FAQs

Frequently Asked Questions

  1. What is narrative computation?
    • Narrative computation is an attempt at creating AI systems that are accurate and explainable.
  2. What do accurate and explainable mean?
    • Accuracy refers to the tendency for an AI system to not provide incorrect information and make best-effort attempts at solving problems, especially in new or unexpected situations;
    • Explainability refers to the tendency for an AI system’s behaviors to be usefully-explained in human terms; i.e. not a black box.
  3. Why are accuracy and explainability important?
    • Accuracy is important for critical applications where wrong answers may have serious consequences, like engineering, healthcare, autonomous driving, and many more; especially involving difficult edge cases that must be handled in safely and reasonably.
    • Explainability is important because understanding how AI systems behave is critical for fixing problems, for improving performance and for increasing confidence in the design of the systems.
  4. How is the narrative computation approach to AI different from generative AI approaches, like ChatGPT?
    • Narrative computation is a form of symbolic approach to AI (relying on systems of rules to create models of the world); whereas generative AI is a form of neural network approach to AI (relying on patterns that emerge in large amounts of data);
    • Although symbolic approaches and neural network approaches can be combined, narrative computation is a symbolic AI approach that does not utilize neural networks directly;
    • As such, narrative computation is a very different approach to AI from generative AI approaches.
  5. How do narrative computation systems perform compared against generative AI systems?
    • NX-RESEARCH’s systems are still in an extremely early research stage; a comparison has not been published.
  6. Given that there is no published performance comparison against generative AI systems, what makes narrative computation a promising line of research?
    • At NX-RESEARCH, we believe that accuracy, robustness, and explainability will become increasingly vital differentiators in critical AI applications, like engineering, healthcare, autonomous driving, and many more;
    • And we believe that the narrative computation approach offers the possibility of systems that may someday be more accurate, robust and explainable than generative AI systems.
  7. How long before a performance comparison will be available for narrative computation systems against generative AI systems?
    • NX-RESEARCH’s systems are still in an extremely early research stage; our current rough estimate for some early comparisons and demos is within about 18 months.
  8. What are some of the key research milestones or obstacles for deploying narrative computation systems?
    • NX-RESEARCH’s systems are still in an extremely early research stage; we haven’t and don’t intend to publish any public roadmaps at this time.

Further reading:

Introduction to Narrative Computation (White Paper)

Job Posting: Software Engineer – AI Evaluation