Quick quiz!

What’s the first thing that comes to mind when you hear the following phrases?

• Artificial grass
• Artificial sweeteners
• Artificial flavors
• Artificial plants
• Artificial flowers
• Artificial diamonds and jewelry
• Artificial (fake) news

These phrases probably evoke thoughts such as “fake,” “not real,” or even “shabby.” Artificial is such a harsh adjective. The word “artificial” is defined as “imitation; simulated; sham” with synonyms such as fake, false, mock, counterfeit, bogus, phony and factitious.

The word “artificial” may not be the right term to use to describe “Artificial Intelligence,” because “artificial intelligence” is anything but fake, false, phony, or a sham. Maybe a better term is “Augmented Human Intelligence,” or a phrase that highlights both the importance of augmenting the human’s intelligence as well as to alleviate the fears that AI means humans become “meat popsicles” (quick, name that Bruce Willis movie reference!). And while I don’t expect this name change to stick (if it does, please give me some credit), I’m using this blog as an excuse to introduce some marvelous new training materials on artificial intelligence and machine learning.

But before I dive into details, let’s first frame the artificial intelligence conversation.

Focusing on the “How” Won’t Lead You to the “What” and “Why”
Organizations have access to a growing variety of internal and external data sources that might yield better predictors of business performance. And while having a process to ideate, validate and prioritize the different data sources that one might want to explore for its predictive capabilities, in the end the data by itself is of little value – organizations need to become more effective at leveraging data and analytics to power their business models (see Figure 1).

Figure 1: Big Data Business Model Maturity Index

But in order to “monetize” that growing bounty of data, you’re going to need to become an expert at advanced analytics to tease out the customer, product, service, and operational insights that are the real sources of economic value (see University of San Francisco “Determining The Economic Value of Data” research paper). Business leaders need to become knowledgeable about advanced analytics capabilities so that they can envision “What” business use cases to target and “Why,” before they get pulled into the “How” discussion.

Preparing for the “How” Discussion
To help business leaders understand where and how to apply the different classes of advanced analytics (i.e., machine learning, neural networks, reinforcement learning, artificial intelligence), I’ve created an advanced analytics roadmap. I then mapped the advanced analytics roadmap against the Big Data Business Model Maturity Index (see Figure 2).

Figure 2: The Path for Creating the Intelligent Enterprise

While certainly not perfect (and certainly not definitive given continued advanced analytics advancements), Figure 2 attempts to classify the different advanced analytics capabilities into a roadmap that organizations can use to help them understand when and where to apply the different advanced analytics capabilities. This is my attempt to try to summarize the advanced analytics confusion, hype and excitement into something actionable.

With that as my goal, here are the different levels of advanced analytics:

• Level 1: Insights and Foresight. This is the foundational level that includes statistical analytics as well as the broad categories of predictive analytics (e.g., clustering, classification, regression) and data mining. The goal of the level 1 is to quantify cause-and-effect, establish confidence levels and measure goodness of fit.
• Level 2: Optimized Human-decision Making. This level includes machine learning, deep learning and neural networks. The goal of these advanced analytic algorithms is to enable computers to learn on their own; to identify patterns in data, build models that explain the data, and predict outcomes without having pre-programmed rules and analytic models.
• Level 3: The Learning and Intelligent Enterprise. This level includes artificial intelligence, reinforcement learning and cognitive computing. These advanced analytic algorithms self-monitor, self-diagnose, self-adjust and self-learn. These analytics perceive the world around them, create goals, make decisions towards those goals, measure decision effectiveness, and learn in order to refine the decisions that advance towards the goals (maximize rewards while minimizing costs).

It is important to be able to summarize and present the wide realm of advanced analytics within a frame that we can explain to business leadership (because eventually we’re going to come to them for money). So using Figure 2 as our business framework, let’s deep dive into each of the advanced analytics levels.

Level 1: Insights and Foresights
The goal of Level 1 is to quantify “cause-and-effect” (i.e., quantify relationships in the data) and predict what is likely to happen at some measureable level of confidence. Level 1 sets the foundation for determining “goodness of fit,” or the extent to which observed data matches the values predicted by analytic models. Level 1 includes the following advanced analytic capabilities:

• Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation and organization of data. Statistical analytics and methods are used to support hypotheses (decisions) and provide credibility to modeling results and outcomes (via confidence levels and “goodness of fit” measures). Check out “Statistics for Dummies Cheat Sheet” for more information about different statistical techniques.
• Predictive Analytics and Data Mining include anomaly detection, clustering, classification, regression and association rule learning. Predictive analytics and data mining uncover statistically significant patterns in large data sets; they uncover relationships buried in the data in order to quantify risks and opportunities. Check out “23 Types of Regression” to see the different types of regression techniques available to the data scientist.

