Aspinity | February 16, 2022
Aspinity, the pioneer in analog machine learning chips, today launched the first member of its analogML family, the AML100, which is the industry’s first and only tiny machine learning (ML) solution operating completely within the analog domain. As such, the AML100 reduces always-on system power by 95%, allowing manufacturers to dramatically extend the battery life of today’s devices or migrate walled powered always-on devices to battery - opening whole new classes of products for voice-first systems, home and commercial security, predictive and preventative maintenance, and biomedical monitoring.
Minimizing the quantity and movement of data through a system is one of the most efficient ways to reduce power consumption, but today’s always-on devices don’t have that capability. Instead, they continuously collect large amounts of natively analog data as they monitor their environment and digitize the data immediately, wasting tremendous system power processing data that are mostly irrelevant to the application. In contrast, the AML100 delivers substantial system-level power-savings by moving the ML workload to ultra-low-power analog, where the AML100 can determine data relevancy with a high degree of accuracy and at near-zero power. This makes the AML100 the only tinyML chip that intelligently reduces data at the sensor while the data is still analog and keeps the digital components in low power mode until important data is detected, thereby eliminating the power penalty of digitization, digital processing, and transmission of irrelevant data.
We’ve long realized that reducing the power of each individual chip within an always-on system provides only incremental improvements to battery life. That’s not good enough for manufacturers who need revolutionary power improvements. The AML100 reduces always-on system power to under 100µA, and that unlocks the potential of thousands of new kinds of applications running on battery.”
Tom Doyle, founder and CEO, Aspinity.
Inside the AML100
The heart of the AML100 is an array of independent, configurable analog blocks (CABs) that are fully programmable within software to support a wide range of functions, including sensor interfacing and ML. This versatility delivers a tremendous advantage over other analog approaches, which are rigid and only address a single function. The AML100, however, is highly flexible, and can be reprogrammed in the field with software updates or with new algorithms targeting other always-on applications.
The precise programmability of the AML100’s analog circuits also eliminates the chip-to-chip performance inconsistencies typical of standard analog CMOS process variation, which has severely limited the use of highly sophisticated analog chips, even when the inherent low power of analog makes it better suited for a specific task.
Aspinity is the world leader in the design and development of analog processing chips that are revolutionizing the power- and data-efficiency of always-on sensing architectures. By delivering highly discriminating analog event detection, Aspinity’s ultra-low power, trainable and programmable analog machine learning (analogML) core eliminates the power penalty of moving irrelevant data through the digital processing system, dramatically extending battery life in consumer, IoT, industrial and biomedical applications.
Silicon Labs | January 24, 2022
Silicon Labs, a leader in secure, intelligent wireless technology for a more connected world, today announced the BG24 and MG24 families of 2.4 GHz wireless SoCs for Bluetooth and Multiple-protocol operations, respectively, and a new software toolkit. This new co-optimized hardware and software platform will help bring AI/ML applications and wireless high performance to battery-powered edge devices. Matter-ready, the ultra-low-power BG24 and MG24 families support multiple wireless protocols and incorporate PSA Level 3 Secure Vault™ protection, ideal for diverse smart home, medical and industrial applications. The SoC and software solution for the Internet of Things (IoT) announced today includes:
Two new families of 2.4 GHz wireless SoCs, which feature the industry's first integrated AI/ML accelerators, support for Matter, Zigbee, OpenThread, Bluetooth Low Energy, Bluetooth mesh, proprietary and multi-protocol operation, the highest level of industry security certification, ultra-low power capabilities and the largest memory and flash capacity in the Silicon Labs portfolio.
A new software toolkit designed to allow developers to quickly build and deploy AI and machine learning algorithms using some of the most popular tool suites like TensorFlow.
The BG24 and MG24 wireless SoCs represent an awesome combination of industry capabilities including broad wireless multiprotocol support, battery life, machine learning, and security for IoT Edge applications."
Matt Johnson, CEO of Silicon Labs.
First Integrated AI/ML Acceleration Improves Performance and Energy Efficiency
IoT product designers see the tremendous potential of AI and machine learning to bring even greater intelligence to edge applications like home security systems, wearable medical monitors, sensors monitoring commercial facilities and industrial equipment, and more. But today, those considering deploying AI or machine learning at the edge are faced with steep penalties in performance and energy use that may outweigh the benefits.
The BG24 and MG24 alleviate those penalties as the first ultra-low powered devices with dedicated AI/ML accelerators built-in. This specialized hardware is designed to handle complex calculations quickly and efficiently, with internal testing showing up to a 4x improvement in performance along with up to a 6x improvement in energy efficiency. Because the ML calculations are happening on the local device rather than in the cloud, network latency is eliminated for faster decision-making and actions.
