2018 held many positives for AI research and development, along with a few low points as well. More and more businesses are embracing AI to improve their processes, while the consumer market is also seeing a lot of AI-powered devices, especially in the domain of the IoT.
While the concept of AI has garnered mainstream acceptance, it has also received quite a bit of negative press. High profile figures like Elon Musk raised fears of AI domination, while issues like Cambridge Analytica and Deepfakes highlighted the potential for mischief inherent in any new technology.
But on the whole, the going has been good for AI and Machine Learning. And there is a general consensus that we are barely scratching at the surface of AI development. There is a lot more left to do, and 2019 should see continued progress, especially in the following fields:
AutoML Will Speed Up AI Deployment in Data Analytics
Teaching an AI to be “smart” is a complex and often highly repetitive task. And when you need software that can analyze complex datasets and business models, your task becomes even harder. AutoML is a machine learning process that tries to introduce automation into the mix, to speed up the work of AI programmers and data scientists. This will result in faster deployments of AI solutions for complicated business scenarios.
AI Will Revolutionize Real-Time Cyber Security
Cyber threats are becoming bigger and more sophisticated with each passing day. With the advent of IoT, big data-based attacks will become even more commonplace. And much like in Big Data and ML, cybersecurity is yet another IT field that is facing an acute shortage of skilled manpower. Here, automation is fast becoming a necessity. 2019 will bring us one step closer to the future world as depicted in Ghost In The Shell (the anime, NOT the shoddy big screen adaptation), where smart AI programs assist humans in tackling cyber attacks.
IoT and AI Will Meet at the Edge
There is a growing convergence between IoT and AI, both at the enterprise level as well as in consumer electronics. But as devices and sensors get smarter and more numerous, the volume of data generated will also scale accordingly. With 5G networks just around the corner, 2019 will see practical iterations of edge computing in a big way. We should be seeing a welcome shift away from the Cloud starting to gather pace this year.
Continued Shortage of Skilled Labour
This is one major negative trend that will continue to plague the field of AI development as well as deployment well into 2019, and possibly beyond as well. The technology is evolving too fast and us humans are still trying to catch up! Businesses will have to look at either aggressive hiring or improved to the training of available IT personnel if they want to harness the power of AI soon.
Hardware Development Will Keep Pace
Advanced AI processes in data analytics and tasks like facial recognition require additional processing power. Even the most powerful CPUs could end up being the bottlenecks. This is why all major chip manufacturers like Intel, IBM, AMD, and ARM are betting big on chips that are optimized to handle AI applications. And even other tech giants like Google, Microsoft, Apple, and Amazon are working on AI-enabled chips. In 2019, we will continue to see more of these in everything from IoT appliances to smartphones and massive servers.