Software × intelligence
APIs, retrieval and agents turn model capabilities into useful applications.
Languages, frameworks and infrastructure for software and AI applications.
Backend services, retrieval, data systems and interactive interfaces.
A conceptual model of an AI application: inference, retrieval and tool interfaces.
Languages, application frameworks, model tooling and infrastructure.
Language models, retrieval, tool interfaces, model development and computer vision.
Language generation and inference within application workflows.
Retrieval of source material to inform model responses.
Model Context Protocol for structured tool and data access.
Tensor computation and deep learning.
Model development, training and deployment.
High-level APIs for neural network development.
Classical machine learning: classification, regression, clustering, evaluation.
Numerical arrays and vectorised computation.
Cleaning, shaping, and analysing tabular data.
Image and video processing for computer vision workflows.
Software and AI are my engineering focus. Physics, robotics and aerospace inform the systems I study.
APIs, retrieval and agents turn model capabilities into useful applications.
Computer vision, feedback and automation connect computation with physical systems.
Mathematics, quantum mechanics and aerospace guide my interests in modelling and physical systems.
Six exercises in patterns, memory, logic and spatial reasoning.
Identify patterns, recall positions and reason through technical scenarios.
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