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AI-Defined Infrastructure | @CloudExpo #AI #DX #IoT #ArtificialIntelligence
The Foundation for New Generation Business Models and Applications

In 2016, artificial intelligence (AI) reached its climax. Research and advisory firm Tractica predicted that the annual worldwide AI revenue will grow from $643.7 million in 2016 to $38.8 billion by 2025. The revenue for enterprise AI applications will increase from $358 million in 2016 to $31.2 billion by 2025, representing a compound annual growth rate (CAGR) of 64.3%. Thus, IT and business decision makers must face up to the potentials of AI already today. For each kind of organization this leads to the question, which type of technologies or infrastructure they can leverage to operate an AI-ready enterprise stack.

What Is Artificial Intelligence (AI)?
In 1955, Prof. John McCarthy defined AI as "The goal of AI is to develop machines that behave as though they were intelligent." Discussing "intelligent" in this context, we are talking about a vigorous system. A system that must be considered as a raw IQ container, a system that needs unstructured input to train its senses, a system that needs a semantic understanding of the world to be able to take further actions. A system that needs a detailed map of its context to act independently and transfer experience from one context to another, a system that is equipped with all the necessities to develop, foster and maintain knowledge.

It is our responsibility to share our knowledge with these machines as we would share it with our children, spouses or colleagues. This is the only way to transform these machines, made of hard- and software, into a status we would describe as "smart", helping them to become more intelligent by learning on a daily basis, building the groundwork to create a self-learning system. In doing so, research distinguishes three types of AIs:

  • Strong AI: A strong AI (or superintelligence) is a self-aware machine with ideal thoughts, feelings, consciousness and all the necessary links. For all those who are already looking forward to a reality á la "Her" or "Ex_Machina" still need to wait. Large neural networks have millions of neurons. Brains have billions of neurons. Neural networks only simulate the electrical system in a brain, the brain also has a chemical, potentially a quantum mechanics based system. The layer based modelling of deep learning networks is to simplify training, the brain has no such restrictions. Neural networks are about as far away from a brain that thinks as a snail is from a supersonic jet. Thus, a strong AI doesn't exist yet and is very far away.
  • Narrow AI: Most business cases in AI focus on solving particular very pointed challenges. These narrow AIs are great at optimizing specific tasks like recommending songs on Pandora ormanaging analyses to improve tomato growth in a greenhouse.
  • General AI: A general AI can handle tasks from different areas and origins with the ability to shorten training time from one area to the next by applying experience gathered in one area and applied in a different area. This knowledge transfer is only possible if there is a semantic connection between these areas. The stronger and denser this connection, the faster and easier knowledge transition is achieved. In comparison to a narrow AI, a general AI has all the necessary knowledge and abilities to improve not only tomato growth in a greenhouse but cucumber, eggplant, peppers, radishes and kohlrabi as well. Thus, a general AI is a system, that can handle more than just one specific task.

However, one thing is obvious. Without technologies, such as cloud computing, AI wouldn't have achieved its boom particularly today. Both cloud services and progress in machine intelligence have made it easier for organizations to apply AI-based functionalities to interact closer with its customers. More and more companies like Airbnb, Netflix, Uber or Expedia are already using cloud-based systems to process AI relevant tasks that draw on an intensive utilization of CPU/ GPU as well as services for comprehensive computing and analysis tasks.

In the context of their AI strategy, companies should evaluate AI services from different cloud providers. Another part of their strategy should contain an AI-defined infrastructure. The foundation for this kind of infrastructure is a general AI that unifies three typical human characteristics, which empower an organization to autonomously operate its IT and business processes.

