A major pain point of AI is that 'we know the model has produced a result, but we cannot understand why it did so.' This is known as the inference black box problem.
In the July update, Lagrange introduced a new concept - Proofs of Reasoning.
Its purpose is to generate encrypted receipts for the logic of AI: recording the path the model took to make decisions without exposing model parameters and user data.
This method allows regulators or industry users to clearly understand the behavioral logic of the model, rather than just relying on results.
For example, a medical diagnostic AI can prove that it reached a conclusion based on a qualified medical knowledge graph, rather than random statistical bias.
The potential of Proofs of Reasoning lies in the fact that it can bring a new dimension of trust to AI - not only is the result correct, but the process is also transparent.
This is an indispensable guarantee for financial compliance, medical safety, and defense missions. Lagrange is providing a brand new trustworthy standard for the industry.
