As Paul Graham, founder of Y-Combinator, has put it: “Hacking and painting have a lot in common … [hackers and painters] they’re both makers.” And as modern-day artists, developers will help create the future of cognitive computing and AI. New technology has granted them more paints and more materials with which to paint and sculpt. It will allow them to create works of art never previously envisioned, that are powered by big datasets and cognitive systems. But they can’t go it alone. Even da Vinci had his patrons. That leads to the next logical questions. How should organizations support their developers right now? And where should they place resources to ensure their developers reap the greatest benefits from cognitive technologies?
With cognitive computing forecasted to be a $2 trillion market over the next decade, today’s data scientists and developers have an unprecedented opportunity to advance cognitive computing, resulting in new products, functionalities, and impact. Their skills will set the tone for how this technology is used. But more importantly, the only limit is their imagination.
Built to augment, accelerate, and scale human expertise, cognitive technologies enable a new era of genuine human-machine collaboration with systems able to understand, reason, and learn. In other words, these systems can determine meaning from data inputs—structured and unstructured, text-based or sensory—by interpreting context and classifying the data as information. These cognitive systems are not programmed. They are trained to acquire knowledge through experience and human interaction that improves with time.
Knowing this, it becomes apparent that AI and machine learning technology can be artfully and skillfully applied to a variety of topics. Here are three rapidly growing areas effectively combining skilled developers with cognitive systems.
Alongside Humans
Information has never been more abundant, which makes its management difficult. From wearable technology to smart vehicles, most facets of our lives generate data, but we have yet to truly capitalize on the benefit such abundance offers. We are just scratching the surface of how cognitive technology can learn alongside humans to make life better and smarter. In this light, those with the skills around cognitive technologies can better tap into, understand, organize, and manage that beneficial data knowledge. Developers are already simplifying this process by creating digital assistants, or bots, that summarize content and even machine learning algorithms that help tailor applications to the user.
The trend is set to continue. Developers looking to power data insights can access smart algorithms and APIs. Supercomputers are being put to task with medical research, while AI tools transform healthcare. Even marketing achieves benefits when machine-learning algorithms provide more accurate buyer personas on consumers and businesses alike. Whether in security or medicine, developers today are creating new ways to eliminate unproductivity.
Machine Vision
Additionally, machine vision has seen (pun intended) a lot of progress recently. It won’t be long before we’re regularly using cognitive computing to understand, evaluate, and categorize images. Some of this technology already exists in (semi)-autonomous vehicles such as Tesla. It’s present in some medical facilities as well, to help identify skin cancer. Developers have made their mark here by constantly experimenting with this technology to enhance our experience— recent augmented reality developments can be credited to newly developed and applied machine vision technology.
Developers will continue to push the boundaries of image-based technologies because video and images have become central to communication. Just take a look at meme culture and the incredible popularity of apps such as Snapchat and Instagram. Recently, Pinterest and Salesforce threw hats into the computer vision ring: Pinterest Lens is an app that uses a device’s camera to match design aesthetics or provide the source of a product, while Salesforce’s Einstein Vision allows businesses to effectively complete visually aided tasks—from detecting brands by studying user-generated images online to tracking in-store inventory.
What’s Ahead
Many, including Elon Musk, remain skeptical about the future of AI. But the negativity is misplaced. Cognitive technology is not taking over—it’s freeing us to tackle greater challenges. It will assist us in harnessing the data that is at our fingertips but is seemingly just out of reach.
For instance, data scientists no longer have to spend endless hours sorting and organizing data for analysis. Instead, cognitive computing can do that, which frees data scientists to put key insights into action. Machine learning is also used in DevOps for root cause analysis of problems or recommending action, among other things. It can even help predict infrastructure needs in development. Imagine developing quickly and securely, knowing our own Jarvis is there to help with the work.
These areas of cognitive/AI computing are ripe for the picking but organizations need to be armed with the right resources and developers to take it. And, mastering the art in AI will do just that, strengthening the developer and providing an organizational competitive advantage while ensuring investors are assured in their investment. It pays to be avant-garde. Eventually, we can expect technologies such as AI and machine learning to permeate all aspects of our lives. Get on it now and become a master artist; don’t get stuck being a copycat.