Level 2: Augmented Human Decision-making
Level 2 builds upon the predictions created in Level 1 in order to prescribe actions and recommendations. Level 2 is the domain of analytic capabilities focused on natural language processing (NLP), text translation, voice recognition, and photo/image/facial recognition. Advanced analytic capabilities in level 2 focus on learning and then making inferences from that learning. Level 2 includes the following analytic capabilities:

• Neural Networks and Deep Learning leverage a system of highly interconnected analytic layers to decompose complex data formats (e.g., images, audio, video) in order to learn about the data and create inferences about the data. For example, Figure 3 shows how a series of interconnected neural network layers work to identify a written number.

Figure 3: Why Convolutional Neural Networks (Source URL provided below)

But beware, as there is not just one neural network technique, as can be seen in Figure 4.

Figure 4: The Asimov Institute, The Neural Network Zoo (Source URL provided below)

Machine Learning empowers systems and applications with the ability to gain knowledge without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data. Machine Learning algorithms identify patterns in observed data, build models that explain the world, and predict things without having to explicitly pre-program rules and analytic models (see Figure 5).

Figure 5: The Difference Between Deep Learning Training and Inference (Source URL provided below)

Fundamentally, Machine Learning does two things: 1) quantifies relationships in the data (quantify relationships from historical data and apply those relationships to new data sets), and 2) quantifies latent relationships (draw inferences) buried in the data.

There are two types of machine learning:

• Supervised machine learning is a type of machine learning algorithm used to draw inferences from data sets with label responses such as fraud, customer attrition, purchase transaction, part failure, social media engagement, or web click.
• Unsupervised machine learning is a type of machine learning algorithm used to draw inferences from data sets without labeled responses such as finding hidden (unknown) patterns, groupings or relationships in data.

See the blog “Top 10 Machine Learning Algorithms” for detailed list of machine learning algorithms.

• Adversarial Machine Learning is a fairly new area of machine learning. Adversarial Machine Learning sits at the intersection of machine learning and computer security. It seeks to enable the safe adoption of machine learning techniques in adversarial settings like spam filtering, malware detection and biometric recognition. Machine learning techniques were originally designed for stationary environments in which the training and test data are assumed to be generated from the same distribution. However in the presence of intelligent and adaptive adversaries, this working hypothesis is likely to be violated. For example, a malicious adversary can carefully manipulate the input data exploiting specific vulnerabilities of learning algorithms to compromise the whole system security.
• Finally, Ensemble machine learning combines several machine learning techniques into one predictive model in order to decrease variance, bias, or improve predict effectiveness. Ensemble methods can be divided into two groups:
  • Sequential ensemble methods where the base learners are generated sequentially. The basic motivation of sequential methods is to exploit the dependence between the base learners. Weighing previously mislabeled examples with higher weight can boost the overall performance.
  • Parallel ensemble methods where the base learners are generated in parallel (e.g. Random Forest). The basic motivation of parallel methods is to exploit independence between the base learners since the error can be reduced dramatically by averaging.

See the article “Ensemble Learning to Improve Machine Learning Results” for more details on ensemble machine learning.

Level 3: The Learning and Intelligent Enterprise
Level 3 focuses on creating an intelligent enterprise that can self-monitor, self-diagnose, self-correct and self-learn. Level 3 is the domain of continuous “learning and adjusting” advanced analytic techniques such as reinforcement learning, artificial intelligence and cognitive computing. Level 3 includes the following analytic capabilities:

• Reinforcement Learning focuses on how software agents take actions in an environment so as to maximize cumulative rewards while minimizing costs. Reinforcement learning uses trial-and-error to map situations to actions so as to maximize rewards. Actions may affect immediate rewards but actions may also affect subsequent or longer-term rewards, so the full extent of rewards must be considered when evaluating the reinforcement learning effectiveness. Reinforcement learning is used to address two general problems:
  • Prediction: How much reward can be expected for every combination of possible future states
  • Control: By moving through all possible combinations of the environment, find a combination of actions that maximizes reward and allows for optimal control

See “Transforming from Autonomous to Smart: Reinforcement Learning Basics” for more details on reinforcement learning.

