5 IBM BUILDING A THOUGHT LEADERSHIP SERIES FOUNDATION TO SUPPORT THE RISE OF COGNITIVE COMPUTING EMERGING TECHNOLOGIES in COGNITIVE COMPUTING and MACHINE LEARNING 2017 | OCT THOUGHT LEADERSHIP SERIES | October 2017 2 THE NEW ERA OF COGNITIVE COMPUTING AND MACHINE-LEARNING A new era of cognitive computing is unfolding and its impact is already being felt across industries, from preventative maintenance at manufacturing plants and patient diagnosis at hospitals, to the rise of sophisticated chatbots ready to assist us across the connected world. According to estimates, the market around cognitive computing products and services will grow to $46 billion in just a few years and intelligent applications will spread like wildfire transforming our lives at work and at home. The goal of cognitive computing is straight- tive computing systems must understand con- operating expenses. There were also a pleth- forward: to simulate human thought processes text. They can identify and extract contextual ora of challenges, from harnessing new data in a computerized model. Through a variety elements such meaning, syntax, time, location, sources, to delivering real-time analytics. On of established technologies such data mining, appropriate domain, regulations, user profile, the road ahead, expect to see a lot of cases pattern recognition, and natural language task, and goal to present information that is where IoT and cognitive computing technol- processing, we can build systems that mimic appropriate for an individual or dependent ogies are combined to deliver new insights. how the human brain works. These systems application. The advantage that machine learning offers rely on machine learning and deep learning To fully deliver value, these systems also organizations—the ability to automatically algorithms to automatically learn and adapt need to be able to easily interact with both their build models that can analyze huge volumes from experience without being explicitly pro- human and machine colleagues. For humans, of data and deliver lightning fast results—has grammed. The experience we provide cogni- that typically means speech and text. The rise also led to a growth in the availability of both tive computing systems is data. of cognitive business applications that deliver commercial and open source frameworks, li- Cognitive computing systems need massive a more engaging user experience is a key de- braries and toolkits for engineers. These re- volumes and varieties of data. The more data, velopment in this area, as well as continued sources are democratizing access to machine the more the system can learn, based on previ- advancements in natural language processing. learning for companies big and small and will ous computations, to produce accurate results For machines, the most exciting area is the continue to play a pivotal role in the spread of and predictions. Meeting the scalability and Internet of Things. According to estimates, the machine learning throughout businesses. performance requirements of cognitive com- IoT universe is on track to exceed over 25 bil- Ultimately, cognitive computing, along puting systems involves complex data connec- lion devices by 2020. Right now, there are more with machine learning, is about increas- tions and serious processing power and storage things connected to the Internet than people on ing efficiency, productivity, and innovation to support high-speed data exploration. the planet. From home appliances and cars, to via data analytics and automation. Today, Out of necessity, the future of IT infra- light bulbs and livestock, if you can attach a sen- many people associate them with high-pro- structures at many organizations will become sor to it, it can be become part of a universe of file examples like self-driving cars and ro- increasingly hybrid; where existing operational physical objects able to communicate and inter- bots, which bring the subject good publicity. systems on premise are augmented with new act digitally. This connectivity means more data, However, harnessing value from these tech- data sources being stored and analyzed in the gathered from more places, than ever before. nologies is far from the exclusive domain of cloud. The spike in Apache Spark usage this year A recent survey found that 29% of Big billionaire entrepreneurs and Fortune 500 in the cloud is a great example. Moving forward, Data Quarterly readers already have IoT proj- companies. The growth of cloud services, flexible deployment and integration options ects underway. The top reasons cited for im- lower storage costs, more efficient data pro- will be a must-have for big data projects. plementing IoT projects included increasing cessing options and, open source tools offers In addition to their self-learning capabili- new business revenue sources, increasing cus- resources to organizations of all types and ties, in order to mimic the human brain, cogni- tomer and product knowledge, and reducing sizes to get started today. n THOUGHT LEADERSHIP SERIES | October 2017 3 COOL COMPANIES IN COGNITIVE COMPUTING No longer the stuff of science fiction, ABBYY provides intelligent capture, intelligently at the edge and “amplify” process the business uses for cognitive computing optical character recognition, innovative intelligence through self-learning, self- and machine learning today include fields language-based, and artificial intelligence assuring business processes for commerce, as diverse as medicine, marketing, defense, technologies to help businesses take action healthcare, and financial services. energy, and agriculture. Enabling these appli- with information. cations is the vast amount of data that com- Crowdflower offers a platform powered by Attivio’s Cognitive Search and Insight panies are collecting from machine sensors, Microsoft Azure Machine Learning that Platform leverages cognitive capabilities, instruments, and websites and the ability to combines machine learning and humans-in- such as machine learning and natural support smarter solutions with faster data the-loop in a single platform for data science language processing to deliver the most processing. relevant information in context but also teams doing sentiment analysis, search It is also clear that we are still in the early offers the flexibility of manual relevancy relevance, or business data classification. days of cognitive computing and machine tuning to optimize results. learning, and to be sure, there are technical, Darktrace was founded in Cambridge, U.K., political, and ethical considerations to be C3 IoT offers a comprehensive technology in 2013 by mathematicians and machine dealt with before this new wave of solutions stack for the rapid design, development, learning specialists from the University of comes closer to reaching its potential. How- deployment, and operation of next- Cambridge, together with world-leading ever, innovative companies do have products generation IoT applications that unlock intelligence experts from MI5 and GCHQ, and services today to help customers put data-driven insights and transform business to bring transformative technology to the more data to work. processes. challenge of cybersecurity. To help readers gain a greater understand- ing about this emerging area of information Cloudera offers a modern platform for Databricks, the company founded by the technology, the solutions available, and their machine learning and advanced analytics creators of the Apache Spark project, recently role in handling real-world challenges, built on open source technologies, and introduced Deep Learning Pipelines, a library DBTA presents the inaugural list of Cool recently introduced its Data Science to integrate and scale out deep learning in Companies in Cognitive Computing. Workbench, based on the company’s Apache Spark, which has the potential to acquisition of data science startup Sense.io, —Joyce Wells accomplish for deep learning what Spark did to accelerate data science and machine for big data—make it approachable to learning for the enterprise. a much broader audience. Alpine Data enables organizations to create Cogitai is dedicated to building artificial Dataiku, whose name is a portmanteau of a culture of analytics at scale by providing intelligences (AIs) that learn continually from data and haiku, espouses the view that data an integrated analytics platform that brings interaction with the real world, with the goal projects should have “a structured process, a machine learning, data, and people together to of building the brains, i.e., the continual- single flow, from start to finish,” and provides create operational solutions for business users. learning AI software that enables everyday the Data Science Studio (DSS), to enable things to get smarter with experience. scalable data science to any organization. Amazon AI services bring natural language understanding, automatic speech recognition, CognitiveScale offers an augmented DataRobot uses advanced enterprise visual search and image recognition, text-to- intelligence platform and the ENGAGE machine learning automation to enable speech, and machine learning technologies and AMPLIFY products that pair humans users to quickly build and deploy highly within the reach of every developer. and machines so they can “engage” users accurate machine learning models. THOUGHT LEADERSHIP SERIES | October 2017 4 DatumBox offers services available through and triaging the most relevant attacks, and SAP has relaunched SAP Leonardo a REST API, including a large number