To Root Artificial Intelligence Deeply in Basic Science for a New
  Generation of AI
  One of the ambitions of artificial intelligence is to root artificial
intelligence deeply in basic science while developing brain-inspired artificial
intelligence platforms that will promote new scientific discoveries. The
challenges are essential to push artificial intelligence theory and applied
technologies research forward. This paper presents the grand challenges of
artificial intelligence research for the next 20 years which include:~(i) to
explore the working mechanism of the human brain on the basis of understanding
brain science, neuroscience, cognitive science, psychology and data science;
(ii) how is the electrical signal transmitted by the human brain? What is the
coordination mechanism between brain neural electrical signals and human
activities? (iii)~to root brain-computer interface~(BCI) and brain-muscle
interface~(BMI) technologies deeply in science on human behaviour; (iv)~making
research on knowledge-driven visual commonsense reasoning~(VCR), develop a new
inference engine for cognitive network recognition~(CNR); (v)~to develop
high-precision, multi-modal intelligent perceptrons; (vi)~investigating
intelligent reasoning and fast decision-making systems based on knowledge
graph~(KG). We believe that the frontier theory innovation of AI,
knowledge-driven modeling methodologies for commonsense reasoning,
revolutionary innovation and breakthroughs of the novel algorithms and new
technologies in AI, and developing responsible AI should be the main research
strategies of AI scientists in the future.
