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VMblog - 2018 Artificial Intelligence and Machine Learning Predictions from 30+ Industry Experts

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VMblog - 2018 Artificial Intelligence and Machine Learning Predictions from 30+ Industry Experts

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Find out what's going on in the world of #artificialintelligence and #machinelearning in 2018. Read #predictions more than 30 of the industry's leading experts to learn more about #AI Hear from industry thought leaders from companies like Chaos Sumo, Couchbase, Druva, Equinix, Hitachi Vantara, Ixia, Pivot3, SAP, SIOS Technologies, SolarWinds, Splunk, Vonage and more. Make sure to also read the more than 280+ other expert predictions from technologies across #virtualization, #cloudcomputing, #hyperconverged, #IoT, #security, etc. here: http://bit.ly/2DQi2OT at VMblog.com.

Find out what's going on in the world of #artificialintelligence and #machinelearning in 2018. Read #predictions more than 30 of the industry's leading experts to learn more about #AI Hear from industry thought leaders from companies like Chaos Sumo, Couchbase, Druva, Equinix, Hitachi Vantara, Ixia, Pivot3, SAP, SIOS Technologies, SolarWinds, Splunk, Vonage and more. Make sure to also read the more than 280+ other expert predictions from technologies across #virtualization, #cloudcomputing, #hyperconverged, #IoT, #security, etc. here: http://bit.ly/2DQi2OT at VMblog.com.

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VMblog - 2018 Artificial Intelligence and Machine Learning Predictions from 30+ Industry Experts

  1. 1. AppViewX - http://bit.ly/2r8qmo7 WITH AUTOMATION, THE FUTURE OF ARTIFICIAL INTELLIGENCE WILL BECOME MORE TANGIBLE Murali Palanisamy, CTO, AppViewX Artificial Intelligence (AI) was the talk of 2017, with predictions and ideas thrown loftily around by tech pioneers. In 2018 we will see the actual implementation of all these revolutionary ideas. It is no longer just a vision we're aspiring to- it is happening. In fact, major global organizations are already investing millions of dollars in AI. One major reason for the booming growth ofAI is the elimination of manual dependencies and the errors they inevitably spur. In enterprise tech, automation is already playing a major role in removing the need for manual intervention and therefore increasing business agility. However, when coupled with AI, users will introduce the essence of human intelligence that will effectively eliminate step-by- step programming and customization.To stay ahead of the curve,AI integration is a must as its presence becomes more and more tangible every day.
  2. 2. Arcadia Data - http://bit.ly/2HTkE2M HOW AI AND BI WILL FARE IN 2018 Steve Wooledge,VP of marketing, Arcadia Data Artificial intelligence (AI) deserves the same treatment Hadoop and other big data technologies have received lately. If the industry is trying to balance the hype around big data-oriented products, it has to make sure not to overhype the arrival of AI.This is not to suggest thatAI has no place in current and future-looking big data projects, just that we are not at a point in time yet where we can reliably turn business decision-making processes over entirely to machines. Instead, in 2018 the industry will begin to modernize BI with machine assistance rather thanAI-driven tasks.Think of it as power steering versus self-driving cars. Business users will get more direction on how to gain better insights faster, as they don't need to be told what the right insights are. We're so enamored by the idea of AI, but the reality is it's not ready to act on its own in the context of analyzing data for business users. In modernizing BI, we'll also start to see a shift in which organizations will bring BI to the data. BI and big data have hit a bit of a brick wall.Companies have spent a lot of money on their data infrastructures, but many are left wondering why they have to wait so long for their reports. Part of the problem is that companies are capturing their data in a data lake built on a technology like Hadoop, but they are not taking full advantage of the power of the data lake. Rather than ideally moving operations to the data, businesses move data from the lake to external BI-specific environments. This process of "moving data to the compute" adds significant overhead to the analytics lifecycle and introduces trade-offs around agility, scale, and data granularity. Next year and moving forward, we'll start to see more companies bringing the processing to the data, a core tenet of Hadoop and data lakes, with respect to their BI workloads.This will speed the time to insight and improve the ROI companies see on their big data infrastructure investments." Dale Kim, senior director, products and solutions, Arcadia Data
  3. 3. BackupAssist - http://bit.ly/2r2kxbH DATA BREACHES AND HACKERS ON THE RISE Linus Chang, Founder and CEO, BackupAssist The positive trends in artificial intelligence (AI) adoption will continue across the board, such as businesses using machine learning to process, trend and analyze information. In particular, I believe the next stage will be an AI evolution in dealing with customer interactions. Of course, anything that can be used for the positive can also be used for the negative. In 2018 we may see the use of these same automated technologies-AI and machine learning-to create, evolve and deploy more virulent forms of ransomware. In late 2017, we saw weaponized AI that simulate spear-phishing attacks that can lure in victims with a higher success rate and output than human hackers.This means the age of ransomware-and the threat to all businesses-will only get worse. Because of this and other factors, we are confident that data breaches, and specifically data leaks, will continue to increase, and I fear that more and more companies will be hijacked and blackmailed. Ransomware will present an ongoing risk to all businesses and organizations, but this blanket risk is only one aspect of the problem.
