Market Insight Details:
Machine learning is an integral part of computer science. It was originally derived from the study of pattern recognition & computational learning theory in artificial intelligence. In laymen terms, it is a segment of computer science that can provide a computer the ability to learn without the need for automated programs. Lately, the demand for this technology has risen owing to which the global machine learning market is gaining traction.
The main emphasis of this technology is on the development of computer programs that can access data and make appropriate use of it to self-learn. In such computers, the learning phase starts with assessments or data like examples, experience or instructions. Patterns are identified in all of these activities and stored for future use. Now the computer is adept enough to make decisions in future if the need arises. The main aim here is to let the computers to learn automatically without the requirement for technical intervention or guidance.
The global Machine Learning Market is poised for growth during the forecast period of 2018-2022. Last year i.e. in 2017, the evaluated value of the market was around USD 1.35 million. By the end of the forecast period the market is expected to earn USD 8.54 million. The market is anticipated to grow at a jaw-dropping CAGR of 43.9%.
There are a number of factors that drive the growth of the market. One of the major ones include machine learning’s versatility in terms of use. Its ability to learn & resolve real life issues just through stored data further adds to the growth of the market.
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The prominent players in the Machine Learning Market are – Google Inc. (U.S.), Facebook (U.S), ,IBM Watson (U.S.), Baidu (China), Apple (U.S), Microsoft (U.S.), Cisco(U.S.), Wipro(India), and Nuance Communications(U.S.) , Amazon (U.S) , Intel (U.S.).
Related/Latest/Industry News
December 2017, Apple commits ‘Turi Create’ machine learning development tool to GitHub. The company claims a new machine learning framework designed to help developers build machine learning models that can be parlayed into apps running on its major operating systems. Turi Create is designed to assist in the development and deployment of machine models, enabling the developers to add recommendations, object detection, image classification, image similarity or activity classification to their app, among other assets. This framework can be used to create a system that can recommend things based on its learning from the surrounding, image classification, image similarity, object detection, text classification and activity classification. All of these capabilities can enable many industries like automotive, media & entertainment and education to classify, implement and conclude things in a better way.
December, 2017, AI, Machine Learning to Be Used by Hackers in 2018: Symantec. Tech giant Symantec claims that cybercriminals will use the artificial intelligence and machine learning to explore weaker, victim networks. Additionally, the internet of things (IoT) devices will be hijacked and used in the distributed denial of service (DDos) attacks. The security tech giant also claimed that 2018 will see artificial intelligence vs. artificial intelligence in a cyber-security context, as in 2017, it had seen massive DDos attacks using hundreds of IoT devices across homes and offices. However, the advancement in machine learning is going to be a major driving factor for the growth of this market in terms of tackling with the security concerns by machines while adopting learning.
December, 2017, NVIDIA Introduces Titan V for Machine Learning Acceleration on the PC. In the past TITAN targeted gamers (TITAN X) or machine learning scientists (TITAN XP). NVIDIA, at the annual NIPS (Neural Information Processing Systems) conference announced the introduction of its new “TITAN V” PC GPU. TITAN V is targeted at machine learning scientists. TITAN V’s 21.1 billion transistors are capable of delivering 110 teraflops of performance. This immense amount of performance makes the TITAN V ideally suited for users looking to explore computational processing for scientific simulation and other deep learning/AI applications on their desktop PCs
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Innovations
One of the most recent and impressive technological innovation that the worldwide machine learning market has seen is the introduction of AlphaGo. It is a computer program that plays the board game Go. It was created using various facets of machine learning & artificial intelligence. It went on to become the first computer program to defeat a human player. This victory marks a milestone for the field of artificial intelligence.
Market Segmentation
The worldwide machine learning market has been divided into 5 distinct parts that include, applications, components, services, organization sizes & regions.
On the basis of applications, the market is divided into BSFI, automotive, healthcare & government.
On account of components, the market has been segmented into cloud, web-based APIs & software tools.
The services segment can be further bifurcated into professional services & managed services. Out of the two managed services section is estimated to grow tremendously over the forecast period. It is because managed service suppliers can look after all the hardware & software functions. With them all the organizations can be at peace as they only need to install & update applications.
The organizational sizes portion has been split into large enterprises & small & medium enterprises.
Geographically, the global market for machine learning is spread across North America, Europe, Asia Pacific & Rest of the World.
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