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Unraveling
prompt engineering

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Oct 17th | 2:00 PM EST

On the face of things, prompting seems intuitive and straightforward. With that said, you'd be hard-pressed to find a developer who'll say that it's easy. This webinar will focus on unraveling the "art" of prompt engineering into best practices and methodologies.

Key topics

  • LLM compatibility: considerations in use case, task, model, infrastructure, and prompting selection and matching.
  • The much-overlooked basics of prompting: understanding model tendencies and biases, chaining, mega prompts, and multi-calls, and adhering to prompt formats.
  • Breakthroughs in prompting techniques: such as Chain-of-Though, Tree-of-Thoughts, Thought frameworks (React), and Chain-of-Density.
  • Bug-driven development for LLMs + some hands-on examples of prompt engineering best practices

Come with questions! But be advised that this is not an intro session to prompt engineering - we won't be covering basic prompt patterns and concepts such as zero-shot or temperature.

 

Advised pre-reading

Prompt Engineering Guide
Eight Prompt Engineering Templates

Design Patterns In Prompt Engineering

 
 

Our speakers 

  • Gad Benran, founder and CTO at TensorOps
  • Gabriel Goncalves, Machine Learning Engineer at TensorOps
  • David Kramer, Lead Innovation Engineer at Blattner Technologies & Superwise
     

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