  • Learning: The general AI receives best practices and reasoning from experts based on ongoing learning units. For this purpose, the knowledge is taught in granular pieces that consist of discrete parts of a process. In the context of a greenhouse, the experts teach the AI any process step by step, e.g., how to grow cucumbers, eggplants or paprika. In doing so, they share their context-based knowledge with the AI that includes among others "what has to be done" and "why this has to be done".
  • Understanding: By creating a semantic data graph the general AI gets an understanding of the world in which the organization is acting with its IT and business objectives. Thus, the semantic data graph of a greenhouse would consolidate different contexts (e.g., information, characteristics and specifics of the greenhouse, cucumber culture, eggplant culture and paprika culture) and enrich (compare learning) it on an ongoing basis. The IT of an organization plays an important role, since all data are running together here.
  • Solving: With the concept of machine reasoning, problems are solved in ambiguous and changing environments. The general AI dynamically reacts to the ever-changing context, selecting the best course of action. Based on the trained knowledge (learning) and the creation of the semantic graph (understanding) the general AI can grow more than one single type of vegetable in a greenhouse. This is ensured with the growing amount of trained knowledge pieces that lead to a knowledge pool that is further optimized by machine selection of best knowledge combinations for problem resolution. This type of collaborative learning improves process time task by task. However, the number of possible permutations grows exponentially with added knowledge. Connected to a knowledge core, the General AI continuously optimizes performance by eliminating unnecessary steps and even changing routes based on other contextual learning. Thus, the bigger the semantic data graph gets, the better and more dynamically further types of vegetables can be cultured.

What Requirements Concerning Infrastructure Environments Does an AI Have?
Right now, AI is the technology that has the potential not only to improve existing infrastructure like cloud environments but expedite a new generation of infrastructure technologies as well. As an important technology trend, AI has influenced a new generation of development frameworks as well as a new generation of hardware technologies to run scalable AI applications.

Mobile and IoT applications have only minor requirements concerning runtime environments to an infrastructure. However, it is critical to provide appropriate services to build a backend for those types of applications. By contrast, AI applications do not only expect sophisticated backend services but also optimized runtime environments that are adapted for GPU intensive requirements of AI solutions. AI applications challenge the infrastructure with regards to the simultaneous task processing in very short time cycles. For accelerating deep learning applications in particular GPU processors are employed. GPU optimized applications distribute CPU-intensive areas of an application to the GPU and let the ordinary computations handle by the CPU. In doing so, the execution of the entire application is accelerated. The advantage of a GPU towards a CPU is reflected in the respective architectures. A CPU is exclusively designed for serial data processing and only has a few cores. A GPU, however, is composed of a parallel architecture with a vast number of small cores that process the tasks simultaneously. According to NVIDIA, the application throughput of a GPU is 10 to 100 times higher in comparison to a CPU. Thus, an infrastructure should be able to provide a deep learning framework such as TensorFlow and Torch over hundreds or thousands of nodes on a demand basis that immediately are deployed with the optimal CPU configuration.

The following list (in a partial state) deals with the requirements for infrastructure to support AI applications:

  • Support of current frameworks: Infrastructure must be able to support AI application based on AI frameworks like TensorFlow, Caffe, Theano and Torch the same way as web applications and backend processes. Thus, an infrastructure should not exclusively focus on AI frameworks but design the portfolio in the interests of a developer.
  • GPU optimized environment: An infrastructure has to make sure that every AI process can be processed. Thus, it must support GPU environments in order to provide fast computational power. Microsoft was the frontrunner in this area by offering its N-series GPU instances.
  • Management environment and tools: One of the biggest challenges of current infrastructure environments is the drawback of management tools for running AI frameworks. Here, in particular, the direct interaction between AI frameworks and the infrastructure is necessary to ensure the best balance and thus deliver the best performance.
  • AI-integrated infrastructure services: Infrastructure provider must and will not only support AI functionalities but integrate AI as a central part of their infrastructure and service stacks. This type of an AI-defined Infrastructure won't only increase the intelligence of cloud services and applications but also simplify the setup and operations of the infrastructure by the customer.
  • Machine Reasoning: Infrastructure providers who provide their customers with technologies for machine reasoning are helping them to solve problems in ambiguous and changing environments. Based on machine reasoning the AI environment is able to dynamically react to the ever-changing context, selecting the best course of action. This is ensured by selecting the best knowledge combinations for problem resolution. In the end, the results are optimized with machine learning algorithms.

