By Daniel Gutierrez 2020-04-07
In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we’re in close touch with vendors from this vast ecosystem, so we’re in a unique position to inform you about all that’s new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive.
Juniper Networks Introduces Mist Premium Analytics Service to Provide Actionable Business Insights Across Network, Security and Location Domains
Mist Systems, a Juniper Networks company and a pioneer in secure AI-driven networks, announced the launch of Mist Premium Analytics, a new service that offers enterprises a comprehensive network visibility and business insights platform to support the increasing demands of digital transformation projects. As a complement to existing Mist wireless, wired and location subscription services and the Marvis AI engine, Mist Premium Analytics helps simplify data collection across heterogenous network, security and location domains and converts that data into actionable insights for better capacity planning, optimal user experiences and positive business outcomes for today’s digital businesses.
“End-to-end network visibility into network, security and location behavior is traditionally both complex and costly because of disparate systems, organizational silos and the lack of an overarching intelligence engine to tie all the pieces together,” said Sudheer Matta, VP of Products at Juniper Mist. “With Mist Premium Analytics, we solve this challenge by taking data from numerous systems and turning it into actionable insights for better IT and business decisions.”
Ascend.io Expands Its Unified Data Engineering Platform and Accelerates the Economics of Data with the Release of Ascend Govern
Ascend.io, the data engineering company, announced it has expanded the Ascend Unified Data Engineering Platform with the addition of Ascend Govern, a first of its kind suite of tracking, reporting, and security capabilities for a more granular understanding of how data is being used throughout an organization. Ascend Govern records and permanently maintains an in-depth understanding of the linkages between code, data, and users, providing a level of visibility and auditability never before possible.
“Until now, data teams have been largely unable to answer questions about the true cost, value, and ultimately, the ROI of their data initiatives,” said Steven Parkes, CTO at Ascend.io. “These questions on the ‘Datanomics’ of the business are vital in demonstrating the business value of data-driven initiatives. Ascend Govern is the first solution to provide the confidence data teams need to know exactly where data came from, where it’s going, what it costs, and what the eventual value is, providing an unprecedented level of understanding to the business.”
data.world Enhances Its SaaS Data Catalog, Delivering Transparency and Simplicity to Enterprise Users
data.world, the cloud-native data catalog company, announced new capabilities designed to accelerate time-to-value by bringing unmatched transparency, simplicity, and usability to its growing base of enterprise customers. This includes a new platform design that optimizes popular features such as social newsfeeds, auto-generated lineage, and agile data governance. The company also launched a free trial of its SaaS-based platform.
“Typical enterprise software is notoriously tough to deploy, maintain, and use, and most companies are cagey about pricing. As a Certified B Corporation and home to the world’s largest collaborative data catalog and community, we’re not a typical software company,” said Brett Hurt, co-founder and CEO of data.world. “As a SaaS business that has been honed by use-cases from data-driven communities all over the world, we believe it’s important to deliver a top-tier product that speaks to the consumer in all of us. Our cloud-native enterprise service and the trial version put customer experience and usability front and center.”
InterSystems Releases New Version of InterSystems IRIS™ Data Platform
InterSystems, a creative data technology provider dedicated to helping customers solve the most critical scalability, interoperability, and speed problems, announced the availability of the latest version of the InterSystems IRIS™ data platform. This is the third major release of InterSystems IRIS, the company’s flagship data platform that enables organizations to solve their most critical interoperability, scalability, and speed problems.
InterSystems IRIS now features a beta version of IntegratedML, which enables application and SQL developers to develop machine learning (ML) algorithms and embed them into sophisticated applications in a simple, intuitive, and scalable way. IntegratedML also improves the productivity of data scientists by automating much of the tedious work involved with developing machine learning algorithms.
“This latest release of InterSystems IRIS data platform expands its usefulness for developing high performance, machine learning-enabled applications that span data and application silos,” said Scott Gnau, head of data platforms for InterSystems. “We continue to drive the platform based on the needs of our customers that are aggressively implementing their digital transformation initiatives.”
