Machine Learning Chip: Smart Strategies of the Research and Development Process

Machine learning is a branch of artificial intelligence that enables machine to develop the ability for self-learning and adaption through experience without being explicitly programmed. It is considered as a method of data analysis that automates analytical model building. Machine learning has been present from decades but not been widely used due to lack of big data it requires for processing. Over the last several decades, enterprises have been dependent greatly on analytics to provide them with competitive advantage and enable them to be more effective. But, enterprises now want real time analytics and the capability to transform data into actionable insight. This has steered the development of machine learning chip.

The rising complex and large dataset has steered the need for artificial intelligence solutions has majorly driven the machine learning chip market. Further, declining hardware cost has supplemented the demand for machine learning chip across diverse verticals. However, lack of skilled workforce is hindering the growth of the market.

Machine learning is a sub-set of artificial intelligence which performs tasks related to AI. It is currently being adopted by several industries around the world. This technology uses algorithms and computational methods to teach computers to think the way humans and animals may react in a particular situation. The performance of this machine learning algorithm can be improved by increasing the number of trials.

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The key players influencing the machine learning chip market are Alphabet Inc., Advanced Micro Devices, Inc., Amazon.com, Inc., Baidu Inc., Bitmain Technologies Ltd., Intel Corporation, Nvidia Corporation, Samsung Electronics Co Ltd., Qualcomm Incorporated, Xilinx

The trend in artificial intelligence (AI), use of machine learning in numerous applications, and emergence of quantum computing are the factors which increase the demand for machine learning chip market. In addition, the development of autonomous robots that control themselves without human intervention is anticipated to provide potential growth opportunities for the market. However, dearth of skilled workforce and AI phobia are the major restraints of the market. Moreover, increase in demand for smart homes & cities, increase in efforts to make more human-like robots, and popularity of IoT across the globe are expected to create tremendous opportunities for the market expansion.

Trending Artificial Intelligence (AI)

AI encompasses machine learning, robotics, and collaborative systems. AI requires a machine learning chip to accelerate the system without human intervention. Moreover, the emergence of AI technology in several applications that range from chatbots to autonomous cars fuels the machine learning chip market. In addition, key players operating in the market are developing a new computing model that uses parallel processors to accelerate computing through advanced chips. For instance, NVIDIA unveiled a palm-sized, energy-efficient AI computer, DRIVE PX 2, which is powered by the company's newest system-on-chip, based on the NVIDIA Pascal architecture.

Growth in Number of Machine Learning Applications

A machine learning chip is applied across media & advertising, manufacturing, finance, healthcare, automotive & transportation, law, electronic industry, and other sectors. The adoption of machine learning technology is expected to be higher in future, as machine learning algorithms are projected to be used to prevent payment frauds and cyberterrorism. Furthermore, machine learning chips are expected to affect healthcare advancements and lead to more accurate treatments and prevention of medical conditions.

Emergence of Quantum Computing

Quantum computers take only a few seconds to complete a calculation that can otherwise take thousands of years. For instance, Google has a quantum computer that is 100 million times faster than today’s computing systems. Quantum computers are an innovative transformation of artificial intelligence, big data, and machine learning. Thus, emergence of quantum computing fuels the growth of the machine learning chip market.

Dearth of Skilled Workforce

Machine learning chips consist of complex algorithms for its development. In addition, management of machine learning and automated systems is difficult at times. This requires exceptional software engineering skills and experience to deal with distributed and concurrent programming or debugging with communication protocols.

AI Phobia

AI is cheaper and more productive than people. In addition, it can work around the clock and quickly learn new skills to avoid mistakes. Furthermore, at the web summit in Portugal, humanoid robot Sophia said such features of AI are expected to replace the jobs of underwriters, office clerks, attorneys, receptionists, and creatives. Advances in machine learning chip allow AI to learn without humans. For Instance, on PolicyBazaar.com, almost 70% of all motor insurance policies are sold by robots. Also, the CEO of Google Sundar Pichai announced that most of the repetitive jobs are expected to be taken by AI in coming years, which is anticipated to hinder the growth of the machine learning chip market.

Increase in Demand for Smart Homes & Smart Cities

Machine learning chip can initiate smart city programs in the developing countries, such as India, China, and more. The tools and technologies already have an inbuilt machine learning chip that possess a huge potential to promote interconnected digital homes and smart cities.