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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 ↗6051 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
Meredith Whittaker on art in the age of AI ↗
Hacker News discussion.
- GitHub · Repository created · First archived
san086041-glitch/FailGate ↗
The acceptance layer for bug fixes: a failing test sealed for every bug, then used to grade every PR that claims to fix it — human or AI agent.
- arXiv · Published · First archived
DreamTest: World-Model Surrogates for Search-Based Testing of Deep Reinforcement Learning Agents ↗
Testing deep reinforcement learning (DRL) agents in cyber-physical systems aims to uncover diverse failures before deployment, but each execution can be expensive. Surrogate-assisted testing reduces this cost by learning to predict which test configurations are likely to fail. Prior surrogates treat the system as a black box and predict pass or fail outcomes directly; we instead model how a test unfolds and estimate failure from an imagined episode. We introduce DreamTest, a world-model surrogate for testing DRL agents. DreamTest adapts a recurrent state-space model to learn agent behaviour an…
- arXiv · Published · First archived
Reactivating Alignment: Defending LLMs from Jailbreaks via Intention-Aware Input-Output Matching ↗
Large language models (LLMs) remain vulnerable to jailbreak attacks that conceal harmful intent within complex adversarial prompts. Existing defenses primarily rely on input perturbation or harmful-output suppression, but they rarely model where malicious intent resides, resulting in brittle protection and excessive over-refusal. We propose SENTINEL, a plug-and-play, generation-time jailbreak defense that reframes mitigation as an intent extraction problem. Our key insight is that instruction-tuned LLMs exhibit strong input--output semantic consistency: regardless of jailbreak complexity, gene…
- GitHub · Repository created · First archived
Jakeschincariol/replica-skill ↗
Eleven free Claude skills that clone any app: reverse-engineer it, rebuild it, test it for bugs, then fix what its users hate. Free, MIT.
- Hugging Face · Model / dataset date · First archived
palerflavius/ro-real-estate-listings — dataset update ↗
# Dataset Card for Romanian Real Estate Listings Dataset ## Dataset Details ### Dataset Description This dataset contains publicly available real estate listings scraped from Romanian property websites. It includes structured information such as price, location, number of rooms, and surface area. The dataset is continuously updated through an automated data pipeline. - **Curated by:** Flavius Paler - **Language(s):** Romanian - **License:** MIT --- ## Uses ### Direct Use - Real estate market analysis in Romania - Data engineering and data pipeline practice - Machine learning experiments on tab
- Hugging Face · Model / dataset date · First archived
mindchain/imajev-9b-GGUF — model release ↗
[](https://huggingface.co/mindchain/imajev-9b-GGUF) [](https://huggingface.co/mindchain/imajev-9b-GGUF) -orange)   ![unverified](https://img.shields.io/badge/image%20path%20unverified%20on%20our%20hardware-lig
- GitHub · Repository created · First archived
trevaintdead/ai-game-modding-guides ↗
Guides for building game mods with AI coding agents: passthrough mods, Rust rewrites, mod loaders, prompting, and troubleshooting.
- arXiv · Published · First archived
The Robots are Coming: Artificial Intelligence Searching for Extraterrestrial Intelligence ↗
Breakthrough Listen, humanity's most ambitious search for technosignatures, or evidence of extraterrestrial technology, is carrying out surveys across the sky and across the electromagnetic spectrum, in images, spectra, time series, catalogs, and alerts. Classical techniques still play a major role in the search, but the recent rapid growth in the capabilities of artificial intelligence is enabling new and more powerful algorithms and approaches to be deployed across enormous datasets. Surveys designed to look for technosignatures are still a major focus for the Breakthrough Listen program, bu…
- GitHub · Repository created · First archived
robdmac/flow ↗
Ambient terminal scenes that move with your coding agent's work, for Claude Code and pi
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.