Over the last decade or so, open source has blossomed into a major movement and the backbone of the tech industry. For instance, check out this project that Uber, yes Uber, has open sourced.

Ludwig is a TensorFlow-based toolbox that allows you to train and test deep learning models without the need to write any of the code. Incubated at Uber for the last two years, Ludwig was finally open sourced this February to incorporate the contributions of the data science community. With Ludwig, a data scientist can train a deep learning model by simply providing a CSV file that contains the training data as well as the YAML file with the outputs and inputs of the model.

The battle for top talent in the AI space is heating up with Apple looking to boost their AI stable. This reminds me of the 90’s when major tech firms would poach talent from each other with impunity. It’s interesting to see how “hot” AI skills have become.

Artificial Intelligence Apple has poached another top engineer from Google as it continues to grow its artificial intelligence and machine learning divisions, with Google’s Dr. Ian Goodfellow having left his role as a “Senior Staff Research Scientist” with Google to join Apple as a “Director of Machine Learning” in […]

DeepMind is definitely at the top of its game with cutting edge projects like AlphaGo, AlphaStar, and, most recently, AlphaFold, but it has even bigger plans. Curiously, it will retain control of any AGI it creates. Granted, an AGI is still years, maybe even decades away. I do, however, find it interesting that DeepMind is already planning a corporate power struggle.

Very Blade Runner-esque, don’t you think?

DeepMind — quite prominently — claims to be the “world leader in artificial intelligence research.” AlphaGo and AlphaStar certainly lend credence to that title, but the Alphabet division’s end goal is artificial general intelligence (AGI). If it ever achieves that landmark accomplishment, DeepMind — and not its parent company — will reportedly retain control.

TensorFlow 2.0 has arrived, with a focus on ease of use, developer productivity, and scalability.

Now there’s a contest to show off your TF2 chops: The #PoweredByTF 2.0 Challenge.

Here’s a synopsis:

Developers of all ages, backgrounds, and skill levels are encouraged to submit projects. Teams may have between 1 and 6 participants. Participants are encouraged to expand the scope of an existing TensorFlow 1.x project, to migrate and continue work on a historic TensorFlow 1.x project; or to create an entirely new software solution using TensorFlow 2.0.

Keras and eager execution . Robust model deployment in production on any platform. […]