Upgrade & Secure Your Future with DevOps, SRE, DevSecOps, MLOps!

We spend hours on Instagram and YouTube and waste money on coffee and fast food, but won’t spend 30 minutes a day learning skills to boost our careers.
Master in DevOps, SRE, DevSecOps & MLOps!

Learn from Guru Rajesh Kumar and double your salary in just one year.

Get Started Now!

Smarter mobile chipsets key to democratization of Artificial Intelligence

Source – livemint.com

New Delhi: Artificial Intelligence (AI) may be a hot topic in tech circles, but its real benefits will be served when it has been truly democratized, making it available for each individuals. While we are not so distant from a personal AI butler, tech firms are already making efforts in that direction. The first and critical aspect of the rollout is deepening the AI integration to the core of mobile phones.

From Samsung Electronics Co., LG Electronics Inc., Huawei Technologies Co. Ltd to Xiaomi Inc., a number of old and new smartphone players are leveraging Artificial Intelligence in their newer phones in one way or another. And then, we have companies like Google (Alphabet Inc.) and Microsoft Corp., which are incorporating AI in their software to deliver smarter products like Google Photos and Windows OS. Besides, we now have Samsung’s Bixby, Microsoft’s Cortana to Amazon.com Inc.’s Alexa—virtual assistants that are a core part of modern mobile computing devices.

The most critical aspect of implementing Artificial Intelligence in your mobile devices is baking the technology into the chipsets.

Before launching widely acclaimed AI phones like Mate 10, Huawei introduced Kirin 970 processor in September last year. Touted as the world’s first mobile AI computing platform, Kirin 970 can use on-device AI to enhance users’ vision and hearing. “The core of the AI technology is the ability to process mass data. Traditional computing architectures centered on the CPU, GPU, and DSP are no longer sufficient to meet overwhelming demands for computing performance in the AI era,” Huawei explains on its website.

“On-device AI processing capabilities are especially important because smartphones need to process data in real time and at any time, while protecting users’ private data as effectively as possible. As a result, on-device performance is the greatest obstacle for further development of mobile AI technology.”

With more brands looking to integrate AI features into their phones, AI chipsets will become highly critical. While Huawei may have hogged the limelight for mobile AI chips, Qualcomm Technologies Inc. has been making giant strides in this direction as well.

Qualcomm is eyeing the next mobile computing frontier with advancements in hardware architectures like vector processing on Snapdragon Hexagon DSP. Qualcomm has been using on-device AI in last three-generations of its Snapdragon mobile chipsets.

Earlier this year, Qualcomm introduced the Qualcomm AI Engine, which comprises several hardware and software components to accelerate on-device, AI-enabled user experiences on select Qualcomm Snapdragon mobile platforms. The AI Engine is supported on Snapdragon 845, 835, 821, 820, 710 and 660 mobile platforms, as well as the recent QCS605 and XR1 platforms.

“Qualcomm is making AI chips more efficient through hardware architecture advancements on all Snapdragon cores and a large investment in software optimizations,” said Gary Brotman, director of product management, Qualcomm Technologies.

“In fact, through software alone, we have been able to improve AI performance across the Snapdragon SoC portfolio by more than 200% over the past year,” he said.

Apart from energy efficiency and user experience, mobile AI chips are also betting big on the security and privacy, a growing concern for modern computing devices.

“Qualcomm Technologies has a rich history of hardware based security on our mobile processors. We believe it is fundamental to our security strategy. We will continue to work with our partners as they begin to implement software security solutions that utilize AI,” said Gary.

Related Posts

What is AIOps?

AIOps, short for Artificial Intelligence for IT Operations, is a practice that combines artificial intelligence (AI) and machine learning (ML) technologies with traditional IT operations to enhance Read More

Read More

What is Natural Language Processing (NLP) tools?

Introduction to Natural Language Processing (NLP) Tools If you’ve ever asked Siri a question or talked to Alexa, you’ve used Natural Language Processing (NLP) tools. In essence, Read More

Read More

What are Emotion Detection Tools and Why Emotion Detection Tools are Important?

What are Emotion Detection Tools? Emotion detection tools are a type of technology that analyses human facial expressions, voice tone, and body language to determine the emotional Read More

Read More

What is Sentiment Analysis and what are the Types of Sentiment Analysis and its Important?

Introduction to Sentiment Analysis If you’re a business owner, marketer, or just someone who’s curious about what people think about your brand, then you’ve probably heard of Read More

Read More

What is Object Detection and Why is Object Detection Important?

Introduction to Object Detection Tools Object detection is the process of identifying and locating objects of interest in an image or video. Object detection tools are software Read More

Read More

What is Face Recognition and Why is Face Recognition Important?

Introduction to Face Recognition Tools We’ve all heard of facial recognition technology, but what exactly is it and why is it important? From unlocking your phone with Read More

Read More
Subscribe
Notify of
guest
3 Comments
Oldest
Newest Most Voted
Inline Feedbacks
View all comments
3
0
Would love your thoughts, please comment.x
()
x