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.
Informatica Launches Data Management Innovations: AI-driven Catalog of Catalogs, Data Marketplace, and Data Quality Cloud
Informatica®, a leader in enterprise cloud data management, announced extensive updates across its Intelligent Data Platform ™ , powered by Informatica’s AI-powered CLAIRE ™ engine, enabling enterprises with leading data management solutions. The innovations include the launch of Informatica’s Catalog of Catalogs, Data Marketplace, and the industry’s first Data Quality Cloud. The updates span Informatica’s solution portfolio with five AI-powered advances for comprehensive, enterprise-scale data management, across customer journeys.
“With this launch, we are releasing industry-first data management innovations that change the game for enterprises looking to power their businesses with data-driven insights,” said Amit Walia, president, Products and Marketing, Informatica. “As today’s enterprises evolve to become data-driven, they require an industry-leading innovative platform that is unified, scalable, and AI-powered. Informatica’s Intelligent Data Platform is all of those things and more, and provides enterprises with the trusted data needed to drive transformational business outcomes.”
Alation Extends the Data Catalog to Include Analytics Stewardship for the Enterprise
Alation Inc., the data catalog company, announced the general availability of its Analytics Stewardship application in the Alation Data Catalog. This industry breakthrough product offering is complemented by a professional services accelerator that together provide an easier and faster way for enterprises to drive more value from self-service analytics while ensuring accurate, compliant data use.
“Enterprises must ensure that data is used properly and that analytics are accurate, and used in adherence with policies and protect consumer privacy, particularly in light of regulations like GDPR and CCPA. Striking the balance between data governance and creating greater value from data is a huge challenge for data leaders. The upside and opportunity from data is massive, but so too are the consequences of noncompliance and inaccurate information,” said Satyen Sangani, CEO and co-founder of Alation. “Alation’s unique Analytics Stewardship application was designed to achieve a single source of reference for all of an organization’s data and analytics governance policies and leverages machine learning within the data catalog to automate stewardship and governance efforts.”
Scale Computing Unveils Smallest HCI Edge Appliance For Edge Computing IT Infrastructure Deployments
Scale Computing, a market leader in edge computing, virtualization and hyperconverged solutions, unveiled its newest HC3 Edge appliance at the Gartner IT Infrastructure, Operations & Cloud Strategies Conference. The new HE150, which is powered by Intel® technology, offers a low-cost edge solution that is built on a tiny form factor, making it ideal to deploy in small clusters where highly available computing was previously cost-prohibitive. The new appliance also introduces HC3 Edge Fabric, which eliminates the need for a backplane network switch requirement, lowering the TCO and delivering simpler connectivity for edge networks.
“A growing number of distributed organizations require infrastructure at the edge of the network, specifically at sites where there are limited IT staff available. With edge computing on the rise, organizations are requiring solutions that can fit small footprint requirements with robust application performance, while still being affordable, efficient and simple to manage remotely,” said Jeff Ready, CEO and co-founder, Scale Computing. “This is why we created our newest HE150 appliance, making edge computing a financially viable and practical option for more organizations. Our ability to deliver HCI technology in a smaller form factor and lower price point is making edge computing capabilities and resources more accessible to many organizations.”
WekaFS Selected by Innoviz to Accelerate AI for Autonomous Vehicle Innovations
WekaIO™ (Weka), a leader in high-performance, scalable file storage for data-intensive applications, announced that Innoviz, a leading manufacturer of high-performance, solid-state Light Detection and Ranging (LiDAR) sensors and Perception Software that enables the mass-production of autonomous vehicles, has selected the Weka File System (WekaFS™) to accelerate its Artificial Intelligence (AI) and deep learning workflows. WekaFS has been chosen by Innoviz to improve application performance at scale and deliver high bandwidth I/O to its GPU cluster.
“Weka is being used by many AI companies to significantly reduce AI training Epochs. We can help companies shorten wall clock time by ensuring the GPU cluster is fully saturated with as much data as the application needs. Managing large amounts of data is challenging when the AI training system spans multiple GPU nodes. A shared file system eliminates this challenge, but legacy NFS-based NAS can cause I/O starvation to the GPUs,” said Liran Zvibel, co-founder and CEO, WekaIO. “Weka solves these issues, with WekaFS presenting a shared POSIX file system to the GPU servers and delivering extreme performance to keep data-intensive applications compute-bound.”
Luminoso Launches Responsible AI System for Text Analysis
Luminoso, the company that turns unstructured text data into business-critical insights, today announced the next generation of its proprietary natural language modeling system, QuickLearn 2.0, which is the first commercially-available solution that reduces biases in AI-powered text analysis.
“QuickLearn 2.0 is a significant advancement in our method of transfer learning,” said Robyn Speer, chief science officer at Luminoso. “More so than any other natural language understanding system, it can solve the difficult problem of how to learn about a new domain quickly, without bias, and without the need for huge amounts of training data.”
AntWorks’ Influence On The AI Industry Continues To Gain Momentum In 2019 – Fuelled By The Launch Of ANTstein SQUARE
It has been a year of milestones for AntWorks™, a global provider of artificial intelligence and intelligent automation solutions powered by fractal science. Most notably, AntWorks introduced its new and enhanced version of ANTstein™ SQUARE, a fullstack Integrated Automation Platform (IAP) that enables enterprises to automate end-to-end business processes quickly, easily and in a scalable manner. To support and accelerate its growth, AntWorks significantly increased its geographic footprint and global headcount, and was widely recognised for its cutting-edge and industry-disrupting technology.
