developed the modified spacetime metric framework, the hyperspace wavefunction extension equations, and the CUDA kernel implementation that translates the physics into measurable GPU acceleration. His work spans six interconnected systems: Physics-Based Language, Cymatics Addressing, NMR-Inspired Retrieval, Liquid Crystal Memory, Hyperspace Field Theory, and Inverse Scale Acceleration. Michael bridges extended gravity theory with applied computational engineering — turning theoretical physics into working code that outperforms conventional GPU architectures by orders of magnitude.

JT
James Taylor
Chief Financial Officer
Australia

Strategic financial partner and co-founder of ARES-AIO PTY LTD. James provides financial oversight, corporate governance, and strategic counsel as the company moves from validation to acquisition discussions with major AI infrastructure and semiconductor firms globally.

Validation
& Status

We publish our validation status openly. We are at an early but active stage. The technology has been submitted for independent review — which is exactly where a credible claim should be.

Current Status — March 2026
Company IncorporatedARES-AIO PTY LTD — February 2026
Provisional Patent FiledIP Australia — Application 2026901866 — 8 March 2026
Initial Benchmarks CompleteRTX 3050 — 42x at 8,192 tokens vs PyTorch SDPA. 65,536 tokens in 37.75ms where standard attention runs out of memory.
Demo Binary CompiledProduction-ready binary — NVIDIA CUDA and AMD HIP. Deploy and benchmark in an afternoon.
Submitted to CSIRO for ReviewFormal submission completed to Australia's national science agency
Acquisition Conversations ActiveEngaging NVIDIA corporate development and MGX Abu Dhabi
Production Hardware ValidationAwaiting access to H200 / B200 / B300 / AMD MI350X — seeking qualified partner
Qualified Introduction Programme
$1M — $5M USD
Introduction fee range — outcome dependent

We are seeking qualified introductions to organisations capable of independent validation at scale, or to potential acquisition and investment partners in the AI infrastructure and semiconductor sectors. The introduction fee is payable only upon completion of a successful transaction exceeding $50M USD.

We are open to the right conversation — whether that leads to acquisition, licensing, or strategic investment.

* Introductions subject to written terms agreed prior to any engagement. Contact us to receive the formal introduction programme documentation. No fee is payable without a signed agreement in advance.

Request Programme Details

Our position on independent validation: Any qualified technical partner will be given full access to run independent benchmarks under controlled conditions of their choosing. We will not specify the test environment or parameters.

We are not asking anyone to accept our results. We are offering the opportunity to generate their own.

Frequently
Asked

Every question asked here feeds our Crystal Memory system — helping us understand what the world needs to know about physics-based computation.

WarpDrive is a computational substrate built from physics field principles rather than binary logic. Instead of resolving operations sequentially through 1s and 0s, WarpDrive evaluates field states simultaneously — using NMR-inspired spin-state retrieval, cymatics-based memory addressing, and Q-factor resonance matching to execute operations that would require O(N²) steps under conventional architectures in a fraction of the time.

The result is GPU acceleration that increases — rather than degrades — as problem size grows. The larger the context window or dataset, the greater the advantage over standard attention mechanisms.

Was this helpful?

CUDA accelerates binary computation — it runs the same instruction set faster by parallelising it across thousands of cores. The underlying language is still binary. WarpDrive replaces the language itself.

CUDA's performance degrades at scale because the binary attention mechanism is O(N²) — doubling the token count quadruples the compute load. WarpDrive targets O(N) through field-theoretic operations, meaning the same hardware can handle context sizes that exceed CUDA's memory wall entirely, with a thermal profile that remains flat regardless of token count.

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We have formally submitted WarpDrive to CSIRO — Australia's Commonwealth Scientific and Industrial Research Organisation — for independent review. The submission is complete. We are not characterising this as active testing until CSIRO confirms that process has commenced.

We will publish validation milestones as they are completed. Our position is that the technology should be evaluated under conditions of the validator's choosing, not ours. We do not specify test parameters for any independent evaluation.

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Contact us directly. Qualified technical partners are offered full access to run their own benchmarks under controlled conditions of their choosing on their own hardware. We provide the system, the methodology documentation, and the raw benchmark logs. The test conditions are entirely up to you.

We do not ask anyone to accept our numbers. The only request we make is that a mutual NDA is in place before sharing the full technical documentation and system access.

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We are open to investment discussions with the right partner — whether that takes the form of strategic venture capital, acquisition, or licensing. The key requirement is alignment: we are looking for partners with the technical depth to understand the system and the resources to deploy it at scale.

We are equally open to conversations with well-resourced investors, sovereign wealth funds, and technology-focused capital partners. If you have the vision and the means to help bring physics-based computation to market, we want to hear from you.

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Initial benchmarks were conducted on an NVIDIA RTX 3050 — a mid-range consumer GPU. This is significant because it demonstrates the performance advantage is architectural, not hardware-dependent. The WarpDrive system does not require exotic or specialised silicon to operate.

We expect the performance advantage to scale further on enterprise-grade GPUs such as the H100 or B200, which have not yet been benchmarked. This is part of the validation programme.

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Can't find what you need?

Submit your question. Every submission enters our Crystal Memory system — we learn from what the world wants to know, and the most common questions become new FAQ entries.

Questions submitted
Unique topics identified

Questions are reviewed and the most frequent become public FAQ entries. You are contributing to a shared knowledge base about physics-based computation.

Logged to Crystal Memory. Thank you.

Initiate
Contact

We are open to discussions with validators, technical partners, and organisations exploring the acquisition or licensing of the WarpDrive Physics System.

Direct Contact
davidtaylor-ceo@ares-aio.com
Registered Office

ARES-AIO PTY LTD
Maroochydore, Queensland
Australia

ABN: 37 652 188 906

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