
AI marketing involves the application of artificial intelligence technologies to enhance and automate marketing strategies, enabling data-driven decision-making and personalized customer experiences.
Artificial intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of human beings or animals. It is a field of computer science that develops and studies intelligent machines, with a primary goal of creating technology that allows computers and machines to function in an intelligent manner. Major AI sub-fields include machine learning, deep learning, natural language processing, and computer vision.

Artificial Intelligence Ethics examines the moral principles guiding the development and deployment of AI systems, addressing issues such as bias, privacy, transparency, and accountability to ensure these technologies benefit society while minimizing harm.

An artificial neural network (ANN) is a computational model composed of interconnected nodes (“neurons”) that learn patterns from data by adjusting connection weights. Originating in mid‑20th‑century attempts to formalize cognition, ANNs underpin modern machine learning and deep learning methods used in vision, language, speech, and decision-making.

Bushnote is a strategic and creative consultancy specializing in marketing, technology, and policy. The firm develops campaigns, narratives, and systems designed to influence opinions, guide decisions, and impact markets.

Deep learning is a subfield of artificial intelligence and machine learning that uses multilayer artificial neural networks to learn hierarchical representations from data. It underpins major advances in computer vision, speech recognition, natural language processing, and decision-making systems since the early 2010s.

The ethics of artificial intelligence examines moral, legal, and societal questions arising from the design, deployment, and governance of AI systems, including issues of fairness, accountability, privacy, transparency, safety, and human oversight. Major international frameworks and regulations—such as the OECD AI Principles, UNESCO’s 2021 Recommendation, the EU AI Act, and national guidance in the United States and elsewhere—aim to translate values into requirements and practices across the AI lifecycle.
Microsoft Corporation is an American multinational technology company founded in 1975, renowned for its software products, including the Windows operating system and Microsoft Office suite, as well as its ventures into cloud computing, gaming, and artificial intelligence.

Midjourney is a generative artificial intelligence program developed by Midjourney, Inc., a San Francisco-based independent research lab. It generates images from natural language descriptions, known as prompts, similar to OpenAI's DALL-E and Stability AI's Stable Diffusion.

Neural networks are computational models inspired by the human brain, designed to recognize patterns and solve complex problems across various domains, including image and speech recognition, natural language processing, and autonomous systems.

Parallel AI refers to the application of parallel and distributed computing techniques to artificial intelligence workloads, especially the training and serving of large machine-learning models. The approach encompasses data, model, pipeline, and expert parallelism, along with optimizer and memory sharding, to scale computation across multi-GPU, multi-node, and heterogeneous systems.

Recraft AI is a generative artificial intelligence platform developed by Recraft, Inc., specializing in creating and editing digital images through natural language prompts. Founded in 2022 by machine learning scientist Anna Veronika Dorogush, the platform is tailored for professional design workflows, emphasizing brand consistency, text fidelity, and layout control.

Robotics is an interdisciplinary field focused on the design, construction, operation, and application of robots—machines capable of performing tasks traditionally carried out by humans. It integrates principles from mechanical engineering, electrical engineering, computer science, and other disciplines to develop systems that can operate autonomously or semi-autonomously in various environments.
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The Turing test is a behavioral criterion for evaluating whether a machine can exhibit human-like conversational performance. Proposed in 1950 by British mathematician Alan Turing as the "imitation game," it assesses whether a human judge can distinguish a computer from a person through text-based dialogue. The test has shaped debates in artificial intelligence and philosophy of mind, inspiring critiques, competitions, and alternative benchmarks.