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Who will go into mass production first for AI ASICs?

Artificial intelligence (AI) and deep learning have generated lot of excitement over the past few years. Many semiconductor startups have emerged to build chipsets optimized for AI. They are tackling compute, communication, and memory-related problems specific to AI algorithm accelerations and building highly optimized architectures that promise low power and high performance. Nervana was perhaps the first company to build a chipset specifically for AI, which got started in 2014. Nervana wanted to sell cloud services based on its chipsets and…

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Is AI the best news for semiconductors since microprocessor days?

The microprocessor chip acts as the brain of any computer system, whether the device is used for the Internet of Things (IoT), consumers, or the cloud. In fact, the semiconductor industry owes its success to Intel’s introduction of its 4004 microprocessor back in the 1970s. That later evolved into the 808X series, which led to the widespread adoption of chips. Even today, microprocessors receive more media coverage than any other type of chipset. Microprocessors are still the single most expensive semiconductor component in terms…

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ASICs for deep learning are not exactly ASICs

The term “application specific integrated circuit” (ASIC) became popular in the 1990s when such chips promised to bring down the cost per chip for a given application, such as mobile phones or Ethernet cards. An ASIC, by definition, meant developing hardware to solve a problem by building gates to emulate the logic. These chips offered little programmability, but provided maximum performance at a given power and cost budget. It is hard to trace the origins of the word ASIC and…

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Will video analytics save retail market?

The world of computer vision has continued to evolve in recent years with computer surpassing the accuracy of human being. Computer vision has enabled many applications that were only part of science fiction a short time ago. The rise of AI has been instrumental to get to the level of accuracy that market demands. A new application enabled for computer vision called video analytics, has emerged in recent years. Video analytics deals with extraction of data from incoming video and…

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Is Nvidia moving towards AI chipset world Domination

Nvidia, by all accounts is the de-facto standard in AI chipsets today. In addition to being a chipset manufacturer, Nvidia has been able to offer additional value to their customers by creating derivative products and solution based on their chipsets. This has helped Nvidia to not only understand customer pain points but become wall street’s darling by creating additional value. Tractica has been following the AI chipset market for some time. We believe that by the end of 2025, the…

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Intel is going ‘all-in’ to dominate AI chipset world

AI revolution, started in 2012 when neural network Alexnet surpassed accuracy of all previous classic computer vision techniques and has not looked back since. The AI algorithms are compute sensitive by nature and the need for accelerating AI algorithms in hardware has long been recognized with over 100 companies jumping in with their chipsets. Intel is currently locked in battle with Nvidia to become world’s dominant AI chipset company. While Nvidia’s focus in on discrete GPUs for AI acceleration, Intel…

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Power limitations will force AI chip makers to look into alternate architectures for AI acceleration

The increasing complexity of AI algorithms posed has given rise to a new industry of AI chipsets. In the past two years, all the top semiconductor companies along with cloud companies as well as startups have jumped in to build chipsets. By Tractica’s own estimates, there are over 100 design starts with more being announced every day and companies coming into existence. The use cases for AI applications are quite widespread and they vary from ultra low power IoT devices…

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Nvidia is moving faster than the competition in AI chipset industry

Since 2015, more than seventy companies have entered the AI chipset market with more than 100 chip starts announced. All of them are trying to tackle the AI algorithm acceleration problem using different techniques. These companies range from cloud companies to top semiconductor companies to start ups.  Intel for instance has poured billions of dollars into AI via acquisition of Altera and Mobileye. Many start-ups have raised capital exceeding $100 million. For instance, Wave Computing, Campbell based company, recently announced…

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AI chip companies continue to raise more capital

Note: This was published on Tractica web site in 2018. High mask costs made it hard for chipset start-ups to raise capital during early 2000s. Today mask costs can range up to 25 million dollars and by some estimates the design costs for a chip at 12nm node can run as high as $174 million. This made it hard for investors to justify ROI as most of them demanded 10X return. Only a few markets offered high volume for chipsets…

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New architectures emerge in AI chipset race

As AI chipset market is getting crowded, many AI companies have started creating  solutions that caters to a niche market. The needs for chipset power, performance, software etc. vary greatly depending on the nature of application. For instance IoT edge market needs ultra low power (in milliwatts), mobile phones can work well with power consumption of up to 1W, drones can consume a bit more, automotive can go from 10-30W and so on. Today two most prominent architectures are CPU…

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