WELCOME TO The THE INTERNET OF THINGS REPORT
IBM Creates Internet of Things Business Unit, Appoints Leader
ANGELA GUESS | March 1, 2016
Think Silicon is designing and developing ultra low power-high performance Graphics Processing Units (GPUs), IP Semiconductor Cores. NEMA GPU’s are designed specifically for ultra-low power IoT.
Article | April 3, 2020
One might be forgiven for thinking that Google had enough operating systems. Other than Android, Google also owns Chrome OS and Google Fuchsia – the latter of which isn’t even finished yet! But then came murmurs of a project called Pigweed, following a Google trademark that surfaced in February this year. At first, speculation was rife that this was yet another operating system, due to wording that described it as “computer operating software.” Now we know that is not the case. So what is Google Pigweed? In a recent blog post, Google officially threw back the curtain. Google Pigweed, it turns out, is a collection of embedded platform developer tools for development on 32-bit microcontrollers. Effectively, these are libraries targeted at Internet of Things (IoT) applications.
Arm wants to help IoT and other embedded devices to think for themselves. Today the company unveiled two chips designed to eliminate the reliance on cloud-based artificial intelligence (AI) by delivering machine learning (ML) capabilities right on the device.“Enabling AI everywhere requires device makers and developers to deliver machine learning locally on billions and ultimately trillions of devices,” said Dipti Vachani, SVP and general manager of Arm’s automotive and IoT line of business, in a statement. The Cortex-M55 processor is the company’s first to leverage the Armv8.1-M architecture and features Arm’s Helium vector processing technology, which is designed with ML and digital signal processing in mind.
As development teams race to build out AI tools, it is becoming increasingly common to train algorithms on edge devices. Federated learning, a subset of distributed machine learning, is a relatively new approach that allows companies to improve their AI tools without explicitly accessing raw user data. Conceived by Google in 2017, federated learning is a decentralized learning model through which algorithms are trained on edge devices. In regard to Google’s “on-device machine learning” approach, the search giant pushed their predictive text algorithm to Android devices, aggregated the data and sent a summary of the new knowledge back to a central server. To protect the integrity of the user data, this data was either delivered via homomorphic encryption or differential privacy, which is the practice of adding noise to the data in order to obfuscate the results.
The Internet of Things continues to grow fueled by applications that solve problems for enterprise customers. One of the biggest barriers to IoT solutions in enterprise settings is reliable and low-cost wireless connectivity. Where Wi-Fi, Bluetooth, LoRa, Zigbee and others have tried to solve the problem before, CBRS (Citizens Broadband Radio Service) is posed to offer a viable alternative for enterprise IoT connectivity. Specific to the United States, Citizen’s Broadband Radio Service (CBRS) is a piece of the radio spectrum between 3550 – 3700 MHz. This is a valuable area of the spectrum because it allows good propagation (ability to penetrate walls and go medium distances) with the benefits of higher bandwidth services, such as LTE and 5G.
Keep me plugged in with the best
Join thousands of your peers and receive our weekly newsletter with the latest news, industry events, customer insights, and market intelligence.
Put your news, events, company, and promotional content in front of thousands of your peers and potential customers.
Not a member yet? Not a problem, Sign Up
Sign up to contribute and publish your news, events, brand, and content with the community for FREE