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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 ↗5428 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.
- Hugging Face · Model / dataset date · First archived
gter1216/glm-reduce-1m-code — model update ↗
# GLM Reduce — reproducible CPU inference Author: Charles Xu. Model: frozen 2026-10-09, 986,520 parameters, FP32. Packaging release: cpu-inference-v1.2.1 (2026-10-13). Inference now uses the pinned implementation's default attention selection; weights are unchanged. This directory is the complete web/CLI inference package. The GitLab release is the canonical version; Hugging Face is published directly from a clean, pushed commit of this directory. There is no separate publication source tree. ## Install and run on Windows Tested with Windows x64, Python 3.14.7 and torch 2.14.0+xpu **executing
- Hugging Face · Model / dataset date · First archived
Magnarks/gemma-4-12B-it-abliterated-uncensored-nvfp4 — model update ↗
> Status: experimental. This is a direct BF16 → NVFP4 quantization made with llama-quantize, without calibration. It was an experiment, and no formal quality measurements are published for it. > > If you want an NVFP4 GGUF of a Gemma 4 12B uncensored model whose NVFP4 weights were produced by a dedicated quantization tool, see the separate repository [Magnarks/gemma-4-12B-it-heretic-NVFP4-GGUF](https://huggingface.co/Magnarks/gemma-4-12B-it-heretic-NVFP4-GGUF). It is a different model (TrevorJS's uncensored Gemma 4 12B, quantized to NVFP4 by xdavxd), not a replacement for this one. # gemma-4-1
- Hacker News · Posted on Hacker News · First archived
Show HN: A 3D sky city where my Claude Code agents work and take coffee breaks ↗
Open source, local and no telemetry.
- Hacker News · Posted on Hacker News · First archived
Don't Feed the AI - Anonymizer Proxy for AI-assisted Pentesting ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: GPT-3.5 answered, GPT-4 voided; I built an EOS gate for AGI ↗
Hacker News discussion.
- GitHub · Repository created · First archived
SubmitGame/awesome-ai-game-dev-tools ↗
Open-source AI tools for making games, and for decompiling, remixing and mashing up games you own. 100+ stars, active in the last year, refreshed daily.
- Hacker News · Posted on Hacker News · First archived
Intel Accelerates Open Infrastructure for the Agentic AI Era ↗
Hacker News discussion.
- arXiv · Published · First archived
Extreme events and statistics in an AI emulator of a global storm-resolving model ↗
We present HiRO-ACEv2 (High Resolution Output Ai2 Climate Emulator), a two-stage framework for AI emulation of the 3~km resolution X-SHiELD global storm-resolving model (GSRM), and highlight its ability to generate large ensembles of data for studying the characteristics of tropical cyclones and extreme events in high-resolution simulations at an inference computational cost over 300 times lower than that of traditional numerical GSRMs. HiRO-ACEv2 expands upon the precipitation-only HiRO-ACEv1 model to generate coherent precipitation, 10~m winds, and sea level pressure outputs, enabling a broa…
- Hacker News · Posted on Hacker News · First archived
Show HN: Search for AI agents with usefulness score built in ↗
Hi HN. I partnered with Simon Kley to build this project at innovation intelligence hackathon (Berkeley). Simply, we’re building a usefulness score on top of search for ai-agents. Instead of agents reading 10 ranked relevant pages, we run a usefulness score first and give it only those that pass. We’re able to save token and cost with this and slightly better answers. During our research, we found out that the current search results already do ju…
- Hugging Face · Model / dataset date · First archived
mradermacher/Cosmos-Reason2-8B-GGUF — model update ↗
## About static quants of https://huggingface.co/nvidia/Cosmos-Reason2-8B ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Cosmos-Reason2-8B-GGUF).*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Cosmos-Reason2-8B-i1-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quan
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.