insideAI News Latest News – 11/10/2020

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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.

Algorithmia Solves ML Model Performance and Drift Detection with Application Performance Monitoring for ML Systems

Algorithmia, a leader in ML operations and management software, announced Insights, a new solution for ML model performance monitoring that provides reliable access to algorithm inference and operations metrics.

Many organizations today don’t have the ability to monitor the performance of ML models working their way into production applications, and organizations that do, use a patchwork of disparate tools and manual processes, often without critical data required to satisfy stakeholder requirements. Without comprehensive monitoring and centralized data collection, organizations struggle with model drift, risk of failure, and the inability to meet performance targets in response to shifts in environment and customer behavior.

Algorithmia Insights addresses these problems by combining operational metrics (execution time, request identification, etc.) with user defined inference metrics (confidence, accuracy, etc.), both of which are essential to identify and correct model drift, data skews and negative feedback loops. The data is accessible within Algorithmia’s Enterprise product. The goal is to deliver metrics where they are most actionable by the teams responsible for these production systems.

“Organizations have specific needs when it comes to ML model monitoring and reporting,” said Diego Oppenheimer, CEO of Algorithmia. “For example, they are concerned with compliance as it pertains to external and internal regulations, model performance for improvement of business outcomes, and reducing the risk of model failure. Algorithmia Insights helps users overcome these issues while making it easier to monitor model performance in the context of other operational metrics and variables.”

Qumulo Introduces New Suite of Data Services to Simplify File Data Management at Scale

Qumulo, a leading file data platform that helps organizations easily store and manage file data so they can build and scale their applications with unrivaled freedom, control and real-time visibility, announced a new suite of data services that radically simplify managing massive amounts of file data. Qumulo unveiled two new data services, Qumulo® Secure and Qumulo Dynamic Scale, and introduced advancements including Instant Software Upgrade to Qumulo Core®, the industry’s first NVMe Cached Performance and Qumulo Shift’s new visual interface.  

“Radical simplicity is critical for customers to be successful with unstructured data. Our software-driven file data platform offers enterprise-level capabilities that radically simplify the process of today’s digital transformation,” said Ben Gitenstein, VP of Product, Qumulo. “With the data services we announced today, Qumulo’s customers can simplify the complexity of their infrastructure, accelerate innovation, and unleash the power of their data, wherever it resides.”

Quest Fuels Game Changing SQL Server Enhancements Through Low-Cost, Automated Compliance and Performance Monitoring Tools    

Quest Software, a global systems management, data protection and security software provider, announced full integration of ApexSQL since it was acquired by Quest in April 2019, as well as enhancements to its SQL Server performance monitoring and diagnostics solution Spotlight Cloud. With ApexSQL integration, Quest offers a range of capabilities across its developer, DevOps, and operations tooling to help SQL Server professionals identify and secure sensitive data to achieve compliance with data privacy standards. New updates to Spotlight Cloud deliver the world’s first SaaS platform that enables deep performance diagnostics for hybrid SQL Server environments. The enhancements to ApexSQL and Spotlight Cloud – both a part of Quest’s newly unified Information Systems Management (ISM) portfolio –  reinforce the company’s commitment to meeting SQL Server professionals’ needs both now and the future. 

“Database security and compliance processes need to be automated, tightly integrated into DevOps pipelines, and then coupled with tamper-resistant database auditing post-deployment to ensure adherence to regional and sectoral standards while continuing to deliver great software,” said Heath Thompson, ISM President and GM, Quest Software. “Quest ApexSQL offers a comprehensive toolset to address security and compliance challenges by simplifying complex processes across the full spectrum of development and operations for SQL Server professionals.”

Brainome Launches Solution To Course Correct Machine Learning With A Fundamentally Different, Measure-First Approach

Brainome, the company behind the first-ever measure-before-build tool for machine learning, launched its product, Daimensions™, for the enterprise market. By introducing measurement as a structured discipline to the field, Brainome changes the way organizations approach machine learning: faster, more effective data preparation, rapid training and execution of models, compact model size, quick identification of most predictive data attributes, and explainability of results. Brainome ultimately delivers a new and complete structured method for analyzing data and creating models. 