Infrastructure Environments and Technologies for AI
In the course of years, cloud platform provider made enormous investments into AI functionalities and services. The leading public cloud provider in particular Amazon, Microsoft and Google are in the lead. But also several PaaS providers extended their offerings with AI services. The current AI technology landscape consists of the following three main categories:

  • Cloud machine learning (ML) platforms:Technologies like AWS Machine Learning or Google Machine Learning make it possible to use machine learning models based on proprietary technologies. Because even if Google Cloud ML sets on TensorFlow, most of the other cloud based ML services do not allow to execute AI applications that e.g. have been written in Theano, Torch, TensorFlow or Caffe.
  • AI cloud services:Technologies like Microsoft Cognitive Services, Google Cloud Vision or Natural Language APIs enable the use of complex AI abilities based on a simple API call. This allows organizations to develop applications with AI capabilities without investing into and owning the necessary AI infrastructure.
  • Technologies for private and public cloud environments: Technologies like HIRO are designed to run on top of public cloud environments like Amazon Web Services as well as private clouds such as OpenStack or VMware. They enable organizations to develop and operate transcontextual AI-based business models based on a general AI.

Further AI relevant categories and vendors are:

  • Machine Learning: Rapidminer, Context Relevant, H20, Datarpm, LiftIngniter, Spark Beyond, Yhat, Wise.io, Sense, GraphLab, Alpine, Nutonian
  • Conversational AI/ Bots: Mindfield, SemanticMachines, Maluuba, Mobvoi, KITT AI, Clara, Automat, Wit.ai, Cortical.io, Idibon, Luminoso
  • Vision: Clarifai, Chronocam, Orbital Insight, Pilot.ai, Captricity, Crokstyle
  • Auto: NuTonomy, Drive.ai, AI Motive, Nauto, Nexar, Zoox
  • Robotics: Ubtech, Anki, Rokid, Dispatch
  • Cybersecurity: Cyclance, Sift Science, Spark Cognition, Deep Instict, Shift Technology, Dark Trace
  • BI & Analytics: DataRobot, Trifaca, Tamr, Esigopt, Paxata, Dataminr, CrowdFlower, Logz.io
  • Ad, Sales and CRM: TalkIQ, Deepgram, Persado, Appier, Chors, InsideSales.com, Drawbridge, DigitalGenius, Resci
  • Healthcare: Freenome, Cloud Medx, Zebra, Enlitic, Two AR, iCarbonX, Atomwise, Deep Genomics, Babylon, Lunit
  • Text Analysis: Textio, Fido.ai, Narrative
  • IoT: Nanit, Konux, Verdigris, Sight Machine
  • Commerce: Bloomreach, Mode.ai
  • Fintech & Insurance: Cape Analytics, Kensho, Numerai, Alphasense, Kasisto

At the end of the day, the progressive developments of AI technologies are going to influence infrastructure environments and let them shift from a supporting mode towards a model where AI applications get the equal support like today's web applications and services.

The Future Is an AI-enabled Enterprise
An AI-enabled Infrastructure is an essential part of today's enterprise stack and builds the foundation for the AI-enabled enterprise. Because one thing is obvious. There are multiple challenges established companies are facing nowadays. Like the often-quoted war for talent or the inability of many large corporates to change effectively. But there is still an underestimated threat called competition - not from their own peers - but from high-tech companies like Amazon, Google, Facebook, etc., that are unstoppably marching into their markets. These high-tech companies invade the well-known competitive space of established companies with unimaginable financial resources and by hijacking the consumer life cycle.

Amazon is just one example who already has started to cut out the middleman within the own supply chain. We can be sure that business models of companies like DHL, UPS or FedEx are going to look different in the future - hint: Amazon Prime Air. Furthermore, Amazon has arranged everything to become a complete end-to-end provider of goods - digital as well as non-digital. It's likely that it won't be long until Facebook gets its banking license. Access to potential customers, enough information about its users and the necessary financial resources already exist. Consequently, established companies need to have powerful answers if they still want to exist tomorrow.

AI is one of these answers in the corporate toolkit to help overcome these competitive threats. However, time is running out for established companies. High-tech companies have already become uncatchable.

About Rene Buest
Rene Buest is Director of Market Research & Technology Evangelism at Arago. Prior to that he was Senior Analyst and Cloud Practice Lead at Crisp Research, Principal Analyst at New Age Disruption and member of the worldwide Gigaom Research Analyst Network. At this time he was considered a top cloud computing analyst in Germany and one of the worldwide top analysts in this area. In addition, he was one of the world’s top cloud computing influencers and belongs to the top 100 cloud computing experts on Twitter and Google+. Since the mid-90s he is focused on the strategic use of information technology in businesses and the IT impact on our society as well as disruptive technologies.

