Reasoning on Financial Intelligence

How you can help fight organized crime using AI. Here we are not talking about some random Ponzi Scheme or how to spend the swag of the robbery of Ocean’s Eleven.

Probabilistic Reasoning on Knowledge Graphs

Using a knowledge graph without reasoning is like having an inviting cake and leave it there to admire it: aesthetically fascinating but a waste of yummy ingredients and, in the long run, pointless!

A Commentary on the Abstraction and Reasoning Challenge 

This competition was hosted by François Chollet. This report has been prepared by Somayeh Gholami and Mehran Kazeminia. Currently, Machine learning techniques can only use the patterns that they have already seen.

Knowledge Representation and Reasoning with Answer Set Programming

Read about the difference between declarative and imperative programming and learn from code examples (Answer Set Programming, Python and C).

A brief pre-history of Classical AI

This article covers what I call the pre-history of Classical AI — those parts of the story that happened before the invention of modern computers (pre 1950s) but are crucial to understanding why we believe that AI is possible.

Determining compatibility

A configuration management example. Across various industries and business models, companies seek to assess compatibility; for example, in regards to industrial configuration management, terms in contracts, points of a supply chain, buyers and suppliers, and so on.

What is Reasoning? (This is part 1 in a series on reasoning)

A while ago, I wrote an article on the six easy and not-so-easy pieces in AI. Reasoning was the first item on my list of not-so-easy pieces.

What is Ambient Intelligence? | Hacker Noon

Mark Weiser, CTO of Xerox Corp's Palo Alto Research Center, said in 1991: “The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.” Weiser proved prescient: satellite-based cell phones and the internet are examples of profound, invisible technologies.

How To Establish Reasoning In NLP Models

Search engines usually employ two techniques to get the most appropriate results: retrieve and read Question Answering (QA) approach, or a Knowledge Base QA (KB) approach. These two, however, have limitations—multi-hop question answering. In short, the challenge is in answering questions where the search engine has to scrape from multiple documents.  To address this limitation,…