‘Together AI’ to Promote Multimodal AI Models to Achieve Superior Results, and Examining into “Mixture of Agents” Technique.

, which refers to utilizing the power of artificial intelligence (AI), particularly by employing multiple AI models together to enhance performance and integrating various AI Agents to achieve better outcomes than using a single model. Ben Athiwaratkun, Senior ML Scientist at Together.AI, shared insights on this topic with Dr. Tanwa Arpornthip, Senior Technical Advisor at SCB 10X.

The Journey to AI Development and Utilizing Mixture of Agents

• Ben began by introducing himself and describing his journey of studying and working in the AI field, eventually joining Together AI. 
  
  
• Ben has a passion for physics and studied in the United States, which ultimately led to a career in AI research and the development of deep learning models. He later met the Together AI team and joined the company, seeing it as a great opportunity in the AI industry and recognizing Together AI as a company with outstanding AI products.

Mixture of Agents and its Distinction from Mixture of Experts

Regarding AI development, Ben explained "Mixture of Agents," a technique that stands out in enabling collaboration among multiple models. He compared it to “Mixture of Experts,” a technique that combines the expertise of multiple models to process data and generate features for accurate results. However, in Mixture of Agents, the models interact using natural language, making the process more understandable and interpretable.

The Working Process of Mixture of Agents

In the Mixture of Agents process, each model acts as a “Proposer,” suggesting ideas or results. Other models function as “Aggregators,” synthesizing and refining the outputs from the Proposers. This process repeats multiple rounds until a high-quality result is achieved. The goal is to produce an output superior to that of a single model. This approach resembles human collaboration, where meetings and discussions lead to the best conclusion.

Advantages and Disadvantages of Mixture of Agents

A key advantage of Mixture of Agents is its ability to combine open-source models from various sources to achieve better results than closed models developed by a single organization. This enhances flexibility in AI usage within organizations and generates high-quality outcomes. Mixture of Agents can also help reduce bias and produce more balanced results.

However, using Mixture of Agents can be slower and more expensive than using a single model, especially in real-time processing. It can also be complex to set up and manage, though ongoing development aims to improve efficiency in this area.

Combining Techniques to Enhance Mixture of Agents' Performance

Together AI has developed various techniques to boost the performance and processing speed of Mixture of Agents. One such technique is “Flash Attention,” which reduces processing time at the hardware level. Improvements have been made at multiple levels, from hardware utilization to model design and user experience. These technological advancements will enable Mixture of Agents to be used in tasks requiring high speed and efficiency.

Challenges and the Future of Together AI

Together AI is committed to developing and maintaining its leadership in AI by enhancing system and algorithm performance. This includes increasing the capability to handle larger datasets and developing new techniques to improve flexibility and efficiency in AI processing.

This section highlights remarkable technological progress in AI and the application of Mixture of Agents, which will transform how AI is developed and used in the future.

Watch this session on Youtube: https://youtu.be/ZLuA3XTVKHc?si=gIj_cKxFSE9oHpqr