Speech entered a real donor and returned a waveform.
The experiment split one learned second projection into eight equal channel experts. Selecting all eight reproduced the donor waveform with zero maximum and RMS error.
ERAIS / working systems
Follow a persistent world. Hear speech. Explore language, vision and reasoning. See how Fracture and native training build capabilities for one adaptive architecture.
Explore the results through the interface. The model weights and proprietary engine stay private.
Start here / real model output
Listen to a LuxTTS control beside its Fracture-converted speech route. The roles stay concealed: focus on the voice, the rhythm and the detail.
“A quiet lantern glowed beside the window while rain softened the empty street.”
“Please carry the blue folder upstairs and place it beside the wooden clock.”
“Can a careful machine explain its choices clearly when the answer is uncertain?”
“Fresh oranges, warm bread, and silver spoons were arranged across the table.”
Choose either voice. Playing one pauses the other.
These released clips use the ERAIS K7 route, which sparsifies two learned projections in one vocoder block. They demonstrate that conversion step; the broader Fracture programme targets the full adaptive native architecture. Explore the speech results.
Beyond the conversation turn
ERAIS carries state forward between observations. The live shared-world loop learns from recorded audio and language, then settles into low-cost maintenance while it waits.
Bring observations into shared state.
Apply the capability and effort needed.
Carry outcomes forward. Rest when quiet.
Fracture / learned capability, modular structure
Fracture reorganises learned components into composable experts. The full adaptive ERAIS architecture is the destination: the system chooses the capability and effort an input needs. This speech experiment lets you inspect one of the measured foundations.
Select an executed mode
Full bank: 8 / 8 experts selected per acoustic frame
Filled blocks show the selected count only. The measured router chose different expert identities for different acoustic frames.
The experiment split one learned second projection into eight equal channel experts. Selecting all eight reproduced the donor waveform with zero maximum and RMS error.
K4 used 50% and K2 used 25% of that projection. Whisper reported zero word edits on the same 12-word target while the quality sweep exposed the reconstruction trade-off.
The next vertical moves routing ahead of dense expansion, converts additional learned blocks, and measures end-to-end speech quality and speed.
A grouped physical-dispatch path is committed and equivalence-tested for the Qwen evaluator. Full-tower quality and speed measurements remain in progress.
8c893869c4bb8af672e6be05…184c9afc3f5fBuild on learned capability. Fracture is the conversion path; adaptive native ERAIS is the destination. Donor weights, activation traces and proprietary methods stay behind the interface. Bring Fracture to a valuable model workload.
Bonus / browser sound playground
A fresh three-stem loop synthesized entirely in your browser.
Interactive · local browser DSP
Change tempo, palette, or stems. Sound is created in this tab after your click; no recording, model request, or upload occurs.
Browser instrument: instant local synthesis with no upload or model request. For actual model-generated speech, listen to the Fracture comparison above.
Vision demo
Three predeclared site-owned cards evaluated offline; no camera or upload.
3 / 3 fixed cards visible
Top fixed output 74.76%
Top fixed output 91.20%
Top fixed output 87.34%
Measured foundation: the retained 5.22M-parameter run recorded 60.45% on its exact CIFAR-10 slice. These fixed cards make the response pattern inspectable while broader vision qualification advances through the next mask-overlap gate.
Text demo
A fixed capture from the reviewed native-byte checkpoint on an owned desktop CPU.
530 UTF-8 bytes · 110 words
Once upon a time, there was a little girl named Lily. She loved to play in the garden. One day,
Once upon a time, there was a little girl named Lily. She loved to play in the garden. One day, she saw a big bird with a big smile. She wanted to see what it was. Lily said, "Lily, it's time to go home. It is not for the big boy." So, they went to the park and saw the bird. The bird was so happy and said, "Thank you, Lily. You are a good friend." Lily smiled and said, "You're welcome, it's important to be careful with the bird."
What this demonstrates: an owned desktop CPU ran the native-byte checkpoint and produced this captured story. The inspector stays entirely on-page; Story Lab unlocks live generation after its service check.
Symbolic reasoning demo
One approved sensor example from the fixed controlled-English receipt.
All 4 receipt steps visible
Fact: the sensor is calibrated. Fact: the sensor is powered. Rule: anything that is calibrated and powered is ready. Question: is the sensor ready?
The sensor is calibrated.
The sensor is powered.
Calibrated and powered implies ready.
The sensor is ready.
Measured foundation: 30 fixed examples completed and 6 deliberately failed closed. The trace makes every conclusion inspectable; the live Lab unlocks after its service check.