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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 ↗5199 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
AI isn't just a tool and it might be dangerous ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: AI investment agreement review for startup founders ↗
Hi HN! First, congrats to the founders who received a term sheet(and those who will!) I made an investment agreement review tool for founders who recently received a term sheet! You can review your term sheets, SAFEs, convertible notes, and financing agreements if your corporation is incorporated in Delaware, from pre-seed through Series A. It also reviews equity purchase agreements, investor rights, voting terms, and side letters. Try it and che…
- Hugging Face · Model / dataset date · First archived
jalenluorion/Qwen3-30B-A3B-moved-store — model update ↗
# Qwen3-30B-A3B-Instruct, experts moved to disk [Qwen/Qwen3-30B-A3B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507) (Apache-2.0) re-laid-out so that only 5% of the parameters have to be in memory. Every expert is stored exactly once on disk as int8; nothing in the released model was retrained. The only trained parts are small routers that name, four layers ahead of time, which experts to read next, so the reads overlap the computation of the layers in between. | part | parameters | where | |---|---|---| | attention, embeddings, norms, the released router gates (`residen
- Hugging Face · Model / dataset date · First archived
jalenluorion/Qwen3-Next-80B-A3B-moved-store — model update ↗
# Qwen3-Next-80B-A3B-Instruct, experts moved to disk [Qwen/Qwen3-Next-80B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct) (Apache-2.0) re-laid-out so that only 3% of the parameters have to be in memory. Every routed expert is stored exactly once on disk as int8; nothing in the released model was retrained. The multi-token-prediction head of the release is not included. | part | parameters | where | |---|---|---| | attention and linear-attention layers, shared experts, norms, embeddings, output head, the released router gates (`resident.safetensors`) | 2.36B | memory (3.8
- Hugging Face · Model / dataset date · First archived
Quat3rnion/halogen-swift1.5-qwen3.8-flash-next-v2 — model update ↗
# Halogen Swift 1.5 Qwen3.8-Flash-Next v2 The current `qwen38-flash-next-v2-swift15.hgn` is a **fresh native-v2 conversion of the complete Swift 1.5 BF16 source**, not the previous 300-tensor transplant into peonist's checkpoint. The pinned source is [ukisai/Swift1.5-Qwen3.8-Flash-Next @ `0bd4fe22431372cdad1979267d3ab45aa7e6150a`](https://huggingface.co/ukisai/Swift1.5-Qwen3.8-Flash-Next/tree/0bd4fe22431372cdad1979267d3ab45aa7e6150a). No abliteration edit was applied. The [separate abliterated repository](https://huggingface.co/Quat3rnion/halogen-swift1.5-qwen3.8-flash-next-v2-abliterated) is
- Hugging Face · Model / dataset date · First archived
sphita/Intel-WebCorpus-forms — dataset update ↗
# 💻 Intel WebCorpus Forms (Enterprise Hardware Q&A) This dataset is a massive, high-fidelity archive of **176,472 technical troubleshooting discussions** (containing nearly **1 million individual messages**) scraped from the official Intel Community Forums. It has been meticulously engineered for Large Language Model (LLM) training. Instead of a raw, messy dump of isolated posts, the data has been **reconstructed into chronological conversation threads**, noise-filtered, deduplicated, and packed into optimized Snappy-compressed Parquet files. ## 📊 Dataset Summary | Metric | Count | | :--- |
- Hacker News · Posted on Hacker News · First archived
Show HN: Panelize – Ask ChatGPT, Claude, Gemini and DeepSeek Side by Side ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Not Found \ Anthropic ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Chiplab - Give your AI agent access to virtual hardware ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Omnis Watchtower – a supply-chain tripwire for Claude Code agents ↗
Hacker News discussion.
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.