Green emphasizes that data is the fuel that refines the AI engine and robust data governance practices can promote sustainability. He also discusses the considerations in choosing the right LLM, including reusing an existing LLM, building a new one, or fine-tuning an existing model. Lastly, he underscores the need for employees to learn how to interact with LLMs effectively and sustainably, including training on best practices, watching out for bias, and encouraging responsible experimentation.
Key takeaways:
- Generative AI can be used to help organizations make progress toward sustainability targets, despite being resource intensive.
- Robust data governance practices and processes are crucial for deploying purpose-built Large Language Models (LLMs) and promoting sustainability best practices.
- Choosing the right LLM to address an organization's needs and expected outcomes is an important step, with considerations for both efficiency and sustainability.
- Upskilling the workforce to interact effectively and sustainably with LLMs is essential, with a focus on refining queries, monitoring for bias, and encouraging responsible experimentation.