As of late 2026, is meaningful recursive self-improvement in AI already underway?

“I think that RSI, is fundamentally how things are done. So we use software. To design a computer, to run software, to design a computer, to run software, to design a computer.”

“And because it, you use it over and over again, some of it is skills, some of it is going to be a memory, we're going to improve the memory. Okay, so that next time you use it, it's even better than last. Recursive self-improvement. You could also decide that you take all of this skills, all of this memory,”

“what we're working on at Recursive is to have humans only be involved in setting up the rewards and the environment and the goals. And then allow the eye to have the entirety of the process of ideation, implementation, and validation of ideas, and have full control over that, and allow for so-called open-ended algorithms, evolutionary search algorithms that combine”

“this year, something major shifted, and that is, AI, can now code, right? And that, is a major shift, in, in the ability for it to change itself. You know, like we now are able to essentially lean into the fact that AI is code, and AI can code, right? So you have a, a loop that you can close”

“I think that that's already here.”

“I think that that's already here. So let's agree that these agents are dangerous. Imagine that you have non-agentic AI, that you have an air gap, you've got a, a computer that can answer and, math problems.”

“there was some interesting commentary, if you remember the AI 2027 scenario, that we're within 10 to 15% of where AI 2027 predicted that we'd be by November 2026. Look at model four on that chart. ... We are so deep in recursive self-improvement at this point.”

“The good news, the silver lining is we're so deep in RSI at this point. I think with just software-only improvements, even if we're sort of subjecting ourselves to a form, the form of export control we're trying to subject China to, we can, I think at this point, just through pure software improvements, get to where we're going, probably”

“they're using it inside Anthropic, and it's building Mythos 3. But they're not going to release any of that. You know, it's accelerating internally. It'll build 4, 5, 6, 7 very, very quickly now inside their walls. But they're not going to release any of that, one, because they don't have the compute to release it anyway. But even if”

“There's lots of cognitive dissonance involved in being part of this. That's what I found. And particularly as RSI gets real, and you know, you talked about we're going faster because of RSI.”

“Anthropic published a very interesting blog talking about how they were using RSI, and, and 26%, they had a chart showing that 26% of their tasks That are involved in basically trying to create the next generation of models, they were already were using RSI to do that.”

“there's no way for them to maintain their lead as the number one superintelligence company without continuing to advance the frontier very rapidly and to continue to pursue recursive self-improvement.”

“the first level is what we call the delegation. You can run recursive self-improvement loop, but it's not strictly better than human doing R&D. And, we believe that all the previous public results are sitting on this level, level zero. And, the level one is what we called net positive, where you run the self-improvement loop, and you found that”

“To us, we care about the outcome of, it actually bending the curve of, recursive self-impro, like, of R&D efforts. We see this is the first evidence that the curve actually starting, get bent, for a fully autonomous system that can improve itself consistently.”

“I think we're already there. I think recursive self-improvement, we're already in the RSI era. Both Anthropic and OpenAI have made a number of pretty detailed and quantitative public statements to that effect. So we're already in an era when RSI is driving the vast majority of research at this point.”

“I personally think that we're further away from that and that the things that the AIs keep getting better at, it's kind of, like, still verifiable stuff and the generalization has been less than, than people, like, expected or, or, or hoped for to, to, like, actually do the last mile of, of fully automating R&D.”

“RSI is the next two years. And, and really, you know, a good strategy around AI really focuses on what are the exact moves for the next two years. Because after that, I mean, we're talking about intelligence like no one's ever even imagined”

“by default, I don't see how you don't get some kind of crazy recursive self-improvement within the next 10 years. But the one reason why that might not happen is in terms of like weight updates, the sample efficiency of weight updates, they just seem way far behind humans”

“there's no way for them to maintain their lead as the number one superintelligence company without continuing to advance the frontier very rapidly and to continue to pursue recursive self-improvement.”

“To us, we care about the outcome of, it actually bending the curve of, recursive self-impro, like, of R&D efforts. We see this is the first evidence that the curve actually starting, get bent, for a fully autonomous system that can improve itself consistently.”

“The good news, the silver lining is we're so deep in RSI at this point. I think with just software-only improvements, even if we're sort of subjecting ourselves to a form, the form of export control we're trying to subject China to, we can, I think at this point, just through pure software improvements, get to where we're going, probably”

“by default, I don't see how you don't get some kind of crazy recursive self-improvement within the next 10 years. But the one reason why that might not happen is in terms of like weight updates, the sample efficiency of weight updates, they just seem way far behind humans”

“I personally think that we're further away from that and that the things that the AIs keep getting better at, it's kind of, like, still verifiable stuff and the generalization has been less than, than people, like, expected or, or, or hoped for to, to, like, actually do the last mile of, of fully automating R&D.”