Arm at 30: Five Ideas Shaping Our Future
Invisibility, however, remains hard work. Improvements in CPUs, NPUs and GPUs will be required. AI processing will also have to shift to devices to save energy and cost, putting an emphasis on creative, elegant algorithms that minimize everything: storage, bandwidth, compute and power. We will also have to give consumers a much-needed sense of privacy and data autonomy: if we don’t give individuals a better way to control how AI impacts their lives, it could become the biggest roadblock of all.
“The ideas range from adding processors to memory cards to building customized memory instances with compute capability,” he adds. “We don’t know which will succeed, but as a concept, memory centric computing is inevitable.”
One estimate puts the number of batteries we’d need in a world of a trillion devices to be 913 million a day. As the IoT gets embedded into more everyday products, energy efficiency and device self-sufficiency become paramount concerns.
The smart label unfurled by Vodafone and Bayer is an early example of how broad-based IoT might work. The printed label collects information about itself—temperature, location, packing integrity—and then periodically sends it to a central tracking hub. Through precise system and network design, the label can provide updates for three years.
Arm’s Project Triffid takes it one step further. The experimental SoC harvests energy from RF beams to perform calculations and gather data. While not as computationally robust as the smart label, integrating computing capabilities into RFID tags can reduce the costs and management overhead of making things “smart” and therefore open the door to integrating intelligence into far more products. Imagine a shoe that offers consumers $5 for old shoes as part of an effort to achieve 100% recyclability.
Are you going to remember to fill in a form or send in the shoes? Not likely, but what if they created a system where you could drop your shoes in a recycling bin or at a retailer? Someone could flash the chip, confirm the purchase and credit $5 to the credit card account while also cloaking the buyer’s information with appropriate levels of security.
Lifetime, over-the-air support for devices will similarly become automated. “Over-the-air automated, secure upgrades will have to become the norm,” says Mark Hambleton, Arm’s Vice President of Software. “The smartphone experience, I believe, will become a template for other industries. Unlike the PC, the smartphone world didn’t go through a phase where it trusted users to do the right thing.”
Does this mean the end of human control over our world? Not really. Engineers will ultimately be working on the more complex tasks.
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Infrastructure 2021 predictions
AI 2021 predictions
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Client 2021 predictions
Auto 2021 predictions
Reference: Ecosystem Predictions & Perspectives
- Invisible AI Artificial intelligence (AI) and machine learning (ML) gain ground when their complexity gets pushed into the background. Over 1.5 billion people enjoy ML algorithms when they take smartphone pictures (or subsequently search for them in their ever-expanding photo files) generally without knowing it. The same phenomenon occurs whenever someone issues a command to one of the estimated 353 million smart speakers deployed worldwide. Invisibility works, according to Jem Davies, Vice President, Arm Fellow and GM of Arm’s Machine Learning Group.
Invisibility, however, remains hard work. Improvements in CPUs, NPUs and GPUs will be required. AI processing will also have to shift to devices to save energy and cost, putting an emphasis on creative, elegant algorithms that minimize everything: storage, bandwidth, compute and power. We will also have to give consumers a much-needed sense of privacy and data autonomy: if we don’t give individuals a better way to control how AI impacts their lives, it could become the biggest roadblock of all.
- Memory-centric computing architectures “The basic rationale for the many flavors of memory-centric compute—integrating CPUs and GPUs directly into memory devices, high speed interconnects inside 3D chiplets, etc.—is that moving data takes as much or more energy as computing,” says Arm Fellow Rob Aitken. “If you can keep the data where it is and move the compute to the memory, energy cost goes down.” Some have shown that 62.7 percent of total system energy gets spent moving data between main memory and compute.
“The ideas range from adding processors to memory cards to building customized memory instances with compute capability,” he adds. “We don’t know which will succeed, but as a concept, memory centric computing is inevitable.”
- Low-power to no-power Devices “For the Internet of Things (IoT) to achieve its full promise to society and become invisible, pervasive, and sustainable it needs to evolve beyond batteries,” says Arm Distinguished Engineer James Myers.
One estimate puts the number of batteries we’d need in a world of a trillion devices to be 913 million a day. As the IoT gets embedded into more everyday products, energy efficiency and device self-sufficiency become paramount concerns.
The smart label unfurled by Vodafone and Bayer is an early example of how broad-based IoT might work. The printed label collects information about itself—temperature, location, packing integrity—and then periodically sends it to a central tracking hub. Through precise system and network design, the label can provide updates for three years.
Arm’s Project Triffid takes it one step further. The experimental SoC harvests energy from RF beams to perform calculations and gather data. While not as computationally robust as the smart label, integrating computing capabilities into RFID tags can reduce the costs and management overhead of making things “smart” and therefore open the door to integrating intelligence into far more products. Imagine a shoe that offers consumers $5 for old shoes as part of an effort to achieve 100% recyclability.
Are you going to remember to fill in a form or send in the shoes? Not likely, but what if they created a system where you could drop your shoes in a recycling bin or at a retailer? Someone could flash the chip, confirm the purchase and credit $5 to the credit card account while also cloaking the buyer’s information with appropriate levels of security.
