Multimodal AI: Shaping the Future of System Implementation

This chapter delves into the evolution of AI systems, focusing on the transformative potential of multimodal approaches that integrate text, speech, images, and videos. It highlights practical applications in fields like sales training and ecommerce, demonstrating how such systems enhance user experience and operational efficiency.

Transcript

chevron_right

Play full episode

chevron_right

Transcript

Episode notes

In this episode, Jason dives deep into the future of multi-agent systems with Saurabh Tiwary, VP & GM of Cloud AI at Google. They explore how teams of AI agents—not just single models—can collaborate to solve complex problems, helping startups scale faster with fewer resources.

Saurabh introduces Google Cloud’s open frameworks:

Agent Development Kit (ADK) for building flexible, debuggable agents
Agent-to-Agent (A2A) Protocol, now part of the Linux Foundation
The emerging Multi-Agent Collaboration Protocol, enabling AI systems to work across platforms and organizations

They also discuss:

Why AI agents are evolving from task-doers to decision-makers
How multimodal inputs (text, image, video, voice) will supercharge agent capabilities
Why openness and interoperability will define the next era of AI infrastructure

Timestamps:

(0:00) Jason introduces Saurabh Tiwary, VP & GM of Cloud AI at Google, and sets the stage for a deep dive on autonomous agents.

(1:09) What is an AI Agent Today?

(2:54) When Will Agents Actually Work?l

(6:30) Inside Google’s ADK (Agent Development Kit)

(8:35l) Agent-to-Agent Protocol & Open AI Standards

(11:35 ) Why Human-in-the-Loop Still Matters

(13:41) What’s Next: Multimodal Agents & Real Startup Use Cases

Google Cloud Report: “The Future of AI: Perspectives for Startups”

Free download → https://goo.gle/futureofai

Google Cloud Homepage

https://cloud.google.com/