9 Artificial Intelligence Trends You Should Keep An Eye On In 2019

Artificial Intelligence has become a hot topic in tech circles. It has not only changed our lives, but it has also disrupted every industry you can think of. Despite all this, people have different perception about it. Some might consider it as a bad thing because they are told that it will take your job away from you in near future. On the other hand, AI advocates continue to think of AI as an enabler which will reduce your burden and make your life easy by automating things.

Whether you like AI or not, if you are interested in what AI has in store for the future, then you are at the right place. In this article, we will look at some of the biggest AI trends that will dominate in 2019.

Unlike other technologies and software tools, AI depend heavily on specialized processors. To meet the complex demands of AI, chip manufacturers will create specialized chips capable of running AI enabled applications.

Even tech giants such as Google, Facebook and Amazon will spend more money on these specialized chips. These chips would be used for specialized purposes involving AI such as natural language processing, computer vision and speech recognition.

2019 will be the year when we will see convergence of different technologies with AI. IoT will join hands with AI on edge computing layer. Industrial IoT will harness the power of AI for root cause analysis, performing predictive maintenance of machinery and detect issues automatically.

We will see the rise of Distributed AI in 2019. Intelligence would be decentralized and will be located closer to the assets and devices that are carrying out routine checks. Highly sophisticated machine learning models that is powered by neural networks will be optimized to run on edge.

One of the biggest trend that will dominate the AI industry in 2019 would be automated machine learning (AutoML). With automated learning capabilities, developers will be able to tinker with machine learning models and create new machine learning models that are ready to handle future AI challenges.

AutoML will find the middle ground between cognitive APIs and custom machine learning platforms. The biggest advantage of automated machine learning would be that it offers developers the customization options they demand without forcing them to go through the complicated workflow. When you combine data with portability, AutoML can give you the flexibility you wont find with other AI technologies.

When AI is applied to how we develop applications, it will transform the way we used to manage the infrastructure. DevOps will be replaced by AIOps and it will enable your IT department staff to conduct precise root cause analysis.

Additionally, it will make it easy for you to find useful insights and patterns from huge data set in no time. Large scale enterprises and cloud vendors will benefit from the convergence of DevOps with AI.

One of the biggest challenges that AI developers will face when developing neural network models will be to select the best framework.