The DeAngelis Review

This article discusses key trends driving artificial intelligence and machine learning in the coming years, including ModelOps, cloud computing, federated learning, edge computing, natural language processing, generative AI, and the pursuit of better-advanced analytics to enable more complex "System 2" thinking capabilities.

This article explains cognitive computing as an "adolescent" form of AI, operating on large datasets to handle ambiguous, complex problems between narrow AI and AGI. It discusses when to use cognitive computing and provides guidelines from the Cognitive Computing Consortium.

This article explores the philosophical debate around the simulation hypothesis - the idea that our reality is an advanced computer simulation. It discusses arguments for and against this proposition, drawing from physics, mathematics, and the fine-tuned nature of the universe's constants.

This article critically examines the term "artificial intelligence" as a misleading buzzword, advocating for the more precise "machine learning" terminology. It discusses the benefits of machine learning, provides guidance on getting started with it, highlights its business applications, and emphasizes the importance of having a clear strategy and relevant data.

This article discusses the value of cognitive technologies, which use AI techniques like machine learning to handle ambiguous situations. It highlights cognitive computing's ability to provide insights, support better decision-making, enable corporate alignment, and adapt to rapidly changing business environments through data analysis and integration.

This article discusses the concept of augmented intelligence, where AI and cognitive technologies augment and enhance human decision-making capabilities rather than replace them. It explores the benefits of this approach, such as resolving ambiguity, automating tasks, transforming employee roles, and introducing new job opportunities through human-machine collaboration.