  4. 4. Chaos Sumo - http://bit.ly/2HX90Ek FEEDING THE ARTIFICIAL INTELLIGENCE DRAGON IN 2018 Information Needs Storage Much of what makes AI possible is the "amount" of data used to teach or train the algorithms. In other words, Artificial Intelligence is as good as the data it can consume.There are times where an algorithm does not have access or time to consume all of the information it could use to make intelligent decisions. As a result, storage is key to the future of AI systems. International Data Corporation (IDC) has suggest that by 2020 each person on earth will create roughly 2MB of data per second, reaching upward of 44 zettabyte. And as AI systems take hold and start creating their own data, I imagine that these numbers will easily be surpassed. Gartner has even suggested there will be more than 20 billion IoT devices in existence by 2020. And if they are allAI enabled, just imagine the amount of information generated. The answer to this tsunami of data is storage. Storage that is simple to use; elastic; scalable in nature; and extremely cost efficient. Increasingly, object storage is considered the answer to this deluge of information.Whether in the cloud, on- premise, or inside devices, object storage has all the requirements to take AI into 2018. Thomas Hazel, Founder, CTO, and Chief Scientist of Chaos Sumo
  5. 5. Couchbase - http://bit.ly/2I2i5ck AI DOESN'T GO MAINSTREAM, BUT BUSINESSES LAY AI GROUNDWORK Ravi Mayuram, SVP of engineering and CTO at Couchbase Today AI is more of a trendy buzzword than practical reality, and it's difficult to execute becauseAI is only as good as its data.While data integrity still varies within the enterprise, true implementation ofAI is still a concept that will not come to fruition for a few years. However, we've seen early stages of machine learning applications in verticals such as advertising and retail. In the years ahead, we'll see more industries, including industrial IoT, digital health and digital finance, begin taking advantage of machine learning within applications to provide more meaningful user experiences.Throughout this transformation, the database will play an instrumental role by accommodating rapidly-changing data at scale while keeping big data sets reliable and secure.
  6. 6. Darktrace - http://bit.ly/2Kgvi1W CYBER INTELLIGENCE EXPERT SHARES PREDICTIONS FOR CYBERSECURITY IN 2018 Justin Fier, Directorof Cyber Intelligenceand Analysis at Darktrace Targeted, machine-speed attacks powered by AI are emerging AI won't just be used by the good guys. In 2018, we will start to see the emergence of sophisticated threat-actors harnessing AI technology to launch targeted, automated, and advanced campaigns. Imagine a highly sophisticated piece of malware that leverages AI to mimic writing styles, review appointments, and send "directions" for an upcoming meeting to the victim.The email is so context-specific that targets instantly click on emails, unknowingly downloading dangerous attachments.The future of cyber defense will be machines vs machines on the battleground of corporate networks - defenders need to be ready. AI won't just be predictive - it will fight back In 2017, AI met the challenge of identifying never-before-seen cyber-threats by understanding ‘self' for corporate networks. In 2018, those networks will become self- defending, uniquely capable of taking precise, targeted action to neutralize cyber- attacks as they emerge. 2018 will truly be the year of machines fighting machines within organizations - may the strongest algorithms win.
  7. 7. Datadog - http://bit.ly/2FjKwzF ROBOT HELPERS Jason Yee, Technical Evangelist, Datadog "AIOps" will not replace DevOps. Whether the invented term intends to replace developers with AI or make operations engineers obsolete, it's safe to say that robots will not be taking your job in 2018. Nor will they take your job in any foreseeable future if your job deals with complex systems and requires critical thinking (as all jobs in technology do).AIOps will not happen in 2018 and likely will never happen in the fanciful, fully autonomous way that many like to dream about. Computers are fantastic at doing menial tasks and finding patterns. Just as automation has helped us reclaim time once wasted on tasks likeOS installs and configuration, machine learning will help us reclaim time spent orienting ourselves.At Datadog we've already used it to help customers find anomalies, outliers and even forecast potential issues. In 2018, we'll see even more machine learning-provided context to help both technical and non-technical roles make more informed, context- aware decisions.We will even see more organizations use it to automate simple decision making and trigger basic remediation.
