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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.

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5972 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.

  1. Hacker News · Posted on Hacker News · First archived

    ALoDLM: Adaptively Looped Diffusion Language Models ↗

    Hacker News discussion.

  2. Hacker News · Posted on Hacker News · First archived

    Enterprise AI is vaporware without access to systems of record ↗

    Hacker News discussion.

  3. Hacker News · Posted on Hacker News · First archived

    Meta's Muse AI agent is building a dossier on you ↗

    Hacker News discussion.

  4. Hacker News · Posted on Hacker News · First archived

    Most AI data businesses should run as cash / dividend businesses ↗

    Hacker News discussion.

  5. Hacker News · Posted on Hacker News · First archived

    Rogue OpenAI agents accessed US Government websites ↗

    Hacker News discussion.

  6. GitHub · Repository created · First archived

    LosaLosSantos/aurelio-finance ↗

    Open-source personal finance app with an AI financial advisor: track your net worth, investments, ETFs, cash and debts on your own computer.

  7. GitHub · Repository created · First archived

    sparklecatta-lang/XSXB-Band ↗

    让 Agent 写谱,用真实录音的乐器演奏 · Let your agent write the score, real CC0 recordings play it. Local studio + agent skill, MIT.

  8. Hugging Face · Model / dataset date · First archived

    RicardoEstep/RPBizkit-v11-12B-Base-GGUF — model update ↗

    # RicardoEstep/RPBizkit-v11-12B-Base-GGUF This model was converted to GGUF format from [`RicardoEstep/RPBizkit-v11-12B-Base`](https://huggingface.co/RicardoEstep/RPBizkit-v11-12B-Base) using llama.cpp via "MY LOCAL COMPUTER". ## Use with llama.cpp or kobold.cpp 👀

  9. Hugging Face · Model / dataset date · First archived

    SZLHOLDINGS/szl-kernels — model update ↗

    # SZL Kernels · Governed Compute Explore the governed kernel suite and its receipted MiniEmbed word embeddings, with separate software and artifact evidence. **Artifact:** Kernel suite and MiniEmbed embedding table · **Stage:** Reference software · intrinsic sanity evidence [Explore in Command Lab](https://huggingface.co/spaces/SZLHOLDINGS/szl-command-lab) · [Build](https://github.com/szl-holdings/szl-kernels) · [Evidence](https://github.com/szl-holdings/szl-kernels/blob/331b259cf6b6dde17c4bdacc245e61c7addff506/README.md) ## Before you use it - MiniEmbed is a PPMI/SVD word-embedding table; it

  10. Hugging Face · Model / dataset date · First archived

    mulligan/real-square-d2-r05-baseline-dp — model update ↗

    # real-square-d2-r05-baseline-dp Part of [Mulligan](https://mulligan.page). Browse evaluations at [Policy Arena](https://arena.mulligan.page); the datasets are in the [mulligan](https://huggingface.co/mulligan) organization. Diffusion-policy actor in LeRobot's checkpoint layout (`config.json`, `model.safetensors`, pre/post-processor normalizers). The config also carries Mulligan fields (camera crop boxes, action target and frame) that stock LeRobot `DiffusionConfig` rejects; loading needs the Mulligan training code. | Property | Value | |---|---| | Task | real-square-d2 | | Model round | R5 |

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.

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These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.