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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 ↗5996 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.
- GitHub · Repository created · First archived
AcademiaSD/AcademiaSD_LoRAlab-TrainerStudio ↗
Train LoRAs for Qwen-Image 2.1, FLUX.2 Klein 9B, Krea 2, Z-Image, Ideogram 4, Anima, SDXL (Pony, Illustrious, NoobAI), LTX 2.3 and MiniMax-H3 on NVIDIA GPUs from 4–8 GB VRAM. One install, one launcher, NF4 models. Windows, Linux and RunPod.
- Hacker News · Posted on Hacker News · First archived
Viral AI agent Instinct raises $1B Series C at a $10B valuation ↗
Hacker News discussion.
- Hugging Face · Model / dataset date · First archived
espnet/yodas3 — dataset update ↗
## YODAS v3 [Paper](https://www.isca-archive.org/interspeech_2026/chen26d_interspeech.html) YODAS v3 is a large web-crawled dataset containing over 1.1 million hours of audio that were originally released under a **CC-BY-3.0** license. The dataset contains audio in over 100 languages. YODAS v3 can be used for a variety of multi-modal tasks, including Automatic Speech Recognition, Text-to-Speech, and Audio Representation Learning. We crawl a distinct set of videos from the [v1](https://huggingface.co/datasets/espnet/yodas) and [v2](https://huggingface.co/datasets/espnet/yodas2) versions of YODA
- Hacker News · Posted on Hacker News · First archived
Jensen Huang says AI distillation is 'competition.' ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Nvidia AI Agent Safety Stack ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Anthropic: Emergent Misalignment from Reward Hacking ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Opus 5.5 vs. GPT-6 in pi-agent: reasoning efforts and DeepSeek, GLM, Qwen ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Visual browser of 1,750 AI startup homepages to spot stylistic patterns ↗
Hacker News discussion.
- arXiv · Published · First archived
Is there a future for models in the LLM era? ↗
In an era where software development is deeply tied with Large Language Models, does Model Driven Engineering (MDE) still make sense? This raises the question of the extent to which MDE can be successfully combined with an LLM approach to address the downsides of each approach separately. In this paper, we try to answer that question by investigating a central Research Question: Can Agents powered by Large Language Models improve code generated from UML diagrams and text specifications by Model Driven Engineering (MDE) tools? To investigate this problem, we developed a novel LLM-powered Multi-…
- Hacker News · Posted on Hacker News · First archived
CrankGPT – hand powered offline physical AI box ↗
Hacker News discussion.
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 ↗
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These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.