Iris.ai the Scientist

— your invaluable team member

Iris.ai is training to become a fully fledged researcher, doing literature based discovery. She will make connections between millions of research based hypotheses to build and validate new ones.
Vision

Iris.ai – the scientist

Today’s available Iris.ai tools are a small beginning. Ultimately Iris.ai will be an invaluable companion to researchers, with the ability of doing inference and find new solutions from a vast body of scientific knowledge.

  • Summarize a paper’s core hypothesis
  • Allow exploration of e.g. only methods
  • Connect individual components to another research
  • Highlight contradictions with other findings
  • Suggest new hypotheses for you
  • Validate new hypotheses and publish

The tech required to build an AI Scientist

Still almost a decade away, there is a range of research challenges required to overcome in order to build an interdisciplinary AI Researcher.

Vision

Pseudo-hypothesis extraction

Build a graph representation of the input document, linking words from each class (problem, solution, evaluation, result) to words from the other classes forming graph path of the form “problem – solution – evaluation – result”.

Vision

Truth tree

Unify all individual resources into a graph representation with the true meaning of each document: a conclusion, a hypothesis, and/or a logical statement, which can be represented in a text or mathematical expression, and subsequently validated or refuted.

Vision

Build new knowledge

Do inference on the existing knowledge in order to discover knowledge gaps/white space as well as new knowledge to be implemented.

 

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Today
Vision