Boost.ai Sidesteps Cold-Start with Industry-First ‘Self-Learning’ AI to Build and Manage Virtual Agents
Boost.ai, a global leader in artificial intelligence for Fortune 1000 companies, has released the industry’s first self-learning technology for conversational AI. Developed and offered exclusively by boost.ai, self-learning AI overcomes the ‘cold start’ challenges of building and managing virtual agents with an automated system that intelligently analyzes and recommends both new conversational dialogs, as well as suggestions to improve existing ones. The new feature is provided alongside additional upgrades in the latest software version of the boost.ai conversational AI platform.
The boost.ai platform discerns customer ‘intents’ to detect and understand user requests and determine what they want to do, and then further invoke the appropriate action such as requesting an insurance quote or getting options for banking products or services. Boost.ai self-learning AI offers a revolutionary new way to overcome the cold-start process. It can update virtual agents with recommended intents and data-training via ‘intent suggestions’, and also makes it possible to build new, full-featured virtual agents in 10 days or less using existing data on customers, products and services.
“With the introduction of self-learning AI, boost.ai now offers the world’s most complete end-to-end conversational AI platform,” said Henry Iversen, co-founder and chief commercial officer at boost.ai. “It is now possible to smartly apply artificial intelligence all the way through from virtual agent development to customer interaction to real-time enhancement of conversations as they take place.”
Espressive Unveils New Barista Innovations to Lead Market in Conversational Chatbots for Enterprise Service Management
Espressive, a pioneer in artificial intelligence (AI) for enterprise service management (ESM) announced new innovations to its flagship product, Espressive Barista, to further extend the accuracy of the advanced NLP engine, expand the power of conversational AI with over 750 million employee phrases, and eliminate the requirement for technical AI expertise to perform content updates. Barista, an AI-based virtual support agent, automates help desks by directly connecting employees to the information and services they need. In addition, the company announced Barista Case Management which cost-effectively extends service management efficiency to enterprise service teams. Together, these new product innovations empower enterprises to leverage intelligent automation to reduce service delivery costs while improving workforce productivity and satisfaction.
“Successful adoption of intelligent automation tools like chatbots requires that employees be able to communicate in ways that come naturally to them,” said Conner Forrest, senior analyst at 451 Research. “That is why investments in NLP, like the one made by Espressive, are so important for intelligent automation because they offer employees a way to ask questions or make requests without first learning what syntax is acceptable to the bot or forcing their communication to fit into a limiting framework. This streamlines the adoption process and boosts the potential improvements to productivity the tools can bring.”
Ververica Introduces Free Community Edition of its Platform to Meet the Increasing Demand for Apache Flink Adoption at All Levels
Ververica, founded by the original creators of Apache Flink®, unveiled Ververica Platform Community Edition, specifically designed to welcome the adoption of stream processing with Apache Flink for everyone. The Community Edition of Ververica Platform is a free edition of the company’s enterprise stream processing platform and presents the easiest way to get started with Apache Flink for every software development and data infrastructure team in the world. Ververica Platform Community Edition encompasses all the knowledge that Veverica has acquired after years of working together with some of the largest and most demanding Apache Flink deployments worldwide.
“With Ververica Platform Community Edition, we have introduced a free-for-production-use, lite platform that encompasses our accumulated knowledge and best practice from years of experience working with some of the largest and most successful data-driven companies in the world,” said Konstantin Knauf, Head of Product, Ververica. “With the Ververica Platform Community Edition, we offer the easiest, fastest and best way to get started with Flink for every developer and data engineer across any organization, no matter its industry or size.”
KNIME Launches Integrated Deployment
KNIME unveiled a groundbreaking approach — Integrated Deployment — to eliminate the gap between the creation of data science models and their use in production. Integrated Deployment allows not just a model but all of its associated preparation and post- process steps to be identified and automatically reused in production with no changes or manual work required. From within the KNIME platform, organizations can replicate the process repeatedly with ease to maintain model performance.
