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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 ↗5931 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
Sunrisepeak/mcpp-language-server ↗
mcppls — a C++20/23 modules language server: one set of module semantics on GCC, Clang, MSVC and MinGW, for editors (VS Code, Zed, CLion, Neovim), AI Agents (MCP) and CI
- GitHub · Repository created · First archived
menma4ever/agentic-team-mcp ↗
Autonomous hierarchical multi-agent team (CEO -> Manager -> Workers) for Model Context Protocol (MCP). Mix Claude Code, Antigravity, Codex & Direct API with persistent SQLite queues and a real-time web UI.
- GitHub · Repository created · First archived
hazelpe/ComptyAI ↗
Turn token activity into compute. A compute-access protocol designed for Robinhood Chain: protocol fees fund GPU capacity for token holders.
- GitHub · Repository created · First archived
electric-capital/quest ↗
An open source, self-hosted, safety-focused AI workbench
- arXiv · Published · First archived
Learning Prognostic Variables for AI Convective Parameterizations via Symbolic Distillation ↗
Hybrid AI-physics climate modeling aims to improve coarse (~100km-resolution) Earth system models by learning to parameterize subgrid processes from high-fidelity data. However, this so far mostly involves local-in-time, diagnostic parameterizations, in which the subgrid state depends only on the current coarse state with no memory of previous states, which is unrealistic for processes such as convection that have intrinsic persistence. To address this, we enhance local-in-time parameterizations by learning prognostic variables that compactly carry important, additional past information where…
- GitHub · Repository created · First archived
malevrigns/agent-jev ↗
AgentJev-0.6B - a fast 'System One' decision model for AI Agents: feed it any unstructured state (diffs, traces, logs) and structured questions, get calibrated probability distributions back in one ~50ms forward pass. Zero output-token decoding.
- GitHub · Repository created · First archived
athrael-soju/Narwhal ↗
Adaptive disaggregated inference on a role-free fleet.
- GitHub · Repository created · First archived
smixs/code-quality ↗
Deterministic code quality gate for AI coding agents (Claude Code, Codex, pi): git hooks that block test tampering, hold the CRAP bar on changed functions, check diff coverage, secrets and dependencies. 12 languages, one config file. Optional Jev classifier for test hunks.
- GitHub · Repository created · First archived
emircan-sahin/gitviber ↗
Vibe code from one app: run agents in parallel worktrees, watch their diffs live, browse, test and commit. A 14 MB git client with a file explorer and terminal built in.
- GitHub · Repository created · First archived
Li-Evan/awesome-jev ↗
The most complete gallery of what people build with Jev, TypeSafe's System One model: 3,400+ projects, demos, and write-ups by scenario, each with its original link, image, and description.
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.