Since the release of ChatGPT 3.5 just four years ago this month, we have experienced a steady to ever-increasing rate of improvement in generative artificial intelligence. Most notably, however, we have experienced some milestones in the past year or two, such as the advent of agentic AI in which semi- to fully autonomous agents endowed with AI capabilities can make changes with relatively little direction from humans.
While the early conceptual roots of agentic AI date back to the 1940s, it wasn’t until late 2024 that “Anthropic introduced the Model Context Protocol (MCP), an open-source framework intended to standardize the way agents integrate and share data with external tools, systems and data sources. The following year, IBM introduced the Agent Communication Protocol (ACP), which aimed to standardize the way agents communicate with one another. ACP later merged with Google’s Agent2Agent (A2A) protocol under the Linux Foundation.”
Change is now happening very rapidly as the capabilities of agentic artificial intelligence accelerate into a near-vertical graph of capabilities day by day, month by month and year by year. We are seeing the beginnings of recursive self-improvement, which Anthropic defines as “a process where an artificial intelligence system iteratively analyzes, redesigns and builds a more capable version of itself, creating a feedback loop that accelerates future development.”
Notably, as MIT Technology Review points out, “some futurists such as Ray Kurzweil have hypothesized that we will someday soon pass through a Singularity—that is, a time period of rapid technological change beyond which we cannot envision the future of society. Most visions of this Singularity focus on the creation of machines intelligent enough to devise machines even more intelligent than themselves, and so forth recursively, thus launching a positive feedback loop of intelligence amplification.”
Source: Inside Higher Ed — Read the full article on the original site ↗