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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 ↗5975 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
Jev and the Return of AI/ML Engineering ↗
Hacker News discussion.
- arXiv · Published · First archived
Terminal-Register Certification for Finite-Measurement Learning of Multiscale Quantum States ↗
Structured quantum-state learning not only depends on an expressive ansatz but also on an operational certificate that stays meaningful with finite measurements and imperfect implementation. We study pure one dimensional states learning by an inverse binary multiscale entanglement renormalization ansatz (MERA). In the learning procedure, the qubits removed during coarse graining are controlled coherently and measured together at the terminal register. We confirm that an ideal sequential and terminal measurement schedule delivers the same complete bit string distribution under matched causal op…
- GitHub · Repository created · First archived
brianhong-dev/omo-jev-plugin ↗
Jev-powered decision support for OmO and senpi agents
- GitHub · Repository created · First archived
scarletkc/seiso ↗
A Markdown convention and linter for project docs written by AI and read by humans and agents
- Hacker News · Posted on Hacker News · First archived
Your AI Agent Forgot Half of What You Told It ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Human-AI partnerships are for alignment, not capability ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Augur – Sandboxed macOS VMs with Xcode for AI Coding Agents ↗
Hacker News discussion.
- arXiv · Published · First archived
EverMine: Dissecting the Self-Evolution of Research Capabilities in Long-Horizon Alpha Research ↗
Self-evolving agents aim to turn research feedback into reusable skills, tools, and research rules. Whether these accumulated capabilities continue to improve later research requires controlled evaluation. Long-horizon alpha discovery provides a state-dependent setting: once a new factor enters the portfolio, the predictive information already covered changes, so the value of the same candidate or experience may change over time. We introduce EverMine, an empirical framework for studying self-evolving research capabilities in long-horizon alpha discovery. EverMine decomposes the research state…
- Hacker News · Posted on Hacker News · First archived
A wall that listens: the local-LLM pipeline behind an AI party in Vilnius ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Understanding the Four AI Risk Domains ↗
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.