The odyssey to next-generation computers: cognitive computers (κC) inspired by the brain and powered by intelligent mathematics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cognitive computers (κ C ) are intelligent processors advanced from data and information processing to autonomous knowledge learning and intelligence generation. This work presents a retrospective and prospective review of the odyssey toward κ C empowered by transdisciplinary basic research and engineering advances. A wide range of fundamental theories and innovative technologies for κ C is explored, and a set of underpinning intelligent mathematics (IM) is created. The architectures of κ C for cognitive computing and Autonomous Intelligence Generation (AIG) are designed as a brain-inspired cognitive engine. Applications of κ C in autonomous AI (AAI) are demonstrated by pilot projects. This work reveals that AIG will no longer be a privilege restricted only to humans via the odyssey to κ C toward training-free and self-inferencing computers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it