The BG24 and MG24 families also have the largest Flash and random access memory (RAM) capacities in the Silicon Labs portfolio. This means that the device can evolve for multi-protocol support, Matter, and trained ML algorithms for large datasets. PSA Level 3-Certified Secure VaultTM, the highest level of security certification for IoT devices, provides the security needed in products like door locks, medical equipment, and other sensitive deployments where hardening the device from external threats is paramount.
AI/ML Software and Matter-Support Help Designers Create for New Innovative Applications
In addition to natively supporting TensorFlow, Silicon Labs has partnered with some of the leading AI and ML tools providers, like SensiML and Edge Impulse, to ensure that developers have an end-to-end toolchain that simplifies the development of machine learning models optimized for embedded deployments of wireless applications. Using this new AI/ML toolchain with Silicon Labs's Simplicity Studio and the BG24 and MG24 families of SoCs, developers can create applications that draw information from various connected devices, all communicating with each other using Matter to then make intelligent machine learning-driven decisions.
For example, in a commercial office building, many lights are controlled by motion detectors that monitor occupancy to determine if the lights should be on or off. However, when typing at a desk with motion limited to hands and fingers, workers may be left in the dark when motion sensors alone cannot recognize their presence. By connecting audio sensors with motion detectors through the Matter application layer, the additional audio data, such as the sound of typing, can be run through a machine-learning algorithm to allow the lighting system to make a more informed decision about whether the lights should be on or off.
ML computing at the edge enables other intelligent industrial and home applications, including sensor-data processing for anomaly detection, predictive maintenance, audio pattern recognition for improved glass-break detection, simple-command word recognition, and vision use cases like presence detection or people counting with low-resolution cameras.
Alpha Program Highlights Variety of Deployment Options
More than 40 companies representing various industries and applications have already begun developing and testing this new platform solution in a closed Alpha program. These companies have been drawn to the BG24 and MG24 platforms by their ultra-low power, advanced features, including AI/ML capabilities and support for Matter. Global retailers are looking to improve the in-store shopping experience with more accurate asset tracking, real-time price updating, and other uses. Participants from the commercial building management sector are exploring how to make their building systems, including lighting and HVAC, more intelligent to lower owners' costs and reduce their environmental footprint. Finally, consumer and smart home solution providers are working to make it easier to connect various devices and expand the way they interact to bring innovative new features and services to consumers.
Silicon Labs' Most Capable Family of SoCs
The single-die BG24 and MG24 SoCs combine a 78 MHz ARM Cortex-M33 processor, high-performance 2.4 GHz radio, industry-leading 20-bit ADC, an optimized combination of Flash (up to 1536 kB) and RAM (up to 256 kB), and an AI/ML hardware accelerator for processing machine learning algorithms while offloading the ARM Cortex-M33, so applications have more cycles to do other work. Supporting a broad range of 2.4 GHz wireless IoT protocols, these SoCs incorporate the highest security with the best RF performance/energy-efficiency ratio in the market.
About Silicon Labs
Silicon Labs (NASDAQ: SLAB) is a leader in secure, intelligent wireless technology for a more connected world. Our integrated hardware and software platform, intuitive development tools, unmatched ecosystem, and robust support make us an ideal long-term partner in building advanced industrial, commercial, home, and life applications. We make it easy for developers to solve complex wireless challenges throughout the product lifecycle and get to market quickly with innovative solutions that transform industries, grow economies, and improve lives.
Denodo | June 23, 2020
Denodo, the leader in data virtualization, will host its Experts Roundtable Series across North America, EMEA, and APAC starting June 25th. The roundtable features data experts from some of the most prominent cloud platform providers, systems integrators, and Denodo customers along with Denodo’s own subject matter experts. Filled with expert opinions and audience interaction, this roundtable will provide cloud and data management best practices!
Sysdig | June 09, 2020
Sysdig, Inc., the secure DevOps leader, today announced new data center options in Frankfurt, Germany and on the west coast of the United States, in Oregon, to satisfy growing demand for the Sysdig Secure DevOps Platform. The expansion of Sysdig services to additional hosting locations prepares Sysdig for the next stage of growth. The two data centers strengthen data protection standards by adding encryption at rest. Organizations recognize the advantages that come with cloud native and are rapidly moving to containers and Kubernetes to accelerate innovation. In the current business environment, many companies are speeding cloud-native transitions, and look to Sysdig to address their security, visibility, and compliance requirements for containers. The data centers in Germany and on the west coast of the United States are in addition to the company’s current data center on the east coast of the United States, in Virginia.