Search Results
11 results for “TPU”
AI Safety
AI safety is a field of research and practice concerned with the development of artificial intelligence systems that behave reliably, avoid harmful outputs, and remain aligned with human values, especially as systems become more capable.
Attention Mechanism
A neural network technique that enables models to dynamically weight the relevance of different parts of an input sequence when producing each output element, forming the core of transformer architectures.
Constitutional AI
Constitutional AI is an alignment method developed by Anthropic that trains language models to follow a set of written ethical principles by using the model itself to critique and revise its own outputs, reducing dependence on human feedback for harmlessness.
Context Window
The maximum number of tokens — including the prompt, prior conversation, retrieved documents, and the model's own output — that a large language model can process in a single forward pass.
Encoder-Decoder Architecture
A neural network design pattern that compresses an input sequence into an internal representation using an encoder, and then generates an output sequence from that representation using a decoder, foundational to machine translation, summarisation, and many other sequence-to-sequence tasks.
Hallucination (AI)
A phenomenon in which an artificial intelligence system generates output that is factually incorrect, fabricated, or unsupported by its input, while presenting it with apparent confidence.
Hidden Markov Model
A statistical model that represents systems with unobservable (hidden) states that emit observable outputs, used widely in speech recognition, bioinformatics, and time-series analysis.
Inference (Machine Learning)
Inference is the phase in which a trained machine learning model is used to generate predictions or outputs from new input data, distinct from the earlier training phase.
Prompt Engineering
The practice of designing and optimising input instructions given to large language models to elicit accurate, relevant, and well-structured outputs for a given task or application.
Retrieval-Augmented Generation
A technique that enhances large language model outputs by retrieving relevant documents from an external knowledge base at inference time, grounding responses in up-to-date and domain-specific information.
Tensor Processing Unit
A tensor processing unit (TPU) is a custom application-specific integrated circuit developed by Google for accelerating machine learning workloads, particularly neural network training and inference.