Weighing up arguments, drawing logical conclusions and deriving a clearly correct answer—such tasks have so far presented ...
Independent Researcher, Dayton, Ohio, USA. The first two papers in this series laid the groundwork for a time-symmetric cosmology rooted in the interplay between causal and anti-causal structures. In ...
SurrealDB Inc. today revealed that it has raised an additional $23 million in funding for its multimodel artificial intelligence-native database. The plan is to accelerate product maturity and ...
A major difference between LLMs and LTMs is the type of data they’re able to synthesize and use. LLMs use unstructured data—think text, social media posts, emails, etc. LTMs, on the other hand, can ...
Google rolled out a brand new experimental AI tool last Thursday called Project Genie. By Friday, video game stocks were tumbling as a result. Gaming industry giants like Unity Software, Roblox, ...
Logical Intelligence, an artificial intelligence company developing energy-based (EBM) reasoning systems, today announced that Kona 1.0, its pioneering EBM for reasoning, will enter pilot programs ...
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 ...
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, ...
ABSTRACT: The advancement of New Liberal Arts continues to drive the integration of Artificial Intelligence (AI) technology across all dimensions of Human Resource Management (HRM). This paper ...
Senate Democrats are seeking to revive a database that had tracked billion-dollar climate and weather disasters for decades until the Trump administration retired it in May. Subscribe to read this ...
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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