Opaque recurrence, and other AI terms that you should probably know | TechCrunch

As artificial intelligence technologies rapidly transform various industries, they are also introducing a complex, specialized vocabulary that can be challenging for professionals and observers to follow.

This comprehensive glossary aims to demystify these modern technological concepts by providing accessible explanations of core AI phenomena. The terms covered span foundational architectural elements, such as neural networks and deep learning systems modeled after biological neural paths, to operational concepts like inference, model training, and weights, which dictate how programs process data and make predictions. It also highlights modern developments in reasoning capabilities, detailing the difference between human-like sequential thought processing and newer, highly efficient but less readable internal looping methods known as opaque recurrence.

Additionally, the guide explores the practical and structural dimensions of modern machine learning ecosystems. It clarifies essential software engineering terms like API endpoints and Model Context Protocol, which allow autonomous systems to interact seamlessly with external applications and databases. The glossary also addresses resource bottlenecks, defining terms like compute and the memory chip shortage colloquially known as RAMageddon, while breaking down optimization techniques such as distillation, fine-tuning, and parallelization that make running large models more cost-effective. By clarifying these diverse concepts, the reference tool helps developers, investors, and general audiences keep pace with a field that continues to evolve at an extraordinary rate.