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Hub AI
Recursive self-improvement AI simulator
(@Recursive self-improvement_simulator)
Hub AI
Recursive self-improvement AI simulator
(@Recursive self-improvement_simulator)
Recursive self-improvement
Recursive self-improvement (RSI) is a process in which an early or weak artificial general intelligence (AGI) system enhances its own capabilities and intelligence without human intervention, leading to a superintelligence or intelligence explosion.
The development of recursive self-improvement raises significant ethical and safety concerns, as such systems may evolve in unforeseen ways and could potentially surpass human control or understanding.
The concept of a "seed improver" architecture is a foundational framework that equips an AGI system with the initial capabilities required for recursive self-improvement. This might come in many forms or variations.
The term "Seed AI" was coined by Eliezer Yudkowsky.
The concept begins with a hypothetical "seed improver", an initial code-base developed by human engineers that equips an advanced future large language model (LLM) built with strong or expert-level capabilities to program software. These capabilities include planning, reading, writing, compiling, testing, and executing arbitrary code. The system is designed to maintain its original goals and perform validations to ensure its abilities do not degrade over iterations.
The initial architecture includes a goal-following autonomous agent, that can take actions, continuously learns, adapts, and modifies itself to become more efficient and effective in achieving its goals.
The seed improver may include various components such as:
This system forms a sort of generalist Turing-complete programmer which can in theory develop and run any kind of software. The agent might use these capabilities to for example:
Recursive self-improvement
Recursive self-improvement (RSI) is a process in which an early or weak artificial general intelligence (AGI) system enhances its own capabilities and intelligence without human intervention, leading to a superintelligence or intelligence explosion.
The development of recursive self-improvement raises significant ethical and safety concerns, as such systems may evolve in unforeseen ways and could potentially surpass human control or understanding.
The concept of a "seed improver" architecture is a foundational framework that equips an AGI system with the initial capabilities required for recursive self-improvement. This might come in many forms or variations.
The term "Seed AI" was coined by Eliezer Yudkowsky.
The concept begins with a hypothetical "seed improver", an initial code-base developed by human engineers that equips an advanced future large language model (LLM) built with strong or expert-level capabilities to program software. These capabilities include planning, reading, writing, compiling, testing, and executing arbitrary code. The system is designed to maintain its original goals and perform validations to ensure its abilities do not degrade over iterations.
The initial architecture includes a goal-following autonomous agent, that can take actions, continuously learns, adapts, and modifies itself to become more efficient and effective in achieving its goals.
The seed improver may include various components such as:
This system forms a sort of generalist Turing-complete programmer which can in theory develop and run any kind of software. The agent might use these capabilities to for example: