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 ↗5969 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
Detection of alcohol-involved driving via machine learning using eye-tracking and vehicle data ↗
Introduction: Alcohol impaired driving remains a significant public safety problem, prompting the United States and the EU to move towards the inclusion of impaired driving prevention technology in future vehicle production. A large body of literature suggests acute alcohol use produces changes in ocular behavior and vehicle control, suggesting driver monitoring system (DMS) data can be used to detect alcohol-impaired driving. Method: We use DMS data from a simulated driving study to assess the role of different monitoring lengths, data inputs, and machine learning methods on the accurate iden…
- OpenAlex · Published · First archived
On-Target Embedded Benchmarking of Mamdani and Neural-Network-Tuned Fuzzy Controllers for Automotive Deceleration Command Computation ↗
Intelligent braking controllers are usually evaluated in simulation or by vehicle-level performance, but few studies isolate the embedded computational cost of deploying them on the same microcontroller. This paper presents a same-platform benchmarking framework running a baseline Mamdani fuzzy logic controller and a neural-network-tuned variant on one STM32H723ZG target, sharing a common CAN input, a 27-rule Mamdani inference path, and an on-target Cortex-M7 cycle-counter (DWT) timing method that needs no external hardware. The controllers differ only in a compact feedforward network that adj…
- OpenAlex · Published · First archived
Development of an AI-Powered Humanoid Robot for Assistive and Collaborative Applications in Education and Industrial Automation ↗
AbstractHumanoid robots that can move through a space, respond to spoken questions and represent an organisation to thepublic are an increasingly common bridge between robotics research and everyday institutional use. This paper reportsthe design, fabrication and field evaluation of an AI-powered humanoid robot developed as an interactive campusinformation assistant. The robot's body was modelled in SolidWorks and additively manufactured in two ABS sectionsthat were bonded, puttied, sanded and painted to a finished shell; mobility is provided by 12 V DC geared motorsdriven through a Cytron 10…
- OpenAlex · Published · First archived
ZD-HybridNet integrates transformer and LSTM models for explainable zero day cyber attack detection ↗
The exponential growth of interconnected systems has dramatically expanded the attack surface of modern networks, making zero-day attacks, which exploit previously unknown vulnerabilities, a critical threat to organizational security. Traditional signature-based and anomaly detection systems often struggle to identify such previously unseen attack patterns, and while deep learning (DL) offers promising detection capabilities, existing DL-based intrusion detection systems (IDS) suffer from poor generalization to novel attacks and operate as opaque black boxes, lacking interpretability for secur…
- OpenAlex · Published · First archived
Data-driven forecasting of transformer oil temperature using deep learning and ensemble models on multivariate time-series data ↗
Abstract Transformers must be maintained within their operating temperature range within their optimal temperatures. Monitoring oil temperature is one way for utilities to know the condition of the insulation and reliability of transformers. Long-term thermal stress on the insulation creates accelerated aging and increases the risk of transformer failure. Existing methods of oil temperature monitoring (i.e., thermal threshold alarm systems, physics-based models of oil temperature, simple linear regression) do not typically account for any of the nonlinear behaviours or long-associative tempora…
- OpenAlex · Published · First archived
Embedded artificial intelligence in battery management systems: Pruning and quantization for efficient state-of-charge and state-of-health estimation ↗
Online battery management requires accurate state-of-charge (SOC) and state-of-health (SOH) estimates within strict memory and timing budgets. To address these constraints, this work investigates how stateful long short-term memory (LSTM) networks with multi-layer perceptron (MLP) heads can be optimized for embedded artificial intelligence (AI), using structured pruning and recurrent-weight quantization to reduce memory and computational costs while retaining estimation accuracy on an STM32H753ZI microcontroller. Using the open Lithium Iron Phosphate (LFP) Cycle Ageing Dataset , full-precision…
- OpenAlex · Published · First archived
Next-generation machine learning optimized graphene-based solar absorber design using Zr-Cr-Fe3O4-TiC for renewable energy mining applications ↗
The widespread adoption of renewable energy can reduce carbon emissions and promote a greener environment. With a primary focus on the thermal conversion of sunlight, solar energy is an important renewable energy solution. A solar absorber is one of the important devices using solar energy and is made with a multilayered design of Zirconium – Chromium, Iron (III) oxide, and Titanium carbide across 2800 nm. With the graphene-based part in the developed design, near-perfect absorption (99%) is achieved over 600 nm (2.0–2.6 μm) and 94.43% with the wide band at 2800 nm, respectively. The resonance…
- OpenAlex · Published · First archived
Exploring the key genes of colorectal “adenoma-cancer” based on graph transformer ↗
Colorectal cancer (CRC) is one of the most lethal malignancies worldwide, and the precise identification of biomarkers from colonic adenoma to cancer is of great significance for preventing the development of adenocarcinoma. Given that existing methods inadequately capture the topological network relationships among genes, this study proposes a graph neural network model based on multifeature learning, named ChebTs, to investigate the correlation between key genes involved in the colorectal “adenoma-cancer” transition. The GSE41657 and GSE31905 datasets from the GEO database were stratified in…
- OpenAlex · Published · First archived
Copy & Return: Evidence-Preserving Damage Suppression with Lightweight AI-Based Ransomware Screening ↗
Dynamic ransomware analysis presents a dilemma: terminating a sample prevents later behavior from being observed, whereas allowing destructive functions to complete can corrupt the analysis environment and its evidence. Copy & Return addresses this problem by suppressing selected destructive effects at function boundaries while allowing the original process to continue. An ABI-compatible substitute is introduced via dynamic-library interposition or binary injection to redirect a dangerous destination, preserve a mutable buffer, or bypass a destructive transformation before returning control to…
- OpenAlex · Published · First archived
Systems oriented review on artificial intelligence as a sustainability enabler in renewable energy modeling and energy transition pathways ↗
Artificial intelligence (AI) has emerged as a critical enabler of renewable energy system development, offering new capabilities for forecasting, optimization, predictive maintenance, and real-time control. However, existing review studies remain fragmented across individual renewable-energy technologies or algorithmic domains, limiting the transferability of knowledge and the development of system-level insights. Unlike traditional, purely technical algorithm reviews that primarily evaluate computational performance in isolation, this review adopts a systems-oriented framework that examines A…
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.