PointClickCare is the leading North American cloud-based healthcare software for the acute and long-term and post-acute care markets. For over 20 years, the company has held the same vision – to help the world care for vulnerable populations. Since its inception, PointClickCare has grown exponentially with over 1,700 employees today all working towards impacting the lives of millions. Recognized by Forbes as one of the Top 100 Private Cloud Companies and acknowledged by Waterstone Human Capital as Canada's Most Admired Corporate Culture, PointClickCare leads the way in creating cloud-based software. Their shared mission to support vulnerable populations is allowing PointClickCare and Collective Medical to connect disparate points of care at scale faster than anyone else in the market.
Edge computing companies offer a more efficient way to process and transmit data, solving two problems: the need for more IT infrastructure, and the massive amounts of unused data generated by edge points. With the rise of 5G networks, some believe edge computing is the next evolution in this space. If you're trying to find the best edge computing company for your business, this article will help you narrow your search. With edge computing, companies gain near real-time insights with less latency and lower cloud server bandwidth usage. With edge computing, companies gain near real-time insights with less latency and lower bandwidth usage.
Creating a programmable software infrastructure for telecommunication operations promises to reduce both the capital expenditure (CAPEX) and the operational expenses (OPEX) of the 5G telecommunications operators. What is exciting to many of us who work in this space is that the convergence of telecommunications, the cloud, and edge infrastructures will open up opportunities for new innovations and revenue for both the telecommunications industry and the cloud ecosystem. In this blog, we focus on video, the dominant traffic type on the internet since the introduction of 4G networks. With 5G, not only will the volume of video traffic increase, but there will also be many new solutions for industries, from retail to manufacturing to healthcare and forest monitoring, infusing deep learning and AI for video analytics scenarios. The symbiotic evolution of video analytics and edge computing provides opportunities for operators to offer new services which they can monetize with their customers.
Deep Vision, a company known for developing AI processors as well as software suites for edge computing applications, has announced that it has raised $35 million through the investment fund Tiger Global. This second round of funding will primarily help the company expand the capabilities of its processor as well as its software. In addition to Tiger Global, Exfinity Venture Partners, Silicon Motion, and Western Digital also participated in the round. In 2021, the edge computing market reached 6.29 billion dollars against 4.68 billion dollars in 2020 according to a report by Grand View Research. A sector in which Deep Vision is involved since 2014.
Platform9, the leader in multi-cloud Kubernetes-as-a-Service, announced that Norna, a leading applied artificial intelligence company, experienced a ten-fold productivity improvement and a 78% total cost of operations (TCO) reduction after implementing Platform9's Managed Kubernetes-as-a-Service to power the company's retail fashion AI technology. Norna's unique AI-driven service helps fashion retailers with assortment planning and pricing through near real-time insights into changes in competitor pricing and offerings. Norna turned to Platform9 to solve two major challenges the company was facing in using a public cloud platform – the rapidly escalating costs for its public cloud-based infrastructure and the high demands on the team's time to manage its Kubernetes infrastructure. Platform9's Managed Kubernetes-as-a-Service provided Norna with the simplest and fastest path to running its production, cloud-native data harvesting, and processing applications, enabling Norna to quickly deploy Kubernetes clusters with a rich set of pre-built, cloud-native services and infrastructure plug-ins. Rather than having to spend valuable engineering cycles on Kubernetes platform operations, Norna is now able to focus on its mission of becoming the world leader in applied AI. "As AI specialists, we cannot have in-house talent spending time becoming production Kubernetes experts," said Jonas Saric, founder and CEO of Norna.
The battle for artificial intelligence hardware keeps moving through phases. Three years ago, chip startups such as Habana Labs, Graphcore, and Cerebras Systems grabbed the spotlight with special semiconductors designed expressly for deep learning. Those vendors then moved on to selling whole systems, with newcomers such as SambaNova Systems starting out with that premise. Now, the action is proceeding to a new phase, where vendors are partnering with cloud operators to challenge the entrenched place of Nvidia as the vendor of choice in cloud AI. Cerebras on Thursday announced a partnership with cloud operator Cirrascale to allow users to rent capacity on Cerebras's CS-2 AI machine running in Cirrascale cloud data centers.
MLOps is the machine learning operations counterpart to DevOps and DataOps. But, across the industry, definitions for MLOps can vary. Some see MLOps as focusing on ML experiment management. Others see the crux of MLOps as setting up CI/CD (continuous integration/continuous delivery) pipelines for models and data the same way DevOps does for code. Other vendors and customers believe MLOps should be focused on so-called feature engineering -- the specialized transformation process for the data used to train ML models.
Snowflake is a cloud data warehouse provided as a software-as-a-service (SaaS). It consists of unique architecture to handle multiple aspects of data and analytics. Snowflake sets itself apart from all other traditional data warehouse solutions with advanced capabilities like improved performance, simplicity, high concurrency and cost-effectiveness. Snowflake's shared data architecture physically separates the computation and storage which is not possible by the traditional offerings. It streamlines the process for businesses to store and analyze massive volumes of data using cloud-based tools.
Salesforce on Thursday introduced a series of new features and tools to Service Cloud, with the intent of streamlining experiences between customer service agents and consumers. Service Cloud is one of the Salesforce tools that now leverages Slack -- in this case, for a "swarming" capability that brings together all of the right experts to quickly solve customer problems. The first batch of new capabilities, including Slack swarming, enable new workflows for faster, more efficient customer experiences. The Slack integration is part of Service Cloud's Customer Service Incident Management feature, which will be generally available in the Winter 2022. It's designed to help companies detect, diagnose, and respond to service disruptions.
The latest winner of the growing interest in enterprise AI is Databricks, a startup that has just secured $1.6 billion in series H funding at an insane valuation of $38 billion. This latest round of investment comes only months after Databricks raised another $1 billion. Databricks is one of several companies that offer services and products for unifying, processing, and analyzing data stored in different sources and architectures. The category also includes Snowflake, which made a massive IPO last year and has a market cap of $90 billion, and C3.ai, another enterprise AI company that went public last year. Why are investors enamored with companies like Databricks?