In the contemporary world, there seems to be an issue in the realm of digital communication which is just waiting to be cracked. The issue lies within the existing end-to-end models of open-ended response generation that these models often create grammatically fluid and contextually appropriate responses, but tend to produce bland, evasive, and sometimes incorrect responses. This is well illustrated in a given scenario, where a user prompts the model with “Tell me more about it.” and the model responds with “I'm not sure . . . Might be a superhero movie . . . ”, demonstrating the lack of specificity and accuracy in its response generation.
This issue has created an inconvenience for individuals who rely heavily on digital communication, often leading to misunderstandings, unintended humour, or simple inaccuracy. It slows down the workflow, and presents a clear need for better artificial intelligence capabilities.
Stepping forward to take a swing at this ongoing issue is Microsoft with their newly announced patent US20230325603A1, titled ‘Grounded Text Generation.’ This patent displays a promising solution that aims to address the problem head-on. It speaks of a technology system which essentially empowers computers to understand and generate text in a more accurate, contextually relevant manner. This innovative approach utilizes machine learning models, capable of outputting more precise and contextually appropriate computer-generated text based on input text.
The world after this problem is addressed opens up new avenues and improves the fluidity of digital communication. Envision improved versions of Microsoft Word, Microsoft Outlook, or Cortana, where the text generated by these platforms would be far more accurate, context-specific, and user-friendly. For instance, a user might be working on a study report on marine life, and the system, understanding the context from the extra information or 'grounding source,' could suggest precise phrases, automatically correct errors, and contribute meaningfully to the composition of the document.
Another instance could be in the preparation of business emails, where the system can use relevant 'control signals' or prompts, to automatically draft or edit mails in a manner that aligns with the user's needs. Moreover, this technology could be used in personal assistant applications, enhancing their utility by improving conversational responses, making them more accurate and engaging for the user.
Figures: FIG. 1 to FIG. 14 in the patent illustrate different aspects of this solution, showing how this text generation computing system uses machine learning models, control interfaces, and grounding interfaces to generate accurate and appropriate text.
It's important to remember, however, that the existence of this patent does not necessarily imply that it will make its way into the market as a tangible product. The journey of an idea from patent to reality can sometimes be a long one. But should this patented technology become a part of our lives, it has the potential to positively transform the landscape of digital communication, making it smarter, more efficient, and more intuitive.
P.S. Please note that as exciting and promising as a patent may sound, there is no guarantee that it will be actualized and appear in the hands of users, as many factors come into play during the complex development process.