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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 ↗6002 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
A Rant About Claude Code's Auto-Memory ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
3 Engineers in Japan built an AI pentester that topped HackerOne VDP (2026 Q3) ↗
Hacker News discussion.
- GitHub · Repository created · First archived
T7moris/GPT-Niang-Usage-Widget ↗
GPT娘额度挂件：白发龙娘陪你查看 Codex 5 小时与每周剩余额度，支持语录、按压反馈、拖动缩放和随主窗口自动显示。Windows 本地插件。
- Hugging Face · Model / dataset date · First archived
Scicom-intl/semantic-vad-eot — dataset update ↗
# Semantic-VAD EOT End-of-turn (semantic VAD) turns, schema-compatible with [`livekit/eot-bench-data`](https://huggingface.co/datasets/livekit/eot-bench-data). Each row is one user **turn**: an audio clip (16 kHz **mp3**), its `words`, and ordered `silence_spans`. Per the eot-bench convention the **last** silence span is the true end-of-turn (`eot`); earlier spans are mid-turn `hold` pauses (labels positional, not stored). Timestamps are on the decoded-audio axis, and the decoded length equals `duration`. ```python from datasets import load_dataset, Audio ds = load_dataset("Scicom-intl/semanti
- Hugging Face · Model / dataset date · First archived
jonasaise/dpo-icelandic-interpreted — dataset update ↗
# Dataset Card for DPO Icelandic Interpreted ## Dataset Description This dataset contains Direct Preference Optimization (DPO) pairs translated and culturally adapted into Icelandic from the original `argilla/ultrafeedback-binarized-preferences-cleaned` dataset. ### Origin and Methodology - **Source Dataset:** [argilla/ultrafeedback-binarized-preferences-cleaned](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences-cleaned) - **Model Used for Synthesis:** `kimi-k3` (via local endpoint) - **Translation Strategy:** The dataset was generated using a specialized prompt desig
- Hugging Face · Model / dataset date · First archived
MehTheHedgehog/TinyQwen3-1.8M-Base — model update ↗
# TinyQwen3-1.8M-Base TinyQwen3-1.8M-Base is a small causal language model using the Qwen3 dense architecture. The tokenizer and model weights were pretrained from scratch on the `50k` configuration of [TinyStories-Tiered](https://huggingface.co/datasets/MehTheHedgehog/TinyStories-Tiered), a cleaned, deterministic and tiered edition of TinyStories. No pretrained Qwen weights were used. ## Model specification | Property | Value | | --- | --- | | Architecture | Qwen3ForCausalLM | | Parameters | 1,836,544 | | Layers | 2 | | Hidden size | 256 | | Intermediate size | 768 | | Attention heads | 4 | |
- Hacker News · Posted on Hacker News · First archived
Open-ended data is a bottleneck for AI systems tackling real knowledge work ↗
Hacker News discussion.
- Hugging Face · Model / dataset date · First archived
Kodjaoglanian/Qwen-3.5-4B-ASVD-Healed — model update ↗
# Qwen-3.5-4B-ASVD-Healed **Qwen-3.5-4B-ASVD-Healed** is a structurally compressed and optimized iteration of the base `Qwen/Qwen3.5-4B` model. It is the result of an advanced post-training neural surgery pipeline combining **Activation-Aware Singular Value Decomposition (ASVD)** with a rigorous recovery phase via **LoRA Healing** (Pruning-Aware Fine-Tuning), operating natively in `bfloat16` precision. ## Architecture Overview Traditional large language model (LLM) compression often relies on static quantization (such as INT4 or INT8), which inherently introduces dequantization latency during
- Hacker News · Posted on Hacker News · First archived
Positron – Purpose-built hardware for the age of generative AI ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Sriti Core – Local-first LLM router that cascades Ollama to cloud to frontier ↗
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.