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4 Popular FPGA Applications for 2017

Posted by Nadeesha Thewarapperuma

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Apr 20, 2017 9:51:54 AM

FPGA is used in ADAS vehichles

 

FPGA are taking the tech world by storm. Two years ago, Intel made the move to take over Altera, one of the dominating FPGA manufacturers in the world. Based on the $16.7 billion bet that Intel placed on Altera, we're taking a look at some of the hottest FPGA applications for the current year.

 

FPGA Infographic: 4 Popular Applications

 

4) Instant voice translations will happen on your phone.

Gone are the days of Rosetta Stone - the product that pledged you can learn any language as long as you take the time to do it. Today's tourists can rely on a simple app on their phone. Speak any phrase into your phone and have your phone translate whatever it is you want to say, making travel a breeze for any tourist in the digital age. Both the iPhone 7 and Samsung's Galaxy S5 phone from 2014 were the first in their lineage to sport an on board FPGA.

 

3) FPGA use in healthcare will continue to grow.

Smart machines will be used in several healthcare applications, including diagnosis, patient monitoring and clinical trials. While patients may be concerned over the idea of a robot replacing an actual doctor, think of AI in the healthcare field as an enhancement, not necessarily a replacement. AI will take care of some of the less-skilled tasks, including laboratory tests. Plus AI will function as a valid second opinion, saving patients both time and money.

 

2) Artificial Intelligence will continue to develop.

We're in the beginning stages of artificial intelligence, and there's still a long way to go, but the exciting factor is that a number of companies are showing interest in developing AI for a variety of fields. AI will be a predominant factor in healthcare. Once patient trust reaches a certain threshold, the idea of using AI to diagnose and treat patients will be universally accepted. And then there are autonomous vehicles. AI will be a major factor in making sure cars can navigate by themselves. Collected data in deep neural networks allows AI to correctly assess the environmental inputs and make the correct decision.

 

1) Autonomous vehicles will take to the road.

At this point, there are a number of companies that are interested in gaining the lead in the autonomous vehicle market. BMW, Nvidia, Google, Tesla and Intel are some of the leading players in the market. Whomever makes the first breakthrough stands to gain the most. Companies are now testing out their ADAS system, determining how the autonomous system reacts to outside stimuli. To address graphics processing, safety requirements, real-time control of the vehicle, video encoding, and connectivity in next-gen automotive and ADAS systems like this, designers often utilize SDSoC™ development environments and heterogeneous processing of Zynq® UltraScale+™ MPSoC devices.

 

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Sources used:

https://www.theregister.co.uk/2017/03/21/whats_next_in_ai/

Topics: FPGA, artificial intelligence, ADAS, Autonomous Driving

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