Towards a New Architecture for Artificial Intelligence
Dr. Venkat Srinivasan, August 2018
AI is in a renaissance powered by the availability of enormous amounts of data, connectedness and the low cost of computing infrastructure. Yet, we believe AI is in its early innings and has to overcome significant challenges in order to deliver on its promise. Indeed, for AI to be successful, we believe the early exuberance around algorithmic acquisition of intelligence has to evolve to a more robust context aware, traceable architecture for intelligence acquisition which can also function in sparse data environments.
We propose a new architecture for AI grounded in principles of transparency, contextretention and ‘computational abstractions’. Computational abstractions, encapsulating structured representations of knowledge in various domains, both abstract and specific, can enable speedier, more validated knowledge acquisition for AI solutions including in sparse data environments. We hope the architecture contributes to and advances successful AI applications in the real world.