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Register
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AI in Action: Applications of ChatGPT for Textual Feature Extraction
Large Language Models (LLMs) open new doors for extracting features from textual data. Join us for an enlightening webinar, that will gradually build an understanding of how LLMs can process textual data to harvest alpha. At this webinar, we'll delve into the core strategies for harnessing textual data effectively, featuring insights from industry leaders and real-world use cases.
Don't miss this opportunity to gain valuable insights, engage with experts, and propel your AI initiatives forward.
This webinar will cover:
An Intro to Systematic Alpha with LLMs
- Safely Integrating Data: How to safely introduce S&P data into your models
- LLM Efficiency Gains: Merging traditional NLP techniques with LLMs to enhance efficiency.
- LLM Feature Generation: Transforming textual data into numerical features.
- Prompt Engineering: Strategies for refining prompts to elicit desired outputs.
AI-Ready Data from Kensho
- Introduction to AI-ready data and its importance in LLMs
- Discussion on preparing unstructured data for LLMs, including extraction, vectorization and embeddings.
- Overview of Kensho's roadmap for advancing AI technologies and methodologies
Speakers
Daniel Sandberg
Managing Director, Head of Quantamental Research
S&P Global Market Intelligence
Liam Hynes
Head of New Product Development, Public Markets
S&P Global Market Intelligence
Tarig Khairalla
Senior Product Manager, AI/ML
Kensho Technologies
Justine Iverson (Moderator)
Head of Analytics, Capital IQ Solutions
S&P Global Market Intelligence
Register On-Demand
AI in Action: Applications of ChatGPT for Textual Feature Extraction
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