“Our open approach and close collaboration with the community means that KNIME is always at the forefront of what is possible in data science. Integrated Deployment represents another big step forward,” said Michael Berthold, CEO and co-founder of KNIME. “This solves perhaps one of the biggest problems in data science today by completely eliminating the gap between the art of data science creation and moving the results into production.”
DataStax Helps Apache Cassandra Become the Industry Standard for Scale-Out, Cloud-Native Data
DataStax released code for an Apache Cassandra™ Kubernetes operator to help enterprises and users succeed with scale-out, cloud-native data. The Cassandra Kubernetes operator is now available and ready for use by the Cassandra community as we work together on a common operator.
“DataStax spent the last decade solving hard data problems for distributed systems,” said Sam Ramji, Chief Strategy Officer at DataStax. “That has standardized and we’re now looking at the decade of scale-out, cloud-native data. We’re deeply focused on helping enterprises and users succeed with open source, scale-out, and cloud-native data.”
Perceive Corporation Launches to Deliver Data Center-Class Accuracy and Performance at Ultra-Low Power for Consumer Devices
Perceive Corporation, an edge inference solutions company, launched the company and debuted its first product, the ErgoTM edge inference processor. Ergo brings breakthrough accuracy and performance to consumer devices such as security cameras, smart appliances, and mobile phones. The Ergo chip and reference board are currently being sampled to leading customers and are ready for mass production in the second quarter of 2020.
In an environment where consumers are demanding greater security and privacy, Ergo removes the need to send sensor data from devices to the cloud for analysis. Ergo’s real-time, on-device inference processing makes it ideally suited for devices where consumer experience and privacy of data such as video and audio are of paramount importance. Whether it is reducing false notifications in a security camera, extending battery life in a mobile device, or simplifying the user interface of a home appliance, Ergo improves key device features by enabling comprehension and intelligent reactions to surroundings—without compromising consumer security.
“Everyone wants smarter devices—but until now, only the cloud has provided the requisite accuracy,” said Steve Teig, Chief Executive Officer of Perceive. “Perceive has developed novel, mathematically rigorous methods for inference that redefine what is possible in an edge device. Our Ergo chip delivers data center-class accuracy and performance in consumer devices, protecting privacy and security while running at ultra-low power.”
dotData Announces Free Trial of dotData Enterprise to Help Enterprises Accelerate their AI and Machine Learning Initiatives
dotData, focused on delivering full-cycle data science automation and operationalization for the enterprise, announced that its autoML 2.0 platform, dotData Enterprise, is available exclusively to US customers. The dotData trial program enables companies to build a viable, usable AI/ML model from their own data set, regardless of data format. Leveraging intelligent data management and preparation features, dotData Enterprise can connect to both flat-files as well as relational data, and automatically generate the required schemas.
Each dotData Enterprise trial will be fully-guided and supported by the dotData data science team, who will assist each company in building a use-case, understanding their data and optimizing the trial experience. dotData’s data science team will also guide the client through AI model selection and interpretation of the results. dotData can host the software environment if needed, or can utilize the client’s own AWS or Azure environment.
“We are seeing a rapid demand for data science and AI capabilities among enterprises of all sizes, many of which do not have the resources to build and deploy their own data science program,” said Ryohei Fujimaki, founder and CEO of dotData. “Our trial program will enable customers to perform an actual proof of concept trial with their own data, to demonstrate how quickly and easily it is to deploy dotData Enterprise to accelerate their data science initiatives.”
cnvrg.io Releases CORE Community Version to Empower Data Scientists to Focus on Innovation
cnvrg.io, the enterprise data science platform simplifying model management with MLOps and continual machine learning automation, announced the release of its community version – CORE. The cnvrg.io CORE community platform is being released amid extended remote work and social distancing to advance ML development and help the data science community leverage cnvrg.io model management and MLOps capabilities at no cost.
