Samsung aims to boost on-device AI with LPDDR5X DRAM

Ryan Daws — Wed, 17 Apr 2024 15:14:35 +0000

Samsung has unveiled the industry’s first LPDDR5X DRAM with speeds of up to 10.7 Gbps, setting a new benchmark for the industry.

Achieved through the use of cutting-edge 12 nanometer (nm)-class process technology, Samsung has not only attained the highest performance metrics but also the smallest chip size among existing low-power double data rate (LPDDR) offerings.

YongCheol Bae, Executive VP of Memory Product Planning at Samsung, commented: “As demand for low-power, high-performance memory increases, LPDDR DRAM is expected to expand its applications from mainly mobile to other areas that traditionally require higher performance and reliability such as PCs, accelerators, servers, and automobiles.”

Bae further assured that Samsung is committed to continuing its innovation trajectory, focusing on delivering products tailored for the forthcoming on-device AI era through strategic collaborations with partners.

On-device AI capabilities are increasingly becoming a pivotal consideration. This shift accentuates the necessity for memory solutions like LPDDR that are both low in power consumption and high in performance.

The new 10.7Gbps LPDDR5X from Samsung not only offers a performance boost of over 25 percent and a capacity increase of more than 30 percent compared to its predecessor, but also caters to the evolving demands of on-device AI with its optimal solution for high-capacity, high-performance, and energy-efficient memory requirements. Mobile DRAM single package capacity has been expanded up to 32 gigabytes, marking a significant milestone for mobile and on-device AI applications.

Furthermore, the LPDDR5X incorporates advanced power-saving technologies, including optimised power variation that dynamically adjusts energy usage according to the workload and expanded low-power mode intervals to facilitate extended energy-saving periods. These enhancements collectively improve power efficiency by 25 percent over the previous generation, enabling not only longer battery life for mobile devices but also reduced energy consumption for servers, thereby lowering the total cost of ownership.

Samsung anticipates the commencement of mass production of the 10.7Gbps LPDDR5X by H2 2024, following comprehensive verification processes with mobile application processor (AP) and mobile device manufacturers.

(Image Credit: Samsung)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Samsung aims to boost on-device AI with LPDDR5X DRAM appeared first on AI News.

AI & Big Data Expo: Unlocking the potential of AI on edge devices

Ryan Daws — Fri, 15 Dec 2023 17:55:42 +0000

In an interview at AI & Big Data Expo, Alessandro Grande, Head of Product at Edge Impulse, discussed issues around developing machine learning models for resource-constrained edge devices and how to overcome them.

During the discussion, Grande provided insightful perspectives on the current challenges, how Edge Impulse is helping address these struggles, and the tremendous promise of on-device AI.

Key hurdles with edge AI adoption

Grande highlighted three primary pain points companies face when attempting to productise edge machine learning models, including difficulties determining optimal data collection strategies, scarce AI expertise, and cross-disciplinary communication barriers between hardware, firmware, and data science teams.

“A lot of the companies building edge devices are not very familiar with machine learning,” says Grande. “Bringing those two worlds together is the third challenge, really, around having teams communicate with each other and being able to share knowledge and work towards the same goals.”

Strategies for lean and efficient models

When asked how to optimise for edge environments, Grande emphasised first minimising required sensor data.

“We are seeing a lot of companies struggle with the dataset. What data is enough, what data should they collect, what data from which sensors should they collect the data from. And that’s a big struggle,” explains Grande.

Selecting efficient neural network architectures helps, as does compression techniques like quantisation to reduce precision without substantially impacting accuracy. Always balance sensor and hardware constraints against functionality, connectivity needs, and software requirements.

Edge Impulse aims to enable engineers to validate and verify models themselves pre-deployment using common ML evaluation metrics, ensuring reliability while accelerating time-to-value. The end-to-end development platform seamlessly integrates with all major cloud and ML platforms.

Transformative potential of on-device intelligence

Grande highlighted innovative products already leveraging edge intelligence to provide personalised health insights without reliance on the cloud, such as sleep tracking with Oura Ring.

“It’s sold over a billion pieces, and it’s something that everybody can experience and everybody can get a sense of really the power of edge AI,” explains Grande.

Other exciting opportunities exist around preventative industrial maintenance via anomaly detection on production lines.

Ultimately, Grande sees massive potential for on-device AI to greatly enhance utility and usability in daily life. Rather than just raw data, edge devices can interpret sensor inputs to provide actionable suggestions and responsive experiences not previously possible—heralding more useful technology and improved quality of life.

Unlocking the potential of AI on edge devices hinges on overcoming current obstacles inhibiting adoption. Grande and other leading experts provided deep insights at this year’s AI & Big Data Expo on how to break down the barriers and unleash the full possibilities of edge AI.

“I’d love to see a world where the devices that we were dealing with were actually more useful to us,” concludes Grande.

Watch our full interview with Alessandro Grande below:

(Photo by Niranjan _ Photographs on Unsplash)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.