Operating in the default “more is better” framework, today’s data science and machine learning teams are encouraged to spend millions of dollars on data preparation and compute power. As a result, experts are getting bogged down by model complexity, size, and opacity, resulting in limited business output and often disappointing return-on-investment. Brainome corrects this massive industry problem by taking a fundamentally different approach: measuring information content in data against target types of models before building anything. Brainome’s approach steers teams towards better outcomes, making it possible to predict project speed, costs, and ultimately success. 

“Every field of engineering and science starts with measurement. Before building a car, plane, bridge, or computer chip, you must measure  before you design and build. Today’s data scientists and machine learning experts are forced to rely on what is essentially guesswork instead of having access to any advanced type of measurement,” said Bertrand Irissou, Co-Founder and CEO at Brainome. “Brainome takes a completely new angle by providing much-needed tools based on  a novel, systematic  measurement-based approach.” 

GoodData Open Sources Next-Generation GoodData.UI Framework to Increase Business Intelligence Adoption

GoodData, a leading global analytics company, released a new version of the GoodData.UI framework for faster and easier development and delivery of data-driven applications. GoodData also open-sourced the library, making the best practices, principles, and tools available to all application developers.

Business analytics are no longer a nice-to-have — they’re a must-have for any organization navigating 2020’s unprecedented demand for faster, smarter digital experiences. By 2022, Ventana Research predicts more than half of line-of-business personnel will have immediate access to cross-functional embedded analytics in their workflow.

“The low adoption of analytics and subsequently limited access to insights are two of the fundamental problems that plague all business intelligence projects. If the industry wants to increase analytics adoption to be closer to 100 percent, data and insights can no longer be isolated from workflows and processes,” said Roman Stanek, CEO of GoodData. “We’ve built GoodData.UI to give embedded BI developers a proven design pattern for architecturing insightful user experiences and data-driven decision-making.”

Moogsoft Delivers Intelligent Observability with Self-Service Platform

Moogsoft, the AI-driven observability leader, announced it has advanced observability in the cloud to meet the demands of a software-defined world. Available today, the Moogsoft Observability Cloud delivers DevOps practitioners and Site Reliability Engineers (SREs) self-service intelligent observability capabilities to begin surfacing actionable insights and performing advanced event management across their digital infrastructure in the time it takes to make a cappuccino.

Companies of all sizes must become agile enough to easily grow and evolve their business at the pace of customer demand, and to constantly deliver customers competitive value. However, teams suffer from unmanageable toolsets laid out in an attempt to understand what’s happening and why, with no real intelligence. The Moogsoft Observability Cloud empowers DevOps practitioners and SRE teams to continue innovating by providing deeper insight and automation across the process of monitoring and event management.

The Moogsoft Observability Cloud extends AI-based intelligence to raw observability data. It turns metric and event data into actionable insights by automating anomaly detection, surfacing important alerts and correlating everything together. This provides teams better visibility about their services, advanced warning of potential outages, and context about the incidents which cause them. With this information, teams can more efficiently collaborate, learn, improve, and innovate their services.

“Old-fashioned monitoring solutions, including many that claim to be new, lead to expensive investments that take months to deliver any results,” said Moogsoft Founder and CEO Phil Tee. “Meanwhile, businesses continue to rely on SREs for manual event management, and on their customers to alert them of an outage. The Moogsoft Observability Cloud empowers DevOps and SRE teams with a platform that deploys in the time it takes to wait for their cappuccino, but leverages the most advanced AI to redefine observability.”

Cazena Launches Instant AWS Data Lake to Accelerate Analytics Migration to AWS

Cazena announced the launch of the Instant AWS Data Lake. Production-ready in just minutes, the Instant AWS Data Lake is the fastest and most cost-efficient solution for enterprises new to AWS or struggling through months-long DIY data lake journeys. The Instant AWS Data Lake has been developed in partnership with AWS; Cazena is an AWS Partner Network (APN) Advanced Technology Partner.

