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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 ↗5192 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
The AI labor apocalypse is on hold (for now) ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
OpenAI's blockbuster math proof isn't what you think it is ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
AI systems are improving rapidly at Slay the Spire and its sequel ↗
Hacker News discussion.
- GitHub · Repository created · First archived
TonyBucket/keys-keys ↗
An open-source Adaptive Hybrid Minecraft Server Copilot
- Hacker News · Posted on Hacker News · First archived
Digital Signatures Using Machine Learning-Based Encoding ↗
Hacker News discussion.
- Hugging Face · Model / dataset date · First archived
alexliap/typakos-140m-it — model update ↗
# Typakos-140M-it  The name "Typakos" comes from the Greek "Τυπάκος," meaning "small dude," a nod to the model's small (140M) parameter count. Typakos-140M-it is the instruction-tuned, preference-aligned chat model built on top of [`alexliap/typakos-140m-base`](https://huggingface.co/alexliap/typakos-140m-base), a 140M-parameter bilingual (Greek/English) base language model. It's produced by a two-stage post-training pipeline on the base checkpoint: supervised fine-tuning (SFT) for instruction-following and chat formatting, followed by Direct Preference Optimization (DPO
- Hugging Face · Model / dataset date · First archived
Asilarkness/DiffuRefill-facts — dataset update ↗
# DiffuRefill facts and teacher data Training data for the DiffuRefill-1B masked-diffusion language model (non-commercial research). - `sft_v1/big/` — Nemotron-Post-Training-Dataset-v1 (CC BY 4.0) math/STEM solutions rewritten by Qwen3.8-27B into short step lines ending `#### `, answer-checked against the source. - `sft_v1/tmpl_train/`, `tmpl_eval/`, `tmpl_code/` — program templates generated from teacher-verified problems, with sampled verified variants. - `sft_v1/teach/` — teacher-generated and teacher-verified questions and solutions. - Other files under `sft_v1/` are converted third-party
- Hugging Face · Model / dataset date · First archived
DaisyChainAI/DaisyChain-Train — model update ↗
# 🌼 DaisyChain-Train — Old Hardware Training Pipeline **Part of DaisyChain on 🤗 Hugging Face → https://huggingface.co/DaisyChainAI** Model page (weights + card): https://huggingface.co/DaisyChainAI/DaisyChain-Train --- > **In plain terms:** DaisyChain-Train lets you use **old / spare machines** to > train neural networks. The training runs through **emulated GPU logic** — > verified INT8 units (GUDA-style) that stand in for a GPU's math — so machines > *without* a modern GPU can still do the work. Chain several together and they > train one shared model as a cluster. > Before you rely on it,
- Hacker News · Posted on Hacker News · First archived
LLM vs. Decision models like Jev and use-cases ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Checkobot – Detect Deepfakes and AI Images ↗
Hello HN, I am Kartikeya & we are building the best AI Slop Detector - Checkobot. Current AI Image Detectors are functionally jagged. Some are not able to detect deepfakes, some fail on the latest flux models. Some have an unacceptable false flag rate on genuine images. We have been solving the deepfake detection problem at our parent company - SpoofSense.ai for a while now & we wanted to train a general purpose AI Image Detector that actually wo…
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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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