  8. 8. Datical - http://bit.ly/2I1ybmB ARTIFICIAL INTELLIGENCE IS THE NEXT BIG THING IN DEVOPS Robert Reeves, co-founderand CTO, Datical Artificial intelligence (AI) holds great promise for DevOps. As humans, we learn from trial-and-error and we share our tribal lore with less experienced members of our tribe.That is exactly the promise ofAI and machine learning.We prize our database administrators (DBAs) with 20 years of experience because they have vast experience in what has (not) worked in the past and because they can see patterns in the issues they deal with daily. However, humans are limited in amount of data they can consume. Enter machine learning: if we are able to collect vast amounts of data on application change and its corresponding impact to our customers and systems, then it's known problem to identify patterns in that data. In turn, we can prevent bad behavior and encourage good behavior, all without having to wake up at 2 a.m. to respond to an on-call issue.
  9. 9. Druva - http://bit.ly/2r2E2jC MACHINE LEARNING WILL EVOLVE FROM THE NEXT BIG THING TO BUSINESS AS USUAL Rick Powles, Regional VP, EMEA, Druva There was a rash of artificial-intelligence (AI) product launches from the major software companies in 2017, all with the aim of demonstrating how the use of machine learning andAI will become embedded within applications in the future.While this was great for raising awareness of the potential for AI, the fact that most of the work will be hidden behind familiar UIs will mean that, for the most part, all of these impressive advancements will quickly become business as usual where and when they are deployed. Should this worry us? I don't think so. Like all technology projects,AI and machine learning will have to start small and prove themselves. Using changes in files and data to spot unauthorized activity or the start of a ransomware attack will be a great first step towards improving data management. However, while these services will be useful for IT teams, they will quickly be taken for granted. Over time, more impressive projects will grow based on these foundations, helping companies improve their performance. However, the value will be created through better data-management services and quality information decisions that are made at the start of this journey to the public cloud. Dave Packer, VP, Product and Alliance Marketing, Druva
  10. 10. Easy Solutions - http://bit.ly/2r5zQ2n ARTIFICIAL INTELLIGENCE - WHOSE SIDE IS AI ON? Maria Lobato, Directorof Marketing, Easy Solutions, a Cyxtera Business As machine learning andAI technologies are providing great advantages and benefits for organizations and individuals, criminals are also taking advantage of similar technologies. AsVilladiego puts it: "The problem is that the same techniques that create incredible conveniences for end users are also being used to create chaos and to harm users and businesses." Easy Solutions' Chief Data Scientist, Dr.Alejandro Correa, agrees. According to Correa, one of the biggest threats that lays ahead is when cybercriminals start using AI generated phishing sites and malware that are designed to avoid detection. Further, as criminals gain a better understanding of how machine learning works, they will start to modify their attack techniques and malicious software to outperform the capabilities of some algorithms.This is especially worrisome for players that are not using or do not have access to large datasets to train their AI algorithms on, as it is easier for criminals to inject an anomaly and damage the training procedure of a machine learning algorithm when only a shallow data set is being used.
  11. 11. Entuity - http://bit.ly/2Ju8meo AI WILL CONTINUE TO GROW Lee Walker, CTO at Entuity Artificial-Intelligence seems to be a broad theme in 2018 across industries - and while the use of AI concepts vary pretty widely, there is no doubt that the days of dumb software that require a lot of manual IT intervention are numbered. This is true for data management as well - by analyzing data usage and growth across storage, intelligent data management solutions can adapt to the nature of the data and its usage in how they automate policies. When done correctly, such automation is subordinate to IT and is driven by policies that are set by humans at a high level, but can self-correct and adapt to patterns in the environment. For instance, a data management solution that moves data can adaptively move larger files before smaller files or when the network is in use by others, slow itself down, etc. By adjusting to the nature of the data and the environment, the system requires less manual management.