• Artificial Intelligence is the ability for a computer system to acquire knowledge within a particular environment, apply the knowledge to successfully interact within that environment, and learn from the resulting interaction so that subsequent interactions get more effective, even to the point where an artificial intelligent application could re-program itself to more successfully perform (survive?) within a complex environment or situation (now that should scare the singularity folks[4]).

Artificial intelligence involves the study of agents that perceive the world around them, form plans, and make decisions to achieve their goals. An intelligent agent is an autonomous entity that observes through sensors and acts upon an environment using actuators (i.e. it is an agent) and directs its activity towards achieving goals (i.e. it is “rational,” as defined in economics). There are 4 general types of intelligent agents:

• Simple reflex agents
• Model-based reflect agents
• Goal-based reflect agents
• Utility-based reflect agents

Figure 6: Simple Reflect Agent (Source URL provided below)

Cognitive Computing is a relatively new concept that is being championed by IBM Watson. Cognitive computing involves self-learning systems that simulate human thought processes and decision-making in complex situations. From Wikipedia, we get cognitive systems features including:

• Adaptive: may learn as information changes, and as goals and requirements evolve
• Interactive: may interact easily with users so that those users can define their needs comfortably
• Iterative: may aid in defining a problem by asking questions or finding additional source input if a problem statement is ambiguous or incomplete
• Contextual: may understand, identify, and extract contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task and goals

Summary
You can’t get to the “What” and the “Why” by focusing on the “How”

It is also important to understand the “How” in order to envision the “What” and “Why.” Sometimes the wide variety of advanced analytic techniques and algorithms cause confusion, and cause business leaders to slow down or even stop until they understand these advanced analytic capabilities better. The goal of this blog was to provide enough of an explanation of advanced analytics to business leaders so that when we get engaged in an envisioning exercise, we get turn off the governors that limit creative thinking.

Appendix: Marvelous Sources of Advanced Analytics Knowledge
There are many sources of excellent education available on advanced analytics, such as Andrew Ng’s deep learning classes on Coursera. One of my favorites is the content provided by the “Machine Learning for Humans” site. It has excellent material and includes a free downloadable e-book.

Figure 7: Machine learning is one of many subfields of artificial intelligence, concerning the ways that computers learn from experience to improve their ability to think, plan, decide, and act.

I’ll continue to share new sources of great educational material on advanced analytics as they get released into the wilds. Understand the “how” will help organizations to envision the realm of what’s possible. Many times, that envisioning is only limited by the organizations creativity and management commitment.

Sources:

Figure 3: Why Convolutional Neural Networks

Figure 4: The Asimov Institute – The Neural Network Zoo

Figure 5: Nvidia – What’s the Difference Between Deep Learning Training and Inference?

[4] The technological singularity is the hypothesis that the invention of artificial super intelligence will abruptly trigger runaway technological growth, resulting in unfathomable changes to human civilization (a.k.a. Skynet).

Figure 6: Philosophy of Artificial Intelligence: Simple Reflex Agent

The post Artificial Intelligence is not “Fake” Intelligence appeared first on InFocus Blog | Dell EMC Services.

CloudExpo | DXWorldEXPO have announced the conference tracks for Cloud Expo 2018, introducing DXWorldEXPO.

DXWordEXPO, colocated with Cloud Expo will be held June 5-7, 2018, at the Javits Center in New York City, and November 6-8, 2018, at the Santa Clara Convention Center, Santa Clara, CA.

Digital Transformation (DX) is a major focus with the introduction of DXWorld Expo within the program. Successful transformation requires a laser focus on being data-driven and on using all the tools available that enable transformation if they plan to survive over the long term.

A total of 88% of Fortune 500 companies from a generation ago are now out of business. Only 12% still survive. Similar percentages are found throughout enterprises of all sizes.

Cloud Expo | DXWorldEXPO 2018 New York
(June 5-7, 2018, Javits Center, Manhattan)

Cloud Expo | DXWorldEXPO 2018 Silicon Valley
(November 6-8, 2018, Santa Clara Convention Center, CA)

Full Conference Registration "Gold Pass" and Exhibit Hall ▸ Here (Register ▸ Here via EventBrite)

DX World EXPO, LLC., a Lighthouse Point, Florida-based startup trade show producer and the creator of DXWorldEXPO® - Digital Transformation Conference & Expo has announced its conference agenda, with three major themes:

* Technology - The Revolution Continues
* Economy - The 21st Century Emerges
* Society - The Big Issues

"DX encompasses the continuing technology revolution, and is addressing society's most important issues throughout the entire $78 trillion 21st-century global economy," said Roger Strukhoff, Conference Chair. "DXWorldExpo has organized these issues along 10 tracks with more than 500 of the world's top speakers coming to Istanbul to help change the world."

