📣 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...
Andrew Stewart Caldin· Zenodo (CERN European Organi...· 0 citations
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...
Karthik Ramakrishna Suresh· Zenodo (CERN European Organi...· 0 citations
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...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
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...
Deepti Bansal, Bhavna Sharma· Zenodo (CERN European Organi...· 0 citations
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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...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
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...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
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...
Aondonenge Dickson Teran· Zenodo (CERN European Organi...· 0 citations
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...
Palvi Sharma· Journal of Intelligent Compu...· 0 citations
"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...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
This paper proposes a novel approach to explainable artificial intelligence (XAI) that leverages causal modeling to enhance the transparency and trustworthiness of AI systems. Current XAI techniques often prioritize interpretability without considering the underlying causal relationships governing the data. We introduc...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduNov 2, 2026
The MIT professors collaborated to identify the first AI-discovered antibiotic, a scientific breakthrough that is widely recognized as a milestone in AI-driven drug discovery.
MIT News · Artificial Intelligence· news.mit.eduOct 30, 2026
MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.
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