Rene Buest is the author of numerous professional technology articles. He regularly writes for well-known IT publications like Computerwoche, CIO Magazin, LANline as well as Silicon.de and is cited in German and international media – including New York Times, Forbes Magazin, Handelsblatt, Frankfurter Allgemeine Zeitung, Wirtschaftswoche, Computerwoche, CIO, Manager Magazin and Harvard Business Manager. Furthermore he is speaker and participant of experts rounds. He is founder of CloudUser.de and writes about cloud computing, IT infrastructure, technologies, management and strategies. He holds a diploma in computer engineering from the Hochschule Bremen (Dipl.-Informatiker (FH)) as well as a M.Sc. in IT-Management and Information Systems from the FHDW Paderborn.

Presentation Slides
To get the most out of their data, successful companies are not focusing on queries and data lakes, they are actively integrating analytics into their operations with a data-first application development approach. Real-time adjustments to improve revenues, reduce costs, or mitigate risk rely on applications that minimize latency on a variety of data sources. In his session at @BigDataExpo, Jack Norris, Senior Vice President, Data and Applications at MapR Technologies, reviewed best practices t...
DevOps promotes continuous improvement through a culture of collaboration. But in real terms, how do you: Integrate activities across diverse teams and services? Make objective decisions with system-wide visibility? Use feedback loops to enable learning and improvement? With technology insights and real-world examples, in his general session at @DevOpsSummit, at 21st Cloud Expo, Andi Mann, Chief Technology Advocate at Splunk, explored how leading organizations use data-driven DevOps to clos...
Recently, REAN Cloud built a digital concierge for a North Carolina hospital that had observed that most patient call button questions were repetitive. In addition, the paper-based process used to measure patient health metrics was laborious, not in real-time and sometimes error-prone. In their session at 21st Cloud Expo, Sean Finnerty, Executive Director, Practice Lead, Health Care & Life Science at REAN Cloud, and Dr. S.P.T. Krishnan, Principal Architect at REAN Cloud, discussed how they built...
The dynamic nature of the cloud means that change is a constant when it comes to modern cloud-based infrastructure. Delivering modern applications to end users, therefore, is a constantly shifting challenge. Delivery automation helps IT Ops teams ensure that apps are providing an optimal end user experience over hybrid-cloud and multi-cloud environments, no matter what the current state of the infrastructure is. To employ a delivery automation strategy that reflects your business rules, making r...
As many know, the first generation of Cloud Management Platform (CMP) solutions were designed for managing virtual infrastructure (IaaS) and traditional applications. But that's no longer enough to satisfy evolving and complex business requirements. In his session at 21st Cloud Expo, Scott Davis, Embotics CTO, explored how next-generation CMPs ensure organizations can manage cloud-native and microservice-based application architectures, while also facilitating agile DevOps methodology. He expla...
The past few years have brought a sea change in the way applications are architected, developed, and consumed—increasing both the complexity of testing and the business impact of software failures. How can software testing professionals keep pace with modern application delivery, given the trends that impact both architectures (cloud, microservices, and APIs) and processes (DevOps, agile, and continuous delivery)? This is where continuous testing comes in. D
Modern software design has fundamentally changed how we manage applications, causing many to turn to containers as the new virtual machine for resource management. As container adoption grows beyond stateless applications to stateful workloads, the need for persistent storage is foundational - something customers routinely cite as a top pain point. In his session at @DevOpsSummit at 21st Cloud Expo, Bill Borsari, Head of Systems Engineering at Datera, explored how organizations can reap the bene...
No hype cycles or predictions of a gazillion things here. IoT is here. You get it. You know your business and have great ideas for a business transformation strategy. What comes next? Time to make it happen. In his session at @ThingsExpo, Jay Mason, an Associate Partner of Analytics, IoT & Cybersecurity at M&S Consulting, presented a step-by-step plan to develop your technology implementation strategy. He also discussed the evaluation of communication standards and IoT messaging protocols, data...
In a recent survey, Sumo Logic surveyed 1,500 customers who employ cloud services such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). According to the survey, a quarter of the respondents have already deployed Docker containers and nearly as many (23 percent) are employing the AWS Lambda serverless computing framework. It’s clear: serverless is here to stay. The adoption does come with some needed changes, within both application development and operations. Tha...