There are 10 tracks running throughout the event and following the major themes. More than 500 breakout sessions will be featured, along with keynotes and general sessions from some of the world's top technology, business, and societal leaders. The event will be held over five days in Istanbul, reflecting the global nature of Digital Transformation and the city's long and historic role as a key business and intellectual center and linchpin between East and West.

Full Conference Registration "Gold Pass" and Exhibit Hall ▸ Here (Register ▸ Here via EventBrite)

DX World Expo's Global Themes and Tracks are as follows:

Technology - The Revolution Continues

DX Tech: Data-Driven Global 2000
DX Tech: The Blockchain Challenge
DX Tech: AI and Cognitive
DX Tech: The Global Cloud

Economy - The 21st Century Emerges

DX Econ: Software is Rewriting the World
DX Econ: Smart Cities, Nations, and Regions
DX Econ: FinTech and the Token Economy
DX Econ: The Industrial Internet and Industrie 4.0

Society - The Big Issues

DX Society: Environment
DX Society: Education
DX Society: Agriculture
DX Society: Health Care

Call for Papers -speaking opportunities- as well as sponsorship and exhibit opportunities will open on November 1, 2017.

World's Most Important Tech Event
DXWorldEXPO® will be the world's most important tech event with 1,000 exhibitors in its first year and 2,000 exhibitors in its second year, as it guides Global 2000 companies through their Digital Transformation journey for the next two decades. The global event is set to launch September 17-20, 2018 in Istanbul. It will be sponsored by Fortune 50 companies, and more than 30 international banks will be among sponsors of its FinTech/InsurTech track.

Gaining a better understanding of customers and acting upon this information is the foundation of Digital Transformation (DX) in the enterprise. Applying the latest technologies in this area is the key to driving new topline revenue opportunities.

Global 2000 companies have more than US$40 trillion in annual revenue - more than 50% of the world's entire GDP. The Global 2000 spends a total of US$2.4 trillion annually on enterprise IT. The average Global 2000 company has US$11 billion in annual revenue. The average Global 2000 company spends more than $600 million annually on enterprise IT.

Governments throughout the world spend another US$500 billion on IT - much of it dedicated to new Smart City initiatives. There are more than a dozen Global 2000 companies in Turkey, including Isbank, Garanti Bank, other financial institutions, Turk Telecom, Turkcell, Turkish Airlines, and ENKA.

Cloud Expo | DXWorldEXPO 2018 New York
(June 5-7, 2018, Javits Center, Manhattan)

Cloud Expo | DXWorldEXPO 2018 Silicon Valley
(November 6-8, 2018, Santa Clara Convention Center, CA)

Full Conference Registration "Gold Pass" and Exhibit Hall ▸ Here (Register ▸ Here via EventBrite)

More Management Quotes
"For the past 10 years at Cloud Expo, we've helped drive the migration to modern enterprise IT infrastructures, built upon the foundation of cloud computing. Today's hybrid, multiple cloud IT infrastructures integrate Big Data, analytics, blockchain, the IoT, mobile devices, and the latest in cryptography and enterprise-grade security," said Fuat Kircaali, Chairman and founder of DX World Expo, LLC.

"As a report from the World Economic Forum and Accenture recently stated, 'Companies need to fundamentally change the way they identify, develop and launch new business ventures.' We agree," said Carmen Gonzalez, president of DX World Expo, LLC.

"Digital Transformation is the key issue driving the global enterprise IT business," said Roger Strukhoff, Conference Chair and Executive Director of the Tau Institute for Global ICT Studies. "DX is most prominent among Global 2000 enterprises and government institutions. Our new event in Istanbul brings together the top companies and delegates from around the world, who are transforming the world."