  12. 12. Equinix - http://bit.ly/2vNSEJ0 ARTIFICIAL INTELLIGENCE-BASED APPLICATIONS SURGE INTO THE MAINSTREAM Artificial Intelligence (AI) technology has existed for six decades, but it's just now going mainstream.Why?The advent of big data, AI-focused processors and deep-learning algorithms has enabled AI to power advances like smart homes, factories and cars, which have broad appeal. In September 2017, IDC forecasted that worldwide revenues for cognitive and AI systems in 2017 would reach $12.0 billion, and we see it making even deeper inroads into the mainstream in 2018. But AI systems need to interpret and fuse data from multiple sources, and they also need to be distributed, with model building happening in clouds and model deployment based at edge locations to satisfy real-time processing requirements. Regulatory bodies are also becoming more interested in ensuringAI apps comply with security and data residency laws. Kaladhar Voruganti, VP, Technology Innovation and Senior Fellow at Equinix
  13. 13. Flowroute - http://bit.ly/2JvxuS4 AI AND MACHINE LEARNING WILL TRANSFORM TELECOM AS WE KNOW IT William King, Chief Technology Officer at Flowroute With its ability to manipulate data and find patterns to help inform business decisions, machine learning has been one of the biggest transformative forces in IT this year.We predict in 2018 that the magical perception of machine learning will carry over to the IP communications arena, enabling carriers to provide better customer service, confirm network status and more effectively mitigate and reroute network outages. For example, by examining call data usage patterns, carriers could make smarter decisions on how to use which network when, based on usage spikes and other factors. Software- based carriers may also gain a competitive leg up on legacy telcos since physical switches and fiber networks can't leverage the power of machine learning software-fueled insights.
  14. 14. Hitachi Vantara - http://bit.ly/2vRfKyr THE RISE OF AUTOMATED MACHINE LEARNING Brad Surak, Chief Product and Strategy Officer, Hitachi Vantara In 2018, we'll see more Artificial Intelligence (AI) techniques pushing the boundaries between reinforcement learning, unsupervised learning and autogenerated training-especially in IoT environments where algorithms and bots will enable edge devices to learn on their own.With a shortage of talented data scientists with the advanced skillsets to label training datasets from sensors and other systems for AI, machine learning (ML) or deep learning (a messy, expensive and time-consuming process in itself), a supervised learning model is impractical.The bandwidth required to submit data from the edge, while enabling programmed, unsupervised learning on real-world data, is still expensive, but automated machine learning can reduce costs.While automated ML is more efficient, this concept raises other, more ethical questions around how algorithms make decisions and who is responsible for those decisions and their consequences.
  15. 15. iManage - http://bit.ly/2KfCA62 AI PREDICTIONS FOR 2018 Peter Wallqvist, VP of Strategy, iManage Practical AI Continues ItsTake Over In 2018 companies will increasingly realize that, rather than being a vague cure for anything and everything, AI's value comes from its ability to solve practical, real-world business problems. In fact,AI will actually become less visible in many cases, as it is more tightly integrated into the everyday applications that people use everyday. Without even realizing it, they will find that AI enables them to be more productive, and frees them to spend more time on strategic business initiatives rather than tedious tasks. More AI technologies will no longer be called AI Just as previous AI technologies like GoogleTranslate,Alexa's speech recognition and Netflix's recommendation engine are no longer perceived to be AI, newer AI technologies, such as document classification and information extraction, will become so integrated into our applications that they will no longer be perceived as AI either. Moreover, as AI technologies continue to proliferate, we will see people speaking about AI in more specific and tangible ways.This is a sign that technology is reaching practicality and maturity as it is increasingly used by a large general audience vs. niche ones.
  16. 16. Io-Tahoe - http://bit.ly/2r2gA60 BIG DATA, ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING WILL CONTINUE TO CHANGE OUR LIVES… Oksana Sokolovsky, CEO, Io- Tahoe The amount of data generated will only continue to grow with more devices, connected via the Internet ofThings (IoT). Data growth will continue to be one (of the many) drivers behind adoption of AI in 2018. With that we foresee business and IT executives becoming increasingly reliant on AI/ML-driven technologies, as they navigate the competitive landscape to gain advantages from improved business efficiency and performance. But first it starts with data discovery.... Before leveraging the actionable and valuable insights, employees must first discover the data. It's simply not possible to manage data that is only partially documented, and undertaking the discovery manually is not feasible either. Automated detection and discovery of data relationships is critical to documenting, understanding and managing the data, and thus protecting it.To do this, employees will continue to utilizeAI and ML, as only these innovative technology solutions will help increase productivity and save time. We are robot-free for now, but AI/ML data discovery solutions are set to take pace in 2018!
