Project Aristo is a flagship project of AI2, a first step towards a machine that contains large amounts of knowledge in machine-computable form that can answer questions, explain those answers, and discuss those answers with users. Central to the project is machine reading – semi-automated acquisition of knowledge from natural language texts. We are also integrating semi-formal methods for reasoning with knowledge, such as textual entailment and evidential reasoning, and a robust hybrid architecture that has multiple reasoning modules operating in tandem. Project Aristo represents a new start towards intelligent systems, building on experience from the prior Project Halo.


In the current two-year phase, we are giving the computer increasingly difficult science exams, at the 4th, 8th, and 12th grade levels, while aiming to gradually improve performance on, and eventually pass, these exams. This is ambitious because it requires the computer to have substantial general and simple science knowledge. Eventually, the system will evolve to field users' questions, shifting the focus from exams to those answers related to direct user queries. The three main technology thrusts within the system are:

Extracting knowledge from relevant natural language texts, supplemented by other sources and techniques such as crowd-sourcing and judicious use of manual encoding.
Performing inference with that knowledge to answer questions.
Use of natural language processing and other techniques to interpret the actual exam questions and connect them with the knowledge.


Click here to see the list of published papers.