New York Times Article – Is There a Smarter Path to Artificial Intelligence?
This article caught our attention because they featured a startup that was using Prolog for AI. We have been strong proponents of Prolog for Semantic Graph solutions for many years.
For the past five years, the hottest thing in artificial intelligence has been a branch known as deep learning. The grandly named statistical technique, put simply, gives computers a way to learn by processing vast amounts of data. Thanks to deep learning, computers can easily identify faces and recognize spoken words, making other forms of humanlike intelligence suddenly seem within reach.
Companies like Google, Facebook and Microsoft have poured money into deep learning. Start-ups pursuing everything from cancer cures to back-office automation trumpet their deep learning expertise. And the technology’s perception and pattern-matching abilities are being applied to improve progress in fields such as drug discovery and self-driving cars.
But now some scientists are asking whether deep learning is really so deep after all……
………Those other, non-deep learning tools are often old techniques employed in new ways. At Kyndi, a Silicon Valley start-up, computer scientists are writing code in Prolog, a programming language that dates to the 1970s. It was designed for the reasoning and knowledge representation side of A.I., which processes facts and concepts, and tries to complete tasks that are not always well defined. Deep learning comes from the statistical side of A.I. known as machine learning.
Our Tweet with links to AllegroGraph Prolog documenation and the full article:
nytimestech “computer scientists are writing code in
#Prolog… It was designed for the reasoning and knowledge representation side of #AI ….” https://buff.ly/2lmYwkv – #AllegroGraph is the only #GraphDatabase to include #Prolog for your AI apps. https://buff.ly/2yv0IzF