  17. 17. ioFABRIC - http://bit.ly/2Kjfawz YOU CAN CALL ME AI Steven Lamb, co-founderand CEO, ioFABRIC No, not "al," "ai." Artificial Intelligence, machine learning, intelligent automation, whatever you call it, it's only getting bigger. It's already in our living rooms in the form of Amazon Alexa's simple AI that learns as we make requests. In the data center,AI's increasing presence will reduce manual setup and administration, minimize the potential for human error, and ultimately improve operations - and operational costs. I am especially keen on a branch of AI called swarm intelligence or emergent behavior, largely mimicking nature, which uses logic to adapt and then apply rules, even to complex environments.The result is technology that is self-configuring, self-healing, efficient, and cooperative.We're at the early stages of seeing AI in commercially available enterprise technology, and I think vendors will tout it with great fanfare in 2018.
  18. 18. Ixia - http://bit.ly/2Hv80DL AI FINALLY RELEASES THE VALUE OF SOFTWARE-DEFINED EVERYTHING Jeff Harris, CMO at Ixia, a Keysight Business Artificial intelligence (AI) is definitely a contender for the top tech buzzword of the year, and for good reason. It has enabled great strides in how businesses handle data everywhere from their security teams to their HR departments.Adoption and innovation in this space is not going to slow down anytime soon. The next big area where we will see investment in AI is the networking space. SD- everything, cloud, and globalization have sidelined the hands-on operating practices IT teams have traditionally used to maintain their networks. Innovative providers are now building machine learning andAI into their network platforms, effectively tailoring network performance as needed, to meet the requirements of the services and applications the network carries.As this trend continues, enterprises will need to maintain the same level of visibility into packet-level data they had with hardware- based networking to take advantage of the possibilities.
  19. 19. Komprise - http://bit.ly/2HzsuLw ANALYTICS ENABLES INTELLIGENT AUTOMATION OF DATA MANAGEMENT POLICIES Krishna Subramanian, COO, Komprise Artificial-Intelligence seems to be a broad theme in 2018 across industries - and while the use of AI concepts vary pretty widely, there is no doubt that the days of dumb software that require a lot of manual IT intervention are numbered. This is true for data management as well - by analyzing data usage and growth across storage, intelligent data management solutions can adapt to the nature of the data and its usage in how they automate policies. When done correctly, such automation is subordinate to IT and is driven by policies that are set by humans at a high level, but can self-correct and adapt to patterns in the environment. For instance, a data management solution that moves data can adaptively move larger files before smaller files or when the network is in use by others, slow itself down, etc. By adjusting to the nature of the data and the environment, the system requires less manual management.
  20. 20. Mist - http://bit.ly/2HVHBSU VIRTUAL WIRELESS ASSISTANTS WILL BECOME A REALITY Bob Friday, CTO and co-founderat Mist Today,AI is making IT organizations smarter, faster, and more efficient than ever before - and before we know it, AI will be at the core of every technology industry sector -- whether it be cloud, big data, analytics, networking, storage, or security. In 2018, I foresee AI accelerating across even more industries and making major advancements to the already thriving wireless industry.We'll see jobs completed faster and more efficiently with the introduction of new virtual assistants who will be able to answer questions on par with domain experts and allow users to proactively identify and fix problems and predict future events more quickly and reliably. Imagine a virtual wireless assistant that combines quality data, domain expertise and syntax (metrics, classifiers, root causes, correlations, and ranking) to provide predictive recommendations on how to avoid problems and actionable insights on how to remediate existing issues. There are decades of innovation ahead for AI.The computing power that exists today makes things possible that couldn't be done five years ago.With new applications popping up every day, we are at the forefront of a new era of machine/human interaction that will completely transform the way we live, work and play on par with the internet.While we are a long way from having machines replace IT administrators, virtual wireless assistants are now a reality.
  21. 21. Mojo Networks - http://bit.ly/2FjRVir INTELLIGENT NETWORKS THAT INCORPORATE ARTIFICIAL INTELLIGENCE WILL DEPEND ON THE CLOUD Lisa Garvey, VP, Marketing, Mojo Networks If your WiFi network was "intelligent" enough to solve problems before they even became problems, imagine how many angry mobs of disgruntledWiFi users who just got dropped from aVOIP call or had to apologize for the poor connection during a customer demo could be prevented from bombarding the IT helpdesk. For the network to become this smart, Artificial Intelligence (AI) is required, which, in turn, depends on big data. For example, if you program a computer to play chess, and you only give it one game and one outcome as sources of input, the computer will be able to win in some scenarios. But to teach the computer to play brilliantly, to win against the world's top chess masters, you need to give it enough data to compute all of the risks and likely outcomes. Similarly, sophisticated algorithms are required for wireless networks that incorporate AI to make real-time decisions and automate troubleshooting.That level of advanced insight and intelligence requires access to massive amounts of data.And enormous quantities of data, as well as nearly unlimited storage, can only be found in the cloud.