“This was a year of records and firsts for AntWorks,” said Asheesh Mehra, AntWorks Co-Founder and Group CEO. “Four years ago, we set out with an ambitious goal of disrupting the AI industry by delivering the first and only authentic IAP to agile and forward-thinking companies across every sector. Now we’re consistently punching above our weight – benchmarked against competitors that have been in the space for far longer. Over 2019, we expanded our global presence across key markets, increased our strategic partnerships, continued to foster an inclusive and collaborative culture, and launched the most innovative product of its kind. Our momentum is always guided by our mission to manifest the power of ethical AI while delivering the greatest value to our clients and the people of AntWorks. I couldn’t be prouder of all the AntWorks Colony has accomplished.”
GigaSpaces Launches Version 15.0 to Operationalize and Optimize Machine Learning
GigaSpaces, the provider of InsightEdge, the fast in-memory real-time analytics processing platform, announced the availability of GigaSpaces Version 15.0, including the InsightEdge Platform and XAP, to operationalize and optimize machine learning with the required speed, scale, accuracy and management tools. GigaSpaces Version 15.0 powers machine learning operations (MLOps) initiatives, helping enterprises maximize the business value derived from big data. GigaSpaces Version 15.0 simplifies integrating AI workloads with the organization’s core infrastructure, accelerating machine learning deployment and enabling enterprises to more readily experience the business benefits of machine learning models.
“Machine learning is becoming an essential component of mission critical applications to optimize operations and deliver superior real time customer experiences,” said Yoav Einav, VP Product at GigaSpaces. “GigaSpaces Version 15.0 provides enterprises with the machine learning model management capabilities, speed and scale that they need to accelerate their machine learning and artificial intelligence journey.”
Explaining Explainability: DarwinAI Team Publishes Key Explainability Paper, Works to Improve Industry-Wide Trust in AI
DarwinAI, a Waterloo, Canada startup creating next-generation technologies for Artificial Intelligence development, announced that the company has conducted academic research that answers a key industry question: “How can enterprises trust AI-generated explanations?” Explainability has been key in addressing AI’s “black box” problem as it is nearly impossible for a human to understand how deep neural networks make decisions. To date, there’s been limited assessment of explainability methods within the nascent deep learning field, and most existing evaluations focus on subjective visual interpretations. DarwinAI’s paper, “Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms,” explores a machine-centric strategy for quantifying the performance of explainability methods on deep neural networks.
“The question of how deep neural networks make decisions has plagued researchers and enterprises alike and is a significant roadblock to the widespread adoption of this particular form of AI,” said Sheldon Fernandez, CEO, DarwinAI. “It is critical that enterprises obtain some understanding of how a neural network reaches its decisions in order to design robust models with a certain level of trust.”
Rice, Amazon report breakthrough in ‘distributed deep learning’
Online shoppers typically string together a few words to search for the product they want, but in a world with millions of products and shoppers, the task of matching those unspecific words to the right product is one of the biggest challenges in information retrieval. Using a divide-and-conquer approach that leverages the power of compressed sensing, computer scientists from Rice University and Amazon have shown they can slash the amount of time and computational resources it takes to train computers for product search and similar “extreme classification problems” like speech translation and answering general questions.
“Our training times are about 7-10 times faster, and our memory footprints are 2-4 times smaller than the best baseline performances of previously reported large-scale, distributed deep-learning systems,” said Shrivastava, an assistant professor of computer science at Rice.
AWS announces the Machine Learning Embark program to help customers train their workforce in machine learning
Amazon has announced the AWS Machine Learning (ML) Embark program to help companies transform their development teams into machine learning practitioners. AWS ML Embark is based on Amazon’s own experience scaling the use of machine learning inside its own operations as well as the lessons learned through thousands of successful customer implementations. Elements of the program include guided instruction from AWS machine learning experts, a discovery workshop, hand-selected curriculum from the Machine Learning University, an AWS DeepRacer event, and co-development of a machine learning proof of concept at the culmination of the program.
The AWS ML Embark program is designed to help customers overcome some common challenges in the machine learning journey. To kick off the program, participants will pair their business and technical staff with AWS machine learning experts to join a discovery day workshop to identify a business problem well suited for machine learning. Through this exercise, AWS machine learning experts will help the group work backwards from a problem and align on where machine learning can have meaningful impact.
New Study Links Enterprise Success to Defeating Time
Hazelcast, a leading in-memory computing platform that delivers the System of Now™, released its “Infinity Data” report that reveals the link between latency, innovation and business performance. The research, commissioned in collaboration with Intel, revealed that more than half (65%) of organizations measure the cost of speed and response time on their business, highlighting how defeating latency is key to an organization’s success. The study surveyed IT decision-makers across five key industries – financial services, e-commerce/retail, telecommunications, energy and the public sector – about how they are addressing new and persistent digital challenges that affect systems and performance.
In an era inundated with the promise of artificial intelligence (AI), machine learning and other advanced technologies, businesses need to view and measure their world through a different, faster time scale to meet the new levels of performance necessary to compete. According to Hazelcast’s research, companies are measuring performance in mere milliseconds and microseconds (58%) rather than seconds (39%). To put it into context, the average blink of an eye is 300 milliseconds or 300,000 microseconds. And these levels of processing speeds are separating business leaders from laggards – the survey found that 25% of companies measuring latency in seconds report having an “extremely difficult” time managing advances in technology speed.
“The intersection of time and data is the next frontier for businesses to conquer, especially if they are to deploy artificial intelligence, edge computing and any other data-centric applications or services,” said Kelly Herrell, CEO of Hazelcast. “While latency has quickly become a significant barrier to company performance, our research reveals that organizations capable of measuring its impact on the business are better positioned to be a leader in the digital era.”
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