The vague concept of AGI is being replaced by Recursive Self-Improvement (RSI)—AI models creating their own successors. This is seen as a more specific and potentially nearer-term threshold that could trigger an uncontrolled explosion in AI progress, moving humans "out of the loop entirely."

The most transformative aspect of AI may be its ability to automate its own research and development. This creates a recursive improvement cycle—an "intelligence explosion"—where progress accelerates exponentially, compressing decades of innovation into a much shorter period.

The concept that AIs can build better AIs, creating an accelerating feedback loop, is no longer theoretical. Leaders from Anthropic, OpenAI, and Google DeepMind have publicly confirmed they are actively using current AI models to develop the next generation, making RSI a practical engineering pursuit.

Once AIs reach human-level competence in AI research and development (R&D), a feedback loop could kick off where they rapidly improve themselves, compressing what would have taken 4-5 years of human-led progress into one.

Silicon Valley insiders, including former Google CEO Eric Schmidt, believe AI capable of improving itself without human instruction is just 2-4 years away. This shift in focus from the abstract concept of superintelligence to a specific research goal signals an imminent acceleration in AI capabilities and associated risks.

Jack Clark of Anthropic estimates a 60% probability of achieving end-to-end automated AI R&D by 2028. This "recursive self-improvement," where AI designs better AI, would mark a critical threshold, leading to an intelligence explosion and a future that is nearly impossible to forecast.

Top AI labs like OpenAI and Anthropic are hinting that Recursively Self-Improving (RSI) AI is imminent, potentially within 3-9 months. This, combined with agentic AI adoption, will create an unprecedented compute demand that current market sentiment underestimates.

While a 2027 superintelligence timeline was once considered aggressive, conversations with current employees at OpenAI and Anthropic reveal internal sentiment has shifted. They now believe this accelerated timeline is plausible, urging forecasters to shorten their own updated, more conservative estimates.

Top AI labs see the race ending not with an IPO, but with "recursive self-improvement"—the moment a model can code its own next version, causing progress to "go vertical." One lab leader believes this will happen by 2028. The strategy is to maintain a lead for just a few more years to win the race permanently.