  22. 22. Ormuco - http://bit.ly/2Fllhga APPLICATIONS HEALING, REPAIRING AND TROUBLESHOOTING WILL BE ENHANCED BY ARTIFICIAL INTELLIGENCE (AI) Orlando Bayter, Founderand CEO, Ormuco IT companies today are keenly focused on automation and scalability of applications, driven by the need to reduce time-to-market and rapidly scale services to ultimately elevate the customer or end-user experience.Therein lies the attraction of cloud. However, the proliferation of applications on cloud platforms has created a challenge for system administrators-monitoring, maintaining and repairing this burgeoning portfolio of applications. And consider for a moment what is coming down the pike: a Cretaceous bloom of connected devices and therefore the number of IoT applications will soon swell, connecting billions of devices.There simply aren't enough system administrators in the world to handle that workload in a timely way. This challenge will be addressed with artificial intelligence (AI).AI will be used within cloud ops toolsets not only to intelligently supervise applications using log file data to trigger reparations, but also to deliver unsupervised "self-learning" in which the system will seek out, consider, and "thoughtfully" apply solutions to hardware and software issues.
  23. 23. Pivot3 - http://bit.ly/2KjbxXt LOOKING TOWARDS SELF-ORGANIZING SYSTEMS OF INTELLIGENCE Bruce Milne, Vice President and Chief Marketing Officer at Pivot3 2018 will be not only be about multi-premise, multi-cloud orchestration, but also about the orchestration of power, speed, efficiency and intelligence within the platform itself. We'll see more compute to power larger volumes of data; faster data access and timely decision making; cost optimization and effective resource management; and autonomous capabilities and programmability. Self-organizing systems will also emerge at the edge - think self-driving cars, routing congestion, smart homes, military and genetics applications, drones, and supply chain - which will place an onus on the evolution of infrastructure agility to become its own continuously optimized system of intelligence. In the next year and beyond, we'll not only see advances in AI, but also in the development of collective intelligence (CI) when exploring the development of integrated system architectures.As systems of intelligence become more autonomous and as cloud computing systems are designed with the goal of reducing their own complexity to select the most optimal outcomes, these inherently intelligence-based technologies will alter the competitive landscape and fundamentally change how IT drives business outcomes.
  24. 24. Pramata - http://bit.ly/2vPGGPn AI WILL NOT STAND ALONE Pedram Abrari, CTO, Pramata In 2017, AI was the hot new technology. In 2018, AI will become an embedded part of other hot technologies and products, instead of standing on its own.Think of it like the path that voice recognition traveled. Nobody buys voice recognition on its own. But we do buy products like Google Home, Amazon Echo and Apple iPhones that seamlessly embed voice recognition to perform their functions and appeal to consumers. Companies like Facebook that use AI successfully have already learned how to integrate AI into their internal businesses. In the year ahead, more enterprises will begin to leverage AI for different uses, such as empowering employees to leverage AI to improve job performance and business outcomes.On the consumer side, look for many products to include embedded AI in 2018 and 2019, particularly from the wide range of companies who acquired or built AI technology in 2017.
  25. 25. Rainforest QA - http://bit.ly/2KheGHp TAKING A LOOK BACK AND FORWARD IN THE WORLD Derek Choy, CIO, Rainforest QA In 2017, AI and machine learning adoption failed to meet the hype. This isn't necessarily a surprise, but it is noteworthy due to the fierce debate over the last year. Prominent CTOs, CIOs and others, such as Elon Musk and Stephen Hawking wondered if AI would "take over," and discussion raged on how robots could uproot jobs en-masse and how people and companies can protect themselves against the "dangers ofAI." Despite this, progress and development in AI did not materialize as expected. In the enterprise,AI and machine learning began adoption, but not at the scale and extent predicted. In 2018, AI will help companies scale and will take on a higher percentage of work. In 2018, business leaders will push to make the business run more efficiently and will turn to AI and machine learning to help. Companies will also turn toAI to help scale and do jobs instead of adding headcount.We will see AI developments and research move from the scientific/abstract concept phase to more practical.As a result, enterprises will use AI and machine learning to push the limits of maximum efficiency -- more work will be completed byAI or machine learning.
