September 26-27, 2016
New York, NY

AI is not a matter of strength but of intelligence

Francisco Webber (
11:50am–12:30pm Tuesday, 09/27/2016
Implementing AI
Location: 3D08 Level: Beginner
Average rating: ****.
(4.20, 5 ratings)

What you'll learn

  • Explore the reasons why many NLP projects fail when trying to apply ML methods
  • Understand how these issues can be addressed with semantic folding, an alternative approach based on computational principles found in the human neocortex
  • Description

    Francisco Webber offers a critical overview of current approaches to artificial intelligence using “brute force” (aka big data machine learning) as well as a practical demonstration of semantic folding, an alternative approach based on computational principles found in the human neocortex. Semantic folding is not just a research prototype—it’s a production-grade enterprise technology.

    Francisco explores the theoretical underpinnings of semantic folding, which solves the representational problem and the semantic grounding problem—both well known by AI-researchers since the 1980s, and offers an introduction to the Retina Engine, an Apache Spark library for semantic processing of text. Along the way, Francisco demonstrates functional prototypes of semantic classification, semantic filtering, and semantic searching and explains the applications of semantic folding for the finance, media, automotive, legal, medical, and safety and security industries.

    Photo of Francisco Webber

    Francisco Webber

    Francisco Webber is co-founder and CEO of, a company that develops natural language understanding solutions for analyzing the big text data of large enterprises. The solutions are based on the actual meaning, rather than on statistical occurrences, of text.
    Francisco’s interest in information technology developed during his medical studies, when he was involved in medical data processing. Over two decades he explored search engine technologies and documentation systems in different contexts but became increasingly frustrated with the limitations of statistical methods.
    Francisco recognized that the brain was the only high-performing system when it came to natural language understanding. While closely following developments in neuroscience, he formulated his theory of Semantic Folding, which models how the brain processes language data. In 2011, he co-founded to apply the principles of cerebral processing to machine learning and text processing and solve real-world use cases related to big data.