AI Glossary: Letter "T"

The Technological Singularity is a hypothetical future point in time when technological growth becomes uncontrollable and irreversible, driven by self-improving artificial intelligence systems surpassing human intelligence, resulting in unfathomable changes to human civilization.

Temperature is a parameter that controls the randomness and creativity of text generated by an autoregressive language model during inference. Higher values increase randomness, while lower values make outputs more deterministic.

A Tensor is a multi-dimensional mathematical array of numbers that serves as the fundamental data structure for representing inputs, weights, and activations in deep learning frameworks like TensorFlow and PyTorch.

Test-Time Compute refers to allocating additional computational resources during inference (test time) rather than training. By letting a model think longer, generate multiple paths, self-correct, or run search trees, it can solve significantly harder problems.

A Token is the fundamental unit of text sequence analyzed or generated by a natural language model (roughly equal to 3/4 of a word). Words are encoded into token IDs before passing into neural layers.

Tokenization is the process of breaking down a text string into smaller pieces called tokens (which can be characters, subwords, or full words). Tokenization converts text into numbers that a neural network can process.

A Tokenizer is a pre-processing component that breaks down raw text strings into discrete units called tokens (words, subwords, or characters) and maps them to numerical integer IDs that can be processed by a neural network.

Tool Ingestion is the capability of an AI Agent to dynamically read, understand, and register external APIs, scripts, or documentation for use. This allows agents to expand their toolsets autonomously during execution.

A Tensor Processing Unit (TPU) is an application-specific integrated circuit (ASIC) custom-developed by Google specifically to accelerate machine learning workloads, specialized in high-performance matrix math operations.

Training Data is the initial dataset used to train a machine learning model, allowing it to learn features, weights, and mathematical relationships by processing inputs and computing adjustments.

Transfer Learning is a machine learning technique where a model developed for one task is reused as the starting point for a model on a second, related task, significantly reducing the amount of labeled data and compute needed.

A Transformer is a deep learning neural network architecture introduced in 2017 by Google researchers, based entirely on self-attention mechanisms. It processes sequential inputs in parallel, capturing long-range dependencies and serving as the foundational engine for all modern LLMs.

Tree of Thoughts (ToT) is a prompt-based reasoning framework that generalizes Chain of Thought by allowing models to explore multiple decision branches (thoughts) over time. It incorporates self-evaluation and backtracking algorithms like search to solve problems.

The Turing Test, originally proposed by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human through text conversation.