Phase Change Random Access Memory for Neuro‐Inspired Computing
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
Abstract Neuro‐inspired computing using emerging memristors plays an increasingly significant role for the realization of artificial intelligence and thus has attracted widespread interest in the era of big data. Thanks to the maturity of technology and the superiority of device performance, phase change random access memory (PCRAM) is a promising candidate for both nonvolatile memories and neuro‐inspired computing. Recently many efforts have been carried out to achieve the biological behavior using PCRAM and to clarify the related working mechanism. In order to further improve device performances, it is helpful and urgent to summarize and discuss the PCRAM solution for neuro‐inspired computing. In this paper, fundamentals, principles, recent progresses, existing challenges, and mainstream solutions are reviewed, and a brief outlook is highlighted and introduced, with the expectation to expound future directions.
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 | 0.001 |
| 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