Machine learning has emerged as one of the most compelling area of IT research and development because at its core, it allows organizations to create algorithms that adapt as data evolves over time. The end result is a new generation of flexible applications that adjust to changing circumstances and business events.
Now Dato, formerly known as GraphLab, wants to democratize machine learning software. Fresh from raising an additional $18.5 million in funding, Dato CEO Carlos Guestrin says that the company is commercializing its open source GraphLab machine learning software.
While there is no shortage of machine learning software options these days, Guestrin says the crown jewel for Dato is application programming interfaces (APIs) and toolkits that Dato is exposing around its machine learning software. Rather than requiring developers to master low-level arcane APIs, the Dato APIs make it a lot easier to build machine learning applications at a much higher level of abstraction.
Data scientists are currently experimenting with all kinds of machine learning applications. But the challenge many of them face is that most machine learning engines are not necessarily ready for prime time consumption in the enterprise. Arguably, machine learning software should eventually be approachable for almost any class of developers.
After all, if machine learning applications require high priests to develop, the number of them that actually make it into production will be very few and far between.