In Artificial Intelligence, Curated Content, Innovation, Machine Learning

Artificial intelligence, cognitive computing, automation, and machine learning are among the top current tech trends. This article shares a bit about the companies that are blazing the trail in these exciting fields. CK

Article written by Joyce Wells originally appeared in Database Trends and Applications on August 8, 2018.

Experts may disagree on the precise definitions of artificial intelligence (AI), cognitive computing, machine learning (ML), or natural language processing. However, there is no debate about whether the proliferation of sensors and mobile devices, the rapid increase in data volume, and the heightened need for rapid decision making is fueling a demand for smarter solutions and greater automation.

According to a 2018 McKinsey Global Institute report, the current projected global impact of adopting what it calls AI is $3.5 trillion to $5.8 trillion annually globally. The McKinsey Institute has identified 400 use cases for AI across 19 industries.

Furthermore, Deloitte Global predicts that by the end of 2018, the number of implementations and pilot projects using machine learning will double compared with 2017, and the number will have doubled again by 2020. In addition, with enabling technologies such as ML application program interfaces (APIs) and specialized hardware available in the cloud, these advances will be generally available to small as well as large companies.

Worldwide spending on cognitive and artificial intelligence systems is forecast to reach $57.6 billion in 2021, according to a recent update of the “Worldwide Semiannual Cognitive Artificial Intelligence Systems Spending Guide” from IDC. With many industries aggressively investing in cognitive and AI solutions, spending is expected to achieve a compound annual growth rate (CAGR) of 50.1% over the 2016-2021 forecast period, the company says.

And, while the focus on machine learning (ML) “may seem like an overnight development,” according to a recent survey conducted by MIT Technology Review Custom and Google Cloud, the use of this technology has been growing steadily since the emergence of big data. “ML is beginning to deliver on the potential created by big data and analytics by turning raw data into useful, predictive tools for business. Innovation-minded business leaders are embracing ML as ‘the next big thing’ and have already crafted ML strategies and initiatives that promise real benefits and return on investment (ROI).”

To help increase understanding about this important area of information technology and how it is being leveraged in solutions and platforms to provide business advantage, DBTA and Big Data Quarterly present the 2018 list of Cool Companies in Cognitive Computing starting below and continuing through the following three web pages.

ABBYY – A global leader of content intelligent solutions and services, ABBYY offers a complete range of AI-based technologies and solutions to help transform business documents and content into business value.

Accenture – Driving innovation to improve the way the world works and lives, Accenture provides a broad range of services and solutions in strategy, consulting, digital, technology and operations, and works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders.

Amazon AI services – With ML algorithms used in many of Amazon’s own internal systems and core to the capabilities its customers’ experience—including path optimization in fulfillment centers,’s recommendations engine, and the retail experience Amazon Go—the company’s goal with Amazon AI services is to  share its learnings and ML capabilities as fully managed services.

Attivio – A cognitive search and insight platform company that enables Fortune 500 enterprises to answer the most complex questions, Attivio puts search at the core of every enterprise, integrating every data source into a single always-learning platform.

BlueData – With BlueData’s container-based software platform, enterprises can quickly deploy multi-node environments for AI use cases with TensorFlow and other ML tools. BlueData makes it easier, faster, and more cost-effective to innovate with AI, ML, and big data analytics—either on-premises, in the cloud, or in a hybrid architecture.

Kumar Sreekanti
Co-Founder and CEO

BlueData AI / ML Accelerator

The promise of AI has been around for several decades, but AI only recently started to become more widely adopted in the enterprise. Read on.

BMC – A provider of IT solutions for the digital enterprise, BMC recently introduced the Helix Cognitive Service Management (CSM) offering, integrating cognitive technologies such as  AI and ML into traditional IT service management,  and enabling end-to-end CSM built for containerized microservices-based architectures multi-clouds.

C3 IoT – While delivering a comprehensive platform as a service (PaaS) for rapidly developing and operating big data, predictive analytics, AI/ML, and IoT software as a service (SaaS) applications, C3 IoT also offers a family of configurable and extensible SaaS products developed with and operating on its PaaS.

Cloudera – Founded in 2008, Cloudera empowers people to transform complex data into clear and actionable insights, Cloudera provides a modern platform for analytics optimized for the cloud.

Cogitai  – Dedicated to building AIs that learn continually from interaction with the real world, Cogitai’s goal is to build the brains, i.e., the continual-learning AI software that will enable everyday things that sense and act to get smarter with experience.

CognitiveScale – Providing augmented intelligence software that emulates and extends human cognitive function through the pairing of people and machines, CognitiveScale helps companies maximize the value of AI.

Darktrace – Founded in 2013 by mathematicians from the University of Cambridge and government cyber intelligence experts in the U.S. and the U.K., Darktrace, which has deep expertise in mathematics and ML, as well as operational experience defending critical national assets, empowers organizations to defend their systems against the most sophisticated cyberthreats.

Databricks – Founded by the creators of the Spark research project at UC Berkeley, which later became Apache Spark, Databricks provides the Unified Analytics Platform powered by Apache Spark that aims to lower the barriers for enterprises looking to integrate AI into their business, by unifying data and AI technologies into one workflow.

Dataiku – Providing a collaborative and team-based user interface for data scientists and beginner analysts, a unified framework for both development and deployment of data projects, and access to features and tools required to design data products from scratch, Dataiku enables users to apply ML and data science techniques to raw data to build and deploy predictive data flows.

DataRobot – A pioneer in automated ML, DataRobot provides an automated ML platform that empowers business analysts and data scientists of all skill levels to build and deploy accurate ML models in a fraction of the time of traditional modeling methods.

