Explainer Articles

Generative AI and Neural Net Fundamentals

There are two answers to the question of how generative AI models work. Empirically, we know how they work in detail because humans designed their various neural network implementations to do exactly what they do, iterating those designs over decades to make them better and better. AI developers know exactly how the neurons are connected; they engineered each model’s training process. Yet, in practice, no one knows exactly how generative AI models do what they do—that’s the embarrassing truth.

Machine Learning Basics for Hotel and Correlation versus Causation Modeling

There are many definitions of machine learning (ML). For purposes of this explainer, ML is the scientific study of algorithms and statistical models that computer systems automatically use in real-time to effectively perform a specific objective function (such as optimizing revenue) without using explicit instructions. Instead, ML relies on patterns and inference. All this is performed using a feedback loop so that each successive iteration further increases precision of the models, which drives and improves the objective function.

Communication in the hospitality industry

Communication in the hospitality industry is the cornerstone of delivering exceptional guest experiences and smooth operational functionality. It encompasses a wide range of interactions, from front-of-house dialogue with guests to back-of-house coordination among staff. It’s about exchanging information, but also building relationships, understanding guest needs, and ensuring an effective workflow within the hotel team.

RevPAR vs. TRevPar

If you work in the hotel business, acronyms are part of the job. Among the many shorthand terms we use, two are particularly important for measuring performance. Their names might strike a similar chord, but delving into these respective metrics reveals crucial distinctions.