The Next Wave of Artificial Intelligence: On-device AI

by April 13, 2019

Artificial Intelligence is no more a science fiction word today. It has turned into a basic piece of our reality as cell phones, smartwatches, tablets, to give some examples. Our lives today revolve around these gadgets to an incomprehensible degree. Utilization of virtual Personal Assistants like Siri and Cortana is on the ascent. We would be powerless if Google maps weren’t there to guide us. To put it plainly, AI is progressing quickly and is changing the manner in which we live our lives. The smart devices today are way ‘more intelligent’ than their ancestors. The fast upgrades in the hardware and software spaces have set off an era where Intelligence is moving from the cloud onto the device and altering our lives.

With new abilities for existing solutions, on-gadget AI makes them all the more brilliant and faster. That could mean more intelligent assistants, more secure vehicles, enhanced security, leaps in robotics, a development in healthcare solutions, and much more. ML and data processing in the cloud won’t leave, yet on-device AI conveys customized experiences with some gigantic advantages, including colossally improved performance, particularly for those AI use cases that can’t manage the cost of even a microsecond slack: like auto security. On-device AI supports security and privacy, ensuring sensitive information like voice ID and face checks that could be undermined in the cloud. Also, when your AI power is in your grasp or readily available, reliability is never again an issue of network accessibility or bandwidth.

It is a typical conviction that AI is about Big data and cloud. Unexpectedly, AI can likewise be localized, directly in the palm of our hands in our cell phones. There has been a consistent development of AI towards the edge devices. This has been possible because of an expansion in computing power combined with upgrades in AI algorithms and the creation of strong software and hardware. These progressions have made it conceivable to run Machine Learning solutions on cell phones and cars instead of in the cloud, and this pattern is on the ascent.



Without a doubt, on-device processing is a lot quicker than the cloud since it spares the trip from telephone to server and back. This is an imperative factor since some used AI cases can’t bear the cost of inactivity. This can be particularly valuable in autonomous vehicles where the vehicle needs to apply brakes and can’t manage the cost of slack of even a second.

Extremely great cameras have been featured in smartphones for quite a while. However, when you apply AI to a camera in a cell phone you can empower extremely demanding computer vision applications, enabling photographers and videographers to shoot soft focus, the bokeh impact, on the fly at 30 frames for every second and the ability to track subjects. These were things that used to require post-preparing in the cloud, or weren’t conceivable, on the grounds that enough data wasn’t gathered when you shot the video to do it adequately.

This can directly affect the business. The enhanced value of the experience for a client builds the sureness that they’ll redesign their device to a flagship model so as to catch those abilities.



Artificial intelligence, obviously, will likewise have a significant effect on security, and privacy just as better execution and unwavering quality. Artificial intelligence powered facial recognition for phone opening and mobile payments are as of now a reality, guaranteeing more noteworthy security. Cell phones can consolidate AI with sensor inputs like biometric information and even advanced analysis of user conduct to improve safety efforts. Artificial intelligence can even analyze things like weight applied on the console or the client’s remarkable style of swiping, typing and strolling to validate access. With time, as these capabilities grow further, AI fueled cell phones can even make passwords and authentication processes redundant.


Hardware Enhancement

Running on-device AI is no mean activity. Power and thermal efficiency are two regions which need significant consideration. Artificial intelligence workloads can be the memory and computationally serious. Again the power, thermal and size requirements of the gadgets must be remembered. In this way leap forward headways and advancements are required in both software and hardware zones to accomplish on-device AI.

Qualcomm vision is to Make on-device intelligence unavoidable. Their emphasis has been on superior HW/SW and upgraded network plan. Qualcomm Snapdragon Mobile Platforms have been the SoC of choice for the most astounding performance cell phones. Qualcomm Hexagon Digital Signal processor is being utilized widely to address AI outstanding tasks at hand.

Artificial Intelligence on cell phones has officially changed the way cell phones work and the value they bring to regular living. As innovation develops further, we will undoubtedly observe more integration with cell phones, offering upgraded performance abilities. Gartner forecasts that by 2022, 80% of all cell phones will be AI-empowered. Taking into account that this number was only 10% in 2017, this is a tremendous jump, indicative of the development in the innovation itself just as the market demand.