Category
2,388 papers
This paper proposes a novel approach to artificial intelligence by integrating hyperdimensional computing (HDC) with neural symbolic computation. The core idea is to leverage the strengths of both paradigms: HDC's efficiency in high-dimensional pattern recognition and neural networks' ability to generate and manipulate...
📣 PROMO READY #270 [IndieHackers] — E8 Intelligence live AI trading ecosystem We spent months explaining E8 Intelligence as a concept. Then we stopped explaining and just let the board run. E8 Intelligence is a live AI trading ecosystem — not a backtest, not a newsletter, not a signal service. It's a 24/7 engine apply...
Explainable AI is the dominant response to automated decision-making, on the assumption that a system able to show how it produced an output has met the conditions for accountability. That assumption fails in a specific way. Selbst and Barocas established in 2018 that explaining a model does not show its decisions to b...
The increasing deployment of machine learning (ML) models in critical applications raises significant concerns regarding transparency and trustworthiness. Many ML models, particularly deep neural networks, operate as "black boxes," making it difficult to understand their internal decision-making processes. This paper p...
Reach audiences
Advertise in front of researchers, engineers, and readers.
Comparative studies of explainable AI in high-stakes tabular domains keep reaching the same conclusion: use a hybrid explanation approach that employs several explanation methods as needed. They stop, however, at that recommendation. They do not specify how to integrate the methods, which method to trust on a given mod...
This paper proposes a novel approach to artificial intelligence combining the strengths of neural networks and symbolic reasoning through dynamic rule extraction. The core idea is to leverage neural networks for pattern recognition and expression generation, followed by a dynamic rule extraction module that iteratively...
Automated theorem proving (ATP) systems have achieved remarkable success in verifying complex mathematical theorems. However, their opacity – the lack of human-understandable explanations for their reasoning – remains a significant barrier to widespread adoption. This research proposes a novel approach to enhance the e...
Artificial intelligence (AI) has become a key enabling technology for business organisations, increasingly embedded in production systems and decision-making workflows. AI models and tools in these settings must satisfy diverse requirements, such as accuracy, traceability, explainability, fairness, and trust, while mee...
This study explores the integration of Artificial Intelligence (AI) in teaching and learning Smart Agricultural Economics, examining its impact on student engagement, learning outcomes, and educational efficiency. A mixed-methods approach was employed to collect data for the study, combining surveys, interviews, and co...
Multi-crop plant disease automatic classification in precision agriculture requires an effective solution but the state-of-the-art deep learning architectures are prone to suffering background shortcut problem, higher inference latency, and inadequate visualization interpretability. This paper presents a better perform...
"This dataset was developed as part of a cybersecurity research initiative focused on detecting phishing attacks through visual analysis of webpage screenshots. It contains approximately 2,759 unique labeled screenshot images with 4,935 detailed visual, structural, and content-based features. The dataset includes 1,316...
This paper presents a novel approach to neuro-symbolic reasoning by representing symbolic knowledge as continuous tensor networks. Traditional neuro-symbolic systems often struggle with the disjointed nature of neural network pattern recognition and symbolic logic inference. Our method overcomes this challenge by allow...
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
Professor Deb Roy contends there should be someone who is “answerable” for every piece of text in public life, no matter its origins.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
GPT-Lab
· gpt-lab.eu
Oct 12, 2026
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.
MIT Statistics and Data Science Center Director Alexander (Sasha) Rakhlin shares important considerations for departments and institutions.
MIT Statistics and Data Science Center Director Alexander (Sasha) Rakhlin shares important considerations for departments and institutions.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
