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Top Trends In Artificial Intelligence 2018

According to Gartner's report, Machine learning and AI is going to rule in 2018. Now we are in the world of AI and every company is going to increase their business through this technology. As this will help in understanding the user behaviour and providing more focused results to the customer.

The emotion over Artificial Intelligence (AI) is euphoric. Corporations like Google, Microsoft, Amazon, and Alibaba are pushing the frontlines as their main role is to provide best results to the customer. There are a surplus of smaller players that are doing cutting-edge work in a niche area. AI is flooding into everyday lives.

Firstly, let's get the context of AI correct.

AI includes the listed below attributes:

  • Machine Learning (subset of AI)
  • Deep Learning (subset of Machine Learning)

Trend #1: Machine Learning to Automate Machine Learning:

Generally the ML procedure includes the following phases:

We knows that a data scientist devotes a lot of time in understanding the data. Data scientist works on the different models and select the one that is going to deliver the effective results. So this procedure takes more time.

Now the role of Automate ML comes into play. This technique is going to automate the process of implementing exploratory testing analysis. And ML is going to handle the procedure of finding hidden patterns. And multiple algorithms can be executed very quickly. So it means this is going to save a lot of data scientist time. Earlier data scientist spends lot of time in model building rather than focussing on evaluation, so this lacks the algorithm preciseness.

Automated AI and ML is also a benefit for non-data scientists as it is going to help them to build effective machine learning models without diving into the mathematics of data science.

In 2018, this trend is going to be the mainstream, Google recently releases AutoML in their cloud computing platform. There are niche corporations like Data Robot who specialize major in this section and are becoming mainstream.

Trend #2: Increase in Cloud Adoption for Machine Learning

ML is the process of analysing, maintaining and storing the data in the right direction and effectively. For AI project cloud computing is the perfect platform to work on. Cloud computing is not a new concept. Previously, clod computing is limited to IaaS only but now many cloud servers now started delivering the Machine learning as a Service. And this trend is going to upscale in 2018 and the cost of clod computing and storage is lower and on demand.

Its very easy for data scientist to work with cloud servers as they can easily signup there, implement the analysis, work with model and then shut it down. Machine learning in the cloud makes the life of a data scientist easier.

Trend #3: Deep Learning Becomes Mainstream

Deep learning is generally the subset of machine learning that works with neural network based algorithms for ML tasks. Deep learning methods have proven to be very useful in the field of computer vision, natural language processing, and speech recognition. There is data now so there is computing process and Deep learning has never been so enthusiastic as compared to previous records.

Trend #4: AI Regulation Discussion Gains Traction

In 2017, data science community avidly followed the debate between Elon Musk and Mark Zuckerberg. The topic of the debate: Should we fear the rise of AI? Elon Musk had a pessimistic view on the topic. His views: the rise of AI has imminent dangers for humanity. On the other hand, Mark Zuckerberg, had a much more optimistic outlook on the topic. His views: AI would benefit humans.

Artificial intelligence (AI) is making significant waves across the globe, with experts predicting that it will increasingly change and reshape the way people live their daily lives. AI is also likely to shake up the legal industry; triggering a profound shift in the delivery of legal services.

You can also follow this blog related to artificial testing services. 

About The Author: 

I work as a Senior Testing Specialist at TestingXperts. I handled day-to-day operations for all aspects of software testing.  With over 7 years of professional experience I know how to build strong connection with the clients and testing capability. Testing plays an important role in the development of new IT programmes and many every day products, like cars and electronic goods.

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