Information retrieval systems rely on specialised data structures and algorithms to index, query and retrieve relevant information from large collections of text or other data types. Traditional ...

AI R&D runs on a cycle of hypothesis, experiment, and analysis — each step demanding substantial manual engineering effort. A new framework from researchers at SII-GAIR aims to close that bottleneck ...

The design, implementation, and analysis of abstract data types, data structures and their algorithms. Topics include: data and procedural abstraction, amortized data structures, trees and search ...

For many people, the phrase generative AI brings to mind large language models such as OpenAI's ChatGPT. Although LLMs are an important part of the generative AI landscape, they're only one piece of ...

In today's fast-paced business world, data is the lifeblood of organizations. However, many companies struggle with a significant challenge: a "data divide" between technology experts and business ...

Like it or not, artificial intelligence has become part of daily life. Many devices – including electric razors and toothbrushes – have become “AI-powered,” using machine learning algorithms to track ...