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 continues 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. With dozens of AI tools available in the market, choosing the best AI tool might not be as easy as it used to be.
The lack of integration and compatibility among different neural network toolkits is hampering AI adoption. Tech giants such as Microsoft and Facebook are already working on developing an Open Neural Network Exchange (ONNX). This will let developers reuse neural network models across multiple frameworks.
The demand for specialized systems will grow exponentially in 2019. Organization have limited data at their disposal but what they want is specialized data.
This will force businesses to acquire tools that can help them generate high quality AI data internally. The focus will shift from quantity of data to quality of data in 2019. This will lay the foundation for AI that could work in real world situations. Companies will look towards specialized AI solution providers who have access to key data sources and could help them make sense out of their unstructured data.
Even though, Artificial Intelligence have transformed every industry you can think of but there is still shortage of talent who have AI skills in abundance. Pat Calhoun, CEO of Espressive said, “Most organizations want to embrace AI as part of their digital transformation but do not have the developers, AI experts, and linguists to develop their own or to even train the engines of pre-built solutions to deliver on the promise.”
Rahul Kashyap, CEO of Awake Security added, “With so many ‘AI-powered’ solutions available to address a myriad of business concerns, it’s time enterprises get smarter about what’s happening within the ‘black box’ of their AI solutions.” He continues, “The way in which Artificial Intelligence algorithms are trained, structured, or informed can lead to significant differences in output. The right equation for one company won’t be the right equation for another.”
Just like a coin which has two sides, AI also has a positive side and a negative side to it. IT security professionals will use AI to detect malicious activities quickly. You can be able to reduce false positives by 90% with the help of AI driven response and machine learning algorithms. AI will land into wrong hands and cyber criminals with malicious designs will abuse it to fulfill their motives. With automation, armies of cyber attackers can launch lethal attacks with greater success. This will force enterprises to fight fire with fire and invest in AI powered security solutions capable of protecting them from such AI driven attacks.
In 2019, AI will be everywhere. From web applications to health care systems, airline to hotel booking systems and beyond, we will see shades of AI everywhere and it will be at the forefront of digital transformation.
Dr. Tung Bui, Chairman of IT department and professor at University of Hawaii said, “Unlike most of the predictions and discussions about how autonomous vehicles and robots will eventually affect the job market — this is true but will take time due to institutional, political, and social reasons — I contend that the biggest trend in AI will be an acceleration in the digital transformation, making existing business systems smarter.”
Original Source of this Article: Tech Science Hub