Cognitive Informatics: Towards Future Generation Computers that Think and Feel
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
This keynote lecture presents a set of the latest advances in cognitive informatics (CI) that leads to the design and implementation of future generation computers known as the cognitive computers that are capable of thinking and feeling. The theory and philosophy behind the next generation computers and computing technologies are CI. The theoretical framework of CI may be classified as an entire set of cognitive functions and processes of the brain and an enriched set of descriptive mathematics, the cognitive computers are created for cognitive and perceptible concept/knowledge processing based on contemporary mathematics such as concept algebra, real-time process algebra, and system algebra. Because the cognitive computers implement the fundamental cognitive processes of the natural intelligence such as the learning, thinking, formal inference, and perception processes, they are novel information processing systems that think and feel. The cognitive computers are centered by the parallel inference engine and perception engine that implement autonomic learning/reasoning and perception mechanisms based on descriptive mathematics
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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