Al parecer, Google lo ha logrado.

Recursive Self-Improvement (RSI) Defined
📌 RSI refers to a system where an AI model possesses the capability to research, develop, and train its own subsequent, more intelligent versions without human intervention.
📈 The process creates an exponential cycle, where the time required for each new iteration decreases while the intelligence of each version increases, potentially leading toward Superintelligence.
🔄 Unlike current AI development, which relies on heavy human oversight, RSI aims to close the loop entirely to reach a state of autonomous advancement.

Evidence and Speculation Surrounding Google
🕵️‍♂️ Rumors emerged after a social media post by an account named "Lira" highlighted the initials RSI, leading to widespread speculation that Google DeepMind has achieved this capability.
🏢 Reports from Reuters indicate that Google co-founder Sergey Brin is actively directing significant resources toward RSI, signaling it as a key pillar in their investment strategy.
📉 Observers noted a shift in Google’s release strategy—slowing down major model launches like Gemini Pro while focusing on incremental updates, leading to theories that internal resources are being diverted to a "gigantic training run."

Industry Dynamics and Perspectives
🗣️ While some "leaks" regarding model versioning and internal code references have circulated on social media, many originated from small, speculative communities, casting doubt on their authenticity.
⚖️ Industry leaders, including those at OpenAI and Anthropic, are navigating the same "continuum" of AI improvement, where the goal is to master agentic loops that allow models to self-correct and improve.
🚀 Experts interpret recent ambiguous statements from Google staff as an indication that they are in the midst of a long-term "AI journey," focusing on the "war" of technological superiority rather than individual product battles.

Key Points & Insights
➡️ The RSI Gap: The primary concern for the industry is that the gap between current AI capabilities and self-improving systems is shrinking uncomfortably fast, increasing the likelihood of a breakthrough.
➡️ Strategic Resource Allocation: Google’s internal restructuring and the prioritization of RSI by founders suggest that the next major leap in AI will likely stem from autonomous, agentic loop development rather than just larger datasets.
➡️ Watch for Year-End Shifts: Based on industry acceleration and current research trends, it is highly probable that major AI labs will unveil significant advancements before the end of the year that surpass current reasoning and coding capabilities.

📸 Video summarized with SummaryTube.com on Sep 16, 2026, 17:43 UTC