Eric Drexler predicts that nanotechnology can be used to assemble arbitrary physically permitted structures to atomic specifications. The development of a such general assembler has significant implications for various fields, including materials science, manufacturing, medicine, and computing. Despite the potential benefits, developing molecular assemblers presents numerous scientific and technical challenges. Some of these challenges include precise control of atomic and molecular assembly, error-correction mechanisms, energy and resource management, and integration of functional components.
Powerful artificial intelligence systems have the potential to make vital contributions to the design and implementation of the first generation of molecular nanotechnology.
A successful demonstration of a general assembler must be accompanied by:
A publicly accessible report or documentation describing the assembler, its structure, and its components.
Independent validation of the results by at least two separate entities with expertise in nanotechnology, molecular manufacturing, or related fields. These entities can be research groups, institutions, or companies.
"Superintelligent AI" is defined for the purpose of this question as an AI which can perform any cognitive task humans can perform as well or superior to the best humans in their domain.
This question resolves as the number of days elapsed after a superintelligent AI came into existence and the first development of a general assembler, according to widespread media and historical consensus. If a molecular assembler is not physically possible or is created before an ASI, this question will resolve as Other.
1,000Ultra compact self replicating molecular assemblers won't ever come to be as bootstrapping pathway or practical advanced manufacturing systems. Eric Drexler himself called them a long outdated early self-suggesting bio-analogy. They are not covered in his more technical book "Nanosystems:…". Nanofactories are a much more practical approach as a far term target. And there are plenty of much more viable approaches than molecular assemblers for the bootstrapping process. Including flat distributed on-chip systems and foldamer self-assembly in fast programmable microfluidic systems approaches that could eventually even combine to a mixed path at much later R&D stages. R&D towards non-mixed pure gemstone based nanotech that can go far beyond the limits of foldamers in operation temperatures and other performance specs.
There won't be a "now it self replicates boundlessly and it explodes" moment ever.
Similarly for AI, while incredibly fast compared to historic developments, the time-frames suggested here are all way to short. Also they assume a clear moment in time a super-intelligent AI emerges. Which is just as unlikely as the nanotechnology analog.