Generative AI and ChatGPT with Logan and Jon
Episode 26: Show Notes
Machine learning and AI are fast becoming integrated into our everyday lives. However, despite its rising popularity, there is still a lot of confusion and misunderstanding around the subject. In this episode, we unravel the fundamental principles of machine learning and artificial intelligence. We start by setting the context before diving into the technical and business side of AI. We explain the different terms used, why people are so interested in machine learning, and how it is going to shake up Silicon Valley. We also provide listeners with an overview of the benefits and drawbacks of AI and machine learning and discuss how using AI can go wrong. Learn about neural networks, the transformer algorithm, the cost of implementing AI, and how to effectively leverage these technologies. We examine both positive and negative use cases, debunk common misconceptions, and emphasize the continuous nature of AI implementation. Lastly, we navigate the landscape of cognitive computing, exploring the threats it presents along with the opportunities it brings. Tune in now to ensure you do not get left behind in the AI and machine learning race!
Key Points From This Episode:
Tweetables:
“Artificial intelligence is a broad field of study. It is an umbrella term under which these technologies fit into.” — Logan Gallagher [0:02:42]
“When you are interacting with a model that uses transformer, it can generate very human-readable and human-intelligible text and outputs that pass off as very convincing.” — Logan Gallagher [0:05:52]
“[Deploying new versions of AI] is a continuous process. If you are standing still, you are going to get left behind.” — Logan Gallagher [0:19:43]
“The business opportunity [of AI] is huge here. Thus, we are not only engaged in the standard hype cycle of technology, but we are looking at a Silicon Valley that is figuring out what business it is going to be in.” — Jon Gallagher [0:22:12]
Links Mentioned in Today’s Episode:
The Transformer Model Tutorial
‘Transformer: A Novel Neural Network Architecture for Language Understanding’
Generative AI and ChatGPT with Logan and Jon
Episode 26: Show Notes
Machine learning and AI are fast becoming integrated into our everyday lives. However, despite its rising popularity, there is still a lot of confusion and misunderstanding around the subject. In this episode, we unravel the fundamental principles of machine learning and artificial intelligence. We start by setting the context before diving into the technical and business side of AI. We explain the different terms used, why people are so interested in machine learning, and how it is going to shake up Silicon Valley. We also provide listeners with an overview of the benefits and drawbacks of AI and machine learning and discuss how using AI can go wrong. Learn about neural networks, the transformer algorithm, the cost of implementing AI, and how to effectively leverage these technologies. We examine both positive and negative use cases, debunk common misconceptions, and emphasize the continuous nature of AI implementation. Lastly, we navigate the landscape of cognitive computing, exploring the threats it presents along with the opportunities it brings. Tune in now to ensure you do not get left behind in the AI and machine learning race!
Key Points From This Episode:
Tweetables:
“Artificial intelligence is a broad field of study. It is an umbrella term under which these technologies fit into.” — Logan Gallagher [0:02:42]
“When you are interacting with a model that uses transformer, it can generate very human-readable and human-intelligible text and outputs that pass off as very convincing.” — Logan Gallagher [0:05:52]
“[Deploying new versions of AI] is a continuous process. If you are standing still, you are going to get left behind.” — Logan Gallagher [0:19:43]
“The business opportunity [of AI] is huge here. Thus, we are not only engaged in the standard hype cycle of technology, but we are looking at a Silicon Valley that is figuring out what business it is going to be in.” — Jon Gallagher [0:22:12]
Links Mentioned in Today’s Episode:
The Transformer Model Tutorial
‘Transformer: A Novel Neural Network Architecture for Language Understanding’