Datumbox – Seeking to eliminate the complex and time-consuming process of designing and training ML models, Datumbox offers an open source ML framework written in Java that allows the rapid development of ML and statistical applications along with an easy-to-use API.

Digital Reasoning – A provider of AI technology that understands human intentions and behavior, Digital Reasoning provides an AI platform to automate key tasks and uncover transformative insights across vast amounts of human communications for many of the world’s leading organizations and government agencies.

Figure Eight – Offering a “Human-in-the-Loop” AI platform for data science and ML teams, the Figure Eight software platform trains, tests, and tunes ML models to allow AI to work in the real world to support a wide range of data types—text, image, audio, video—and use cases including autonomous vehicles, intelligent chat bots, facial recognition, and others.  – Transforming the use of AI with software with its open source ML platform, H2O, partners with leading technology companies such as NVIDIA, AWS, Azure, and Google, and, in June 2018, announced a strategic global partnership that combines IBM POWER Systems and H2O Driverless AI to address the AI and ML demands of enterprises.

IBM – Informed by IBM’s rich industry expertise, Watson, IBM’s branded AI platform, provides organizations with the ability to build models from scratch, or leverage its APIs and pre-trained business solutions so they can integrate AI into their most important business processes.

iManage – Transforming how professionals in legal, accounting and financial services get work done by combining the power of AI with document and email management, iManage automates routine cognitive tasks, provides powerful insights, and streamlines how professionals work, while maintaining security and governance over critical client and corporate data.

– A global provider of next-generation digital services and consulting, Infosys supports enterprise clients with an AI-powered core that helps prioritize the execution of change and empowers the business with agile data at scale to deliver high performance.

– Furthering development and delivery of autonomic and cognitive technologies, Ipsoft’s mission is to power the world with intelligent systems, eliminate routine work, and free human talent to focus on creating value through innovation in order to ultimately increase quality and speed of service, drive up productivity, enable profitable growth, and reduce risk.

– With the belief that the proper application of AI and ML can produce a safer world where existing cyberthreats are mitigated without human intervention, JASK’s engineering and data science teams apply the knowledge from decades of hands-on experience to drive advancements in autonomous technology to address the gaps that restrict security modernization efforts.

MapR – Providing a data platform for AI and analytics, MapR enables enterprises to inject analytics into their business processes to increase revenue, reduce costs, and mitigate risks that helps address the data complexities of high-scale and mission-critical distributed processing, across cloud to the edge, IoT analytics, and container persistence.

Nara Logics – Founded in 2010 with a mission to help people find what matters amidst vast quantities of data, Nara Logics provides what it calls “synaptic intelligence” for real-time, context-relevant recommendations that also makes context-sensitive adjustments to help companies make smarter decisions.

OpenText – Powering digital transformations to support the intelligent and connected enterprise, OpenText allows companies to digitize processes and supply chains and discover value in their information with analytics and AI, by offering greater business insight to make data-driven decisions for success.

Oracle – In 2017, Oracle outlined its vision for an autonomous enterprise, unveiling the world’s first Autonomous Database, and continues to build on that initiative, with the recent introduction of next-generation Oracle Cloud Platform services, including Oracle Mobile Cloud Enterprise, Oracle Data Integration Platform Cloud, and Oracle API Platform Cloud, with embedded AI and ML.

Progress – Offering a platform for developing and deploying mission-critical business applications, Progress empowers enterprises and ISVs to build and deliver cognitive-first applications that harness big data to derive business insights and competitive advantage.

RapidMiner – Providing a software platform for data science teams that unites data prep, ML, and predictive model deployment, RapidMiner helps organizations build ML models and put them into production faster than ever, using its lightning fast visual workflow designer and automated modeling capabilities.

Saffron Technology (part of Intel) – Inspired by human reasoning, Intel Saffron Cognitive Solutions seeks to extend the capabilities of the human brain to use information to anticipate what will happen next and how to prepare for it, at scales that far exceed human memory, enabling a comprehensive landscape of actionable knowledge for faster, more informed and more accurate decision making.

SAP –Supporting businesses and public sector organizations in their digital innovation strategies, SAP provides Conversational AI that comes with NLP technology, and has created the SAP Leonardo ML Foundation that connects developers, partners, and customers to ML technology through the SAP Cloud Platform.

SAS – With AI an integral part of SAS software for years, SAS now provides AI solutions across the SAS portfolio that incorporate ML, computer vision, natural learning, NLP, and forecasting and optimization technologies to help unlock new possibilities.

Sinequa – An independent software vendor providing a cognitive search and analytics platform for Global 2000 companies and government agencies, Sinequa combines search with advanced NLP, ML, and deep learning algorithms to extract insight from both structured and unstructured data for users in their work context.

SparkCognition – With a mission to build AI systems to advance the most important interests of our society, SparkCognition helps customers to weave AI into the fabric of their organizations so that human-level intelligence can be applied at machine scale to optimize operations and find new solutions to old problems.

Tamr – Founded in 2013 by Vertica’s founding CEO Andy Palmer and Turing Award winner and MIT professor Michael Stonebraker, Tamr provides a patented software platform for enterprise-scale data unification that combines ML with human expertise—fusing the power of ML with the experts’ knowledge of their own data to automate the rapid unification of data silos at scale.

TIBCO – With data visualizations and predictive analytics, reporting, and dashboards embedded within key applications, and streaming analytics combining real-time connectivity with analytical insights, TIBCO provides a wide range of analytics technologies to enable digital business initiatives.

Zylotech – Providing a self-learning customer data platform powered by AI, Zylotech helps automate complicated and time-consuming work involved in analyzing and executing marketing, uses the force of AI and ML to establish how best to engage with customers, and  offers a data analytics dashboard to enable an interactive, visual understanding of customers.

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