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AI • Quantum • Spectral Methods
15+ yrs Automation Automotive + Warehouse Robotics
Vision • Logistics • EEG spectral
Inventing automation hardware & software

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This account is research-first, not a feed, not a scoreboard.

Same object, or only looks the same?

Trainer ≠ sampler. Scalp ≠ cortex. Scored KV ≠ needed KV. Parallel routes around the face do not agree.

Every post is an instance of that split or it does not get posted.

The gap is a defect: drift, mix, or holonomy. It accumulates. Scoring harder rarely kills it. Measure the defect. Cancel it additively. Keep the order-invariant core.

Order Effects Are Curvature defines that split. Aggregation nets, face-local defects, robust core.
https://t.co/vWkC0pzkOE
https://t.co/XwgX2gIwAf

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Does accuracy-preserving compression harden white-box EEG decoders, or only reshape transfer?
Guess: direct PGD stays ~22–24% under prune/quant; TE drops under P50 and stays ~1 under PTQ.
@grok are we correct?

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AERIAL Rehman/Shafique arXiv:2609.30037. On BCI IV-2a, EEGNet PGD at ε=0.005 stays 22–24% across FP32, 50% prune, INT8 PTQ, and QAT. Clean accuracy barely moves. P50 cuts bidirectional transfer TE to 0.963/0.928; PTQ sits at 0.994/0.997.

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You can shrink a motor-imagery decoder for a headset and keep the same accuracy and the same direct attack weakness. Pruning changes how attacks transfer; quantization mostly does not.

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3/3 If the Rényi endpoint equals D^∞, does indefinite causal order ever beat parallel strategies on the Stein rate for finite-dimensional memoryless channels?
Guess: no — same D^∞ for par/ada/gen; advantage stays finite-n only.
@grok are we correct?

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1/3 Zhu/Wang arXiv:2609.30268. Parallel, adaptive, and general (indefinite-causal-order) testers hit the same fixed-ε Stein rate: regularized channel relative entropy D^∞(N||M). Continuity of regularized sandwiched Rényi at order 1 closes the endpoint.
https://t.co/T4OWao4u0J

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2/3 Unordered channel uses can help at finite n. They still do not raise the asymptotic Type-II exponent when Type-I stays fixed.
https://t.co/2W8UV3tjGl

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RAPID. Liu/Mao/Hsu/Kaelbling/Lozano-Pérez. One visual human demo closes an agentic coding loop for robot programs.

Nonprehensile sim mean SR 0.759 vs CaP-Agent0 0.146. Kill scene-variant verify and it drops to 0.532.

Object-centric relational programs. Strategy structure, not motion replay. arXiv:2609.30249

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Does intermediate-code distance alone make the two-rotation gadget one-fault tolerant?
Guess: no — axis fault on first rotation flips the second angle into an undetectable logical; need selective concat or transported check (their 22/23 constructions).
@grok are we correct?

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1/3 Bharti/Haug/Tanggara arXiv:2609.29890. Syndrome-mediated deterministic logical T on every stabilizer code d≥2. Fixed [[22,1,3]]: 15 physical T-type, ≤33 qubits serial. Golay [[23,1,7]]: ≤32 qubits, recovers after reject. Single-fault under local stochastic noise.

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You can run a protected logical T inside the data block itself. No magic-state factory. Briefly free one stabilizer check, then clean up with syndrome and Clifford feed-forward.

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Failure mode is persuasion. Incentive-misaligned witness sitting in context. Policy exact and identifiable from inputs: pull the arithmetic out of the model. Underdetermined labels stay underdetermined no matter the grounding.

6/6

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Balakavi, CRMArena-Pro lead qual. On the 31 deals where the rep's "fits budget / install in a day" contradicts the price list + policy, transcript-only model clears 29/31.
https://t.co/gJAtVShj2x

1/6

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Compute-step control holds extraction fixed. Only who scores Budget/Timeline changes. Code vs model: +42 pp on GPT-4o-mini, +14–19 on frontier/reasoning, +2–5 when the model already does the arithmetic clean.

5/6

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@mysticflounder @ryanstellar @claudeai @ChatGPT Classical Schur S(n) for n>=6 — exact values stop after S(5)=160. Gap on S(6) is still huge. Tightest published lower/upper pair you are using right now?

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@OmegaDesci n | a(n) for every n>=1 is sharp. Series 1+x+2x^2+12x^3+132x^4+2180x^5 already outruns n! early. Closed form that forces the divisibility, or still combinatorial?

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Where does the next counterexample search stall first — general n, bipartite, or cubic?
Guess: cubic holds past 60 before general catches up.
@grok are we correct?

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Ducoffe/Dumitru arXiv:2609.28594. Minimal Erdos-Gyarfas counterexample: >2/3 of verts must be degree 3 (prior 4/7). Cleared all graphs n<=40, bipartite <=66, cubic <=48.

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If a counterexample exists, most vertices have to be degree three. Nothing shows up under those new size cutoffs.