In part 1 of this series we’ll explore the fundamentals of machine learning and step through how a developer can implement AI, neural networks, and more into their projects.
We’re taking our chatbot a step further, exploring search & slack integration with IBM’s Watson API to create a more intelligent, human-like interface.
We explore creating a chatbot using IBM’s Watson API to onboard new employees and answer their employment and HR-related questions.
We explore the feasibility of using an inexpensive Bluetooth Low Energy (BLE) approach to detect the distance between a beacon and a single-antenna receiver.
Learn how we developed a Virtual Gift Exchange app to allow us to continue our company’s White Elephant tradition while still adhering to social distancing guidelines.
Needing some quick mockups for an upcoming Labs project we’d normally turn to Sketch. We decided to give Adobe XD a try and here’s what we found.
While wearable technology usually calls to mind devices such as smartwatches and fitness trackers, one exciting new avenue of research is augmented reality glasses. Virtual reality (VR) takes the user to a whole new virtual space, but augmented reality (AR) instead aims to enhance the real world by providing software interactions with physical things, through mediums like phone screens or glasses. This allows for a whole new approach to user interfaces, because programs can now interface with the real world in more meaningful capacities.
In the last two months, Amazon released their new machine learning camera to the public, the AWS DeepLens. The DeepLens is a unique video camera because it carries an onboard Intel Atom processor, meaning that not only can it run a full OS (it runs Ubuntu 16.04 by default), but it can also process video in real time using a machine learning model deployed to it over Amazon Web Services.
The advent of Bluetooth Low Energy (BLE) devices has allowed for the addition of wireless capability to low-powered devices, and expanding the possibilities for the Internet of Things. Because BLE was part of an update to the Bluetooth Standard in 2011, new code had to be written to support devices that utilized the technology. The Generic Attribute Profile (GATT) specification allows for a standardized method of accessing data from BLE devices, and libraries have been written to support this data collection in various languages. By using this technology, we explored the possibility of creating a “smart” kitchen, such that we could wirelessly receive temperature readings from a variety of Bluetooth thermometers.