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Earlier sources: Artificial Intelligence
Artificial intelligence covers systems that learn from data, generate content, perceive their surroundings, or act toward a goal. Follow model research, agent tooling, evaluation, and the infrastructure used to build and run these systems.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗5401 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- Hugging Face · Model / dataset date · First archived
Asilarkness/DiffuRefill-1B — model update ↗
# DiffuRefill-1B **Status: pretraining, about half way.** Step ~100k of 200k, ~46B effective training tokens, merge round 290. The weights here are a live pretraining checkpoint: fluent English, facts still unreliable, not instruction-tuned. Use `global_ema.pt`; it is the best checkpoint at every round. A 1.08B masked-diffusion language model decoded with **confidence-targeted re-infilling**: draft the whole sequence in a handful of parallel denoising passes, then spend a few more passes rewriting only the tokens the model is least sure about. An autoregressive model needs one pass per token;
- Hugging Face · Model / dataset date · First archived
KrynexLabs/KrynexAI-1.4-150M-Mobile-Model — model update ↗
# KrynexAI 1.4    KrynexAI 1.4 is a compact, ultra-lightweight 150M-parameter language model designed for high-efficiency text generation, fast inference, and on-device deployment. ## 🧠 Model Summary KrynexAI 1.4 features an optimized Llama-based architecture trained on a multi-trillion token mix of web content, code, and educational data. It provides strong base capabilities in reasoning, instruction following,
- Hugging Face · Model / dataset date · First archived
shinonome4649ne/test — model update ↗
# shinonome_test ## Download model Weights for this model are available in Safetensors format. [Download](/shinonome4649ne/test/tree/main) them in the Files & versions tab.
- Hugging Face · Model / dataset date · First archived
francesca9805/tam-100mb-after-wc-zipf-newlex-after-ckpt500-packed-bfdiso_seed3407 — model release ↗
# Model Card for tam-100mb-after-wc-zipf-newlex-after-ckpt500-packed-bfdiso_seed3407 This model is a fine-tuned version of [francesca9805/ppt-wc-zipf-newlex-tam-after-100mb-packed-bfdiso_seed3407](https://huggingface.co/francesca9805/ppt-wc-zipf-newlex-tam-after-100mb-packed-bfdiso_seed3407). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation",
- Hacker News · Posted on Hacker News · First archived
Show HN: Anima – Interactive, cited biology figures using Claude Code ↗
Hacker News discussion.
- GitHub · Repository created · First archived
Alpha-Park/genpark-agentic-canary-deployment-drift-guard-skill ↗
Agentic Canary Deployment Drift & Metric Regression Guard. Conducts Welch's t-test statistical hypothesis testing between baseline and canary agent versions across P99 latency, error rates, and hallucination scores to execute instant automa | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550
- GitHub · Repository created · First archived
alphaparkinc/genpark-agentic-canary-deployment-drift-guard-skill ↗
Agentic Canary Deployment Drift & Metric Regression Guard. Conducts Welch's t-test statistical hypothesis testing between baseline and canary agent versions across P99 latency, error rates, and hallucination scores to execute instant automa | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550
- GitHub · Repository created · First archived
Alpha-Park/genpark-personal-agent-daily-information-diet-synthesizer-skill ↗
Personal Agent Daily High-SNR Information Diet Synthesizer. Aggregates research papers, industry feeds, and executive memos, scores signal-to-noise ratios (SNR), penalizes clickbait and domain echo chambers, and distills personalized 3-minu | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550
- Hacker News · Posted on Hacker News · First archived
Veda: The Agentic Hobby OS Added Video Player ↗
Hacker News discussion.
- GitHub · Repository created · First archived
alphaparkinc/genpark-personal-agent-daily-information-diet-synthesizer-skill ↗
Personal Agent Daily High-SNR Information Diet Synthesizer. Aggregates research papers, industry feeds, and executive memos, scores signal-to-noise ratios (SNR), penalizes clickbait and domain echo chambers, and distills personalized 3-minu | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550
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How to assess evidence about Artificial Intelligence
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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