  26. 26. SAP S/4HANA Cloud - http://bit.ly/2Kdp1nP BIG DATA & ANALYTICS INVESTMENT WILL GROW Christian Pedersen, Chief Product Officer and SVP, SAP S/4HANA Cloud A top priority for any company embarking on their digital transformation journey in 2018 will be quality data, and more specifically, access to real-time data in which end- users can pull actionable results from.There will be more focus on the data-driven organization, where internal, external, structured or unstructured data will provide crucial insights for new innovations and strategies. Data-driven analytics will prove to be advantageous in 2018, so companies will need the tools to manage, govern, analyze and harvest data accordingly. As we look ahead into 2018, AI and machine learning will play a growing role in not just automating tasks, but using deep learning to take on activities that free-up workers time to focus on more complex projects that require human intervention. Additionally, digital assistant devices will start to take on a completely new role in supporting the next generation workforce.As companies continue breaking down the barriers to IT - specifically when looking at actionable data insights across organizations - these digital assistants serve as a powerful tool to simplify access and analysis for the digital workforce, helping work to be completed more efficiently and intelligently.
  27. 27. SIOS Technologies - http://bit.ly/2vNYhqC INCREASED USE OF MACHINE-LEARNING BASED TOOLS Jerry Melnick,President and CEO, SIOS Technology Corp. IT managers cannot continue to oversee the increasingly complex and data-intensive environments of today's IT infrastructure manually. New machine-learning-based tools are providing high-efficiency, automated solutions to help them find root causes of performance and availability issues and eliminate wasted resources. Sophisticated machine learning solutions learn the patterns of behavior between related components in the cloud infrastructure over time.They correlate application performance issues and failovers to changes in the infrastructure and apply causality algorithms to determine the cause with remarkable accuracy and precision.These tools also provide important information for helping IT teams right-size their virtual and cloud environments to meet their RTO/RPOs and SLAs without over spending.
  28. 28. SolarWinds - http://bit.ly/2JuGLK0 AUTOMATION ANXIETY WILL RELAX AROUND AI & MACHINE LEARNING Patrick Hubbard, Head Geek and technical product marketing directorat SolarWinds To date, much of the noise surrounding AI and automation has been around how these tools and technologies could jeopardize job functions currently being held by people.This fear, uncertainty and doubt around the "next big thing" in technology is common in any new cycle of rapid adoption.Consider the Industrial Revolution: the introduction of assembly lines seemed poised to reclaim countless jobs. Instead, the nature of those jobs simply adapted to the needs of new technology-even giving way to the emergence of new skills and jobs such as machine maintenance, servicing, etc. While this anxiety is not without cause, 2018 will mark a turning point in the perception of AI and automation from foe to friend. In the year ahead, more organizations will embraceAI, machine learning and automation as ways to augment (not replace) their existing human resources. For IT professionals, this will necessitate the cultivation of AI- and automation-era skills such as programming, coding, a basic understanding of the algorithms that govern AI and machine learning functionality, and a strong security posture in the face of more sophisticated cyberattacks. For businesses, the challenge will now be approaching these unchartered "intelligent technology" waters strategically in order to derive specific value- adds for their business and to effectively communicate the ROI to decision- makers.
  29. 29. Splunk - http://bit.ly/2HwgGtr ARTIFICIAL INTELLIGENCE SPURS THE REINVENTION OF IT Rick Fitz, SVP and GM IT Markets, Splunk Artificial intelligence will evolve IT by seeing predictive analytics replace manually intensive activities with intelligent automation.This evolution has been coined AIOps. This will allow organizations to leverage data and AI to quickly identify problems, provide recommendations on how to resolve existing issues, streamline automation with self-service and self-recovery capabilities, and predict future outcomes to forecast costs. AIOps will take IT operations analytics (ITOA) to the next level by automatically applying insights to ensure high performing IT environments are proactively making decisions that ultimately improve the health of the business.
  30. 30. Sumo Logic - http://bit.ly/2JvhEHa AI WILL NOT TRANSFORM THE ENTERPRISE IN THE NEAR FUTURE Christian Beedgen, Co-Founder,CTO, Sumo Logic Previous predictions and claims about the direct impact of AI on enterprises have been overblown.There is excessive hype around how AI will lead us to new discoveries and medical breakthroughs. However, those expectingAI to be the ultimate truth conveyer are mistaken. It will be very hard to design a model that can determine unbiased truth, because human bias - whether explicitly or implicitly - will be coded into these data analytics systems and reinforce existing beliefs and prejudices.With that said, there are certain applications where systems can make better decisions in a shorter amount of time than humans, such as in the case of autonomous vehicles. In 2018 we will begin to see real use cases of the power of AI appear in our everyday lives -- it just isn't ready to be the shining star for the enterprise quite yet.When you look at the maturity of the enterprise, only half of the Global 2000 offer fully digital products. So, despite all of the buzz around digital transformation, there's a lot of catch-up to be done before many of these companies can even consider looking at advanced developments such as AI.
