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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 ↗5306 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
akitaonrails/ai-book-2026 ↗
e-book version of the akitaonrails.com blog.
- Hugging Face · Model / dataset date · First archived
SilvioS/illegal_dumps_croatia_ortophoto — dataset update ↗
# Croatian Historical Illegal Dump Sites (2017-2026) ## Citation ```bibtex @misc{croatia_illegal_dumps_2026, author = {Silvio Sopic}, title = {Croatian Historical Illegal Dump Sites (2017-2026)}, year = {2026}, publisher = {Hugging Face}, url = {[https://huggingface.co/datasets/SilvioS/illegal_dumps_croatia_ortophoto](https://huggingface.co/datasets/SilvioS/illegal_dumps_croatia_ortophoto)} }
- Hugging Face · Model / dataset date · First archived
nvidia/PhysicalAI-Robotics-PhysicalAssets-VoMP — dataset update ↗
# VoMP: Predicting Volumetric Mechanical Properties ## Dataset Description: The Pre-Processed 3D Dataset is a dataset that is composed of 4 individual 3D asset datasets which are processed to render them from multiple views, voxelize the assets, and propagate VLM annotations for material properties. We release pre-processed data derived from the 3D assets, specifically: voxels, rendered images, and LLM-annotated material descriptions. This dataset is for research and development only. ## Dataset Owner(s): NVIDIA Corporation ## Dataset Creation Date: 27 October 2025 ## License/Terms of Use: Thi
- Hugging Face · Model / dataset date · First archived
FluidVerse/2D_SABW_SSOO — dataset update ↗
# 2D Shock-Induced Air Bubble Collapse in Water with Symmetric BC ## Description The dataset captures the time-evolving behavior of 2D cylindrical air bubbles subjected to an external shock wave in water. The interaction with the shock wave results in a collapse of the air bubble. Here we investigate a scenario with symmetric boundary conditions at the north and south walls. ## About the data |Metadata|Description| |-----|------| |Solver|[ALPACA](https://www.sciencedirect.com/science/article/abs/pii/S0010465521003581)| |PDE|2D compressible Euler equations| |Dimension|2D| |Number of Trajectorie
- Hugging Face · Model / dataset date · First archived
mist-models/mist-conductivity-27.0M-2mpg8dcd — model update ↗
# MIST: Molecular Insight SMILES Transformers MIST is a family of molecular foundation models for molecular property prediction. The models were pre-trained on SMILES strings from the [Enamine REAL Space](https://enamine.net/compound-collections/real-compounds/real-space-navigator) dataset using the Masked Language Modeling (MLM) objective, then fine-tuned for downstream prediction tasks. Further information is available in [our pre-print on arXiv](https://arxiv.org/abs/2510.18900). ## Model Details ### Model Description This fine-tuned MIST variant consists of the MIST-28M encoder finetuned t
- Hugging Face · Model / dataset date · First archived
vectorlink/multilingual-e5-base-GGUF — model release ↗
# multilingual-e5-base — GGUF (Q8_0) GGUF build of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) — a multilingual XLM-RoBERTa embedding model (278M params, 768 dimensions, 100 languages, `passage:`/`query:` asymmetric prefixes). Built **from first-party intfloat safetensors**, because no reputable quantizer publishes this model — this repo exists so downstream projects (vectorlink, TerminusDB) have an auditable supply chain rather than pulling a random community upload. ## Provenance | Step | Tool | Pin | |------|------|-----| | Source weights | `intfloa
- Hugging Face · Model / dataset date · First archived
apoorvumang/deepseek-v4-flash-news2026-lora — model update ↗
# DeepSeek-V4-Flash · Apr 2025 – Aug 2026 news knowledge (LoRA) A LoRA adapter that teaches `deepseek-ai/DeepSeek-V4-Flash-0731` world events from **April 2025 to August 2026**, past its knowledge cutoff, by continued pretraining on **909M tokens of real news** — no synthetic data, no QA pairs. Code, evaluation harnesses and the full recipe: **[github.com/apoorvumang/continual-learning](https://github.com/apoorvumang/continual-learning)** ``` Who is the mayor of New York City? base "Eric Adams ... took office January 1, 2022" + this "Zohran Mamdani ... took office January 1, 2026" When did Cha
- Hacker News · Posted on Hacker News · First archived
OpenAI finds recording device in one of their offices ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Parsimony – an open-source benchmark for how much code AI models add ↗
Existing benchmarks measure solve rate and token output/cost, but don't punish excess code, which makes a codebase harder to work with in the long term. I wanted to measure this since it matters most for long-term projects. Method: it takes the patches that benchmarks already publish (DeepSWE, SWE-bench Verified, SWE-bench Live) and counts "coding units": syntax elements like statements, calls, names and literals. I didn't use lines of code, so c…
- Hacker News · Posted on Hacker News · First archived
The UAE embraces AI for kindergartners ↗
Hacker News discussion.
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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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