2018 Conference Agenda and Tracks, June 5-7, Javits Center

Track 1 | Cloud Expo - Enterprise Cloud
Track 2 | DXWorld Expo - Digital Transformation (DX)
Track 3 | The API Enterprise | Mobility & Security
Track 4 | DevOps | Containers & Microservices
Track 5 | Cognitive Computing | AI, ML, DL
Track 6 | Big Data | Analytics
Track 7 | IoT | IIoT | Smart Cities
Track 8 | Hot Topics | FinTech | WebRTC

Cloud Expo covers all of these tools, with the most comprehensive program and more than 120 top world-class speakers throughout our Industry presenting Keynotes, General Sessions, Breakout Sessions along eight focused tracks, as well as our signature Power Panels. Our expo floor brings together the world's leading companies throughout the world of Cloud Computing, DX, and all they entail.

As your enterprise creates a vision and strategy that enables you to create your own unique, long-term success, learning about all the technologies involved is essential. Companies today not only form multi-cloud and hybrid cloud architectures, but create them with built-in cognitive capabilities. Cloud-native thinking is now the norm in financial services, manufacturing, telco, healthcare, transportation, energy, media, entertainment, retail and other consumer industries, as well as the public sector.

Cloud Expo is the world's most important, independent event where technology buyers and vendors meet to experience and discuss the big picture of Digital Tranformation and all of the strategies, tactics, and tools they need to realize their goals.

Full Conference Registration "Gold Pass" and Exhibit Hall ▸ Here (Register ▸ Here via EventBrite)

Only Cloud Expo brings together all this in a single location:

• Cloud Computing
• Big Data & Analytics
• Software-Defined Infrastructure
• Industrial IoT
• Industry 4.0
• Artificial Intelligence
• Cognitive Computing
• Microservices
• Machine Learning
• DevOps
• WebRTC
• FinTech
• Digital Transformation

Attend Cloud Expo. Build your own custom experience. Learn about the world's latest technologies and chart your course to Digital Transformation.

21st International Cloud Expo, taking place October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, will feature technical sessions from a rock star conference faculty and the leading industry players in the world.

Download Show Prospectus ▸ Here

Full Conference Registration "Gold Pass" and Exhibit Hall ▸ Here (Register ▸ Here via EventBrite)

Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy. Meanwhile, 94% of enterprises are using some form of XaaS - software, platform, and infrastructure as a service.

With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation.

2018 Conference Agenda and Tracks, June 5-7, Javits Center

Track 1 | Cloud Expo - Enterprise Cloud
Track 2 | DXWorld Expo - Digital Transformation (DX)
Track 3 | The API Enterprise | Mobility & Security
Track 4 | DevOps | Containers & Microservices
Track 5 | Cognitive Computing | AI, ML, DL
Track 6 | Big Data | Analytics
Track 7 | IoT | IIoT | Smart Cities
Track 8 | Hot Topics | FinTech | WebRTC

Cloud Expo | DXWorldEXPO 2018 New York
(June 5-7, 2018, Javits Center, Manhattan)

Cloud Expo | DXWorldEXPO 2018 Silicon Valley
(November 6-8, 2018, Santa Clara Convention Center, CA)

Full Conference Registration "Gold Pass" and Exhibit Hall ▸ Here (Register ▸ Here via EventBrite)

Download Show Prospectus ▸ Here

Every Global 2000 enterprise in the world is now integrating cloud computing in some form into its IT development and operations. Midsize and small businesses are also migrating to the cloud in increasing numbers.

Companies are each developing their unique mix of cloud technologies and services, forming multi-cloud and hybrid cloud architectures and deployments across all major industries. Cloud-driven thinking has become the norm in financial services, manufacturing, telco, healthcare, transportation, energy, media, entertainment, retail and other consumer industries, and the public sector.

Cloud Expo is the single show where technology buyers and vendors can meet to experience and discus cloud computing and all that it entails. Sponsors of Cloud Expo will benefit from unmatched branding, profile building and lead generation opportunities through:

• Featured on-site presentation and ongoing on-demand webcast exposure to a captive audience of industry decision-makers.
• Showcase exhibition during our new extended dedicated expo hours
• Breakout Session Priority scheduling for Sponsors that have been guaranteed a 35-minute technical session
• Online advertising in SYS-CON's i-Technology Publications
• Capitalize on our Comprehensive Marketing efforts leading up to the show with print mailings, e-newsletters and extensive online media coverage.
• Unprecedented PR Coverage: Editorial Coverage on Cloud Computing Journal.
  
• Tweetup to over 75,000 plus followers
• Press releases sent on major wire services to over 500 industry analysts.

For more information on sponsorship, exhibit, and keynote opportunities, contact Carmen Gonzalez by email at events (at) sys-con.com, or by phone 201 802-3021.

