In 2018, the number of devices connected to the Internet of Things (IoT) is expected to exceed 11 billion. By 2020, that number is expected to nearly double to over 20 billion. These devices will produce a tremendous amount of data—data we can use to address issues like assistants to research and completing tasks on our behalf, to increase productivity and to make our lives more convenient by allowing us to create smarter robots and act as a second mind.
Machine learning (a subset of AI) enables computers to learn without explicit programming instructions. Computers learn by detecting patterns in data. We often encounter the end products of machine learning online, where websites determine our interests and preferences by analyzing our past behavior. For example, YouTube uses machine learning to list other videos to watch based on the video we are currently watching. Online magazines suggest articles to read based on an article we are currently reading.
Our Mascot Textbox and the Use of Machine Learning
Not only will he be used to help around this website and current projects, he’ll be able to have human-like conversations, also will be used to make a critical decision as well.
This is where Mycroft comes in. However, analyzing the terabytes of information he will exceed the natural intelligence of humans. Unlocking the full potential of IoT depends on using artificial intelligence (AI) to help him learn more effectively.
General history of AI and how it’s used Today
Artificial intelligence is already used in medicine to manage medical records and to find the most effective cancer drug treatments by analyzing medical research. IoT devices can help with this as well since they can collect data from humans in real time. Thus, as IoT devices become even more interconnected, they will allow humans to make even better and timelier decisions. For example, with the use of Google technology, the UK National Health Service collects data by means of a mobile app to discover health risks. In 2017, Thomas Jefferson University Hospitals in Philadelphia worked with IBM and Harman to develop smart speakers that answer patients’ questions (like “When is lunch?”) and allow patients to use voice commands to control their room environment (by, for example, adjusting the thermostat). As a result, doctors and nurses can spend more time on healthcare. And although many of us already wear fitness trackers, as IoT devices, they will not only track our health but will also provide updates to our doctors in real time. Machine learning promises to make the future of IoT one of nearly countless possibilities.