DataFramed

#96 GPT-3 and our AI-Powered Future

Jul 18, 2022

01:03:46

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Episode notes

What Are the Limitations of Gpty 3?

02:44

Using Value Targeted Data Sets

04:29

Tips on Tom Design

03:48

Introduction

2min

Gety Three - Your Book on the Future of AI and Data Science

4min

What's the Origin of Gp Three?

5min

The Changes That Have Led to the Barf of Gt Three

3min

Gpty Three Scaling and the Api Model?

2min

Tips on Tom Design

4min

Scale Is a Part of Gt Three Success?

4min

Is There a Way to Scale Language Models?

3min

What Are Your Favorite Use Cases of Gp Three?

6min

10.

What Use Cases Will Be Really Transformative in the Short Term?

2min

11.

The Limitations of Chippity Three

6min

12.

What Are the Limitations of Gpty 3?

3min

13.

Using Value Targeted Data Sets

4min

14.

The Future of Anop Systems

4min

15.

Is There a Future for Chatbolts?

2min

16.

What Are You Most Excited About?

5min

17.

Is There a Risk of Misinformation and Bias?

2min

18.

Data Framed - A Podcast by Data Camp

2min

In 2020, OpenAI launched GPT-3, a large language AI model that is demonstrating the potential to radically change how we interact with software, and open up a completely new paradigm for cognitive software applications.

Today’s episode features Sandra Kublik and Shubham Saboo, authors of GPT-3: Building Innovative NLP Products Using Large Language Models. We discuss what makes GPT-3 unique, transformative use-cases it has ushered in, the technology powering GPT-3, its risks and limitations, whether scaling models is the path to “Artificial General Intelligence”, and more.

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DataFramed

#96 GPT-3 and our AI-Powered Future

What Are the Limitations of Gpty 3?

Using Value Targeted Data Sets

Tips on Tom Design

Get the Snipdpodcast app

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Save anymoment

Share& Export

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