Digital transformation is about embracing digital technologies into a company's culture to better connect with its customers, automate processes, create better tools, enter new markets, etc. Such a transformation requires continuous orchestration across teams and an environment based on open collaboration and daily experiments. In his session at 21st Cloud Expo, Alex Casalboni, Technical (Cloud) Evangelist at Cloud Academy, explored and discussed the most urgent unsolved challenges to achieve f...
With tough new regulations coming to Europe on data privacy in May 2018, Calligo will explain why in reality the effect is global and transforms how you consider critical data. EU GDPR fundamentally rewrites the rules for cloud, Big Data and IoT. In his session at 21st Cloud Expo, Adam Ryan, Vice President and General Manager EMEA at Calligo, examined the regulations and provided insight on how it affects technology, challenges the established rules and will usher in new levels of diligence arou...
In his general session at 21st Cloud Expo, Greg Dumas, Calligo’s Vice President and G.M. of US operations, discussed the new Global Data Protection Regulation and how Calligo can help business stay compliant in digitally globalized world. Greg Dumas is Calligo's Vice President and G.M. of US operations. Calligo is an established service provider that provides an innovative platform for trusted cloud solutions. Calligo’s customers are typically most concerned about GDPR compliance, application p...
Mobile device usage has increased exponentially during the past several years, as consumers rely on handhelds for everything from news and weather to banking and purchases. What can we expect in the next few years? The way in which we interact with our devices will fundamentally change, as businesses leverage Artificial Intelligence. We already see this taking shape as businesses leverage AI for cost savings and customer responsiveness. This trend will continue, as AI is used for more sophistica...
Smart cities have the potential to change our lives at so many levels for citizens: less pollution, reduced parking obstacles, better health, education and more energy savings. Real-time data streaming and the Internet of Things (IoT) possess the power to turn this vision into a reality. However, most organizations today are building their data infrastructure to focus solely on addressing immediate business needs vs. a platform capable of quickly adapting emerging technologies to address future ...
In his session at 21st Cloud Expo, Raju Shreewastava, founder of Big Data Trunk, provided a fun and simple way to introduce Machine Leaning to anyone and everyone. He solved a machine learning problem and demonstrated an easy way to be able to do machine learning without even coding. Raju Shreewastava is the founder of Big Data Trunk (www.BigDataTrunk.com), a Big Data Training and consulting firm with offices in the United States. He previously led the data warehouse/business intelligence and B...
Most technology leaders, contemporary and from the hardware era, are reshaping their businesses to do software. They hope to capture value from emerging technologies such as IoT, SDN, and AI. Ultimately, irrespective of the vertical, it is about deriving value from independent software applications participating in an ecosystem as one comprehensive solution. In his session at @ThingsExpo, Kausik Sridhar, founder and CTO of Pulzze Systems, discussed how given the magnitude of today's application ...
Nordstrom is transforming the way that they do business and the cloud is the key to enabling speed and hyper personalized customer experiences. In his session at 21st Cloud Expo, Ken Schow, VP of Engineering at Nordstrom, discussed some of the key learnings and common pitfalls of large enterprises moving to the cloud. This includes strategies around choosing a cloud provider(s), architecture, and lessons learned. In addition, he covered some of the best practices for structured team migration an...
The “Digital Era” is forcing us to engage with new methods to build, operate and maintain applications. This transformation also implies an evolution to more and more intelligent applications to better engage with the customers, while creating significant market differentiators. In both cases, the cloud has become a key enabler to embrace this digital revolution. So, moving to the cloud is no longer the question; the new questions are HOW and WHEN. To make this equation even more complex, most ...
As you move to the cloud, your network should be efficient, secure, and easy to manage. An enterprise adopting a hybrid or public cloud needs systems and tools that provide: Agility: ability to deliver applications and services faster, even in complex hybrid environments Easier manageability: enable reliable connectivity with complete oversight as the data center network evolves Greater efficiency: eliminate wasted effort while reducing errors and optimize asset utilization Security: imple...
