Large Language Models (LLMs) and Generative Pre-trained Transformers (GPT)
- Introduction to LLMs, GPT-3, ChatGPT, and other large language models
- Typical Applications of GPT-3 and other language models
- How GPT-3 and other language models work.
- Utilizing ChatGPT on the web and through the API
Building Applications with GPT
- Overview of Prompt engineering
- Building applications such as text generation, summarization, etc.
- Few-shot learning with GPT
- Introduction to embeddings
- Overview of the OpenAI embeddings API and its usage
Risks Associated with LLMs
- Understanding main risks with LLMs, such as, hallucinations, bias, consent and security
- Methods for reducing the risks of Hallucinations, such as, retrieval augmentation, prompt engineering, and self-reflection
- Methods to detect and address hallucinations, including human feedback and model-based approaches
Individual Company ESG Ratings using Generative AI
- Introduction to how ESG ratings are calculated
- Main sources of divergence are in ESG ratings across different benchmarks provided agency
- Selecting Relevant ESG Factors: identifying key ESG factors for inclusion in the computation such as climate and DEI data
- Company data collection and preprocessing using NLP from sustainability reports & news articles, etc.
- Derive ESG ratings for listed companies based on selected factors
Establishing Benchmarks for Validating ESG ratings
- Establish the main sources of divergence in ESG ratings
- Establish ESG’s industry benchmark
- Analyzing and addressing any divergences or discrepancies in the results
- Visualizing the scores across time and sectors
- Benefits and potential of using generative AI for ESG ratings
- Importance of continuous improvement, validation, and refinement in ESG analysis using generative AI
- Guidelines for utilizing additional information sources, such as corporate filings, earnings calls, corporate announcements, and press releases, to enhance ESG computation
Deploying GPT and Other Language Models in Production
- Best practices for deploying GPT in production
- Overview of alternative generative models such as Cohere, LLaMA, Alpaca, etc.