US 11,989,527 B2
Computer implemented methods for the automated analysis or use of data, including use of a large language model
William Tunstall-Pedoe, Cambridgeshire (GB); Robert Heywood, Cambridgeshire (GB); Seth Warren, Cambridgeshire (GB); Paul Benn, Cambridgeshire (GB); Duncan Reynolds, Cambridgeshire (GB); Ayush Shah, Cambridgeshire (GB); Luci Krnic, Cambridgeshire (GB); and Ziyi Zhu, Cambridgeshire (GB)
Assigned to UNLIKELY ARTIFICIAL INTELLIGENCE LIMITED, Cambridgeshire (GB)
Filed by UNLIKELY ARTIFICIAL INTELLIGENCE LIMITED, Cambridgeshire (GB)
Filed on Apr. 17, 2023, as Appl. No. 18/301,560.
Application 18/301,560 is a continuation of application No. PCT/GB2023/050405, filed on Feb. 22, 2023.
Application PCT/GB2023/050405 is a continuation in part of application No. 18/001,368, previously published as PCT/GB2021/052196, filed on Aug. 24, 2021.
Claims priority of application No. 2202347 (GB), filed on Feb. 22, 2022; application No. 2219268 (GB), filed on Dec. 20, 2022; application No. 2300624 (GB), filed on Jan. 16, 2023; and application No. 2302085 (GB), filed on Feb. 14, 2023.
Prior Publication US 2023/0274094 A1, Aug. 31, 2023
Int. Cl. G06F 17/00 (2019.01); G06F 40/30 (2020.01); G06F 40/40 (2020.01)
CPC G06F 40/40 (2020.01) [G06F 40/30 (2020.01)] 30 Claims
OG exemplary drawing
 
1. A computer-implemented method of interacting with a large language model (LLM), including the steps of:
(a) the LLM processing first input data to the LLM to generate first output from the LLM based on the first input data to the LLM;
(b) a processing system using a structured, machine-readable representation of data that conforms to a machine-readable language, in which semantic nodes are represented in the machine-readable language, the semantic nodes including semantic links between semantic nodes wherein the semantic links are themselves semantic nodes, in which each semantic node denotes one specific meaning, in which a combination of semantic nodes defines a semantic node, in which expressions in the machine-readable language are nestable, in which the first output from the LLM is represented in the machine-readable language, in which reasoning steps are represented in the machine-readable language to represent semantics of the reasoning steps, in which computation units are represented in the machine-readable language;
(c) the processing system verifying the first output from the LLM using the reasoning steps, the computation units and the semantic nodes, and
(d) providing second input data to the LLM, including the verified first output from the LLM in order to generate improved first output from the LLM, wherein the improved first output from the LLM is generated by the LLM in response to the second input data.