Kubernetes is an open source system for automating deployment, scaling, and management of containerized applications. Kubernetes was originally built by Google, leveraging years of experience with managing container workloads, and is now a Cloud Native Compute Foundation (CNCF) project. Kubernetes has been widely adopted by the community, supported on all major public and private cloud providers, and is gaining rapid adoption in enterprises. However, Kubernetes may seem intimidating and complex ...
In his session at 21st Cloud Expo, Michael Burley, a Senior Business Development Executive in IT Services at NetApp, described how NetApp designed a three-year program of work to migrate 25PB of a major telco's enterprise data to a new STaaS platform, and then secured a long-term contract to manage and operate the platform. This significant program blended the best of NetApp’s solutions and services capabilities to enable this telco’s successful adoption of private cloud storage and launching ...
You know you need the cloud, but you’re hesitant to simply dump everything at Amazon since you know that not all workloads are suitable for cloud. You know that you want the kind of ease of use and scalability that you get with public cloud, but your applications are architected in a way that makes the public cloud a non-starter. You’re looking at private cloud solutions based on hyperconverged infrastructure, but you’re concerned with the limits inherent in those technologies.
Blockchain is a shared, secure record of exchange that establishes trust, accountability and transparency across business networks. Supported by the Linux Foundation's open source, open-standards based Hyperledger Project, Blockchain has the potential to improve regulatory compliance, reduce cost as well as advance trade. Are you curious about how Blockchain is built for business? In her session at 21st Cloud Expo, René Bostic, Technical VP of the IBM Cloud Unit in North America, discussed the b...
Companies are harnessing data in ways we once associated with science fiction. Analysts have access to a plethora of visualization and reporting tools, but considering the vast amount of data businesses collect and limitations of CPUs, end users are forced to design their structures and systems with limitations. Until now. As the cloud toolkit to analyze data has evolved, GPUs have stepped in to massively parallel SQL, visualization and machine learning.
In this strange new world where more and more power is drawn from business technology, companies are effectively straddling two paths on the road to innovation and transformation into digital enterprises. The first path is the heritage trail – with “legacy” technology forming the background. Here, extant technologies are transformed by core IT teams to provide more API-driven approaches. Legacy systems can restrict companies that are transitioning into digital enterprises. To truly become a lead...
IoT is at the core or many Digital Transformation initiatives with the goal of re-inventing a company's business model. We all agree that collecting relevant IoT data will result in massive amounts of data needing to be stored. However, with the rapid development of IoT devices and ongoing business model transformation, we are not able to predict the volume and growth of IoT data. And with the lack of IoT history, traditional methods of IT and infrastructure planning based on the past do not app...
Cloud applications are seeing a deluge of requests to support the exploding advanced analytics market. “Open analytics” is the emerging strategy to deliver that data through an open data access layer, in the cloud, to be directly consumed by external analytics tools and popular programming languages. An increasing number of data engineers and data scientists use a variety of platforms and advanced analytics languages such as SAS, R, Python and Java, as well as frameworks such as Hadoop and Spark...
In his session at @ThingsExpo, Dr. Robert Cohen, an economist and senior fellow at the Economic Strategy Institute, presented the findings of a series of six detailed case studies of how large corporations are implementing IoT. The session explored how IoT has improved their economic performance, had major impacts on business models and resulted in impressive ROIs. The companies covered span manufacturing and services firms. He also explored servicification, how manufacturing firms shift from se...
Businesses and business units of all sizes can benefit from cloud computing, but many don't want the cost, performance and security concerns of public cloud nor the complexity of building their own private clouds. Today, some cloud vendors are using artificial intelligence (AI) to simplify cloud deployment and management. In his session at 20th Cloud Expo, Ajay Gulati, Co-founder and CEO of ZeroStack, discussed how AI can simplify cloud operations. He covered the following topics: why cloud mana...
Docker containers have brought great opportunities to shorten the deployment process through continuous integration and the delivery of applications and microservices. This applies equally to enterprise data centers as well as the cloud. In his session at 20th Cloud Expo, Jari Kolehmainen, founder and CTO of Kontena, discussed solutions and benefits of a deeply integrated deployment pipeline using technologies such as container management platforms, Docker containers, and the drone.io Cl tool. H...

