The new breakthroughs in the realm of AI that will disrupt the tech and industrial landscape in 2019

Anil Kaul, Co-Founder and CEO, Absolutdata

A little over a decade ago, the idea of a phone that connects to the internet and does just about all that a computer can do – while fitting into your pocket – may have seemed a bit far-fetched. However, today technology has advanced in such a way that it has made life so much more convenient than ever before, while smartphones and wireless technologies have become ubiquitous to our daily lives.

Arguably one of the biggest technological advancements of the 21st century so far, AI has also heralded what is being termed as the Fourth Industrial Revolution, bringing automation to several industries and sectors globally. From recognizing speech, visual perception, to even being able to imitate physical traits and behaviours, AI characterizes a form of computing system that self-learns by simulating a wide array of functions. AI-enabled technologies are bringing a level of robustness to the enterprise, unlike any other technology before them. Furthermore, AI has enhanced efficiencies at the enterprise level by adding to the existing capabilities of information and communication technology and making them far more efficient than ever before.

Anil Kaul Co-Founder and CEO Absolutdata

From finance, banking, retail to healthcare, automotive manufacturing, etc. the adoption of AI and automation has been met with highly successful results across segments. AI can augment the capabilities of existing technologies, thus enabling machines to perform much more than dull and repetitive tasks which add no value to the business process.

Be it on an organizational or decision-making level, AI has undoubtedly brought a major paradigm shift to a rapidly-evolving global business landscape. However, the technology itself is constantly evolving, and major business trends are also fueling innovations in the realm of AI. Here are some of the most significant breakthroughs that will influence AI innovation in 2019:

Next-generation computer architecture

The current class of CPUs and microprocessors are not adequately equipped to run advanced technologies like Machine Learning and Deep Learning models. The CPUs that are supposedly the fastest still do not match up to the speeds required to deliver the computational capabilities needed. Graphics Processing Units (GPUs) are capable of enabling easier ML training since they are made up of thousands of cores, making these processors extremely effective while executing AI-based programs.

Besides GPUs, Field Programmable Gate Arrays (FPGAs) are best equipped to undertake high-intensity computational functions. FPGAs are backed by public cloud vendors for the development of customized and completely optimized infrastructure to ensure seamless AI deployments and executions. Google Cloud’s Processing Unit (TPU) is one of the most significant innovations that have simplified and accelerated the process of programming, training, and executing deep learning models.

Increasing convergence of Augmented Reality and AI

Augmented Reality embodies the next level of interactivity with AI, and is a technology that is quickly being adopted across industries. Take education, for instance, wherein the use of AI and augmented reality can revolutionize learning and teaching both. From school students to medical students, aspiring surgeons, engineering students, etc. AI and AR have the potential to make learning more dynamic, interactive, and personalized for all.

One of the simplest, yet most influential augmented reality innovations in recent times was the mobile game Pokemon Go, which revealed the kind of engagement and immersive content AI and AR can offer. Further, we have also increasingly seen that its potential applications in marketing or advertising are immense, most significant of which is that brands will be able to tell better, more engaging stories with far more creative tools.

Deeper and contextual interactions between machines and humans

Artificial Intelligence is going beyond the simple routine to a focused strategic consideration among businesses today. An increasing number of companies are thus investing significant sums and resources towards developing interactive interfaces not only for customers but also for their employees to enable them to understand and work with more advanced AI. Since the key purpose of AI is to enhance man-to-machine interactions, virtual assistants are being made more intelligent, and thus capable of performing more complex tasks than humans can. This intelligence also provides them with the ability to identify patterns or critical information which humans cannot do. Hence, efforts are on to make man-to-machine interactions more real and informative. This is because an AI interface in the organization can help human employees incorporate the AI’s insights when taking important decisions.

The use of machine learning across various industries and verticals is rising exponentially, along with that of its allied technologies like deep learning or natural language processing (NLP) – in both enterprise and customer-facing applications. This only goes to show that we will continue to find more ways through which we can leverage and uncover the vast potential of AI and other digital technologies in the coming years. One can, then, expect some significant changes on an industrial as well as a user/consumer level, as a result of the innovation in the space.