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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 ↗5512 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
Show HN: LLM skill to generate editable 3D house designs ↗
I loved the stunning 3D designs created with Astra but they typically require a decent knowledge of Blender or Unreal engine which made it inaccessible. It also generated something you couldn't edit which is tricky for the design process where you typically need to try different ideas out. This is especially painful if each series of Astra loop's took 4 hours to complete. So... using Arcadium's online house editor tool - I created a skill to gene…
- arXiv · Published · First archived
EviRepair: Evidence-Driven Agents for Reliable Vulnerability Repair ↗
Recent advances in large language models (LLMs) have enabled agent-based approaches for repository-level automated vulnerability repair (AVR), showing promising repair capabilities. However, an important issue has received limited attention: how can we ensure that the evidence generated during the repair process is reliable enough to support accurate vulnerability understanding and patch generation? In this paper, we propose EviRepair, an evidence-driven multi-agent framework for repository-level AVR. EviRepair introduces evidence review into the repair process by enabling agents to collaborat…
- GitHub · Repository created · First archived
LeeJuls/ai-relay ↗
Local message relay between existing Codex Desktop and Claude Code conversations. Experimental Windows preview, MIT licensed.
- Hacker News · Posted on Hacker News · First archived
Show HN: Agentswap – Account Switcher for Claude Code, Codex and Antigravity CLI ↗
Hacker News discussion.
- GitHub · Repository created · First archived
qzkinhit/research-builder ↗
Research and paper-writing skill for Claude Code and Codex: faithful baselines, rigorous experiments, bilingual LaTeX papers, de-AI writing, figures and tables
- Hacker News · Posted on Hacker News · First archived
OpenAI sacks three safety researchers for breach of trust ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
AI leaders game out public revolt scenarios after catastrophic events ↗
Hacker News discussion.
- GitHub · Repository created · First archived
futureweb/intervals-mcp-server ↗
Advanced Intervals.icu MCP server for ChatGPT & Claude: Garmin-enriched metrics, all custom fields & streams, recovery insights, endurance performance analysis, OAuth. Community-maintained continuation of mvilanova/intervals-mcp-server.
- Hugging Face · Model / dataset date · First archived
GCSA-AiLab/GLM-5.3-Flash-Abliterated-LoRA-GGUF — model update ↗
# GLM-5.3-Flash-Abliterated-LoRA-GGUF Unofficial community derivative of [zai-org/GLM-5.3-Flash](https://huggingface.co/zai-org/GLM-5.3-Flash), published by GCSA-AiLab. 这是 GCSA-AiLab 发布的 [zai-org/GLM-5.3-Flash](https://huggingface.co/zai-org/GLM-5.3-Flash) 非官方社区衍生版本。 LoRA adapters only; a compatible base model is required separately. V1 and V2 differ in the distribution of edited layers. Select a version after testing it against your evaluation goals. 仅包含 LoRA 适配器，须另备兼容的基础模型。V1 与 V2 的差异在于修改层的分布，请按评测目标验证后选择。 ## Introduction and usage / 介绍与使用 [English](https://huggingface.co/GCSA-AiLab/GLM-5.3-F
- Hugging Face · Model / dataset date · First archived
mradermacher/Goetia-26B-A4B-v1.7-i1-GGUF — model release ↗
## About weighted/imatrix quants of https://huggingface.co/Naphula/Goetia-26B-A4B-v1.7 ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Goetia-26B-A4B-v1.7-i1-GGUF).*** static quants are available at https://huggingface.co/mradermacher/Goetia-26B-A4B-v1.7-GGUF **This is a vision model - mmproj files (if any) will be in the [static repository](https://huggingface.co/mradermacher/Goetia-26B-A4B-v1.7-GGUF).** ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70
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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