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

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.

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

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.

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

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.

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.

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.

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.

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

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.

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.

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

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.

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.

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.

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!

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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?".

READ 280+ EXPERT PREDICTIONS AT http://bit.ly/2DQi2OT

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

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