Last Week in AI
Every week, Invector Labs publishes a newsletter that covers the most recent developments in AI research and technology. You can find this week’s issue below. You can sign up for it below. Please do so, our guys worked really hard on this:
From the Editor: Architectures for Building AI at Scale
Building artificial intelligence(AI) systems at scale seems like a problem that only a few companies have and, as a result, there are not many available guidance about what works and what doesn’t. If you are a machine learning architect looking to implement an infrastructure to run machine learning programs at scale, where do you start? As a new industry, we are all learning and trying to figure best practices as we go along.
In our experience, the best reference architectures for implementing machine learning at scale are coming from big technology players like Microsoft, Google, Facebook, Uber, Amazon, etc. After all, they are the companies dealing with these challenges. The great thing is that these companies have been open sourcing many of the frameworks and tools of their infrastructure. Just this week, Uber open sourced its Fiber framework for running parallel, highly scale computations. Following the new releases of those machine learning teams is a great way to spot new best practices and ideas that could be adapted to your machine learning architecture.
Now let’s take a look at the core developments in AI research and technology this week:
Adversarial Neural Networks at Amazon
The Amazon Research team published some details about how the retail giant uses adversarial neural networks to improve product discovery.
Training Robots to Navigate Using Simulations
Microsoft Research published a paper and a dataset about how to use photorealisitic simulated environments to teach robots how to see and navigate.