In this in-depth chat between Allen Firstenberg and Linda Lawton, they dive into the functionalities and potential of Google's newly released Gemini model. From their initial experiences to exciting possibilities for the future, they discuss the Gemini Pro and Gemini Pro Vision models, how to #BuildWithGemini, its focus on both text and images, and speedier and more cohesive responses compared to older models. They also delve into its potential for multi-modal support, unique reasoning capabilities, and the challenges they've encountered. The conversation draws interesting insights and sparks exciting ideas on how Gemini could evolve in the future.

00:04 Introduction and Welcome

00:23 Discussing the New Gemini Model

01:33 Comparing Gemini and Bison Models

02:07 Exploring Gemini's Vision Model

03:03 Gemini's Response Quality and Speed

03:53 Gemini's Token Length and Context Window

05:05 Gemini's Pricing and Google AI Studio

05:33 Upcoming Projects and Previews

06:16 Gemini's Role in Code Generation

07:54 Gemini's Model Variants and Limitations

12:01 Creating a Python Desktop App with Gemini

14:07 Gemini's Potential for Assisting the Visually Impaired

18:35 Gemini's Ability to Reason and Count

20:15 Gemini's Multi-Step Reasoning

20:33 Testing Gemini with Multiple Images

21:52 Exploring Image Recognition Capabilities

22:13 Discussing the Limitations of 3D Object Recognition

23:53 Testing Image Recognition with Personal Photos

24:52 Potential Applications of Image Recognition

25:45 Exploring the Multimodal Capabilities of the AI

26:41 Discussing the Challenges of Using the AI in Europe

27:26 Exploring the AQA Model and Its Potential

33:37 Discussing the Future of AI and Image Recognition

37:12 Wishlist for Future AI Capabilities

40:11 Wrapping Up and Looking Forward