Artificial Intelligence and Understanding Time
Computer Systems That Innately Grasp Time
On the 6th of September in the New Yorker an article called How to Build Artificial Intelligence We Can Trust was published. The article was written by Gary Marcus and Ernest Davis. Dr. Marcus is cognitive psychologist and robotics entrepreneur. Dr. Davis is a computer scientist. This article was sent to me by a postdoctoral fellow at the Department of Social Anthropology. It interested me for several reasons, however the main reason was the concepts it mentioned of which I will talk of one: time.
Time to write some code
It is timely that code has to be written or programming has to be done, because problems has to be solved. It is the way to engineer the world better or do the problem solving of less, quicker or better. The authors broadly state:
“In particular, we need to stop building computer systems that merely get better and better at detecting statistical patterns in data sets — often using an approach known as deep learning — and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space and causality.”
Why does not computer systems understand time? They start and they stop, 🛑 ✋ is that not enough? It must be said that the empirical material in this article is not very impressive, a few Google searches and a search on Google’s Talk to Books is not notable as source material. However the premise of the article or suggestion that running machine learning techniques have to take time into consideration to a larger degree is an interesting one.
Stacking and continuity: On temporal regimes in popular culture
Is the perception of time important for society, does technology change this, or even lack this? I think time, space and causality sounds so easy yet hard in practice. Another professor of mine has recently studied time at the Centre of Advanced Studies. His name is Thomas Hylland…