Advancements in generative AI

Understanding ChatGPT

James Chapman

Curriculum Manager, DataCamp

Coming up...

 

  • What's to come in generative AI?
  • What challenges need to be overcome?
Understanding ChatGPT

Performance improvements

 

  • More human-like content
  • Handle more complexity
  • Greater reliability

 

A graph of steadily increasing performance.

Understanding ChatGPT

What's driving the improvements?

 

Large Language Models (LLMs)

  • Learns from a huge text dataset
  • Algorithms detect patterns in text
  • Fine-tune the model by rating responses

The three key components of a large language model: the training data, the algorithms to detect pattern in the training data, and a fine-tuning process.

Understanding ChatGPT

What's driving the improvements?

 

 

  • Amount of training data will increase

 

A larger brick wall representing more training data.

Understanding ChatGPT

What's driving the improvements?

 

 

  • Amount of training data will increase
  • Usage data will help in fine-tuning

Usage data feeding into the fine-tuning of the model.

Understanding ChatGPT

Building balanced datasets

 

Challenge: Ensuring data is high quality and balanced

  • Quantity of data makes detecting bias prior to training difficult

 

Goal: Develop more robust bias mitigation procedures

An icon demonstrating how a model can learn biases from the data it has seen.

Understanding ChatGPT

Opportunities for misuse

 

  • Misrepresenting AI-generated content
  • Creating malicious content (e.g., spam)

 

Intervention by lawmakers:

  • Regulations could help or hinder AI advancement

 

A statue of the scales of justice.

Understanding ChatGPT

From generalized to specialized

 

  • ChatGPT is a generalizable model
  • Generative AI models will become more specialized
  • Example: a model specifically designed to write long and complex code

An example of using ChatGPT to generate code to scrape a table from a website.

Understanding ChatGPT

Other types of generative AI

 

image-generation.png

The three key components of a large language model: the training data, the algorithms to detect pattern in the training data, and a fine-tuning process.

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Understanding ChatGPT

AI for everyone!

 

  • Accessibility is key to ChatGPT's success
  • Democratization of AI tools
    • Everyone should benefit from the technology

A selection of people from different cultures that could all benefit from AI tools.

Understanding ChatGPT

Let's practice!

Understanding ChatGPT

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