With the Instant AWS Data Lake, Cazena now provides a first-in-industry “easy button” for AWS analytics and moving enterprises’ AI/ML initiatives forward. The Instant AWS Data Lake is ready for analytics in minutes, without requiring operational skills or resources. All enterprises seeking to modernize around cloud data lakes can now securely and rapidly migrate to AWS, and benefit from the rich and continually growing analytics stack that AWS offers. Cazena’s Instant AWS Data Lake orchestrates and integrates myriad AWS analytics services – from ingestion to analytics – into a unified, easy-to-operate, and production-ready SaaS experience. This experience includes seamless connections with AWS solutions including EMR, Athena, Glue, MSK, S3, SageMaker, and more.

“Getting cloud data lakes off the ground continues to be a major source of frustration for enterprises,” said Prat Moghe, CEO, Cazena. “Production deployments often require a minimum of six months to get off the ground, and millions of dollars are spent annually on operations teams to build and manage them – if a business can recruit, hire, and retain this particularly scarce talent. Cazena’s Instant Cloud Data Lakes deliver a secure, hybrid, production-ready experience – with instant time-to-analytics – without requiring additional skills or resources. And we are delivering this SaaS solution at half the cost of DIY data lakes.”

Olea Edge Analytics Launches Smart Water Management Platform to Power Cities with Complete Visibility of All Managed Assets

Olea Edge Analytics, an intelligent edge computing platform for the water utility industry, launched its Smart Water Management Platform, a single dashboard that gives cities and utilities complete visibility of all their managed assets.

Up to half of a utility’s annual revenue comes from large commercial and industrial water meters. Every penny of that revenue is crucial today, with city budgets straining under the economic effects of COVID-19. Olea Edge Analytics’ history with numerous utilities shows that up to 40% of all high-volume meters are underbilling and need repair. Even in the best of conditions, they can lose accuracy by more than 10% per year. Those inaccurate measurements and unaddressed maintenance add up to millions of dollars in potential revenue.

Olea Edge Analytics is a proven leader in helping utilities recover revenue. The City of Atlanta – Department of Watershed Management recently legislated an expanded $3.9 million agreement that is expected to recover millions of dollars. The new Smart Water Management Platform extends the company’s offerings into asset management for operations.

“We combine edge computing with artificial intelligence and machine learning to help cities make more informed decisions,” said Dave Mackie, Olea Edge Analytics’ CEO. “Our network operations center can remotely manage all of the endpoints across the city, prioritizing repair work, giving the ideal route and directions, and transmitted work plans and specifications to provide everything crews need for a right-first-time trip.”

Swarm64 DA 5.0 Brings Hybrid Transactional/Analytical Processing to the Open Source PostgreSQL Database

Swarm64 announced the immediate availability of Swarm64 DA 5.0, which now enhances free, open source PostgreSQL with hybrid transactional/analytical processing (HTAP) capabilities. Swarm64 DA is turnkey software that extends free, open source PostgreSQL with much faster query performance to help customers lower costs, scale more easily, and simplify database application development.

“HTAP is no longer the sole domain of expensive proprietary database software like Oracle, SAP HANA, and MemSQL,” said Thomas Ricther, CEO and co-founder of Swarm64. “Swarm64 DA 5.0 is an important breakthrough. It greatly simplifies database development for PostgreSQL users and gives enterprises a free, open source HTAP option in PostgreSQL.”

MachEye Brings Audio-Visuals to Business Intelligence, Coupled With Natural Search and AI-Powered Click-less Analytics

MachEye, the natural search and AI-powered analytics leader, publicly unveiled its enterprise business intelligence (BI) SaaS platform built to enable all users within an organization to explore data and find intelligence. Combining natural search, AI-powered recommendations and interactive audio-visuals, MachEye offers a complete analytics platform to replace a staid market of tools limited largely to data analysts and IT. The company also announced $4.6 million in seed funding, led by Canaan Partners and with participation from WestWave Capital.

