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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 ↗5912 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.
- Hugging Face · Model / dataset date · First archived
wxzhang/Fast-dLLM-v2-7B-dTRPO-Lite — model update ↗
# Fast-dLLM-v2-7B-dTRPO-Lite dTRPO preference-finetuned Fast-dLLM-v2-7B. The dTRPO estimator selects positions using target-token probabilities within 32-token blocks. Policy and frozen reference use the same noisy inputs and selected positions. The reference is forwarded in training mode without parameter updates. ## Training parameters | Parameter | Value | |---|---| | Base model | Efficient-Large-Model/Fast_dLLM_v2_7B | | Learning rate | 5e-7 | | DPO beta | 0.01 | | # GPU |4 | | Per-device batch size | 2 | | Gradient accumulation | 64 | | Monte Carlo noise samples | 4 | | Noise microbatch s
- Hacker News · Posted on Hacker News · First archived
AI agent posted personal bank balances into company Slack ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
We tried to reproduce LLM judge position bias ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Woman Arrested After Conversation with Claude That Allegedly Included 'Threats' ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
A lightweight Codex–Claude Code pairing tool ↗
Hacker News discussion.
- GitHub · Repository created · First archived
xcisxc29/dsh-wechat ↗
WeChat channel for DeepSeek Harness
- Hugging Face · Model / dataset date · First archived
Rootport/HareSkip-calibration — dataset update ↗
# HareSkip Calibration Dataset ## 1. Summary This dataset contains all images and measurements generated during a July–September 2026 recalibration and method-comparison experiment for **HareSkip**, a step-skipping inference-acceleration extension for DiT-based image diffusion, implemented on top of [Forge neo](https://github.com/Haoming02/sd-webui-forge-classic/tree/b61642140acb7c2f1c65c5d0f2ab961b7366c02e) (upstream repository `Haoming02/sd-webui-forge-classic`, branch `neo`; the link is pinned to the commit used throughout the experiment). The HareSkip extension itself is in a separate repo
- Hugging Face · Model / dataset date · First archived
MartynU/hektor-wakeword — model update ↗
# hektor: wake word «Гектор» (openWakeWord) Кастомна модель openWakeWord для слова **«Гектор»**. Вхід: ознаки з embedding-моделі openWakeWord, форма `x [1, 16, 96]`; вихід: ймовірність 0..1. ONNX opset 18 (onnxruntime >= 1.14). > **Статус: перша експериментальна модель, якість поки замала для щоденного використання.** ## Метрики (validation, поріг 0.5) | Метрика | Значення | Ціль | |---|---|---| | Recall | 0.22 | > 0.8 | | Хибні спрацювання на годину | 1.42 | < 0.5 | | Accuracy | 0.66 | | Поріг краще підбирати на реальному пристрої, ймовірно нижче за 0.5. ## Дані та навчання - Позитиви: синтет
- Hugging Face · Model / dataset date · First archived
LegumMagister/chsm8-labeler-gemma3-1b — model update ↗
# Chess style labeler (Gemma-3-1B, distilled from Gemma-4-31B) Given one side of one chess game (moves plus a card of features measured from the board), the model writes five natural-language style instructions describing how that player played, at five lengths. It is a full fine-tune of `google/gemma-3-1b-it` on 3.02M label sets written by Gemma-4-31B (the [distill set](https://huggingface.co/datasets/LegumMagister/chsm8-labeler-distill)), and runs at about **154 games/s on one GH200 with vLLM**, about 80x the per-GPU throughput of the 31B teacher (7.4 records/s on 4 GH200 in FP8). ## Input a
- arXiv · Published · First archived
Artificial intelligence pathways from weather to climate ↗
Deep learning has made rapid advances in weather forecasting: autoregressive models trained on atmospheric reanalyses now rival dynamical models across nowcasting, medium-range, and subseasonal-to-seasonal lead times, producing well-calibrated ensemble forecasts at reduced cost. We review these advances and consider their extension to climate horizons, where the challenge shifts from initial-condition skill to producing reliable statistical responses under altered forcings. AI-powered climate prediction systems must produce credible forced responses to drivers (e.g., greenhouse gases, land-use…
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.
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