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Aether AI
AETHER AI · PREDATOR · SOFTWARE ANALYSIS & SECURITY RESEARCH

Predator by Aether AI — Reason deeply. Prove the result. AI reasoning, adaptive compilation and software verification.

Gen3 milestone: Q3 native PASS Protected cases: 24 of 24 passing
Gen3 program: research continues Separate hardware experiment: published IBM pilot

The program   ·   Q3 result   ·   Completed chain   ·   Quantum data   ·   What follows   ·   Use Predator   ·   Join the research

Predator combines adaptive compilation, advanced frontier-AI reasoning, and quantum-depth research to advance software analysis, vulnerability analysis, threat modeling, and resolution modeling.

The program investigates how software can fail, how risks connect, and which changes can resolve them while preserving required behavior. It turns reasoning into candidate changes, tests those changes on the software itself, and carries the resulting evidence into the next round. Quantum depth here means successive, dependent quantum-method interventions in that reasoning process; it does not mean every round runs on a quantum processor.

The first Gen3 repair win is complete. Q3 reached 24/24.

Aether AI’s research loop carried evidence through C0 → Q1 → C1 → Q2 → C2 → Q3 → C3. C marks a saved evidence checkpoint; Q marks an intervention that uses the preceding evidence. On the controlled CharLS benchmark, the final repair closed all eight remaining cases while preserving every prior pass. Gen3 continues toward its objective: proving quantum advantage under credible, matched comparisons.

CharLS is one repair case within the broader Predator program. This public repository contains the showcase and selected research records; the research engine remains private. Supported customer checks run through Predator CI / Aether Actions.

Owner-supplied image of the private Predator operator console. The pictured session and counters are illustrative, not research measurements.
Predator operator console · Illustrative session and counters; the measured Q3 result follows below.

First Gen3 win

CharLS · completed September 14, 2026 · producer-verified native PASS · C3 banked

Native PASS means the checks passed on the software itself. Protected cases are the campaign’s private evaluation cases. C3 banked means the result and its linked evidence were saved and verified by the execution lane.

First Gen3 repair win: C2 16 of 24 passing becomes C3 24 of 24. Blue marks 16 preserved passes; purple marks 8 newly passing cases. Zero prior passes lost. The case is complete; the quantum-advantage objective remains open.

Protected result Before · C2 After · C3 Change
Cases passing 16/24 · 66.7% 24/24 · 100% +8 passes · +33.3 percentage points
Prior passes retained 16 16/16 0 prior passes lost
Remaining cases failing 8 0 All eight closed

What was fixed? A fragment-copy defect on real CharLS C++ source with deliberately introduced faults. After copying a fragment, the destination advanced one byte too little, causing the next fragment to overwrite the previous fragment’s last byte. Q3’s repair advanced by the full fragment length. 24/24 counts deterministic private test cases, not vulnerabilities or CVEs.

Supporting validation: 516/516 stock tests, including 17/17 compliance, sanitizer PASS and 10,000 fuzz executions. These support the result; they are not extra protected cases.

Read the concise result →   ·   Public data and fingerprints →   ·   Visual showcase →

Research loop

The dependent chain has now completed this case. Each intervention used the preceding evidence. Q2 left eight cases failing—the remaining repair obligation, or residual. That failure and the resulting source were recorded in C2. Q3 repaired that source and produced C3.

Completed chain: C0 frozen problem; Q1 reaches the continuation and banks C1; Q2 exposes FRAGMENTDATA failure and banks C2 at 16/24; Q3 repairs fragment advancement and banks C3 at 24/24. No comparable C0 or C1 scores are supplied. Follow-up objective: demonstrate quantum advantage.

