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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 ↗6029 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
Making AI helpful for everyone, including the planet ↗
Hacker News discussion.
- GitHub · Repository created · First archived
VORNEX-01/JARVIS-VORNEX ↗
Voice-first desktop assistant for Windows — talk to your PC and it works inside real apps, safely. By VORNEX.
- Hacker News · Posted on Hacker News · First archived
Anthropic IPO prospectus reveals surging costs, $42B 2025 net loss ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Lemma.work – Open-source AI coworkers your whole team can share ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Rsync.ai – self-hosted CDC and ETL/ELT, source-available (ELv2) ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Meta's new AI agent built lists of people in vulnerable groups on request ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
When single AI agents become a swarm ↗
Hacker News discussion.
- GitHub · Repository created · First archived
Anil-matcha/awesome-uncensored-llms ↗
Source-tracked catalog of abliterated, low-refusal, and community-reported open-weight and hosted language models
- arXiv · Published · First archived
TaskBridge: Bridging Unsupervised Tabular Anomaly Detection and In-Context Learning via Virtual Tasks ↗
Unsupervised tabular anomaly detection (TAD) aims to identify anomalous rows in tabular data using normal training samples. While conventional methods rely on dataset-specific training and configuration search, recent tabular foundation models (TFMs) enable zero-shot anomaly detection on unseen datasets via in-context learning. Most TFM-based approaches, however, require anomaly-specific pretraining from scratch, making detection inherently dependent on synthetic TAD-specific priors and costly to update. Some approaches instead repurpose pretrained general-purpose TFMs for TAD to avoid this bu…
- arXiv · Published · First archived
Beyond Token Importance: Preserving Spatial Scaffolds for Efficient Vision-Language-Action Inference ↗
Existing VLA pruning strategies primarily select individual visual tokens according to task-level semantic relevance, while overlooking the spatial information required for robotic manipulation. To examine this limitation, we construct a simple Stride baseline that uniformly samples tokens along the flattened one-dimensional visual sequence, representing a purely geometric pruning strategy. Surprisingly, Stride outperforms semantic pruning and random pruning at certain pruning ratios, but collapses when the token budget is only slightly reduced. We characterize this phenomenon through the spat…
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.