THE INTERNET IS THINKING

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 ↗
Share this page ↗

5425 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. GitHub · Repository created · First archived

    Schuture/ai-systems-playground ↗

    Open-source repository in Python.

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

    Epic Games delays Disney game and tells developers to go "AI first" ↗

    Hacker News discussion.

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

    AI Can't Think for You ↗

    Hacker News discussion.

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

    wesjos/mario-html-4B — model update ↗

    # 🍄 Mario-HTML-4B A visual-UI language model fine-tuned from **Qwen3.5-4B**. It answers in a small semantic HTML component system — bento grids, metric cards, steppers, callouts — wrapped in one ` ` root, instead of plain Markdown. Multimodal, reasoning-native, and no system prompt required. | | | |---|---| | **Base** | [`Qwen/Qwen3.5-4B`](https://huggingface.co/Qwen/Qwen3.5-4B) · 4.66 B (bf16) · 8.68 GiB | | **Architecture** | `Qwen3_5ForConditionalGeneration` · 32 layers (24 linear + 8 full attention) · hidden 2560 | | **Context** | 262,144 native | | **Modalities** | text → HTML, text + im

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

    Threat of AI share crash puts world financial stability at risk, says IMF ↗

    Hacker News discussion.

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

    Ask HN: CAD for wood working with LLM support? ↗

    I’m a hobbyist woodworker. I manually design simple things in Shapr3d with a lot of patience when I build things. I wonder in the time of LLMs if there is an effective way to accelerate the 3D model design using AI.. Anybody tried using AI to model wood projects? Any tools to recommend?

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

    Lossless Image Editing with AI ↗

    Hacker News discussion.

  8. GitHub · Repository created · First archived

    PNWcoastie/REA-Argonaut ↗

    Zero-G Reverse Engineering Anything & Verified Safe Rust Reconstruction for Gemini 4 Argon + Google Antigravity 2.0 (4-Mount Recon Kits, Whole-Subgraph Extraction, 10,000-Vector Differential Parity Referee)

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

    DocCloak – Browser-Based Document Anonymizer for AI Submissions ↗

    Hacker News discussion.

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

    gter1216/glm-reduce-1m-multimodal-fp32 — model update ↗

    # GLM Reduce — frozen FP32 weights Author: Charles Xu. 986,520 parameters, frozen 2026-10-09. `model.safetensors` contains the trained FP32 tensors; `config.json` defines the reduced network. This weight-only repository does not include the executable model implementation or web server. Use the complete [CPU inference package](https://huggingface.co/gter1216/glm-reduce-1m-code) for installation and inference. The full package includes these same weights and pinned original Transformers source. `publication.json` identifies the GitLab source commit shared by both publications. Current evaluatio

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 ↗

Follow a thread

Explore related regions

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