The relationship of TSM (The Schwartz Method) to Artificial Intelligence (AI)

The relationship of TSM (The Schwartz Method) for drafting airtight utility patents to Artificial Intelligence (AI) is tangential, but substanative in a critical way. TSM is a generative method that is suited to (1) the synthesis of a non-provisional patent application and/or (2)  the reading of a preexisting patent to determine its compliance with all MPEP rules for non-provisionals.

As a method, it is designed to provide an Augmented Intelligence (not “AI” persay) to any patent drafter or to any patent auditor...ie to a human. TSM today, taken as is, remains a human operative technique.  The current set of IP SAVVY Tools is based on this purpose designed algorithm.

Although TSM does not use AI (and therefore is not AI), it uses a generative method similar to how predictive AI applications work. If a version of TSM were to be developed, it would be comprised of the self-same method employed as the operative framework of TSM. The structured, iterative nature of how Schwartz built this novel patent drafting technology is the reason why it is so readily taught.  It is the primary reason why TSM can be delivered as a learnable skill in the advanced learning management platform in which it is offered.

In summary, TSM is a robust human engineered method that can be readily taught and applied for the purpose of writing (drafting) and reading (auditing) patent applications. The single minded purpose of TSM is to enable  inventors and their patent counsel to secure more high quality patents that are drafted, understood, filed, examined on merit, and issued to notice of allowance with properly scoped claims.

It is in our plan to find an app company to ensure TSM’s use in the form of an AI (automated) patent drafter/patent reader program.