Unlike traditional BI solutions, which require expensive implementations and rely on rigorous training to properly use, MachEye has drastically simplified the user experience in order to increase the speed, quality and ubiquity of data-driven decisions. Seamlessly integrating NLP and NLG, MachEye orchestrates AI in a completely automated and click-less way to produce data stories as “interactive audio-visuals” – instantly. The power of MachEye, often compared to Google and YouTube in terms of its approachability, simplicity and personalized experience, is designed to grow users’ autonomy and increase use of data for smarter decision-making across companies.

“Existing technologies have made strides in usability but still failed to empower all users to easily explore data and make decisions quickly. These solutions are complex to use and have resulted in a paradigm of ‘what you ask is what you get.’ The net result is that businesses lose trillions of dollars because the right decision is not being made on time or not being made at all,” said MachEye Founder and CEO Ramesh Panuganty. “MachEye empowers entire organizations to make smarter decisions at scale, which we believe will lead to happier customers, more efficient operations, and, eventually, more valuable companies.” Launches TextChat, The Only Ecommerce Sales Tool That Turns Live Chats into Texts, a leader in live chat and AI-driven chatbots, announced the launch of TextChat, a new sales tool enabling Shopify merchants to receive live chats from their stores via text message. TextChat ensures merchants never miss a sale due to an unanswered live chat inquiry, leading to much higher conversion rates and many more sales. 71 percent of consumers said they would be less likely to choose a brand if it did not have human customer service representatives available. Merchants equipped with TextChat easily close sales by providing customers with real-time live chat responses from anywhere.

“At, we understand the value of time to small business owners and their customers,” said Eric Kades, CEO and founder. “As a small business ourselves, our own salespeople experienced frustrations with the other live chat platforms that made us keep a desktop app open or respond to app notifications. We were missing sales opportunities, so we created TextChat to make our lives easier and grow our business. Our clients wanted to try it, and they also saw their conversions jump immediately.”

Gluent Provides Customers with a New Path to Google BigQuery Through the Release of Gluent Data Platform 4.0

Gluent, a leader in Transparent Data Virtualization, announced the immediate availability of Gluent Data Platform 4.0. The major feature of this new release is support for BigQuery, Google Cloud’s highly scalable, serverless, enterprise data warehouse that’s designed for business agility.

“We have been impressed with Google Cloud, and as our customers began asking for connectivity to BigQuery, developing a connector to support the platform was an easy decision,” said Gluent’s CEO, Kerry Osborne. “We believe that by eliminating the need to re-write your applications, Gluent provides one of the fastest and safest ways to move your data and processing to the cloud.”

Lightmatter Introduces Passage – a Wafer-Scale, Programmable Photonic Interconnect Fabric Using Light to Increase Computational Performance and Reduce Energy

Lightmatter, a leader in photonic computing, announced Lightmatter Passage – a wafer-scale, programmable photonic interconnect that allows arrays of heterogeneous chips (CPUs, GPUs, memory, accelerators) to communicate with each other at unprecedented speeds. Delivering on the reality of a rack-on-chip interconnect, Passage offers a fully-reconfigurable connection topology between chips, reducing the cost and complexity of building heterogeneous computing systems.

The unique design of Passage packs forty switchable integrated photonic lanes into the same space that traditionally supports just one optical fiber. Passage, the first in a multi-year roadmap of interconnects with increasing performance enables 1Tbps dynamically reconfigurable interconnect across an array of 48 chips spanning 8 inches by 8 inches, with a maximum communication latency of 5 nanoseconds. The result is higher bandwidth communication at lower energy and without the costly process of fiber-to-chip packaging. This architectural approach provides a proven path to deliver chip-to-chip communications with 100Tbps bandwidth—100x that of currently available state-of-the-art photonic interconnect solutions.

“Lightmatter is leading a necessary paradigm shift in computer architecture needed to power the next giant leaps in compute technology, while also reducing the negative impact on our planet of rapidly-growing state of the art, yet inefficient, compute and communications solutions,” said Nick Harris, co-founder and CEO at Lightmatter. “Modern compute workloads call for system-level performance. With Passage, we’ve created a photonic rack-on-chip solution capable of supporting the future of computing by enabling ultra-high bandwidth interconnection between different kinds of chips, and simultaneously reducing cost, complexity, and energy consumption.”