The data science community has been central to the rapid growth of AI and machine learning innovation. Before its hype across the industry, data science was an unexplored pasture for enthusiasts to gain deeper insights combining the power of math, statistics and computer science. What once was a way of tinkering with algorithms, has become widely embraced by the corporate world as a competitive strategy. With the growing technical complexity of the AI field, the data science community has lost touch with the core of what makes data science such a captivating profession- the algorithms. cnvrg.io CORE opens its end-to-end solution to the community to help data scientists focus less on technical complexity and DevOps, and more on the core of data science.
“The release of cnvrg.io CORE is our contribution to the strong data science community responsible for advancing AI innovation.” says Yochay Ettun, CEO of cnvrg.io “CORE’s release marks a new vision for data science field. As data scientists, we built core to fill the need that so many data scientists require, to focus less on infrastructure and more on what they do best – algorithms”
DataRobot Unveils Latest Version of Enterprise AI Platform, Introducing Visual AI, AI Applications, and Automated Deep Learning
DataRobot, a leader in enterprise AI, announced enhancements to its enterprise AI platform, including AI Applications, Automated Deep Learning, and Visual AI. These new introductions further unlock the value of AI by putting the power of AI into the hands of more users and making it simpler to build and deploy deep learning models. In the latest version of the platform, DataRobot has introduced:
- Visual AI: With Visual AI, users can address computer vision use cases and combine incredibly diverse types of data in their models. Visual AI offers immediate support for use cases requiring image recognition and classification. Users can simply drag and drop a collection of images into a project and build custom deep learning models in minutes. DataRobot’s Visual AI then takes image-based machine learning one step further by allowing users to leverage images alongside any other feature types such as numeric, categorical, dates, and raw text.
- AI Applications: With the latest platform release, any machine learning model, including DataRobot-generated models or models written in R or Python, can be turned into an AI application. This enables employees of all skill levels to interact with the predictive insight of the underlying model and experiment with different scenarios, predict results, and make more informed business decisions. The new feature also includes an Applications Gallery – a one-stop shop that allows business users to find the application that best suits their needs.
- Automated Deep Learning: DataRobot has significantly boosted its deep learning capabilities, powered by a new Keras-based model framework for which DataRobot recently secured a provisional patent. Traditionally, training deep learning models is expensive and time consuming. DataRobot’s new capabilities allow users to build successful and reliable deep learning models that are ready to deploy into production. The new capabilities also make it easy to understand these models – all with the infrastructure a user has in place.
“Having pioneered the automated machine learning category, we are proud to push the boundaries of what’s possible with the technology by offering these novel automated deep learning and Visual AI capabilities,” said Phil Gurbacki, SVP of Product and Customer Experience, DataRobot. “Subject matter experts from any industry can now solve new business problems by including relevant image-based content along with other more traditional data types. This latest evolution of our platform will empower users to leverage AI to make even better decisions based on broader perspectives.”
Kogniz Health Launches AI-Based Fever Detection Cameras for Crowds to Help Limit Coronavirus Spread
Kogniz, an innovator in physical security and machine learning, is launching an AI-enabled camera and software system that scans groups and crowds entering a facility and identifies anyone with an elevated temperature. Called Kogniz Health, the highly-accurate solution alerts company personnel in real time so that any individual with a fever can be isolated as needed. The company already has more than 12 large customers, each using multiple cameras.
As state and local governments ramp up to protect the public against the COVID-19 pandemic as well as other illnesses, the scalable system offers a means for organizations to avoid the cost and risk of posting staff with handheld thermal devices at entrances to take individual temperatures. Kogniz Health Cams can be deployed at every entrance to an office, campus, warehouse or distribution center where many people are coming through.
“Companies want to keep their employees healthy and safe,” said Daniel Putterman, Co-founder and Co-CEO, Kogniz. “During a pandemic such as this one it is critical that organizations be able to quickly identify people who might be sick, and one way to do that is to detect fever. Handheld thermal guns are very expensive, labor intensive, and create a bottleneck. We are able to provide temperature detection for high-flow environments so individuals with elevated temperature can be further checked.”