DSAIL - Domain-Specific AI Logic
DSAIL - Domain-Specific AI Logic
By Jaxon AI
DSAIL systematizes the procedure of crafting intricate AI systems. It arranges diverse components like metadata, abstract concepts, requirements, and overarching frameworks. By simulating model performance, individuals can delve into design trade-offs and achieve the correct architecture from the outset.
Delivery method
Jaxon’s AI-powered ‘Fact Checker’ addresses large language models' hallucination problem and brings trust into the LLMs. At its core, DSAIL lets users specify the problem to be solved in abstract terms. Users can express this in declarative natural and/or formal languages to state unambiguously what is needed for a performant task, but not how to accomplish it. By asserting constraints on any candidate solution, DSAIL ensures accurate model systems that can be trusted.
Rigorously Automate the Design Cycle
By defining the appropriate categories, functors, and natural transformations, Jaxon captures the specific relationships and properties of your system in a rigorous mathematical framework.
Reason About the Design in an Abstract Way
DSAIL employs a novel, patent-pending method to define, contemplate, rationalize, and determine the range of potential solutions. This approach facilitates the selection of a practical (optimal or nearly optimal) solution prior to developing the implementation strategy that outlines how it will be achieved.
A Formal Fact Checker
DSAIL's 'Fact Checker' plays a key role in solving the issue of misleading information. It does this by creating a straightforward system that focuses on your main goals. This involves organizing information and tweaking it through a method called graph rewriting, ensuring that the system improves in areas that matter most to the user.