The Gentle Singularity; The Fast Takeoff - prinz

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The Gentle Singularity; The Fast Takeoff

prinz<br>Jan 10, 2026

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On June 10, 2025, Sam Altman published a blog post entitled “The Gentle Singularity”, in which he wrote that “[w]e are past the event horizon; the takeoff has started”.<br>This blog post gathered some attention, and its ideas have since been mindlessly copied by others. Mark Zuckerberg claimed a few days later that “[o]ver the last few months we have begun to see glimpses of our AI systems improving themselves”.1 More recently, Elon Musk, too, said that we have entered the singularity.<br>It has typically been assumed that these claims have been principally driven by the generally fast rate of improvement in AI models (i.e., “AI is improving fast today; AI will improve even faster tomorrow”). With respect to Altman’s claims specifically, I am of a different view. I believe that Altman meant something very specific when he said that “we are past the event horizon”, and that this “something” is the most important thing happening in AI today .<br>Codex

On May 16, 2025 (a few weeks before Altman’s blog post), OpenAI released its agentic coding tool, Codex. The release flew a bit under the radar, overshadowed by the previous month’s release of o3 and endless speculation about the then-impending releases of o3-pro and OpenAI’s open-source models. But no matter. The coding agent, which was OpenAI’s answer to Claude Code, released just three months earlier, was merely the first step on OpenAI’s path to full automation of AI research .<br>OpenAI likely set out on this path in or around March 2025, just a few weeks after Anthropic’s release of Claude Code. This is why OpenAI’s Preparedness Framework was updated to include recursive self-improvement (RSI) as a Tracked Category in April 2025. Other circumstantial evidence also points to the project’s launch in March 2025: OpenAI’s goal of developing a fully automated AI researcher falls exactly three years later (March 2028), and its mid-way goal of developing an automated AI research “intern” falls exactly mid-way through this three-year process (September 2026, or 18 months after March 2025).<br>Even OpenAI insiders were initially not convinced by Codex until a much more powerful version arrived with August’s release of GPT-5:

roon links Codex to “the takeoff”<br>By September 2025, OpenAI began leaking that an automated AI researcher has become the focus of its entire research program . Here’s Jacub Pachocki explaining that OpenAI has been building most of its projects with the goal of achieving an automated AI researcher:<br>Our set goal for our research program has been getting to an automated researcher for a couple years now. And so we’ve been building most our projects with this goal in mind.

The following month, OpenAI officially announced to the world that it is focusing on developing the automated AI research “intern” by September 2026 and the fully automated AI researcher by March 2028. Sam Altman added that the “intern” will run on hundreds of thousands of GPUs.<br>Since this announcement, OpenAI has repeatedly stressed that automated AI research is now its primary focus. “We’re very excited about our 2026 roadmap and advancing work toward an automated scientist,” Mark Chen said just yesterday.<br>Again, the path towards fully automated AI research starts with Codex. This is clear, e.g., from this description of the “intern” from Lukasz Kaiser:<br>Where AI researchers have great hope to help themselves... is that if you could just say ‘hey, Codex, this is the idea, and it’s fairly clear what I’m saying, please just implement it so it runs fast on this 8-machine setup or 100-machine setup’. I think that’s what OpenAI [means by] an AI intern by the end of next year.

Claude Code

Not surprisingly, Anthropic views Claude Code in exactly the same way as OpenAI views Codex - i.e., as a coding tool that will eventually lead to automation of AI research. Indeed, Sonnet 4.5 and Opus 4.5 system cards conspicuously included results of surveys of Anthropic employees designed to evaluate whether the model, paired with Claude Code, is good enough to fully replace a junior AI researcher. In the Opus 4.5 survey, two (2) out of 18 participants classified Opus 4.5 as a “near-complete entry-level researcher replacement” - albeit with “meaningful caveats”.

This is also why we’ve heard Sholto Douglas speak about withholding models with capabilities to perform AI research from Anthropic’s competitors:<br>As AI models get better at [machine learning research tasks], I do expect the labs to to hold back some of the the capabilities. If a model's capable of writing out a whole new architecture that's a lot better, even if it's just capable of writing all their kernels for them, you probably don't want to release that to your competitors.

And what is “the main thing” that Jack Clark worries about these days? But of course, closing the loop on AI R&D, which would...