Dremio Enables BI Directly on Cloud Data Lakes and Reduces Data Warehouse Costs

Dremio, the cloud data lake engine company, announced innovations that deliver sub-second query response times directly on cloud data lakes and support for thousands of concurrent users and queries. In addition, Dremio now includes a built-in integration with Microsoft Power BI, enabling users to instantly launch the data visualization software from Dremio and immediately start querying data via a direct connection.

“The fact that organizations don’t need to copy their data into a data warehouse for BI workloads has been unthinkable for the last 30 years,” said Tomer Shiran, Dremio co-founder and chief product officer. “Today, our users can leverage Dremio to power live dashboards and reports directly on S3 and ADLS, instead of waiting weeks to have data moved into a data warehouse. We’re removing limitations, accelerating time to insight and empowering data teams.”

InterSystems Announces General Availability of IntegratedML

InterSystems, a creative data technology provider dedicated to helping customers solve the most critical scalability, interoperability, and speed problems, announced that its InterSystems IRIS® IntegratedML facility is now generally available to users of the InterSystems IRIS and the InterSystems IRIS for Health™ data platforms.

IntegratedML embeds automated machine learning capabilities directly into the core of the InterSystems IRIS Data Platform and makes them available through intuitive SQL commands. SQL developers can easily develop machine learning algorithms within InterSystems IRIS and incorporate them into applications, where they run with high-performance directly on the data, enabling response to real-time events. IntegratedML also frees data scientists to focus on high-value tasks by automating much of the tedious work involved with data preparation.

“Harnessing the benefits of machine learning dramatically improves overall business insights, and when ML based predictive models are executed in line with transactions there is unparalleled ROI,” said Scott Gnau, vice president of Data Platforms at InterSystems. “With InterSystems IRIS and IntegratedML, teams can easily and quickly develop applications that deploy intelligent, prescriptive programmatic actions in response to real-time data, gaining vital competitive insights and business benefits. This enables organizations to act quickly on new strategies, to accelerate new product launches, and to accurately respond to customer preferences.”

Protegrity Launches Enhanced Data Protection Platform to Secure Sensitive Data in Hybrid-cloud, Multi-cloud, and SaaS Environments

Protegrity, a global leader in data security, announced a significantly transformed Protegrity Data Protection Platform, offering enterprises the flexibility to easily secure sensitive data across cloud environments from a single platform. Built for hybrid-cloud and multi-cloud serverless computing, Protegrity’s latest platform enhancements allow companies to deploy and update customized policies across geographies, departments, and digital transformation programs. Protegrity enables businesses to quickly and safely turn sensitive data – wherever it resides – into intelligence-driven insights to deliver better customer experiences, monetize data responsibly, and support vital artificial-intelligence (AI) and machine-learning initiatives.

With sophisticated new data-security capabilities, including data anonymization, enterprises can confidently protect sensitive data as it moves outside of an organization’s perimeter and is shared with third parties. Protegrity’s expanding cloud-protection ecosystem gives customers the ability to easily deploy the security methods that best fit their needs, so businesses can embrace emerging technologies and new computing environments without slowing the speed of innovation. This latest version of the Protegrity Data Protection Platform builds on a legacy of innovation, spanning 87 U.S. patents and more than two decades of experience delivering data security and protection to the world’s largest enterprises.

“Too often, data protection can create huge barriers that diminish customer experience and businesses’ ability to pivot quickly,” said Rick Farnell, President and CEO of Protegrity. “Enterprises that try to run their data protection through disparate systems have gaps in protection, requiring more resources to manage these systems. Also, enterprises are often stymied by their own governance teams that won’t let sensitive data out of their vault. Protegrity enables data to be everywhere businesses need it to be. We support the world’s largest enterprises to have confidence on their journey to the cloud and ability to leverage AI. Protegrity is purpose-built to uphold privacy and comply with evolving global data regulations, while helping businesses realize the value of sensitive data as they accelerate digital transformation and AI initiatives.