- Systems for our systems Our demand for software is outstripping traditional methods for developing it. IDC estimates 500 million apps and services will be developed by 2023 using cloud-native approaches, as many as were developed 40 years previously.
Lifetime, over-the-air support for devices will similarly become automated. “Over-the-air automated, secure upgrades will have to become the norm,” says Mark Hambleton, Arm’s Vice President of Software. “The smartphone experience, I believe, will become a template for other industries. Unlike the PC, the smartphone world didn’t go through a phase where it trusted users to do the right thing.”
Does this mean the end of human control over our world? Not really. Engineers will ultimately be working on the more complex tasks.
- Neural networks everywhere “We will see Neural Networks continue to replace classical computing methods across a range of industries. What started as fun tech for recognizing cats in pictures will have evolved into a technological juggernaut, completely transforming most industries. Consumer electronics, healthcare, law, communications, the automotive industry—all will be transformed as Neural Network technology marches forward, achieving things once thought impossible by machine,” writes Ian Bratt, Arm Fellow and Senior Director of Technology.
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Infrastructure 2021 predictions
- Infrastructure remains resilient Resilience is an issue that will come up a lot over the next 12 to 18 months as COVID-19 has stressed networks and computing in ways that could hardly be imagined. Yet, on the whole, the infrastructure has shown up very well. It remains one of the strongest growth markets in technology as more companies shift their workloads to the cloud and more individuals come to rely on videoconferencing and broadband to work, keep in touch and perform daily tasks like shopping or watching TV.
- Cost is key Cost considerations will be the biggest factor in moving applications to the cloud. In a recent survey Arm commissioned of its ecosystem partners, 49% of respondents viewed cost as the factor that could have the most important impact. This is closely followed by security considerations, with 48% of respondents viewing it as the most important consideration for customers.
- Edge and distributed cloud architecture on the rise With cities like Beijing and Amsterdam placing strict limits on data center construction, due to the space and power they require, the edge and a distributed cloud architecture will continue to increase in 2021. In a recent survey Arm commissioned of its ecosystem partners, 30% of respondents said that having a cloud-to-edge architecture was extremely important, whilst 43% said a distributed cloud architecture would be an important factor in their architectures.
- There will be an uptick in HPC in the cloud 56% of respondents to an Arm commissioned survey plan to increase adoption of HPC in the near future.
- Growing interest in cloud native We’ll see continued and growing interest in cloud native technologies like Kubernetes and containers, which provide both cloud providers and their customers a great degree of agility. Cloud native, along with industry standards for security and hardware, will become an elemental part of the fabric linking the cloud and the edge.
AI 2021 predictions
- Shift towards putting AI on edge or on endpoint over cloud We will see a shift towards edge computing, or resources placed closer to the devices accessing them, over cloud for most favoured infrastructure to access AI in 2021. In a recent survey Arm commissioned of its ecosystem partners, 30% of respondents said that having a cloud-to-edge architecture was extremely important, while 43% said a distributed cloud architecture would be an important factor in their architectures.
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Client 2021 predictions
- The new office Remote working during Covid-19 has changed the way we interact with our mobile devices. With masses of people thrown into home working environments, key productivity devices need to be available whenever and wherever they are needed. In our recent survey, nearly three quarters of respondents (72%) believe that the remote workforce is important for future designs. As part of these design evolutions, I believe we’ll see increased demand for laptops capable of all-day working as users look for devices that don’t need recharging after a few hours of Zoom calls.
- Staying connected Video conferencing has become a staple for not only the work environment but for family and friends keeping in touch during this pivotal year. With this in mind, video camera quality and technology will become increasingly important and consumers won’t compromise on this. 43% of respondents in our recent survey said they are interested in exploring new AI features inside camera technology during 2021. Expect better and better image quality from cameras with dedicated system on chips (SoCs) capable of AI-powered image correction in future generations of laptop-class devices, bringing an even more immersive experience to productivity devices.
Auto 2021 predictions
- The increasing need for heterogeneous compute To meet consumer demand for in-vehicle infotainment, ADAS and the other systems in cars, car manufacturers need to adopt not only a holistic approach to electronics design, but also heterogeneous compute approaches.
- Software drives hardware In our recent survey, self-driving cars was ranked first by 65% of respondents as the top area where they see potential for autonomous decision making. This demonstrates the need for heterogeneous compute: different applications like cameras, sensors, ML, CPUs and GPUs coming together, but with the flexibility that the software requires.
- Redefining functional safety Given the concept around functional safety was developed for vehicles that had limited or no autonomous features, the industry needs to reexamine the technology that underpins functional safety as the burden on automotive electronics rises. This is supported by a recent Arm-commissioned survey of its ecosystem partners, which revealed that functional safety is the most important factor for achieving success in autonomous computing, and the biggest impediment to the mass deployment of Level 4 vehicles.
- The mobile office In 2021, productivity will become more mobile as people return to the office and their daily commute. 57% of respondents to Arm’s ecosystem partner survey believe that working from the car will be a major draw for adoption of autonomous vehicles.
Reference: Ecosystem Predictions & Perspectives
