We're thrilled to announce a major milestone in AI agent research: Agent Q. Our team has developed a groundbreaking approach to autonomous web navigation, pushing the boundaries of what's possible in AI-web interactions.

Key Highlights of Agent Q 🌟

• 440% Improvement: We enhanced LLaMa-3's zero-shot performance in real-world booking experiments in just one day!

• Novel Approach: Combining guided Monte Carlo Tree Search, AI self-critique, and reinforcement learning.

• Enhanced Generalization: Improved capabilities in multi-step reasoning tasks.

• Innovative Fine-Tuning: Utilized the Direct Preference Optimization (DPO) algorithm for iterative improvements.

Dive Deeper into Agent Q

Want to explore the technical details? Check out our blog post for an in-depth look at Agent Q and its implications for the future of AI agents.

Join the Conversation

We're excited to hear your thoughts on Agent Q! Join us on Discord to discuss the research with our team and community.

What's Next for MultiOn?

Agent Q is just the beginning. We're continuously working on pushing the boundaries of AI agent capabilities. Stay tuned for more updates and breakthroughs!

Stay Connected

• Follow us on X and LinkedIn for real-time updates.

• Subscribe to our YouTube channel for demos and explainers.

• Find Resources: Check out our guides and documentation for helpful information that can support your projects.

Thank you for being part of our journey towards more intelligent and reliable AI agents. Your support and feedback drive our innovation!

Cheers, 

The MultiOn Team