THE INTERNET IS THINKING
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 ↗5208 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
AI researchers are taking up smoking to signal to other researchers ↗
Hacker News discussion.
- GitHub · Repository created · First archived
0xgetz/notion-bulk-9router ↗
Bulk-create Notion accounts and auto-wire each into 9Router as an OpenAI-compatible AI provider. Zero-dependency Node toolkit: disposable-email signup, automatic session/token/cookie extraction, and one-command 9Router registration.
- Hacker News · Posted on Hacker News · First archived
Anthropic reinvents source control as Claude floods the world with code ↗
Hacker News discussion.
- arXiv · Published · First archived
The Code of Theseus: Can Agents Rebuild Software from Recovered Design Documents? ↗
LLM agents increasingly design a system before implementing it, yet the data to train and evaluate them centres on implementation and testing: requirements and design artefacts are often missing, outdated or private. Source code, in contrast, is abundant. Prior work recovers architecture documentation by feeding LLMs the source code or letting agents explore it, which saturates the context, does not scale to many repositories, and yields a single artefact rather than aligned ones. We present a framework that recovers aligned stakeholder intent, requirements and architecture from a compact repo…
- Hugging Face · Model / dataset date · First archived
software-mansion/react-native-executorch-multi-qa-MiniLM-L6-cos-v1 — model update ↗
# multi-qa-MiniLM-L6-cos-v1 This repository hosts the **multi-qa-MiniLM-L6-cos-v1** models exported for the [React Native ExecuTorch](https://www.npmjs.com/package/react-native-executorch) library as ExecuTorch `.pte` programs, ready to run on device. Upstream model: [multi-qa-MiniLM-L6-cos-v1](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/tree/main) ## Variants | Path | Backend | Precision | | --- | --- | --- | | `coreml/multi_qa_minilm_l6_cos_v1_coreml_fp16.pte` | coreml | fp16 | | `coreml/multi_qa_minilm_l6_cos_v1_coreml_int8.pte` | coreml | int8 | | `vulkan/multi_q
- Hugging Face · Model / dataset date · First archived
incrediblecrab/us-local-laws — dataset update ↗
# US Local Governments and Ordinance Coverage Every local government the Census Bureau's 2022 Census of Governments counts, 90,837 of them in the 50 states and the District of Columbia; which of them have ordinance text in [LOCUS](https://huggingface.co/datasets/LocalLaws/LOCUS-v1), a public corpus of local ordinances; and every local law in the New York Department of State's online search, 148,024 filings, with the State's older index of local laws, 130,075 rows, each matched where it can be to the government that filed it. It maps who makes local law, how much of that law LOCUS holds, and, f
- Hugging Face · Model / dataset date · First archived
mliu48/telearms-yam-cube-v4 — dataset update ↗
# TeleArms Bimanual YAM — Cube Manipulation (v4, sim-time) Teleoperated bimanual manipulation demonstrations collected in MuJoCo with a BimanualYAM robot, packaged in LeRobot v3.0 format for pi0.5 training. | | | | --- | ---: | | Episodes | 53,832 | | Frames | 28,326,930 | | Tasks | 48 | | Videos | 161,496 (3 cameras per episode) | | Control rate | 30 Hz | | Image size | 224 x 224 | | Size | ~180 GB | ## Observations and actions Three RGB views per frame — `camera_front`, `camera_left`, `camera_right` (224x224, H.264). Robot state and action are both 14-dimensional: 6 arm joints plus 1 gripper
- Hugging Face · Model / dataset date · First archived
software-mansion/react-native-executorch-all-MiniLM-L6-v2 — model update ↗
# all-MiniLM-L6-v2 This repository hosts the **all-MiniLM-L6-v2** models exported for the [React Native ExecuTorch](https://www.npmjs.com/package/react-native-executorch) library as ExecuTorch `.pte` programs, ready to run on device. Upstream model: [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2/tree/main) ## Variants | Path | Backend | Precision | | --- | --- | --- | | `coreml/all_minilm_l6_v2_coreml_fp16.pte` | coreml | fp16 | | `coreml/all_minilm_l6_v2_coreml_int8.pte` | coreml | int8 | | `vulkan/all_minilm_l6_v2_vulkan_fp16.pte` | vulkan | fp16 | | `xnnpac
- Hugging Face · Model / dataset date · First archived
nlpai-lab/MixLID — model update ↗
# MixLID ### Token-Level Language Identification in Mixed-Language Text **Demo:** [Hugging Face Space](https://huggingface.co/spaces/hongst/MixLID) **Paper:** [MixLID: Token-Level Language Identification in Mixed-Language Text](https://huggingface.co/papers/2610.16601) ([arXiv](https://arxiv.org/abs/2610.16601)) MixLID identifies the language of individual tokens, including short expressions embedded in another language. It supports **111 language labels** and returns both **language spans** and **one predominant language per input**. Numbers, punctuation, and symbols have separate labels: `NU
- Hacker News · Posted on Hacker News · First archived
Show HN: Fuel Gauge – Claude knows its own usage limits and stops at 95% ↗
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 ↗
Follow a thread
Explore related regions
These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.