Rust
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)
Rust has 70 facts recorded in Dontopedia across 14 references, with 3 live disagreements.
Mostly:rdf:type(5), uses cached rotor state(2), depends on cached state for o1(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (11)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
assessesCoverageOfAssesses Coverage of(1)
- Helmholtz Breakthrough Audit
ex:helmholtz-breakthrough-audit
confirmedByConfirmed by(1)
- Paper Claim Gelation Step 11
ex:paper-claim-gelation-step-11
existsBetweenExists Between(1)
- Commutator Table Sign Discrepancy
ex:commutator-table-sign-discrepancy
impliesPrecisionAdvantageImplies Precision Advantage(1)
- Rust More Precise Than Sigmoid Schedule
ex:rust-more-precise-than-sigmoid-schedule
isCorrectIs Correct(1)
- Kappa Init
ex:kappa-init
isFullyIntegratedIs Fully Integrated(1)
- Givens Coupling
ex:givens-coupling
isSimilarForIs Similar for(1)
- Structural Evolution
ex:structural-evolution
lacksContentAwarePoleTrackingLacks Content Aware Pole Tracking(1)
- Helmholtz Fiber Adaptive
ex:helmholtz-fiber-adaptive
lacksTestsLacks Tests(1)
- Entity Binding Curriculum
ex:entity-binding-curriculum
notConnectedToInferenceCodeNot Connected to Inference Code(1)
- Metal Kernel in Lib Rs
ex:metal-kernel-in-lib-rs
requiresContentAwareDecayRequires Content Aware Decay(1)
- Helmholtz Fiber Adaptive
ex:helmholtz-fiber-adaptive
Other facts (68)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Implementation | [9] |
| Rdf:type | Software Implementation | [11] |
| Rdf:type | Software Implementation | [12] |
| Rdf:type | Implementation | [13] |
| Rdf:type | Software Implementation | [14] |
| Uses Cached Rotor State | Rotor State | [1] |
| Uses Cached Rotor State | true | [8] |
| Depends on Cached State for O1 | Rotor State | [1] |
| Uses Pure Cpu Vec F32 Arithmetic With Loops | Inference | [1] |
| Performs Raw F32 Arithmetic | Inference | [1] |
| Criticized for No Gpu Yet | Interlocutor | [1] |
| Presupposes Rotor Models Optimal | Cached State | [1] |
| Superior in Speedup With Sequence Length | Python Mlx | [1] |
| Scales Better With Sequence Length | Python Mlx | [1] |
| Known to Be Cpu Only Currently | Xenonfun | [1] |
| Accounts for Large Constant Factor | Algorithmic Advantage | [1] |
| Has Zero Overhead | Framework Overhead | [1] |
| Advocated As Superior | Python Mlx | [1] |
| Avoids All | Python Mlx Overhead | [1] |
| Teleologically Designed for Low Overhead | Raw Arithmetic | [1] |
| Is Native | true | [2] |
| Superior Performance | Mnist Task | [3] |
| Goes Further Than | Python Proposal | [4] |
| Achieves High Coverage | Helmholtz Breakthrough | [4] |
| Uses Explicit Tau | Pole Time Constants | [4] |
| Covers | Helmholtz Breakthrough | [4] |
| Covers Percentage of | 90 | [4] |
| Extends Beyond | Cals Full Pipeline Python | [4] |
| Integrates | Givens Coupling | [4] |
| Is More Precise Than Python | Pole Time Constants | [4] |
| Is Superior in Precision | Python Proposal | [4] |
| Matches | Helmholtz Fiber Fixed Decay | [4] |
| Superior Training | Python Implementation | [5] |
| Outperforms | Python Implementation | [5] |
| Trains Harder | Mnist Mlp Train | [5] |
| Presupposes Porting Needed | Cnn Support | [6] |
| Achieves Better Test Acc | Python Implementation | [6] |
| Has Not Ported | Cnn Front Ends | [6] |
| Replicates | Python Implementation | [6] |
| Lacks Kernel Fusion | Torch Compile Analogue | [7] |
| Post Prefill Complexity | O(1) | [8] |
| Scaling Reason | Cached Rotor State | [8] |
| Avoids Python Overhead | true | [8] |
| Avoids Graph Building | true | [8] |
| Avoids Gil | true | [8] |
| Avoids Framework Dispatch | true | [8] |
| Performance Advantage Source | Algorithmic Advantage | [8] |
| Overhead | zero | [8] |
| Execution Mode | raw f32 arithmetic | [8] |
| Uses Gpu | false | [8] |
| Cpu Implementation Detail | Vec<f32> arithmetic with loops | [8] |
| :is | Native Implementation | [9] |
| Has Accuracy | 99.1 | [10] |
| Compares Favorably to | Best Python Baseline | [10] |
| Uses Gpu Acceleration | Training Process | [10] |
