Generative AI (or GenAI) refers to AI systems that can create new content like text, images, music, code, or video. These systems learn patterns from training data and generate novel outputs that resemble the original data, often powered by architectures like GANs, transformers, diffusion models, and variational autoencoders. These models power applications including chatbots, code generation, and creative tools. They also raise questions about the potential for misuse including creating misinformation and deepfakes.
Source: https://hai.stanford.edu/ai-definitions/what-is-generative-ai
Prompt Engineering is the discipline of providing inputs, in the form of text or images, to generative AI models to specify and confine the set of responses the model can produce. The inputs prompt a set that produces a desired outcome without updating the actual weights of the model (as done with fine-tuning). Prompt engineering is also referred to as "in-context learning," where examples are provided to further guide the model.
Source: https://www.gartner.com
Prompting Techniques
A Practical Guide to Building Agents (OpenAI)
Building Trusted AI in the Enterprise (Anthropic)
Claude Code: Best Practices for Agentic Coding (Anthropic)
Identifying and Scaling AI Use Cases (OpenAI)
Tracking AI - Monitoring Artificial Intelligence (A Maximum Truth Project)
Mahidol University provides free access to Google Gemini for Education for faculty members, staff, and students.
Mahidol University provides free access to Microsoft Copilot 365 for Education for faculty members, staff, and students.
These advanced AI systems are developed to support learning, research, and organizational management with the highest efficiency.
A Central procurement initiative to provide enterprise AI licenses (ChatGPT) to the Mahidol community at a lower cost than individual retail subscriptions.
Scopus AI
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