Fewer FPGA engine cycles
2,523 → 13 cycles
The same bounded witnessed-path task on the same FPGA: conventional scalar firmware versus source-generated native dataflow.
Hardware comparison & complete timing →SEED STATE OS · INTEGRATION PROGRAMME
Make retained structure useful again. Seed State OS brings native execution, selective reconstruction and qualified structural reuse to application, device and system integration.
A SMALL CHANGE. A FOCUSED UPDATE.
Retained state Affected state
Workflow illustration, not a measured workload.UK patent application GB2624953.2 · Filed 22 October 2026 · Pending
RETAINED HARDWARE & GPU ACHIEVEMENTS
Native execution and selective reconstruction tackle different sources of repeated work. These are retained measurements from their respective qualified workloads.
2,523 → 13 cycles
The same bounded witnessed-path task on the same FPGA: conventional scalar firmware versus source-generated native dataflow.
Hardware comparison & complete timing →One changed tile. 4,095 retained.
131,072 versus 536,870,912 logical GPU threads across 32 rounds of a deterministic structured update.
GPU workload & output contract →Same device. Same operator.
Measured primary-run GPU execution ratios. Wider operational update comparisons recorded approximately 21–27× across the primary and repeat studies.
Timing boundaries & repeat →These results come from separate studies. In one FPGA task, timing the engine together with communication and verification fell from 2.9465 to 2.3319 milliseconds: 20.9% less elapsed time (1.264×). That figure describes this FPGA experiment alone. The CPU validation and GPU results have their own workloads and timers. The GPU operational comparison used warm retained state and excluded initial construction and the independent full-output evaluator. Follow the evidence notes for each comparison.
QUALIFIED SOFTWARE ROUTES
A retained repeat study compared compact route validation with expanded validation across 96 compatible structured-state fixtures, using an existing local atlas and receipts. The original study recorded approximately 2,548×.
CPU workload, retained dependencies & repeat →MAKE RETAINED STRUCTURE WORK AGAIN
Later tests measured the value of retaining several structures, competing with an optimised conventional cache, and reusing a qualified transformation on recurring requests.
A 16-slot collection versus one slot of the same native algorithm, over repeated four- and sixteen-structure request streams.
Collection comparison →156,524 versus 188,610 cycles against an optimised conventional 16-slot cache with hardware multiplication and equivalent current assertions.
Optimised comparator →Qualified retained-transform nomination enabled versus disabled. The complete mixed request corpus saved 20.42% of producer cycles.
Recurring and mixed results →Each percentage has its own comparator and workload. The 17.01% is a later, separate resident test; it is not an additional percentage applied to the 13-cycle engine result.
GLYX + SEED STATE
Exact archive restoration and current readmission have been checked in component studies. A newer 17 October versioned-data comparison retained 57.3% fewer logical bytes than trained Zstandard and 37.9% fewer than compacted Borg, with exact reconstruction checks.
The archive connection, with full accounting →REUSE ACROSS REQUESTS
Qualified bases and successful transform nominations can help compatible future inputs, including new related inputs. A growing-stream comparison combined checked-history reuse with route nomination and used 14.73% less conservative total time than size-based selection with repeated history scans, including setup and diagnostics. All 7,680 fresh full/range checks passed.
This measures a particular combined archive/state workflow. Conventional dictionary processing was faster on that workload, and individual requests did not continually become faster. Gains depend on applicable structure and the cost of maintaining it.
The growing-stream comparison and conditions →HISTORICAL CONDITIONAL MODEL · NOT ELECTRICALLY MEASURED
The arithmetic average of three historical scenarios is 94.05%, with scenario estimates from 89.72% to 97.71%. This projects energy per equivalent completed work under assumed workload shares. It is not a measured device-wide saving or a forecast for every customer.
The model uses work, timing and byte-avoidance proxies for energy reductions and assumes unchanged overhead shares of 10%, 5% and 2%. These assumed shares are not a calibrated workload survey. Average power in watts, battery life and electricity bills need their own deployment measurements.
See the three scenarios and assumptions →THE SEED STATE OS FILM · NARRATED BY AETERNUM · 6:04
The measured CPU, GPU and FPGA results, growing structural reuse, a clearly labelled historical energy projection and a focused integration route.
English captions are included in the film. Recorded comparisons retain their stated workloads and measurement boundaries. UK patent application pending.
THE OPPORTUNITY
When much of a structured state remains applicable, a system can focus on the necessary changes and dependencies, then check the reconstructed result.
Build the state a supported operation needs from retained information and exact changes.
Keep applicable foundations across updates instead of repeating the same preparation.
Make source, version and current applicability part of the release decision.
Evaluate a defined runtime or state engine within an existing application or device programme.
A PRACTICAL INTEGRATION PATH
Agree the state boundaries, dependencies and output contract for one workload.
Reuse applicable structure, apply exact changes and account for the complete reconstruction cost.
Compare exact outputs, latency, resource use and recovery with your existing implementation.
WHERE TO BEGIN
Choose a bounded integration where retained state and repeated reconstruction already matter to your product.
Explore selected restoration of verified tool state and task dependencies. Pair with TokenHoloFold for supported local execution.
Connect complete observed changes to affected state and, with a compatible renderer, affected image regions.
Target repeated state work within a phone, controller or appliance. Measure device latency, memory and joules on the intended hardware.
Restore exact records from GLYX, qualify them for current use and rebuild the required state.
These are integration opportunities. The component fixtures do not yet qualify this full set of applications or a general-purpose replacement operating system.
NON-EXCLUSIVE LICENSING
Begin with a scoped runtime integration. A successful device or application evaluation can support a wider commercial deployment.
SOFTWARE TEAMS
Proposed annual licence scoped to the deployed application or service, with agreed capacity and support.
DEVICE & PLATFORM MAKERS
Proposed development agreement followed by per-device royalties or annual volume bands. BBF retains its technology ownership.
MULTI-PRODUCT WORKLOADS
Assess Seed State, GLYX and TokenHoloFold together. Agree one measurement boundary and count shared savings once.
Private component and prototype evidence supports integration planning. UK patent application GB2624953.2 was filed on 22 October 2026 and is pending. Platform support, distribution, security, recovery and customer acceptance are qualified for each delivery.
SEED STATE LICENSING
Choose the agreement around your application or product. A fixed price follows the workload, target platforms, distribution rights and support scope.
Proposed annual runtime licence with agreed deployment and capacity bands. First qualify one repeated state operation against your best feasible current approach.
Proposed development agreement followed by per-shipped-device royalties or annual volume bands. Measure complete work on the intended hardware.
A proposed single savings share can cover agreed combined benefits. Shared storage or processing savings enter one ledger once, rather than attracting multiple percentage charges.
Seed State prices and OEM terms are to be agreed. Engine-cycle and logical-work reductions are technical measurements; pricing uses accepted deployment scope or actual eligible financial savings.
Prepare a Seed State evaluation brief ↗