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nfrastructure

MOULINE
Everbridge

MARSH
Blue Pillar

PARKS
SecureRF

PEROTTI
Plantronics

HOFFMAN
EastBanc

WATSON
Trendalyze

BENSON-
OFF

Unigma

SHAN
CTS

MATTELA
Redpine

GILLEN
Spark
Coginition

SOLT
Netvibes

BERN-
ARDO

GE Digital

ROMAN-
SKY

TrustPoint

BEAMER
GoTransverse

LESTER
LogMeIn

PONO
-MAREVA

Google

SINGH
Sencha

CALKINS
Amadeus

KLEIN
Rachio

HOASIN
Aeris

SARKARIA
PHEMI

SPROULE
Metavine

SNELL
Intel

LEVINE
CytexOne

ALLEN
Freewave

MCCAL-
LUM

Falconstor

HYEDT
Seamless

WebRTC Summit Silicon Valley All-Star Speakers Include

SCHULZ
Luxoft

TAM-
BURINI

Autodesk

MCCARTHY
Bsquare

THURAI
SaneIoT

TURNER
Cloudian

ENDO
Intrepid

NAKAGAWA
Transparent

SHIBATA
Transparent

LEVANT-LEVI
testRTC

VARAN NATH
GE

COOPER
M2Mi

SENAY
Teletax

SKEEN
Vitria

KOCHER
Grey Heron

GREENE
PubNub

MAGUIRE
HP

MATTHIEU
Octoblu

STEINER-
JOVIC

AweSense

LYNN
AgilData

HEDGES
Cloudata

DUFOUR
Webroot

ROBERTS
Platform

JONES
Deep

PFEIFFER
NICTA

NIELSEN
Redis

PAOLAL-
ANTORIO

DataArchon

KAHN
Solgenia

LOPEZ
Kurento

KIM
MapR

BROMHEAD
Instaclustr

LEVINE
CytexOne

BONIFAZI
Solgenia

GORBA-
CHEV

Intelligent
Systems

THYKAT-
TIL

Navisite

TRELOAR
Bebaio

SIVARAMA-
KRISHNAN

Red Hat
Cloud Expo New York All-Star Speakers Included

DE SOUZA
Cisco

POTTER
SafeLogic

ROBINSON
CompTIA

WARUSA
-WITHANA

WSO2 Inc

MEINER
Oracle

CHOU
Microsoft

HARRISON
Tufin

BRUNOZZI
VMware

KIM
MapR

KANE
Dyn

SICULAR
Basho

TURNER
Cloudian

KUMAR
Liaison

ADAMIAK
Liaison

KHAN
Solgenia

BONIFAZI
Solgenia

SUSSMAN
Coalfire

ISAACSON
RMS

LYNN
CodeFutures

HEABERLIN
Windstream

RAMA
MURTHY

Virtusa

BOSTOCK
IndependenceIT

DE MENO
CommVault

GRILLI
Adobe

WILLIAMS
Rancher Labs

CRISWELL
Alert Logic

COTY
Alert Logic

JACOBS
SingleHop

MARAVEI
Cisco

JACKSON
Softlayer

SINGH
IBM

HAZARD
Softlayer

GALLO
Softlayer

TAMASKAR
GENBAND

SUBRA
-MANIAN

Emcien

LEVESQUE
Windstream

IVANOV
StorPool

BLOOM-
BERG

Intellyx

BUDHANI
Soha

HATHAWAY
IBM Watson

TOLL
ProfitBricks

LANDRY
Microsoft

BEARFIELD
Blue Box

HERITAGE
Akana

PILUSO
SIASMSP

HOLT
IBM Cloudant

SHAN
CTS

PICCIN-
INNI

EMC

BRON-
GERSMA

Modulus

PAIGE
CenturyLink

SABHIKHI
Cognitive Scale

MILLS
Green House Data

KATZEN
CenturyLink

SLOPER
CenturyLink

SRINIVAS
EMC

TALREJA
Cisco

GORBACHEV
Systems Services Inc.