  31. 31. Talend - http://bit.ly/2HylnDc BIG DATA FUELS THE FUTURE Ashley Stirrup, Chief Marketing Officer, Talend In 2018, Machine Learning Will be the Ultimate Weapon in the Cloud Wars We are one major announcement away from the technology industry being pushed into a machine learning renaissance. 2018 will be a year of search and exploration of machine learning to determine how best to use it, and what things can be automated that you never thought possible before. Cloud will make machine learning pervasive and soon enough, it will be built into every application - used by everyone either directly or indirectly. Pervasiveness of Flawed Data Will Lead to Machine Learning Instability 2018 will usher in organizations refining their AI, machine learning and deep learning algorithms to leverage company and third-party data for the improvement of the broader customer experience. However, only 3% of companies are working with acceptably accurate data. Unless companies get a handle on their data and ensuring 100% accuracy, machine learning could be learning from flawed data, resulting in inaccurate analytics and predicted outcomes, leading to poor business decisions.
  32. 32. Veritone - http://bit.ly/2I2VfS0 AI NEEDS TO BE AVAILABLE WHEREVER THE DATA IS LOCATED Tyler Schulze, vice president and general manager, Veritone AI needs to prove itself and lend credibility to its work Take for example,AWS. Currently, it's enabling scalable, flexible and cost-effective solutions for startups to global enterprises.To support the seamless integration and deployment of these solutions, AWS established the AWS PartnerCompetency Program to help customers identify Consulting andTechnologyAPN Partners with deep industry experience and expertise. As AWS claims, "Out of all of the innovations that are being driven by cloud, the areas of artificial intelligence (AI) and machine learning (ML) are perhaps the most exciting." In order for AI companies to tap into some of that excitement, they need to prove themselves with something notable like the designation that AWS provides. The future of business application is found in AI AI deployments can help augment the daily and tedious roles of the modern workforce, democratize services that were originally costly or unavailable and tap into the wealth of unstructured data for actionable use because now, every frame of video or second of audio can be searched for objects, faces, voices, brands, sentiment, text and more.The speed at which AI can tackle the previous tactics of manual discovery open a world of opportunity via human-machine thinking partnerships.
  33. 33. Vonage - http://bit.ly/2Flfw22 EVERY BUSINESS WILL COME WITH A BUTLER Omar Javaid, Chief Product Officer, Vonage Virtual assistants like Siri and Alexa have given consumers a taste of what it is like to work in tandem with artificial intelligence. In 2018, enterprises will either roll out their own versions or announce integrations with existing AI. The same seamless ease that consumers experience at home when asking Siri to find them a pizza spot will soon follow them to work. In the near future, employees across industries could find themselves saying, "Alexa, cancel my 10:30 and run my expense report." In fact, it's already happening. Financial and business analyst firms are already using Amazon Echo for research-- a BI growing startup called Sisense connected Alexa to their digital systems, to act as an analyst, at double the speed.They also connect the Echo to connect light bulbs, which glow different colors when Alexa uncovers potential issues. Amazon's major recent announcement of Alexa for Business will only accelerate adoption ofAI in the workplace. Having virtual assistants integrated into business communications systems will enable workers to collaborate more easily, work through projects more efficiently, and stay better organized.This seamless, connected style of work will become a new norm.
  34. 34. ZingBox - http://bit.ly/2r1Vkhj ARTIFICIAL INTELLIGENCE WILL BE A REQUIREMENT FOR MODERN CYBER SECURITY Xu Zou, co-founderand CEO, ZingBox 2018 will signify the end of traditional cyber security based solely on manual research and signatures. Antivirus, Intrusion Prevention and other technologies based primarily on development of signatures by cyber security researchers will finally hit the scalability barrier many have predicted.The sheer scale and sophistication of attacks will greatly surpass the rate at which the manual signatures can be developed. The lack of real-time response and the residual pain from 2017 attacks will require organizations to look for security solutions based on modern architecture. While AI and machine learning are broad terms, in context of security, they represent a modern approach to an old problem. Using AI efficiently, organizations can focus on ensuring that every device behave as intended rather than trying to identify the latest attack pattern or virus. By relying on AI to define and continuously refine what constitutes a "normal" behavior, organizations won't find themselves in a constant race against hackers. I predict 2018 will be the year where organizations will ask "Are all our devices behaving normally?" vs. "Are we secure from the latest attack?".
  35. 35. READ 280+ EXPERT PREDICTIONS AT http://bit.ly/2DQi2OT

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