Multimodal Agents

Based on CES and other recent announcements, I asked Claude and Perplexity to generate a simple summary of the latest in Multimodal Agents…take a peek here (Claude) and here (Perplexity).

While Claude was up front that its knowledge cutoff is April, 2024, it authored a blog to briefly cover the following and deemed Gemini the winner based on enterprise readiness:

1. Detailed architectural diagrams using Mermaid

2. Code examples for each platform

3. Comparative analysis with metrics

4. Implementation strategies

5. Best practices and recommendations

Perplexity deemed CrewAI the winner based on openness, quantifying the requested criteria (market opportunities, platform openness, price/performance, and ecosystem strength).

Below captures a brief summary of the combined scores and more updated links that drove this comparative analysis:

• Google Gemini - Project Astra and AgentSpace

  • Claude: Google's Project Astra and AgentSpace extend Gemini with advanced agent orchestration capabilities, focusing on distributed coordination and persistent memory management, scoring 8.5/10 for enterprise readiness.

  • Perplexity: Google Gemini excels in integration with the Google ecosystem and offers strong price/performance for high-volume applications. (32/40)

• NVIDIA Cosmos and Omniverse++

  • Claude: NVIDIA's Omniverse++ enhances the Cosmos platform with physics-aware agent simulation and real-time collaboration features, achieving 8.0/10 for technical sophistication.

  • Perplexity: NVIDIA Cosmos/Omniverse leads in physical AI development, particularly for robotics and autonomous vehicles. (30/40)

• CrewAI Multi AI Agents

  • Claude: CrewAI's Multi AI Agents platform offers the most open and flexible architecture for heterogeneous model integration, scoring 7.5/10 overall. While Gemini excels in enterprise scalability and Omniverse++ in simulation accuracy, CrewAI offers superior flexibility. Selection should prioritize specific use cases: enterprise integration (Gemini), physics simulation (Omniverse++), or architectural adaptability (CrewAI).

  • Perplexity: CrewAI provides a flexible, open-source framework for creating complex, multi-agent AI systems. (33/40)

One of the most insightful experts on AI Engineering is Chip Huyen, who writes about Agents (specifically Agent-driven Tools and Planning) in this post. She points out that “an agent is characterized by the environment it operates in and the set of actions it can perform”. This upfront definition highlights how critical it is to define clear incentives, objectives and outcomes that can be optimized and aligned across the planning, perception and control stages.

XQuest is specifically taking on an AI-driven biopic and storytelling platform, where AI agents could help augment and optimize the full lifecycle. Listen to how we are modernizing storytelling and expanding media market opportunities here.

Cloudpeers has been focused on domain-specific B2B2C AI/ML-driven interactions, including healthcare, hospitality and AEC workflows. As businesses re-platform leveraging Cloud/AI, the business, operational, cultural and technical challenges will present enormous challenges and opportunities.