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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 ↗5216 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.
- Hacker News · Posted on Hacker News · First archived
Escaped AI Agents Polluted the Web with Self-Replicating Code ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Center for the Alignment of AI Alignment Centers ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: ReliaMesh – Open-source reliability monitoring for AI agents ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Cicada: Sub-ms Go Zero-Trust gateway and gVisor firewall for AI agents Apache 2 ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
SGLang – High-performance serving framework for LLM's and multimodal models ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: HireReady, interview prep with spaced repetition and AI voice mocks ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
FTC probes Anthropic, OpenAI after Trump dismissed AI fears as "hoax" ↗
Hacker News discussion.
- Hugging Face · Model / dataset date · First archived
justicedao/uscode-autoformal-span-cache — dataset update ↗
# Paired US Code conversions, diagnostic census and deferred repair goals ## Read the actual formula strings Select **[formal_logic_text](https://huggingface.co/datasets/justicedao/uscode-autoformal-span-cache/viewer/formal_logic_text/train)** for source text and emitted formula text as the first columns, or read the **[annotated examples](https://huggingface.co/datasets/justicedao/uscode-autoformal-span-cache/blob/bf95253007ce123fb44a551806f4e29e9a30834b/autoformal/uscode/formula-text/v1/1c3c60623f70fc1466fbe65bd57d0b5fca95670ea0c67c3e33c7c93784d8005c/EXAMPLES.md)**. This is a fixed audit of
- Hugging Face · Model / dataset date · First archived
eac123/ptr-recurrent-depth — model update ↗
[](https://hf.co/chat?mode=ml-intern) # Do recurrent transformers learn length-generalising algorithms for pointer chasing? **Status: COMPLETE.** 17 trained models, full evaluation sweeps, figures and the technical report are in this repo. See **[REPORT.md](REPORT.md)** for the full write-up, `results/results_table.csv` for per-seed numbers, and `plots/` for figures. Live training dashboards: [eac123/ptr-recurrent-depth-trackio](https://huggingface.co/spaces/eac123/ptr-recurrent-
- Hugging Face · Model / dataset date · First archived
HermiHg/Qwen3.8-27B-Optimized-MTP-Heads-exl3 — model release ↗
# Qwen3.8-27B Optimized MTP Heads (EXL3) A **per-tensor mixed-precision EXL3 quantization** of the [Qwen3.8-27B](https://huggingface.co/Qwen/Qwen3.8-27B) **MTP (multi-token prediction) draft head**, packaged as a **sidecar** that shadows the built-in MTP weights of the base model. Each optimized checkpoint is *smaller* than the same-size uniform quant while posting equal-or-better draft acceptance — because bits are concentrated where the draft head is actually sensitive (the feature projection `fc`) and spent far more cheaply where it is not (`q`, `k`, `v`, `gate`). This is **not a standalone
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
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.
See the collection and counting methodology ↗ · Read the weekly synthesis ↗
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These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.