Menell] have shown that AI Large Language Models (LLMs) can fail to correctly distinguish between different instruction ...
As a result, researchers are exploring ways to embed better logic into AI. The goal isn’t so much to make LLMs smarter; it’s ...
Nuance and Judgement are Needed for an AI Resilient Enterprise. While multi-modal AI can ingest vast amounts of data, it ...
The company said on Tuesday that it was holding back on releasing the new technology but was working with 40 companies to explore how it could prevent cyberattacks. By Kevin Roose Reporting from San ...
VIENNA, VIENNA, AUSTRIA, February 27, 2026 /EINPresswire.com/ — digna today announced the release of digna 2026.01, introducing significant enhancements to database ...
Here’s what you’ll learn when you read this story: Large language models (LLMs) like ChatGPT show reasoning errors across many domains. Identifying vulnerabilities is good for public safety, industry, ...
SAN FRANCISCO--(BUSINESS WIRE)--Logical Intelligence, an artificial intelligence company developing energy-based (EBM) reasoning systems, today announced that Kona 1.0, its pioneering EBM for ...
A new technical paper “Mitigating hallucinations and omissions in LLMs for invertible problems: An application to hardware logic design automation” was published by researchers at IBM Research. “We ...
The Rise of Logical Data Management by Christopher Gardner is a thoroughly researched and timely guide for understanding how organizations can rethink their data architecture at a moment when AI, ...
Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...
The trend of AI researchers developing new, small open source generative models that outperform far larger, proprietary peers continued this week with yet another staggering advancement. The goal is ...
Integrating Reinforcement Learning and Model Predictive Control for Mixed- Logical Dynamical Systems
Abstract: This work proposes an approach that integrates reinforcement learning (RL) and model predictive control (MPC) to solve finite-horizon optimal control problems in mixed-logical dynamical ...
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