{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11468362","patent":{"patent_number":"US-11468362","title":"Quantum random, self-modifiable computer","assignee":null,"inventors":[],"filing_date":"2019-06-09T00:00:00.000Z","publication_date":"2022-10-11T00:00:00.000Z","cpc_codes":["G06N","G06F","G06N"],"num_claims":6,"abstract":"We describe a computing machine, called an ex-machine, that uses self-modification and randomness to enhance the computation. The name ex-machine is derived from the latin extra machinam because its can evolve as it computes so that its complexity increases without an upper bound. In an embodiment, an ex-machine program can compute languages that a Turing or standard machine cannot compute. In an embodiment, the ex-machine has three types of instructions: standard instructions, meta instructions and random instructions. In an embodiment, the meta instruction self-modify the machine as it is executing so that new instructions are added. In an embodiment, the standard instructions are expressed in the C programming language or VHDL dataflow language. Random instructions take random measurements from a random source. In an embodiment, the random source produces quantum events which are measured.In an embodiment, an ex-machine receives a computer program as input, containing only standard instructions. In an embodiment, the ex-machine combines its random instructions and its meta instructions to self-modify the ex-machine instructions, so that it can evolve to compute (i.e., verify) the correctness of the computer program that it received as input. In an embodiment, an ex-machine uses its meta instructions and random instructions to improve its machine learning procedures as the ex-machine is computing.In an embodiment, machine computation that adds randomness and self-modification to the standard digital computer instructions has more computing capability than a standard digital computer. This capability enables more advanced machine learning procedures where in some embodiments meta instructions 1 and random instructions improve the machine learning procedure, as it is executing. In an embodiment, differential forms, the curvature tensor, and curvature of saddle points are used to help self-modify and improve an initial, standard gradient descent method."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Quantum random, self-modifiable computer","description":"We describe a computing machine, called an ex-machine, that uses self-modification and randomness to enhance the computation. The name ex-machine is derived from the latin extra machinam because its c","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11468362","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11468362","citation_suggestion":"Patentable. \"Quantum random, self-modifiable computer\" (US-11468362). https://patentable.app/patents/US-11468362","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11468362","json":"https://patentable.app/api/llm-context/US-11468362","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T23:10:53.138Z"}