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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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5219 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

    Cohere to acquire AISLE for cyber-resilient sovereign AI ↗

    Hacker News discussion.

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

    What 1,866 popular GitHub projects tell their AI coding agents ↗

    Hacker News discussion.

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

    Why We're Banning AI ↗

    Hacker News discussion.

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

    Why "Replacing Engineers" Is the Wrong Goal for AI in Semiconductor Fabs ↗

    Hacker News discussion.

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

    Inside Agentic AI Workloads ↗

    Hacker News discussion.

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

    Show HN: Just gave Claude Code the website and ad budget to see what it would do ↗

    I build websites for a living. Lately, it's more about prompting than actually writing the code (the art part is still there). So I decided to leave that part to Claude too and see what it would come up with. So far, I have given it - A baseline website - Full access to Google, X, LinkedIn and Reddit Ads, with a budget - Apify access - Openrouter access I also wanted it to personalize the website completely based on the user. No 2 users see the s…

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

    Ask HN: Has anyone made real money from AI gen vibe coded app? ↗

    Hacker News discussion.

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

    turintech/d3-flash-Artemis-GGUF — model update ↗

    # d3-flash Artemis GGUF This is a decision model: use llama-server's `/v1/systemone` endpoint with `-ub 4096 -b 4096`. Follow [Run it](#run-it) for supported settings and app compatibility. **Start here.** Download `d3-flash-Artemis-IQ4_XS.gguf` (4.87 GB). 94.5% same answers as BF16; public Q4_K_M is slightly closer at a larger size. [Details](#how-it-was-tested). ![d3-flash: Typed-decision accuracy (%) versus file size. Upper left is smaller and better. Exact values are in the comparison tables below.](assets/comparison.png) Typed-decision accuracy on the card's selection panel, with the meas

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

    turintech/Kev-27B-Artemis-GGUF — model update ↗

    # Kev-27B Artemis GGUF This is a decision model: use llama-server's `/v1/systemone` endpoint with `-ub 4096 -b 4096`. Follow [Run it](#run-it) for supported settings and app compatibility. **Start here.** Download `Kev-27B-Artemis-IQ4_XS.gguf` (13.91 GB). 97.8% same answers as BF16; public Q4_K_M is closer on the benchmark sample. [Details](#how-it-was-tested). ![Kev-27B: Typed-decision accuracy (%) versus file size. Upper left is smaller and better. Exact values are in the comparison tables below.](assets/comparison.png) Typed-decision accuracy on the card's selection panel, with the measured

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

    nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-GGUF — model update ↗

    # NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-GGUF ![Accuracy](./accuracy.png) ## Description **NVIDIA Nemotron 3.5 Bolt 74B-A9B 24GB** is a vision-language model (VLM) designed to run everyday agentic tasks locally, using a native 2-bit quantization to fit in 24GB of memory and run alongside other applications. It optimizes intelligence and speed per GB. It aims to achieve the optimal balance between speed and intelligence, being faster than most popular dense models while smarter than most popular MoE models with a similar memory footprint. This model is ready for commercial or non‑commercial use.

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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Agents ↗AI Infrastructure ↗Coding Agents ↗Computer Vision ↗Language Models ↗Multimodal Systems ↗Research ↗Robotics ↗

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

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