Dependency hell: If you’ve done any significant amount of programming or system administration, no matter which framework you used, you’ve been there — you’ve found yourself bogged down in cross-dependency and package configuration issues.
If there is one thing I've noticed in my years of working on Komodo, it's that people are full of misconceptions about what it is. Some of it comes from it having been around for over 15 years, some of it comes from it being an IDE and all the "baggage" that comes with that terminology. I thought why not address some of these misconceptions in a fun and short blog summarizing some of the items that in, my eyes, need to get some time in the spotlight.
If you visited the ActiveState booth at PyCon, QCon, GopherCon or PyData Seattle, you may have had a chance to play NeuroBlast - a simple arcade space shooter, but powered by machine learning. It was created as a demonstration of the power and accessibility of open source tools for machine learning, and uses Google’s popular TensorFlow library to drive the enemy AI in the game.
Created by Google, the Go programming language (aka golang) is an up-and-coming, modern language for building high performance, scalable applications. Our aim with ActiveGo is to make it easier for enterprises to adopt Go, and to increase the adoption of the Go language worldwide.
One of the challenges with machine learning is figuring out how to deploy trained models into production environments. After training your model, you can "freeze" the weights in place and export it to be used in a production environment, potentially deployed to any number of server instances depending on your application.
It’s becoming a common adage that every company is a tech company. As customer expectations have shifted in a “digital-first” world, companies in every industry are moving to faster development cycles, web based services, advanced data insights and even machine learning, in order to deliver greater value to customers and stay ahead of the competition.
For more than a decade, ActiveState has hosted a vast repository of code recipes and discussions over at https://code.activestate.com/ - but in recent years it began to seem out-of-sync with the way developers shared code. New users and recipe updates had to be disabled to prevent spam and yet there remained a treasure-trove of interesting and useful pieces of code in this archive.
Some of the world’s largest companies use Ruby as the underlying technology to drive value for their customers. Twitter, Bloomberg, AirBnB, Shopify and many others have built world class solutions with Ruby (and Rails). And why not? It is highly productive, fun to use, and easy to maintain by individuals all the way up to large teams of engineers. At ActiveState, our interest in Ruby goes back many years, and we knew eventually we would produce a distribution to help teams work with Ruby.
MacOS 10.12.4 came with an interesting surprise for Komodo users, one that made Komodo randomly hang when running processes. Many of you reported this bug to us and helped us diagnose it over the weeks and months following the MacOS 10.12.4 release. Sadly this was just one of THOSE bugs. The kind that take months to diagnose properly and minutes to fix.
Machine learning is often held out as a magical solution to hard problems that will absolve us mere humans from ever having to actually learn anything. But in reality, for data scientists and machine learning engineers, there are a lot of problems that are much more difficult to deal with than simple object recognition in images, or playing board games with finite rule sets.