Making Your AI Results More Predictable

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Ronnie Sheer

54:38

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01 - Introduction

01 - Embracing the unpredictable.mp4

00:48

02 - What you should know.mp4

01:03

03 - Warning Use responsibly.mp4

00:41

04 - Language model overview.mp4

06:14

05 - Hallucinations, biases, and randomness.mp4

02:36

02 - 1. Enhancing User Prompts

01 - The value and limitation of processing user prompts.mp4

01:53

02 - Leveraging system instructions.mp4

03:06

03 - Few shot learning.mp4

04:03

04 - Challenge Use system instructions.mp4

00:54

05 - Solution Use system instructions.mp4

02:30

03 - 2. Human Oversight

01 - Keeping a human in the loop.mp4

00:38

02 - Designing for human oversight.mp4

02:10

03 - The value of user feedback.mp4

01:38

04 - Conveying risks to users.mp4

01:00

04 - 3. Implementing Robust Systems

01 - Using moderation components.mp4

03:53

02 - Fine-tuning models.mp4

04:22

03 - Semantic similarity search.mp4

05:33

04 - RAG Value and drawbacks.mp4

07:26

05 - Chunking approaches for RAG.mp4

01:49

06 - Adding re-rank to RAG systems.mp4

01:12

05 - Conclusion

01 - Staying up-to-date with evolving tech.mp4

01:09

Description

Explore the fundamentals of working with AI and large language models, focusing on responsible usage, the intricacies of writing effective user prompts, and how to ensure human oversight while implementing strong, reliable systems. Instructor Ronnie Sheers shows you practical ways to recognize and mitigate biases, hallucinations, and randomness in AI outputs, as well as how to leverage system instructions for improved interaction efficiency. Get started applying few-shot learning techniques to generalize data more effectively. Find out why keeping a human in the loop enhances decision-making and accountability while also ensuring ethical system design through user feedback and risk management. Along the way, learn how to use moderation components, fine-tuning models for specific tasks, semantic similarity searches for better information retrieval, and retrieval-augmented generation (RAG) systems for enhanced system performance.

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Artificial Intelligence

Ronnie Sheer

Instructor's Courses

Experienced full stack developer focusing on scalable services using Python and Javascript. A seasoned public speaker, with a passion for teaching and mentoring in tech.

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