Published On : 11 Apr 2018
Artificial intelligence refers to a branch of computer science which comes with the aim of creating intelligent machines. At present times, it has become a significant part of the industry of technology. Various researches that are associated with the field of artificial intelligence are considered highly specialized and technical. At the core of the problems of artificial intelligence lie programming of computers for specific traits like ability to manipulate and move objects, knowledge, planning, problem solving, perception, learning, and reasoning.
Knowledge engineering has been the core area of artificial intelligence research. Machines that can frequently act and react as well like the humans only if they have substantial data pertaining to the world. Artificial intelligence must have gain access to various relations, properties, objects, and categories between all of them so as to implement knowledge engineering. Making an initiation of problem-solving power, reasoning, and common sense in machines is a tedious and difficult approach.
Semiconductor Industry to be Revolutionized Like Never Before
In the recent years, however, with the development and emergence of many different technologies, artificial intelligence has become a reality and the same is influencing many businesses and lives alike. In addition to that, the evolution of many other supplementary technologies like cognitive computing, machine learning, and cloud computing is collectively making way for the growth of the market for artificial intelligence. A few of the eminent market players in the artificial intelligence market in the recent times comprise names such as NVIDIA Corporation, Amazon.com, Inc., Intel Corporation, Microsoft Corporation, Baidu, Inc.. and Google Inc.
Machine learning algorithms frequently comprise matrix operations. These calculations are benefitted sufficiently from parallel computing, which results in model training which is performed on graphics cards as opposed to CPU only. The major kinds of chipset which have been considered as artificial intelligence or AI chipsets for various AI applications are as follows:
CPU & GPU: Before the year 2001, general computing tasks were executed by CPU and graphical computation was done by GPU. The need for faster and more efficient matrix factorization and multiplication techniques have resulted in the creation of various programming languages that enable general-purpose computing on GPUs, comprising CUDA and OpenCL.
GPU: Various major manufacturers such as Nvidia Corporation are looking to address the issue of consumption of high power by various devices whilst solving complex machine learning algorithms and programs on the basis of priority.
FPGA: FPGAs refers to integrated circuits whose logic blocks can be reconfigured and programmed using a hardware description language (HDL). A series of FPGA-based mining systems provided increase in throughput performance as well as energy efficiency. The cost of electricity has created a break-even, thereby favoring low-power systems.
ASIC: The need for statistical inference and deep learning is further driving the industry of hardware toward Machine Learning (ML) which is a specialized hardware.
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