The Raspberry Pi 4 could not have come at a better time and now is the moment for new developers to start experimenting with the technology. This powerful, yet tiny, computer can be used for a variety of functions, but our focus today will be on using the Pi 4 for image processing in a small package and low power setting.

The computing power of the Raspberry Pi 4 is higher compared to previous generations. This means that it can perform inference fairly quickly. It can be used for various types of applications. These include a rock-paper-scissors detection machine, home surveillance through motion detection, object detection for authorized entry (pet vs. animal) or even to give vision to a robot.

In this video, Lex Fridman interviews Jeff Hawkins. He is the founder of Redwood Center for Theoretical Neuroscience in 2002 and Numenta in 2005. In his 2004 book titled On Intelligence, and in his research before and after, he and his team have worked to reverse-engineer the neocortex and propose artificial intelligence architectures, approaches, and ideas that are inspired by the human brain. These ideas include Hierarchical Temporal Memory (HTM) from 2004 and The Thousand Brains Theory of Intelligence from 2017.

It can become overwhelming as a data scientist to simply keep track of all that’s happening in machine learning. This series of blog posts takes that pain away by highlighting the top ML GitHub repos each month. Check out the top 6 machine learning GitHub repositories created in June.

There’s a heavy focus on NLP again, with XLNet outperforming Google’s BERT on several state-of-the-art benchmarks. All machine learning GitHub repositories are open source; download the code and start experimenting! Introduction Do you sometimes feel that […]

MIT has unveiled an artificial intelligence system that it said could make an array of AI techniques more accessible to programmers, while also offering adding value to experts.

Researchers said the system, called Gen, is similar to TensorFlow, a set of tools developed by Google for automating AI tasks, principally those involved with deep learning and neural networks.