The development of increasingly powerful AI models will grab headlines, but the big challenge is getting communication to intelligent agents.
There are all these capable systems now, but they all speak different languages. It is Babel’s digital tower, limiting the true potential of what AI can achieve.
To move forward, you need a common tongue. Universal translators that allow these different systems to connect and collaborate. Several candidates have stepped up to the plate, each with their own ideas on how to solve this communication puzzle.
Anthropic’s Model Context Protocol (MCP) is one of the big names in the ring. You try to create a secure, organized way for AI models to use external tools and data. MCPs are relatively simple and have gained popularity as they are supported by major AI players. However, rather than AI teams working together, a single AI is designed to use different tools.
It also contains other protocols such as the Agent Communication Protocol (ACP) and the Agent-to-Agent Protocol (A2A).
IBM’s open source project, ACP, is about enabling AI agents to communicate as peers. It is built on familiar web technologies that developers are already comfortable with, making it easier to adopt. It is a flexible and powerful solution that allows for a more decentralized and collaborative approach to AI.
Meanwhile, Google’s A2A protocol takes slightly different tacks. It is designed to work with the MCP rather than replacing it. A2A focuses on how AIS teams can collaborate on complex tasks and move back and forth between information and responsibility. Using a system of “agent cards” like digital business cards, helps AIS find and understand each other.
The real difference between these protocols is their vision for the future of how AI agents communicate. MCP is for a world where there is a single powerful AI in the center to get things done using a variety of tools. The ACP and A2A are designed for distributed intelligence, and professional AIS teams work together to solve problems.
The universal language of AI will open the door to a whole new world of possibilities. Imagine the AIS team collaborates to design new products, one agent handles market research, the other design, and one third of the manufacturing process. Or a network of medical AIs that work together to analyze patient data and develop personalized treatment plans.
But we’re not there yet. The “Protocol War” is full-scale and there is a real risk that it could lead to even more fragmentation than it is now.
The future of how AI communicates may not be a one-size-fits-all solution. Various protocols may be displayed, each one being used for the best one. One thing is for sure: figuring out how to get AIS to talk to each other is one of the next big challenges in this field.
(Photo by Theodore Poncet)
reference: Humanity deploys AI agents to audit models for safety
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