Current technology trends in the Global Machine Learning Market

As businesses get bigger, the data that they’re likely to process will be larger too and machine learning is a technology that appears to be the best way to handle that data. Simultaneously, the new development being made in AI, algorithms, and data models are the other reasons why the Global Machine learning Market Size will grow to a value of USD 13.5 Bn by 2023.

In any market, growth is usually followed by the creation of trends and while AI might’ve been ‘created’ in 1955, big developments have only taken place recently in the last decades. So far, the Global Machine Learning Market, software engineers have managed to master AI in its applied form, using ML to build solutions that work on problem-solving, reasoning tasks specific to certain domains. 

• Recognizing text and speech using natural language processing and programs computers to analyze how humans speak, helping to foster the interactions humans have with their devices. Popular examples include Apple’s Siri, Amazon’s Alexa, Samsung’s Bixby and Microsoft’s Cortana.  
• Helping computers to visualize or ‘see’ images so that it can process them further or identify what is in front of it. Examples here include image restoration for photo editing, facial recognition for face unlock security patterns in mobiles and motion analysis for using gestures also in mobiles.   
• Assisting cars when they drive themselves even though autonomous vehicles aren’t exactly big or very favorable with consumers. They aren’t on roads yet as companies still have to perfect their ML mechanisms, but the fact that manufacturers have made so much process is amazing. One con here is that such cars require very complex internals comprising of voice search, deep learning, and image & speech recognition and motion detection.
• The Global Machine learning Market Size has increased largely due to the product recommendation systems utilized by many online retailers. These applications are huge because they are simple in nature and easy to use with the ML algorithms to guess what the shopper will do next.