to nine months in advance, organisations can ensure they have the necessary environment for scalable inference.
Alongside cost optimisation and model routing, another critical evolution driving enterprise efficiency is the transition toward autonomous systems.
The shift to agentic AI systems Beyond physical and gen AI, the industry is seeing a transition towards agentic systems. Unlike traditional gen AI, which generally responds to prompts, agentic systems are designed to perform tasks, make decisions and interact with other systems autonomously.
The development of new protocols is enabling these agents to communicate with each other, creating complex workflows. This is akin to how the TCP / IP protocol – the fundamental communication language of the internet – allowed disparate computer systems to exchange data and facilitate global commerce.
“ Agentic systems are going to be like that,” Vijay says.“ They are allowing systems to talk to each other. That was not the capability earlier with gen AI systems. You can build one agentic system and then your agent can talk to another agent, can create workflows and can get work done.
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