Machine Learning (ML) — sometimes referred to as Artificial Intelligence — is a powerful set of techniques used by intelligent enterprises and innovative startups to leverage the vast quantities of data they rapidly accumulate. ML is used to reduce or eliminate the labor involved in information-intensive tasks, as well as to make recommendations to shoppers, to fine-tune algorithms and to better understand customer and user behavior. ML creates efficiencies, cuts labor and makes new services possible.
We find many of our developers are graduating from school with exposure to Machine Learning in their coursework and a great interest in applying these techniques in industry. At ÆLOGICA we see ML as a natural compliment to our work in Ruby on Rails because our clients, the owners of large Ruby on Rails systems are accumulating vast data repositories. They need to leverage this data for competitive advantage. The returns of ML and the spoils of victory will go to the winners who successfully apply this technology first.
One of the great challenges of Machine Learning is obtaining data from operational systems and transforming it into a form that can be easily processed by Neural Network algorithms running on distributed computing services. This is where much of the effort lies and where we can most rapidly assist clients in realizing the promise of Machine Learning.
The returns of Machine Learning and the spoils of victory will go to the winners who successfully apply this technology first.