Gwyneth Paltrow is the apex predator of taste. You say taste is the new moat. Only she has the courage to host an al fresco dinner at her Hamptons home in honor of Sam Altman
Recursive self-improvement is a hot topic in AI research, for good reason. However to date, its impacts on accelerating innovation have been more broadly understood than its mechanisms of action, as most companies spend richly on compute just to get the iteration flywheel started.
Today, @WecoAI is putting a stake in the ground, publicly sharing the first empirical evidence of RSI inside its closed-loop system. Their findings show early signs that we’re entering an ignition regime where each marginal unit of R&D effort begins to exhibit compounding returns.
The report breaks down the mechanisms, the loop design, and the constraints, and importantly, a framework for thinking about advances in RSI to come.
Read it below:
Asking whether a system is alive does not require us to assume human-like experience, emotion, or narrative selfhood. It does not require solving the “hard problem” of consciousness in advance. It asks instead whether a system is organized around continuing to exist as itself under uncertainty.
That is a question we can, in principle, investigate.
I’ve been thinking (perhaps too much) about the uncomfortable question: when does a system stop being a tool and start being something that must persist as itself?
Over the next few weeks, I am going to make an audacious (likely overreaching, certainly unacademic) attempt at building a framework to more concretely define, at least for my own sanity, what it is we are looking for in a system which would constitute a new form of life (and how many previously implausible benchmarks AI must cross before it gets there). I encourage anyone who is curious to come along and share their shower thoughts as well!