Abstract: A system includes at least one processor, and a non-transitory computer-readable storage medium storing instructions which, when executed by the at least one processor, cause the at least one processor to perform a method that includes generating a knowledge graph having multiple nodes, each node including at least one field to store data, and being associated with at least one other node. The method further includes, at a particular node, defining a plurality of fields, such that a first field in the multiple fields has a dependence on a second field in the multiple fields. The method further includes receiving data at the knowledge graph, using the received data to define a value of the second field, using the value of the second field to generate a computed value for the first field based on the dependence, and updating the first field using the computed value.

Abstract: Systems, methods, and computer-readable storage media for receiving data at a computer system, wherein the data has a plurality of rows; receiving, from a user at the computer system, a description of a task associated with the data; receiving, from the user at the computer system, a plurality of example transformations; combining, via at least one processor of the computer system, the task description together with the plurality of example transformations and input and output labels, resulting in a prompt; executing, via the at least one processor, a machine learning model, wherein the prompt is an input to the machine learning model, and wherein output of the machine learning model comprises an algorithm for executing the task; and executing, via the at least one processor, the task on the data using the algorithm.