Smart Artificial Intelligence (AI) Chips
Smart Artificial Intelligence (AI) Chips

With the availability of enormous amount of data and vast scalability of cloud-based compute power, artificial intelligence has become a huge trend across industries in these past few years. In today’s digital world, information is the key for enterprises to be successful and to maintain sustainable growth. Most industries especially service sector rely deeply on analytics to provide them with useful business insights and enable them to remain competitive in the market. Enterprises have been continuously automating their business processes that were earlier conducted either programmatically or manually. With advancements in AI chips and introduction of application-specific custom chips, enterprises now have the capability to collect real-time analytics and to transform their data into actionable insights. There are numerous use cases available in the market of AI being successfully implemented across industry verticals.

What is AI?
The term, artificial intelligence (AI), came into existence owing to the need for performing various statistics and logic in real time. AI is the simulation of human intelligence processes by machines, especially computer systems. It is used for various purposes, including identification, calculation, control, design, surveillance, and diagnosis.
Why do we need smart AI chips?
AI chips help in making more intelligent decisions about some critical issue in absence of humans. These AI chips usually involve machine learning and deep learning algorithms to perform computations. The chip is designed with high parallel calculations to commercial hardware, mainly graphics processing units (GPUs). The AI chips accept input in the form of machine language (ML) and process this input with cloud data. The resultant data is stored on devices. AI chips are as smart as computers, robots, or software that work the same as humans think and use their logical and computational methods intelligently.
Most of the chip makers have been focusing on developing new solutions for smart AI chips and investing to have their impact in the competitive market. This gained the interest of small-scale companies and startups for development of smart AI chips.
How a smart AI chip works?
AI has natural language processing, which makes it capable of interpreting what you speak or type. Much of the processing in an AI chip involves matrix multiplication and addition. Large numbers of GPUs working in parallel offer an inexpensive approach, but the penalty is the higher power. When a question is asked, AI uses algorithms and machine learning to search through the huge database and delivers the best answer in a matter of seconds.
Consider the following figure that shows the working of smart AI chips. A person asks a question to the smart AI chip, which processes that question as input data to perform the task. The smart AI chip then uses its intelligence by performing natural language processing to convert the human language to machine language. It, then, performs certain calculations and uses logic, methods, or cloud data to get the required answer. The obtained result is then converted back to human-understandable language. This process is done within an eye blink, and hence, they are called as smart AI chips.

How smart is an AI chip?
The fusion of cloud and AI is a source of innovation and a means to accelerate change. The smart AI chip carries out a multitude of functions, which provide information about products, company, people, current updates, and others. It answers a wide array of questions and responds to them using its intelligence. Smart AI chips are used in devices for performing tasks, such as recognizing your voice commands, faces in photos, and human voices interaction; for example, if we ask, “how much traffic is there on route to office?”, the smart AI chip uses a real-time location tracer and answers the question. The top giant companies, such as Google and Amazon, have been working to provide products based on smart AI chips.
To become a leader in the AI technology, the top tech giants started investing in this field. The AI systems are made of software and hardware that work in parallel to support the calculations. This generated the need to develop their own AI chips for supporting their AI development. These chipsets have grown smaller and more sophisticated; for example, Google has designed an application-specific integrated circuit (ASIC) that handles complex processes. This chip is known as the tensor processing unit (TPU). It has an instruction set, so as TensorFlow programs are changed or new algorithms are developed, they can run on the TPU. This reduced its dependence on hardware makers. In consequence, the demand for specialized AI chips has been growing rapidly.
New approaches for smart AI chips
The AI chip market witnessed an increase in the adoption of this technology especially in the developing countries. The adoption of innovative techniques provides end users with advanced and innovated product offerings. The organizations have adopted strategies, such as cooperation, collaboration, product launch, partnership, R&D, and accession, to expand their geographical presence and increase their market share.
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