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AI and ML have seen a rapid rise in the year that passed touching almost all different business verticals such as healthcare, agriculture, legal, manufacturing, automobile to name a few. With AI and AI enabled applications, spearheading the technological arena, big giants like Amazon, Apple, Facebook, Google, IBM and Microsoft are also investing in the research and development of AI technologies.
Looking out for the various developments in AI here are some trends to watch out for in 2019:
The speciality of AI is the use of processors. As AI performs tasks like complex computations using natural language processing, computer vision and speech recognition. AI can beat even the fastest and the most sophisticated CPU processors. This requires the use of specialised chips.
Tech giants like Google, Facebook and Amazon will spend much on the research and development of these specialized chips. Intel, Qualcomm and ARM will be involved in developing specialized chips that will make AI enabled applications to work faster. These chips will find applications in a number of industries that rely on AI applications to deliver intelligent solutions to their end users.
Query processing and predictive analytics are some of the areas where different business verticals would put these chips to extensive use.
IoT will utilize much of AI capability. Industrial IoT (IIoT) will lead the scenario in its use of AI to perform detection, predictive analysis and report generation of equipment.
There will be a decentralisation of intelligence which will be centered closer to your data and devices carrying out regular checks. Sophisticated Machine Learning models supported by neural networks will be running on the edge.
While developing a neural network, AI developers face the challenge of choosing the right framework, as the currently available tools are not easy to choose. This becomes a roadblock in the adoption of AI technologies.
Tech giants like Microsoft and Facebook are now into developing Open Neural Network Exchange (ONNX), which will help developers reuse these models on multiple frameworks.
Automated Machine Learning will help business analysts and developers through the development of Machine Learning Models. This will enable them to address different complex situations without going through the training models. It will help them focus on the solution rather than on the process of creating workflows.
They bridge the gap between cognitive APIs and custom ML models. It helps deliver on the perfect customisable level without going through tedious workflows. Besides, it is flexible and portable.
AI models are used more for predictive analysis. Applications are generating a lot of logs which are captured for searching and indexing. The data obtained from this can be collected for analytics and insights and with the applications of AI and ML can be used for predictive analysis. DevOps will be more intelligent in nature, making it more analytical in nature.
This will make AIOps become mainstream adoption in 2019 with enterprises benefiting from this convergence.
The popularity of Machine learning and artificial intelligence will make it the key trends of 2019. This will disrupt business applications with AI influencing the industrial segment.