Machine Learning Capabilities Come to the Majority of Open Source Databases with MindsDB AI-Tables

MindsDB, the open source AI layer for existing databases, announced official integrations with open source relational databases PostgreSQL and MySQL. These join a growing list of integrations with community-driven databases including MariaDB and Clickhouse to bring the machine learning capabilities of MindsDB to over 55% of open source databases.

MindsDB brings machine learning to those who work with data to allow users to create and deploy ML models using standard SQL queries and increase AI projects’ efficiency. Through the use of AI-Tables, database users can apply machine learning models straight from their database and automatically generate predictions as simple as querying a table.

“Bringing machine learning resources to the open source database community is a huge part of our mission to democratize machine learning,” said MindsDB co-founder, Adam Carrigan. “Staying connected to this community has helped us identify the main challenges of users that know their data best and give them machine learning tools to help them solve those problems.”

YottaDB Announces Octo 1.0, a YottaDB Plugin for Using SQL to Query Data in YottaDB

YottaDB, the database for transactional systems where data integrity is paramount, announced production-grade Octo 1.0, a YottaDB plugin to query YottaDB application data using popular SQL tools. YottaDB excels for transactional systems, where data integrity and application robustness are paramount – applications that effect database state change to provide mission-critical functionality, such as electronic health record systems, core banking systems, library systems, and election systems.

There is a vast ecosystem of tools using SQL/JDBC for reporting, visualization, analysis, and more. Octo 1.0 makes databases of transactional applications that use YottaDB, accessible to those tools.

“YottaDB is a versatile hierarchical key-value (NoSQL) database that delivers in the most challenging use cases, from IoT to Internet scale,” said K.S. Bhaskar, president and founder, YottaDB. “Octo 1.0 lets YottaDB users gain insights to the data in those application databases.” Inventa™ Tames PII Data Discovery and Classification with Supervised AI, the pioneer of the AI-based sustainable data discovery and management platform for Privacy, Security, and Data Governance, announced a cutting-edge solution, Supervised AI™, built on its flagship platform, Inventa™.  This wizard-based machine learning solution empowers business users to modify AI-models, enabling the platform to automatically identify the relevant personal and sensitive information within massive amounts of data in the identified data sources.  Once the model is trained, it continually scans the environment and updates when a new data source or sensitive information is identified.

“Data records in today’s enterprises can be numbered in the millions – or even billions. Discovery tools that require ongoing human decision-making are also prohibitive with regards to resources, requiring dedicated personnel to babysit the discovery process, and causing errors,” said Zak Rubinstein, CEO and Founder of “Inventa’s game-changing Supervised AI solution empowers enterprises to automatically detect and analyze vast amounts of data, leveraging non-data scientists to easily modify AI-models to identify personal and sensitive information at scale. It dramatically reduces risk, improves productivity, and enhances business agility.”

Alluxio Accelerates Scale, Introduces New Management Console to Advance Hybrid and Multi-cloud Data Orchestration

Alluxio, the developer of open source cloud data orchestration software, announced the immediate availability of the next major release of its Data Orchestration platform featuring an expanded metadata service, a new management console for hybrid and multi-cloud deployments, and more cloud native deployments. Data platform teams can now save on infrastructure and operational costs, while easily managing data access across multiple environments.

Enterprises leverage Alluxio at enormous scale, both in data size and number of files.  Data orchestration decouples compute from the location of data to optimize for which data resides where and for how long without the management overhead. With this announcement, users will be able to manage namespaces with billions of files without relying on third party systems, greatly reducing the overall deployment footprint of the solution. The new management console will make it easy to connect an analytics cluster, with engines such as Presto and Spark, with data sources across multiple clouds, single cloud or on-premises using Alluxio.

“Organizations have adopted an infrastructure with compute engines and data sets spread across private data centers and public clouds for business agility and cost effectiveness. Our customers have turned to Alluxio to bridge the gap between applications and the storage systems spread across regions and cloud providers,” said Haoyuan Li, founder and CEO, Alluxio.

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