OPENAI_API_KEY

gpt.tar.gz

Python

Golang

Java

Sandbox

Python_textGen

In this course, you’ll start a transformative learning journey exploring the applications of GPT-3 in AI and gaining hands-on experience with this powerful language model.

You’ll start the course by understanding the basics of GPT-3 and its applications across domains and then learn to use the OpenAI API with Python, Go, and Java. Next, you’ll dive into prompting techniques with GPT-3, exploring essential topics to understand how to use GPT-3 for next-gen startups with real-world use cases and applications. You’ll explore its role in prominent companies like GitHub, Algolia, and Microsoft’s Azure. Lastly, you will navigate the ethical considerations of GPT-3, addressing issues like AI bias, anti-bias countermeasures, and the environmental impact of LLMs.

After completing this course, you’ll gain a deep understanding of GPT-3. Whether you are an aspiring developer, entrepreneur, or professional transitioning to AI-focused roles, this course equips you with the skills to advance your career.

Unleashing the Power of AI with OpenAI’s GPT-3

Lack of human involvement in the training process.


Careful fine-tuning to remove societal biases.

The nature of GPT-3's training data being all content available on the internet.

Exclusively relying on user-generated content for training.


What contributes to the encoding of biases in GPT-3?


What contributes to the encoding of biases in GPT-3?

Reduced toxicity and adherence to predetermined values

What is one example of the PALMS process being effective in improving GPT-3's behavior?


What is one example of the PALMS process being effective in improving GPT-3’s behavior?

A lack of human-like interaction in machine-generated content.


An amplification of encoded human biases, stereotypes, and negative sentiments.

Encoding positive sentiments towards all social groups.

Reduced capabilities in automated content generation.

What is a potential risk associated with language models like GPT-3?



What is a potential risk associated with language models like GPT-3?

What experiment did a computer science student conduct to showcase GPT-3's ability to mislead people?


What experiment did a computer science student conduct to showcase GPT-3’s ability to mislead people?

Seeding involves creating new narratives while wedging targets specific groups.

Seeding focuses on rewriting existing narratives while wedging generates entirely new content.

Seeding aims to change the views of targets while wedging prompts certain actions.



Seeding is about narrative persuasion while wedging is about narrative elaboration.

How does narrative seeding differ from narrative wedging in the context of language model-generated content?


How does narrative seeding differ from narrative wedging in the context of language model-generated content?

It failed to generate persuasive messages.

Users were not influenced by GPT-3's messages.

GPT-3 effectively promoted falsehoods, particularly in one-to-many misinformation.


GPT-3's impact on narrative persuasion was insignificant.


What is revealed about GPT-3’s narrative persuasion capabilities?


What is revealed about GPT-3’s narrative persuasion capabilities?

By selecting the right neural network, datacenter, and processor.


By increasing the size of the neural network.

How can the carbon footprint of LLMs be reduced, according to Patterson et al.?

How can the carbon footprint of LLMs be reduced, according to Patterson et al.?

Spend time creating solid content filters.

Fine-tune the model without any curated dataset.

Leave filtering and release for immediate use.

What is the initial recommendation for using GPT-3 in a specific task?


What is the initial recommendation for using GPT-3 in a specific task?

Test your comprehension of the concepts discussed in this chapter. 

Course Introduction

The Large Language Model Revolution

Getting Started with OpenAI API

GPT-3 and Programming

GPT-3 Enabler for Next-Gen Startups

GPT-3 as the Next Step in Corporate Innovation

GPT-3—The Good, the Bad, and the Ugly

Conclusion—Democratizing Access to AI

GPT-3: Prompt Engineering and Uses

Quiz: GPT-3—The Good, the Bad, and the Ugly