The World's Largest "Cloud Digital Transformation" Event

@CloudExpo | @ThingsExpo 2017 Silicon Valley
(Oct. 31 - Nov. 2, 2017, Santa Clara Convention Center, CA)

@CloudExpo | @ThingsExpo 2018 New York
(June 12-14, 2018, Javits Center, Manhattan)

Full Conference Registration "Gold Pass" and Exhibit Hall ▸ Here (Register ▸ Here via EventBrite)

Sponsorship Opportunities

Sponsors of Cloud Expo | @ThingsExpo will benefit from unmatched branding, profile building and lead generation opportunities through:

• Featured on-site presentation and ongoing on-demand webcast exposure to a captive audience of industry decision-makers
• Showcase exhibition during our new extended dedicated expo hours
• Breakout Session Priority scheduling for Sponsors that have been guaranteed a 35 minute technical session
• Online targeted advertising in SYS-CON's i-Technology Publications
• Capitalize on our Comprehensive Marketing efforts leading up to the show with print mailings, e-newsletters and extensive online media coverage
• Unprecedented Marketing Coverage: Editorial Coverage on ITweetup to over 100,000 plus followers, press releases sent on major wire services to over 500 industry analysts

For more information on sponsorship, exhibit, and keynote opportunities, contact Carmen Gonzalez (@GonzalezCarmen) today by email at events (at) sys-con.com, or by phone 201 802-3021.

Secrets of Sponsors and Exhibitors ▸ Here
Secrets of Cloud Expo Speakers ▸ Here

All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades.

With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo | @ThingsExpo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-4, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation.

Delegates to Cloud Expo | @ThingsExpo will be able to attend 8 simultaneous, information-packed education tracks.

There are over 120 breakout sessions in all, with Keynotes, General Sessions, and Power Panels adding to three days of incredibly rich presentations and content.

Join Cloud Expo | @ThingsExpo conference chair Roger Strukhoff (@IoT2040), October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, for three days of intense Enterprise Cloud and 'Digital Transformation' discussion and focus, including Big Data's indispensable role in IoT, Smart Grids and (IIoT) Industrial Internet of Things, Wearables and Consumer IoT, as well as (new) Digital Transformation in Vertical Markets.

Full Conference Registration "Gold Pass" and Exhibit Hall ▸ Here (Register ▸ Here via EventBrite)

Financial Technology - or FinTech - Is Now Part of the @CloudExpo Program!

Accordingly, attendees at the upcoming 21st Cloud Expo | @ThingsExpo October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, will find fresh new content in a new track called FinTech, which will incorporate machine learning, artificial intelligence, deep learning, and blockchain into one track.

Financial enterprises in New York City, London, Singapore, and other world financial capitals are embracing a new generation of smart, automated FinTech that eliminates many cumbersome, slow, and expensive intermediate processes from their businesses.

FinTech brings efficiency as well as the ability to deliver new services and a much improved customer experience throughout the global financial services industry. FinTech is a natural fit with cloud computing, as new services are quickly developed, deployed, and scaled on public, private, and hybrid clouds.

More than US$20 billion in venture capital is being invested in FinTech this year. @CloudExpo is pleased to bring you the latest FinTech developments as an integral part of our program, starting at the 21st International Cloud Expo October 31 - November 2, 2017 in Silicon Valley, and June 12-14, 2018, in New York City.

@CloudExpo is accepting submissions for this new track, so please visit www.CloudComputingExpo.com for the latest information.

Speaking Opportunities

The upcoming 21st International @CloudExpo | @ThingsExpo, October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY announces that its Call For Papers for speaking opportunities is open.

Submit your speaking proposal today! ▸ Here

About @CloudEXPO and @DXWorldEXPO
SYS-CON Media (www.sys-con.com) has since 1994 been connecting technology companies and customers through a comprehensive content stream - featuring over forty focused subject areas, from Cloud Computing to Web Security - interwoven with market-leading full-scale conferences. The company's internationally recognized brands include among others Cloud Expo® (@CloudExpo), Big Data Expo® (@BigDataExpo), DevOps Summit (@DevOpsSummit), @ThingsExpo® (@ThingsExpo), and DXWorldEXPO® (@ExpoDX).

@CloudExpo® and @ThingsExpo® are registered trademarks of CLOUD EXPO INC.

DXWorldEXPO® is a registered trademark of DX WORLD EXPO LLC.