Welcome to the future of IoT and perceptive intelligence, where user interaction is optional and contextual awareness is machine learning enabled.
Human interface that connects us with machines — the way we interact and control them — has changed a lot over the years. From tactile methods like knobs, buttons, keyboards, pads and touch screens to more recent voice and visual command capabilities, we’ve adapted our devices to become more user-friendly and more humanlike by using more intuitive input techniques. We’ve all grown accustomed to the swipe, the pinch, the “Hey, Google,” and the hand gesture to tell our devices what to do. But they still require the human element, a proactive direction by a person. That, too, is changing.
A new generation — indeed, ecosystem — of devices, will be driven by interfaces that perceive your wants and needs. Welcome to the future of IoT and perceptive intelligence, where user interaction is optional and contextual awareness is machine learning enabled. When devices transition from collecting and transferring information to using that information intelligently on their own, computing has become ambient.
Although based on some level of human interaction, ambient computing doesn’t require active participation. Artificial intelligence and deep learning can now power entire integrated ecosystems of devices to learn about users, their environments and their preferences, and then adjust accordingly to provide the optimal response or action. This kind of perceptive intelligence is enabled by sensors and vision and is embedded in our living and working spaces in a way that allows its use without being fully aware that we are doing so.
This level of intelligence is a result of the progression of AI and machine learning to deep neural networks that change the paradigm from sensing to perception and, ultimately, recognition of intent. Recent breakthroughs in deep learning are creating a revolution in the application of AI-to-speech recognition, visual object recognition and object detection. The connected devices provide the data and the AI learns from that data to perform certain tasks without human intervention.
Best of all, perceptive intelligence doesn’t even require a connection to the internet. Edge-based processing now has the performance and accuracy required (as well as the energy efficiency and small form factors to fit in battery-powered consumer products) to run sophisticated AI and machine learning algorithms locally, sparing users the cost, bandwidth, latency and privacy challenges of a cloud-based model. Now, devices can collect and analyze video and audio data and respond intelligently in near real time — without the risk of compromising user privacy or security or the cost of transmitting literally zettabytes of data to the cloud-based data centers. […]