| Performs More Effective Optimization | Training Process | [10] |
| Has Gelation Step | 12 | [10] |
| Has Evolutionary Dynamics | Equivalent Dynamics | [10] |
| Reaches Depth | 6 | [10] |
| Has Similar Parameter Counts | Python Implementation | [10] |
| Has Slower Wall Clock Time | Python Implementation | [10] |
| Has Test Accuracy | 69 | [10] |
| Overfits to | 1000 Sample Subset | [10] |
| Overfits More Than | Python Implementation | [10] |
| Trains More Effectively | Python Implementation | [10] |
| Has Coverage Percent | 90 | [11] |
| Coverage Is Approximate | true | [11] |
| Training Intensity | harder | [12] |
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
References (14)
ctx:discord/blah/watt-activation/part-454ctx:discord/blah/watt-activation/part-456ctx:discord/blah/watt-activation/part-468ctx:discord/blah/watt-activation/part-473ctx:discord/blah/watt-activation/part-477ctx:discord/blah/watt-activation/part-469ctx:discord/blah/watt-activation/part-641ctx:discord/blah/watt-activation/452- full textwatt-activation-452text/plain3 KB
doc:agent/watt-activation-452/ff1dd4f5-3233-4ae2-8f83-249a90fd3e1dShow excerpt
[2026-03-21 05:42] xenonfun: ⏺ The Rust timings include process startup + weight loading (~230ms), so let me subtract that overhead for a fair comparison: ``` ┌────────┬──────────────────┬──────────────────────────┬─────────┐ │ Tokens │…
ctx:discord/blah/watt-activation/454- full textwatt-activation-454text/plain3 KB
doc:agent/watt-activation-454/4f6603bc-7db5-4694-932b-2c38bbe4bc5bShow excerpt
[2026-03-21 06:17] xenonfun: Back to Rust ``` 1 - [project_vision.md](project_vision.md) — HarmonicRust replaces Python HarmonicMLX + Phase Hub with Rust 2 - [user_profile.md](user_profile.md) — User builds novel manifold-based ML architect…
ctx:discord/blah/watt-activation/464- full textwatt-activation-464text/plain3 KB
doc:agent/watt-activation-464/599938d0-3182-4b42-bb04-4488236f82bcShow excerpt
[2026-03-21 18:08] xenonfun: ``` Key observations: - Rust achieves significantly higher accuracy (99.1% vs 89.5% best) — the GPU-accelerated training does more effective optimization per epoch - Gelation detected at the same step (12)…
ctx:discord/blah/watt-activation/471- full textwatt-activation-471text/plain3 KB
doc:agent/watt-activation-471/2422db4e-e816-4cee-91c6-8067b50fc309Show excerpt
[2026-03-21 19:31] xenonfun: ``` ⏺ Pushed. Here's the summary of both research results: Helmholtz Breakthrough Audit Rust covers ~90% of the breakthrough. Key findings: ┌───────────────────────────────┬────────────────────────────────…
ctx:discord/blah/watt-activation/475- full textwatt-activation-475text/plain2 KB
doc:agent/watt-activation-475/e1172583-2318-4515-b9d4-b2208603f689Show excerpt
[2026-03-21 20:42] xenonfun: ``` ⏺ Clean tree, all pushed. Here's the full session summary: Session Summary: 15 commits, ~20K new lines FedSym Evolutionary Framework (complete): - 15 modules: config, activation, unit, training, fusi…
ctx:discord/blah/watt-activation/486- full textwatt-activation-486text/plain3 KB
doc:agent/watt-activation-486/c8568fef-e9f2-4d48-9840-89f375514ea3Show excerpt
[2026-03-22 03:19] xenonfun: ``` ⏺ The IVF was useless before because ivf_dirty got set on every insert (128/step), and only cleared every 500 steps on rebuild. So 99.7% of lookups fell back to linear scan. Now: - New entries get assigne…
ctx:discord/blah/watt-activation/631
See also
- Rotor State
- Inference
- Interlocutor
- Cached State
- Python Mlx
- Xenonfun
- Algorithmic Advantage
- Framework Overhead
- Python Mlx Overhead
- Raw Arithmetic
- Mnist Task
- Python Proposal
- Helmholtz Breakthrough
- Pole Time Constants
- Cals Full Pipeline Python
- Givens Coupling
- Helmholtz Fiber Fixed Decay
- Python Implementation
- Mnist Mlp Train
- Cnn Support
- Cnn Front Ends
- Torch Compile Analogue
- Cached Rotor State
- Implementation
- Native Implementation
- Best Python Baseline
- Training Process
- Equivalent Dynamics
- 1000 Sample Subset
- Software Implementation
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