Intervention What it added Banked evidence
Q1 Reached a deeper continuation and released the committed stage-two options C1 · next obligation exposed
Q2 Selected the frozen continuation repair; gates A/B passed and C failed FRAGMENTDATA C2 · 16/24, residual retained
Q3 Applied C2-H1, a new repair prepared from C2 on Q2’s result tree C3 · 24/24, prior passes preserved

Q3 introduced a new repair for the exact source produced by Q2, with its evidence linked to C2. Its catalog contained one candidate. The optimization compiler and decoder—the rules that encode and select a repair—kept their earlier semantics. Q3 succeeded by closing the remaining software obligation; a stronger optimizer was not demonstrated. The earlier result remains CHARLS_Q2_EXECUTED_NATIVE_FAIL.

C = evidence checkpoint carried into later reasoning. Q = intervention. Reasoning-chain depth differs from circuit depth. Comparable protected scores are supplied only for C2 → C3, so the chart does not invent earlier scores.

The producer reports recovered replay/lineage verification, signed native bindings and full-hash readback of 17 C3 objects. Readers can rebuild the published figures from the public JSON. Independent end-to-end campaign reproduction requires the retained private material; this summary does not distribute it. Evidence and replay scope →

Recorded quantum selection

Q2 · Aer simulation · 2,048 samples · exact frozen objective

A QUBO models yes/no repair choices and their costs. Its energy is the modeled cost to minimize, not electrical energy or a guarantee that the code works. Aer simulates quantum circuits on classical computers. The selected repair still has to pass native software tests.

Q2 Aer counts: 00 has 635 rejected samples, 01 has 291 selected samples at energy one quarter, 10 has 324 feasible samples at energy two, and 11 has 798 rejected samples. 615 feasible out of 2048; regret zero; exact classical selection agreed.

The selected state 01 was the unique feasible optimum at energy 1/4, regret 0: no better valid choice existed under that frozen model. The policy chose the lowest feasible sampled energy, not the most frequent sample. Exact classical selection agreed and reached the same native failure. The remaining question concerned the repair space and its modeled costs; these data do not implicate sampling.

Q1/Q2 used simulation. Q3’s one-candidate catalog supplies no optimizer comparison, and this summary supplies no Q3 histogram. The CharLS result establishes neither execution on a quantum processor nor quantum advantage. It establishes the completed dependent repair and measured gain described above. Counts, graph scope and comparison limits →

Next objective: quantum advantage

Important

First Gen3 win achieved. Gen3 research continues. The next question is whether quantum participation produces an attributable advantage over strong AI-only and classical alternatives. Completing this case does not complete the program or automatically start Q4.

Established milestone Evidence still needed for the objective
Dependent repair · C2 feedback supported a successful Q3 repair Transfer to fresh tasks with inherited knowledge disclosed
Native utility · +8 passes, 16 preserved, 0 lost Prospective AI-only and classical comparisons on the same acceptance contract
Banked chain · recorded parent bindings and C3 durability Matched information and query access, total cost accounting, uncertainty and independent replication

Before protected Q3, public development already passed 516/516 tests and the resulting source matched pinned upstream across 68 source/include files. That limits novelty and blindness claims. Future comparisons must separate known-source restoration, better candidate generation and the quantum selector’s contribution. Research and release roadmap →

Published quantum data

Separate hardware experiment · IBM Fez · September 6, 2026

The earlier joint5 compiler pilot reduced native two-qubit gates 144 → 103 per circuit (28.5%) and improved agreement with a fixed ideal output in two related cases. Expected energy increased in both, so minimization worsened. This pilot is separate from CharLS Q3.

Explore the IBM hardware measurements and their limits

IBM Fez author-reported pilot: 144 to 103 two-qubit gates per circuit. Output distance improved in both cases; expected-energy minimization worsened. One hardware job, no independent confirmation or quantum advantage.

