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Cloud with virtually unlimited computing capacity has given us the possibility of adding (artificial) intelligence into our applications. Machine learning, chatbots and other advanced services are becoming everyday life, and the features can even be added to older applications.

Face Recogition as Commodity

By |2019-06-04T09:39:08+03:00June 3rd, 2019|Categories: AI and Analytics|

Face recognition has become a commodity, you can now get it off the shelf. If your app needs to find faces, identify persons, detect age, gender, or other facial features, there's an API you can subscribe to, and just start doing it. My company WildCode is currently looking for preview customers [...]

Publish Your Machine Learning Model

By |2018-11-01T13:41:14+02:00October 24th, 2018|Categories: AI and Analytics|

It's time to celebrate! All the tests on your data scientist workstation prove that this is really it: Your machine learning model finally makes excellent predictions about the future, classifies the input text/images to right categories, or does something else your model is supposed to do. Day after the celebrations your project manager asks you how [...]

AI: Choosing the Right Flavor

By |2018-06-11T15:06:40+03:00June 5th, 2018|Categories: AI and Analytics|

We'd like to enhance our apps with AI, but we have nobody who understands the neural nets, TensorFlows, Spark GPU clusters or the higher Σ-math involved. The good news is you don't need to be a math or AI magician to have AI infused in your apps. Instead you'll utilize either premade AI services, or standard [...]

Modern Chatbot Reference Architecture

By |2018-03-06T19:40:23+02:00March 6th, 2018|Categories: AI and Analytics|

Wanted to make a chatbot, but wondered if you were doing it right? This short blog shows an architecture reference model how most of today's bots seem to be internally organized. I've seen this architecture used on most text based customer service, FAQ and other one trick bots. The Architecture Making bots understand us or respond [...]