With one of the strongest processor ecosystems in the industry, arm's role to accelerate the adoption of machine learning (ML) at the edge can't be overemphasized, and its effort to enhance its CPU performance and software support for ML workloads is now in full swing.3 cognitive learning styles according to jem davies, arm fellow, VP and GM, machine learning group, the market outlook, challenges, and arm's overall strategy to address the huge opportunity are clearly disclosed.3 cognitive learning styles

For example, the use cases come from the embedded and iot spaces, such as life improving medical devices like smart asthma inhalers, through to industrial sorting and robotics to voice assistants, more intelligent home security and even things like dtvs where there is a lot of activity in super scaling, scene recognition and picture quality enhancement and gesture recognition.3 cognitive learning styles

Of course, there are some of the more interesting ones, including the well covered autonomous vehicle and driver assistance; in smartphone a huge range of applications are implementing ML improvements like smarter games engines, richer social media applications, and even utility applications built directly into the OS like predictive text and voice assistants.3 cognitive learning styles

"From an arm perspective, the thirst for ML in edge devices is just beginning and we expect it to continue growing substantially for several years yet," he said. "The use cases are still growing rapidly and we expect an explosion of creativity over the next couple years as the algorithms become more understood and smaller and the developer community really engages with what ML can bring."

3 cognitive learning styles

"Two years ago or even a year ago, it wasn't uncommon for people to think that if you wanted to do any ML on a device, you needed to have an ML dedicated processor - a view fuelled by people with dedicated processors to sell - and so we would get asked which processor was best for ML a lot.3 cognitive learning styles it depends on what is important to you. So we've spent a lot of time explaining when a small CPU, large CPU, multi-processor CPU, GPU or ML processor would best meet people's needs."

3 cognitive learning styles

"You can see this in the cpus we have been releasing the last couple years which have had major performance improvements specifically targeted at ML workloads.3 cognitive learning styles often these are 4x or even 10x on generation improvements. This also extends to our latest gpus and even our efficient cortex-M family where we recently released our helium extensions specifically supporting 15 times improved ML performance in microcontrollers."

3 cognitive learning styles

"So arm is focused on offering a huge range of 'processors' that can give customers a vast range of price, performance and power trade-offs.3 cognitive learning styles we will be extending that further through 2019 with a range of complementary ML processors for all markets given the market options where heavy ML workloads are needed or ML power efficiency is critical."

3 cognitive learning styles

He explained that arm's strategy has been to add capabilities to its CPU and GPU architectures to support ML for some years now. And the company has launched a range of scalable and extensible npus (neural processing units) to provide more efficient ML processing in a range of market segments with performance requirements such as in automotive, right down to the tiniest low-power embedded microcontrollers.3 cognitive learning styles

"We recently launched a survey to measure where ML processing is being performed, and the most popular was the arm cortex CPU architecture, followed by the arm mali GPU architecture," he said. "That's a huge advantage for us - it gives us great connections to developers who can then tell us what they need us to develop in terms of software libraries, compilers, development tools etc and what they will want to do themselves."

3 cognitive learning styles

He explained that project trillium, which covers all of arm's ML activities, is arm's and third-party hardware IP and software running ML workloads and applications.3 cognitive learning styles within it are CPU and GPU improvements started many years ago in research, a broad range of complementary current and future ML processors software to enable ML on arm, tools, ecosystem and a ramping amount of educational material.3 cognitive learning styles

With one of the strongest processor ecosystems in the industry, arm's role to accelerate the adoption of machine learning (ML) at the edge can't be overemphasized, and its effort to enhance its CPU performance and software support for ML workloads is now in full swing.3 cognitive learning styles according to jem davies, arm fellow, VP and GM, machine learning group, the market outlook, challenges, and arm's overall strategy to address the huge opportunity are clearly disclosed.3 cognitive learning styles

For example, the use cases come from the embedded and iot spaces, such as life improving medical devices like smart asthma inhalers, through to industrial sorting and robotics to voice assistants, more intelligent home security and even things like dtvs where there is a lot of activity in super scaling, scene recognition and picture quality enhancement and gesture recognition.3 cognitive learning styles

Of course, there are some of the more interesting ones, including the well covered autonomous vehicle and driver assistance; in smartphone a huge range of applications are implementing ML improvements like smarter games engines, richer social media applications, and even utility applications built directly into the OS like predictive text and voice assistants.3 cognitive learning styles

"From an arm perspective, the thirst for ML in edge devices is just beginning and we expect it to continue growing substantially for several years yet," he said. "The use cases are still growing rapidly and we expect an explosion of creativity over the next couple years as the algorithms become more understood and smaller and the developer community really engages with what ML can bring."

3 cognitive learning styles

"Two years ago or even a year ago, it wasn't uncommon for people to think that if you wanted to do any ML on a device, you needed to have an ML dedicated processor - a view fuelled by people with dedicated processors to sell - and so we would get asked which processor was best for ML a lot.3 cognitive learning styles it depends on what is important to you. So we've spent a lot of time explaining when a small CPU, large CPU, multi-processor CPU, GPU or ML processor would best meet people's needs."

3 cognitive learning styles

"You can see this in the cpus we have been releasing the last couple years which have had major performance improvements specifically targeted at ML workloads.3 cognitive learning styles often these are 4x or even 10x on generation improvements. This also extends to our latest gpus and even our efficient cortex-M family where we recently released our helium extensions specifically supporting 15 times improved ML performance in microcontrollers."

3 cognitive learning styles

"So arm is focused on offering a huge range of 'processors' that can give customers a vast range of price, performance and power trade-offs.3 cognitive learning styles we will be extending that further through 2019 with a range of complementary ML processors for all markets given the market options where heavy ML workloads are needed or ML power efficiency is critical."

3 cognitive learning styles

He explained that arm's strategy has been to add capabilities to its CPU and GPU architectures to support ML for some years now. And the company has launched a range of scalable and extensible npus (neural processing units) to provide more efficient ML processing in a range of market segments with performance requirements such as in automotive, right down to the tiniest low-power embedded microcontrollers.3 cognitive learning styles

"We recently launched a survey to measure where ML processing is being performed, and the most popular was the arm cortex CPU architecture, followed by the arm mali GPU architecture," he said. "That's a huge advantage for us - it gives us great connections to developers who can then tell us what they need us to develop in terms of software libraries, compilers, development tools etc and what they will want to do themselves."

3 cognitive learning styles

He explained that project trillium, which covers all of arm's ML activities, is arm's and third-party hardware IP and software running ML workloads and applications.3 cognitive learning styles within it are CPU and GPU improvements started many years ago in research, a broad range of complementary current and future ML processors software to enable ML on arm, tools, ecosystem and a ramping amount of educational material.3 cognitive learning styles