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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 ↗6062 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.
- OpenAlex · Published · First archived
Application of Retrieval-Augmented Generation Large Language Models in Stomatology: A Scoping Review ↗
Large language models (LLMs) have been gradually applied to tasks such as specialized question answering, educational assistance, clinical decision support, and knowledge integration in stomatology. However, general-purpose LLMs still suffer from critical limitations, including outdated knowledge, hallucinatory generation, untraceable information sources, and inadequate clinical adaptability. Retrieval-augmented generation (RAG) offers a core solution for improving the accuracy, interpretability, and evidential traceability of model outputs by integrating external authoritative knowledge sourc…
- OpenAlex · Published · First archived
PIGNN3D: an accelerated physics-informed graph neural network for 3D thermal field simulation in data centers ↗
Abstract Efficient thermal management is critical in data centers, where computational fluid dynamics (CFD) simulations provide high-fidelity airflow and temperature predictions but remain computationally demanding and time-intensive. While data-driven methods have emerged as promising alternatives, most existing works are limited to small-scale or 2D flow simulations and face challenges when extended to complex 3D domains. To overcome these challenges, we present PIGNN3D, a physics-informed graph neural network designed for fast and efficient 3D thermal field simulation in data centers. PIGNN…
- OpenAlex · Published · First archived
Potential of multi-anomalies detection using quantum machine learning ↗
Machine learning is widely used for industrial anomaly detection; however, when anomaly distributions overlap, high false positive rates (FPR) often occur, hindering practical implementation. While quantum kernel methods have been proposed as a solution, the specific conditions under which they outperform conventional methods remain unclear. This study investigated the conditions under which quantum kernels outperform the classical RBF kernel in industrial acoustic anomaly detection. Using autoregressive (AR) features and an unsupervised One-Class SVM, we compared a conventional radial basis f…
- Europe PMC · Published · First archived
AntiCapt: Fine-Tuned Nucleotide Language Models for Predicting and Designing Anticancer Aptamers ↗
Over the past decade, aptamers have emerged as promising therapeutics, with cancer therapeutics as a major research area. Existing computational methods, however, either predict aptamer-target pairs or design aptamers against a specific target. In this study, we present AntiCapt, a computational method for identifying single-stranded DNA (ssDNA) anticancer aptamers (ACAs) using sequence descriptors and fine-tuned nucleotide language models. The main dataset comprises 1,021 experimentally validated ACAs and an equal number of non-aptamer sequences. Comparative analysis revealed distinct pattern
- Europe PMC · Published · First archived
Bacterial Cheminformatics: Large Language Models and Challenges in Bacterial Chemspace ↗
The escalating global crisis of antimicrobial resistance (AMR), often characterized as a "silent pandemic," necessitates a paradigm shift in antibiotic discovery. Traditional cheminformatics pipelines, reliant on hand-crafted molecular descriptors and low-throughput screening, are increasingly insufficient to address the evolving threats of multidrug-resistant pathogens. This Opinion article explores the transformative integration of Large Language Models (LLMs) and foundational Transformer architectures into bacterial cheminformatics. We argue that the field is transitioning from simple discr
- Europe PMC · Published · First archived
Prompt-as-a-Protocol with Agentic Research Automation: A Validated Methodology for AI-Native Biomedical Data Science Producing Peer-Reviewed Findings Across Genomics and Biosensor Domains ↗
Recent advances in large language model (LLM)-driven agentic systems have demonstrated capabilities for automating biomedical data analysis workflows. However, existing systems are predominantly validated on synthetic benchmarks or retrospective tasks, without demonstrated production of novel, peer-reviewed biological findings. Here we describe Prompt-as-a-Protocol (PaaP), a methodology that converts natural-language research questions into structured, executable analytical protocols, coupled with an agentic Generative Research Automation (GRA) layer that executes these protocols with integrat
- Hugging Face · Model / dataset date · First archived
mlai-dante/road-model-public — model update ↗
# ROAD Barbados Historic Handwriting Qwen3-VL Adapter This repository contains a LoRA adapter fine-tuned for the Zindi R.O.A.D. Barbados Historic Handwriting Challenge. Base model: `Qwen/Qwen3-VL-8B-Instruct` The adapter was trained to transcribe cropped images of historical handwritten Barbados archival records into text. ## Validation - cer: 0.079004 - wer: 0.222702 - score: 0.150853 ## Inference Prompt ```text You are transcribing a cropped image from an old Barbados archival record. The image contains handwritten historical text, usually one line or a short phrase from an 18th or 19th cent
- Hugging Face · Model / dataset date · First archived
mulligan/real-routing-d2-r05-mulligan-dp — model update ↗
# real-routing-d2-r05-mulligan-dp Part of [Mulligan](https://mulligan.page). Browse evaluations at [Policy Arena](https://arena.mulligan.page); the datasets are in the [mulligan](https://huggingface.co/mulligan) organization. Diffusion-policy actor in LeRobot's checkpoint layout (`config.json`, `model.safetensors`, pre/post-processor normalizers). The config also carries Mulligan fields (camera crop boxes, action target and frame) that stock LeRobot `DiffusionConfig` rejects; loading needs the Mulligan training code. | Property | Value | |---|---| | Task | real-routing-d2 | | Model round | R5
- Hacker News · Posted on Hacker News · First archived
Noodle AI Bots Mac App ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
LibDragon (N64): Explicit Anti-AI Contributor Stance (GitHub Issue) ↗
Hacker News discussion.
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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.
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