Infinity
Plesiochronous gradient consensus for distributed AI training using sub-nanosecond hardware synchronization.
Mechanism
A distributed computing apparatus in which each compute node operates from an independent local clock oscillator disciplined by a hardware-distributed sub-nanosecond timing reference. Per-node hardware elastic buffers operate at gradient-tensor granularity. A hysteretic-watermark occupancy monitor, plus a phase-correction sideband signaling path electrically distinct from the high-speed serial data interface, closes the loop on cross-node drift.
A downstream gradient-consensus circuit reads from all elastic buffers when all simultaneously satisfy a minimum readout threshold, performs sign-quantized majority-vote consensus via parallel popcount, and commits the voted result to a temporally coherent shared memory pool indexed by a 64-bit regime identifier. A watchdog timer decoupled from the epoch counter renders graceful degradation deadlock-free.
Prior-art differentiator
Software collective communication libraries hide timing in queue management at microsecond-to-millisecond latency. Infinity exposes timing as a first-class hardware primitive at nanosecond latency. In-network aggregation schemes buffer transiently for line-rate arithmetic but lack the closed-loop hardware feedback to throttle source compute. Cache coherence protocols cannot meet the deterministic ordering required at epoch boundaries.
Five load-bearing elements of the apparatus claim do not jointly appear in any single prior reference: hardware-disciplined master read-side clock; elastic buffer with hysteretic watermark feedback at gradient-tensor granularity; cross-node minimum-readout-threshold trigger; popcount-based majority vote; regime-versioned temporally coherent shared memory pool with watchdog-driven graceful degradation.
Empirical validation
A controlled continual-learning simulation of the plesiochronous consensus mechanism shows a substantial reduction in catastrophic forgetting versus a non-plesiochronous baseline running the identical sequential fine-tuning task. The result was reproduced across NVIDIA A100, NVIDIA H100, and Apple silicon hardware within tight tolerance, and a subsequent multi-vendor verification pass across three cloud providers reproduced the headline result. Per-mechanism dose-response data is held back per ordinary commercial-disclosure judgment.
Counsel posture
Twelve-month conversion and PCT deadline 2027-05-01. Track One Prioritized Examination alongside PCT filing recommended; claim count limited to four independent and thirty total claims to comply with Track One requirements. UALink Consortium engagement target 2026-07-30 (ninety-day post-filing window). Exhaustive freedom-to-operate sub-search across hyperscaler-specific interconnect references prior to non-provisional drafting.
Parent primitive. Trinity establishes plesiochronous synchronization at video-scanline granularity; Infinity scales the same primitive to gradient-tensor granularity for distributed AI training.
Software analog. Infinity is the apparatus parent; K-Pool LoRA mirrors the K-pool retention, sign-quantized active update, and regime-identified routing at the LLM adapter-pool layer.