Glossary

IBM Watson is an innovative, question-answering computer system that interprets and responds to natural language inquiries, formulated under IBM’s DeepQA project.

Vectorization is the conversion of input data into numerical arrays known as vectors. This process is crucial for machine learning algorithms to effectively operate on numerical data instead of raw data such as text or images.

An ingenious conceptual device, a Turing Machine is an abstract model of computation and data manipulation pioneered by Alan Turing. It’s capable of simulating intricate computer algorithms and is a crucial foundation of theoretical computer science.

TruthfulQA offers a platform for ensuring language models relay accurate and truthful information when responding to queries, making it a crucial element in AI honesty evaluation.

Unsupervised Learning is a ML strategy where untagged, unlabeled data trains models, enabling them to act independently, uncovering concealed structures in raw datasets.

Gain a deep understanding of Systems and Computer Science with the concept of a Transition System. Comprises states and transitions, it depicts the probable behavior of discrete systems. Leveraging labeled transitions, it operates under a set of rules, yielding varied outcomes. Explore the dynamic Transition System here.