Published measure Ordinary joint5 Interpretation
Native two-qubit gates, each circuit 144 103 28.5% fewer
Output distance · vulnerable case 0.395175 0.316523 Closer to ideal ↓
Output distance · fixed case 0.403859 0.307958 Closer to ideal ↓
Expected energy · vulnerable case −2.345352 −2.013768 Higher; minimization worsened ↑
Expected energy · fixed case −2.366837 −1.954590 Higher; minimization worsened ↑

One six-variable fixture, two related cases, four circuits at 1,024 shots each, one hardware job and 3 seconds of billed QPU time. Billed QPU time is not end-to-end runtime. Output distance is total-variation distance. The author-reported acquisition is not independently confirmed and establishes no quantum advantage.

Measurement note and uncertainty → · Full-precision data →

Want to join the research?

We’re looking for developers and skilled contributors to help advance Aether’s AI + Quantum research program. Work includes improving the research CLI, developing and debugging repair chains, and strengthening the tools and experiments behind the program.

Applications are reviewed by Aether. Selected applicants receive access to the relevant research repositories and approved work areas after approval.

This is a research and development opportunity, not a red-teaming or security engagement.

Apply to join the research →

Tell us about your skills, relevant projects, and the research you’d like to contribute to.

Start here

Explore Aether Actions: connect a repository, review the permitted scope and approve usage. Explore the first Gen3 Q3 result: 24 of 24 cases passing, eight new passes and zero prior passes lost. Read the completed chain and the ongoing quantum-advantage objective.

Check coverage first. Predator Security requires an approved assurance profile. The current product page lists AetherCloud backend coverage; customer-specific profiles are private preview. Hosted Build & Test is a separate Actions service.

Generation map

Generation Current role Next threshold
Gen1–2 · Assurance foundation Locked Predator Actions profiles and scoped evidence Independently qualify each profile update
Gen3 · Active research First dependent-repair win: Q3 24/24 Demonstrate quantum advantage with credible comparisons
Gen4 · Conditional transfer Replicate qualifying research on assurance workloads Independent review and a separate profile release decision

A locked profile is a fixed, versioned set of checks and execution rules. Repository eligibility is checked before the customer approves UVT usage — Aether’s usage credits. Passing a profile does not mean every defect has been found. Gen3’s first win does not automatically qualify Gen4 or change a production profile.

Access and scope

Customers use approved Actions. Aether operates the private research engine. This public repository is not an installable research CLI. Connecting a repository does not expose arbitrary research loops, private model settings or quantum hardware controls. Engagements require an agreed, authorized scope.

The CharLS summary publishes approved aggregate outcomes and fingerprints. Private inputs, patches, raw receipts, trust material and execution infrastructure remain private. Public disclosure and replay scope →

Explore the tools behind the research

Serena / Arbiter develop and challenge proposals. Joint5, AQRC, Atlas and Crucible support compilation, verification and the return of evidence to later reasoning.

Nano supplies structured workflow rules. Unlimited Context retains context. Aether Protocol provides signed records that help detect changes to evidence. Signatures establish integrity within their trust assumptions; they do not independently prove a scientific claim.

Read the evidence

Resource What is available
Completed Q3 result Mechanism, completed chain, lift, provenance and limits
Q3 public data Counts, Q2 samples, stage identities and reproducibility scope
IBM Fez measurement note Separate hardware pilot, both outcomes and uncertainty
IBM public numerical record Full-precision measurements and retained-artifact fingerprints
Research and release roadmap Ongoing advantage objective and promotion criteria
Visual showcase Designed public overview
README consistency review Claim, link, rendering-structure and disclosure checks

First Gen3 win banked. The pursuit of quantum advantage continues.

Public overview and selected research notes · Proprietary research CLI and backend
© 2026 Aether AI LLC. All rights reserved. IBM is identified as the hardware provider; no affiliation or endorsement is implied.
Badges are editorial labels, not live CI or validation indicators. Visual sources.

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Predator by Aether AI: AI security assurance, adaptive compilation, and AI-quantum reasoning research. Locked profiles through Aether Actions. Public research showcase; research CLI remains private.

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