Generative AI is always on the Built Right podcast agenda, and this episode is no exception because we decided it was time to hear the thoughts, opinions, and predictions of a PhD data scientist, and take a deep dive into the science behind it.

We invited Nikolaos Vasiloglou, Vice President of Research ML at RelationalAI, onto this episode to share his thoughts on how far generative AI will advance, give us an in-depth look at how knowledge graphs work, and explain how AI will affect the job market, the future of learning and the social media landscape.

Plus, he explores the main differences between generative AI and regular AI.

Key Moments:

The differences between generative AI and regular AI
How foundational AI models compare to larger language models
How generative AI works when our language isn’t the input
How far will generative AI go?
Why the progression of AI will change the job market
Defining knowledge graphs and how they work
The most disruptive and intriguing AI use cases
How AI is affecting reading and learning
Why generative AI is the future of social networking

Key links:

Visit the RelationalAI website: https://relational.ai/
Connect with Nikolaos on LinkedIn: https://www.linkedin.com/in/vasiloglou/

Mentioned in this episode:

Talking AI - Conversations with AI experts and early adopters

Welcome to the Talking AI podcast, where we dive deep into the world of artificial intelligence with host Matt Paige. Formerly known as the Built Right podcast, Talking AI brings you insightful conversations with AI experts, founders of AI products, and industry leaders who are leveraging AI in their businesses. Whether you're an AI expert or a beginner, our episodes will help you understand how AI technology works and how early adopters are deriving value from it. New episodes drop starting August 6th.

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How Generative AI Works, as Told by a PhD Data Scientist

Talking AI

How Generative AI Works, as Told by a PhD Data Scientist