SOFTWARE
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.
Read More
Red Hat | August 17, 2020
Red Hat, Inc., the world's leading provider of open source solutions, today announced the general availability of Red Hat Advanced Cluster Management for Kubernetes, the latest addition to Red Hat’s portfolio of IT management technologies designed for the hybrid cloud. Red Hat Advanced Cluster Management for Kubernetes is designed to help organizations further extend and scale Red Hat OpenShift with enterprise-grade management capabilities across hybrid and multicloud environments, allowing them to manage multiple Kubernetes clusters and enable multi-cluster application deployments across hybrid clouds while ensuring policy and governance.
Read More
AI APPLICATIONS
Yellow.ai | May 02, 2022
Yellow.ai, the world's leading next-gen total experience (TX) automation platform, trusted by 1000+ enterprises globally, today announced that it has augmented its Marketplace with pre-built, low-code Dynamic AI agents, enabling faster time-to-market and quicker time to value for enterprises. In line with its commitment to foster continuous innovation through its product offerings, the addition of pre-trained, ready to deploy vertical AI agents is aimed at helping enterprises accelerate their TX automation journey.
According to Gartner, digital business acceleration is putting pressure on IT leaders to increase application delivery speed and time to value. Addressing this challenge with greater solution accuracy, the centralized solution library of Yellow.ai's Marketplace enables enterprises to deploy AI Agents in just a few clicks, reducing time-to-market by upto 50%. It offers Prebuilt Industry Templates supporting use-cases across key industries including retail and automotive; Prebuilt Channel Integrators supporting 35+ channels including WhatsApp, Facebook Messenger, Wechat, Slack, Twitter, MS Teams, Instagram and Prebuilt Solution Templates for use cases across customer support, customer engagement, conversational commerce, HR and ITSM automation.
Enterprises can also leverage the pre-built Dynamic AI agents for employee experience (EX) to automate end-to-end EX journeys, right from hire to retire including onboarding, training and routine employee engagements. Supporting seamless integrations with existing HCMs, ITSMs such as SuccessFactors, Service now, the pre-trained AI agents result in improved employee productivity by upto 30% and employee satisfaction by upto 40%. Currently offering over 40 prebuilt accelerators, the company aims to offer over 100 prebuilt accelerators on its Marketplace spread across industries, channels and solutions by the end of the second quarter.
"To address the evolving needs of customers and employees, enterprises, today, prefer Total Experience automation solutions that deliver results in no time. With our pre-built, vertical Dynamic AI agents, we aim to enable them through easy to use, pre-trained customizable models that deliver accuracy, speed to value and consistency specific to their business needs. For instance, with our verticalized solutions for one of the leading automobile manufacturers, we were able to automate the end-to-end buying journey for their end customers and improve month-on-month customer engagement rates by 300%."
Rashid Khan, CPO and Co-founder, Yellow.ai
Yellow.ai also announced feature upgrades to its existing solution Inbox - an Omnichannel Agent-Assist Platform that now supports features such as WhatsApp 24hr window expiry support and Video Calling functionality on cloud, delivering improved CSAT by upto 40%. The company has also added interesting feature upgrades to its Voice offering aimed at humanizing and enhancing conversational experiences with its Voice AI agents. Its customer engagement product Engage now allows enterprises to have access to unified user profiles to enable higher engagement rates with two-way conversations and deliver seamless omnichannel experiences.
About Yellow.ai
Yellow.ai is the world's leading next-gen Total Experience Automation Platform, enabling enterprises to make every conversation fulfilling and delightful for customers and employees. The platform is trusted across 85+ countries by 1000+ enterprises, Domino's, Sephora, Hyundai, Biogen International, Edelweiss Broking, Siemens Limited, Waste Connections, American Bureau of Shipping, and MG Motors. Powered by Dynamic AI agents for enterprises, the company aims to deliver human-like interactions that boost customer satisfaction and increase employee engagement at scale, through its no-code bot builders. Recognised by Frost & Sullivan, Gartner, Forrester, IDC, and G2 crowd as a leader, the company has raised more than $102M from blue-chip investors and has offices across six countries.
Read More
AI APPLICATIONS
Dataiku | June 15, 2021
Dataiku is going downstream with a new product today called Dataiku Online. As the name suggests, Dataiku Online is a fully managed version of Dataiku. It lets you take advantage of the data science platform without going through a complicated setup process that involves a system administrator and your own infrastructure.
If you’re not familiar with Dataiku, the platform lets you turn raw data into advanced analytics, run some data visualization tasks, create data-backed dashboards and train machine learning models. In particular, Dataiku can be used by data scientists, but also business analysts and less technical people.
The company has been mostly focused on big enterprise clients. Right now, Dataiku has more than 400 customers, such as Unilever, Schlumberger, GE, BNP Paribas, Cisco, Merck and NXP Semiconductors.
There are two ways to use Dataiku. You can install the software solution on your own, on-premise servers. You can also run it on a cloud instance. With Dataiku Online, the startup offers a third option and takes care of setup and infrastructure for you.
“Customers using Dataiku Online get all the same features that our on-premises and cloud instances provide, so everything from data preparation and visualization to advanced data analytics and machine learning capabilities,” co-founder and CEO Florian Douetteau said. “We’re really focused on getting startups and SMBs on the platform — there’s a perception that small or early-stage companies don’t have the resources or technical expertise to get value from AI projects, but that’s simply not true. Even small teams that lack data scientists or specialty ML engineers can use our platform to do a lot of the technical heavy lifting, so they can focus on actually operationalizing AI in their business.”
Customers using Dataiku Online can take advantage of Dataiku’s pre-built connectors. For instance, you can connect your Dataiku instance with a cloud data warehouse, such as Snowflake Data Cloud, Amazon Redshift and Google BigQuery. You can also connect to a SQL database (MySQL, PostgreSQL…), or you can just run it on CSV files stored on Amazon S3.
Read More