With the increasing hype of trends like AI and digital transformation, companies have become data-driven. They have started relying on data and analytics instead of gut feelings, and Data Science has emerged as a lucrative profession. There are 2.72 million job openings for data scientists at present, and this demand will only go higher. If […]
Case Study: Deriving Spark Encoders and Schemas Using Implicits
Click to learn more about author Dávid Szakallas. In recent years, the size and complexity of our Identity Graph, a data lake containing identity information about people and businesses around the world, begged the addition of Big Data technologies in the ingestion process. We used Apache Pig initially, and then migrated to Apache Spark a […]
New AI Programming Language Goes Beyond Deep Learning
According to a recent press release, “A team of MIT researchers is making it easier for novices to get their feet wet with artificial intelligence, while also helping experts advance the field. In a paper presented at the Programming Language Design and Implementation conference this week, the researchers describe a novel probabilistic-programming system named “Gen.” […]
Big Data and Citizen Data Scientists: Knowledge, Skill, and Wisdom Revisited
Click to learn more about author Ian Rowlands. It’s been a while since I posted. It’s been a busy summer as we’ve been working on launching our latest product. However, I’ve also taken some time to experiment with some of the tools that Citizen Data Scientists (CDS, for short) might be working with, to get more […]
The Knowledge Representation Corner: Procedural vs. Declarative Part 2 – Logical Languages
Click here to learn more about author Adam Pease. In Part 1 I discussed the difference between procedural and declarative languages, and mentioned the confusion that can come from thinking that Turing equivalence applies to declarative languages. Now I’ll discuss some different logical languages. This is just an informal introduction. For the formal logician who is […]