Together AI Introduces Mixture of Agents (MoA): An AI Framework that Leverages the Collective Strengths of Multiple LLMs to Improve State-of-the-Art Quality

Together AI has introduced an innovative AI framework called Mixture of Agents (MoA), which leverages the strengths of multiple large language models (LLMs) to enhance the quality and performance of AI. The MoA approach integrates diverse capabilities and insights from various models to create a more robust and versatile combined model, achieving a remarkable score of 65.1% on the AlpacaEval 2.0 benchmark. The concept of "collaborativeness" among LLMs has been crucial in developing MoA, which categorizes models into "proposers" and "aggregators" to generate refined responses through an iterative process. This results in comprehensive and refined outputs. The Together MoA framework has demonstrated superior performance on benchmarks, including AlpacaEval 2.0 and MT-Bench, while offering cost-effectiveness, particularly evident in the MoA-Lite configuration. This success is attributed to the collaborative efforts of several organizations in the open-source AI community, and Together AI plans to further optimize the MoA architecture and enhance its capabilities in reasoning-focused tasks. Furthermore, Together AI provides practical advice on how AI can redefine company processes, identify automation opportunities, define KPIs, select AI solutions, and implement AI gradually. Interested parties can connect with Together AI for AI KPI management advice at hello@itinai.com. Additionally, Together AI offers insights into leveraging AI for sales processes and customer engagement, providing solutions at itinai.com. For free consultations, individuals can join the AI Lab in Telegram @itinai or follow Together AI on Twitter @itinaicom.