A world made better by artificial intelligence (AI) has been one of humanity’s longest-held technological visions, and in 2021 that vision is being realized.
AI is in our pockets, our homes, our cars, our workplaces, and it’s already making a real difference in how we experience the world around us. A quarter of all respondents stated that the greatest impact of AI would be in healthcare. C-suite respondents were even more likely to view healthcare (35%) as having the greatest impact. Healthcare and many other industries taking advantage of AI are no doubt yielding the benefits of powerful and power-efficient new hardware systems that are enabled by specialized compute.
No longer are AI developers forced into a one-size-fits-all hardware approach. They’re increasingly mixing and matching CPUs, GPUs and NPUs that best deliver their AI-based innovation visions. The ability to run AI from endpoint to cloud, on the billions of Arm devices in the market, creates a tremendous opportunity for new and innovative applications.
Paul Williamson, SVP and GM IoT & Embedded
I’m not surprised that after the events of the past 18 months, healthcare is seen as a key area in which AI will have the most impact. AI technology is already enabling healthcare professionals to diagnose and treat patients far more quickly thanks to its ability to spot patterns in data.
During the pandemic, it enabled companies like DarwinAI to rapidly deploy initiatives to help in the fight against COVID-19. DarwinAI built COVID-Net, a deep neural network (DNN) using the Arm NN inference engine to identify critical COVID-19 symptoms in chest X-rays.
It’s also very interesting to see how much work is going into data center and storage technology within healthcare. Healthcare is going to be a big driver in data: Genome data alone is doubling every eight months. Before healthcare introduces AI into therapies, they will have to figure out the back end.
The healthcare market is still dominated by health-wearables development, but there’s emerging focus in other application areas that can be enabled through AI. For example, of the respondents developing healthcare technology, almost 1 in 5 will be working on AI-powered smart camera/computer-vision products in the next three years. These products might detect anomalies in live scans, monitor and analyze patient behavior or use facial recognition to ensure that everyone in a hospital is supposed to be there.
With such applications comes an intensifying focus on data consumption, analysis and security. For instance, as applications leverage more AI to make sense of these data, developers need to think more broadly about how to properly leverage compute from the cloud to the edge and endpoints. This means understanding how to put the right compute capabilities along that spectrum for optimal performance and time-to-results. It also means understanding how to think about end-to-end security that ensures patient privacy and trust as well as regulatory compliance.
