Home Assistant is arguably a staple of home labs for IoT devices and this year they’ve been running a “Year of Voice” campaign about their efforts to enable voice assistant functionality. So, I decided to take a peek and see how well it works.
A few years ago, Google released a neat little product called Coral, a “tensor processing unit” (TPU), aka, an AI accelerator. Targeted at IoT/embedded devices, such as a Raspberry Pi, Coral can run models using TensorFlow Lite and has enough performance to allow these devices to do some AI in a reasonable amount of time.
Linux distributions come with a built-in documentation function through what are called “man” (manual) pages. However, reading the manual generally requires knowing the name of the program or function you’re working with. So, let’s see if we can do a little better.
This project is an interactive dashboard visualization of the Smithsonian Institute’s Smithsonian Open Access dataset, which contained 11.9 Million Records at time of. The dashboard allows insight into the composition of the Smithsonian’s collections, including what, when, and where items come from. Specifically, the visualization looks at the unit (such as the National Museum of…
This project is a narrative visualization seeking to interpret some of the information that can be obtained by looking at a museum’s collections. The dataset contains about 62,000 records including data like department, type (such as “print” or “jewelry”), and whether the item is on display.