COLLISON
Apcera

PRABHU
OpenCrowd

LYNN
CodeFutures

SWARTZ
Ericsson

MOSHENKO
CoreOS

BERMING-
HAM

SIOS

WILLIS
Stateless Networks

MURPHY
Gridstore

KHABE
Vicom

NIKOLOV
GetClouder

DIETZE
Windstream

DALRY-
MPLE

EnterpriseDB

MAZZUCCO
TierPoint

RIVERA
WHOA.com

HERITAGE
Akana

SEYMOUR
6fusion

GIANNETTO
Author

CARTER
IBM

ROGERS
Virtustream
Cloud Expo Silicon Valley All-Star Speakers

TESAR
Microsoft

MICKOS
HP

BHARGAVA
Intel

RILEY
Riverbed

DEVINE
IBM

ISAACSON
CodeFutures

LYNN
HP

HINKLE
Citrix

KHAN
Solgenia

SINGH
Bigdata

BEACH
SendGrid

BOSTOCK
IndependenceIT

DE SOUZA
Cisco

PATTATHIL
Harbinger

O'BRIEN
Aria Systems

BONIFAZI
Solgenia

BIANCO
Solgenia

PROCTOR
NuoDB

DUGGAL
EnterpriseWeb

TEGETHOFF
Appcore

BRUNOZZI
VMware

HICKENS
Parasoft

KLEBANOV
Cisco

PETERS
Esri

GOLDBERG
Vormetric

CUMBER-
LAND

Dimension

ROSENDAHL
Quantum

LOOMIS
Cloudant

BRUNO
StackIQ

HANNON
SoftLayer

JACKSON
SoftLayer

HOCH
Virtustream

KAPADIA
Seagate

PAQUIN
OnLive

TSAI
Innodisk

BARRALL
Connected Data

SHIAH
AgilePoint

SEGIL
Verizon

PODURI
Citrix

COWIE
Dyn

RITTEN-
HOUSE

Cisco

FALLOWS
Kaazing

THYKATTIL
TimeWarner

LEIDUCK
SAP

LYNN
HP

WAGSTAFF
BSQUARE

POLLACK
AOL

KAMARAJU
Vormetric

BARRY
Catbird

MENDEN-
HALL

SUPERNAP

SHAN
KEANE

PLESE
Verizon

BARNUM
Voxox

TURNER
Cloudian

CALDERON
Advanced Systems

AGARWAL
SOA Software

LEE
Quantum

OBEROI
Concurrent, Inc.

HATEM
Verizon

GALEY
Autodesk

CAUTHRON
NIMBOXX

BARSOUM
IBM

GORDON
1Plug

LEWIS
Verizon

YEO
OrionVM

NAKAGAWA
Transparent Cloud Computing

SHIBATA
Transparent Cloud Computing

NATH
GE

GOKCEN
GE

STOICA
Databricks

TANKEL
Pivotal Software


Testimonials
This week I had the pleasure of delivering the opening keynote at Cloud Expo New York. It was amazing to be back in the great city of New York with thousands of cloud enthusiasts eager to learn about the next step on their journey to embracing a cloud-first worldl."
@SteveMar_Msft
General Manager of Window Azure
 
How does Cloud Expo do it every year? Another INCREDIBLE show - our heads are spinning - so fun and informative."
@SOASoftwareInc
 
Thank you @ThingsExpo for such a great event. All of the people we met over the past three days makes us confident IoT has a bright future."
Yasser Khan
CEO of @Cnnct2me
 
One of the best conferences we have attended in a while. Great job, Cloud Expo team! Keep it going."

@Peak_Ten


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@CloudExpo Blogs
While Artificial Intelligence (AI) may not be a new concept, its contribution to automation may just change the face of business. AI's conception dates as far back as 1950, when Alan Turing proposed the Turing test in order to evaluate a machine's ability to exhibit intelligent behavior. Fast-forward a couple of decades and research led to the creation of well-known theoretical tools such as Fuzzy Logic, Bayesian Networks, Markov Models and Neural Networks. Concurrently, new types of programming languages such as Prolog, LISP and Smalltalk set the scene for most of the modern interpreted langu...
Blockchain offers impeccable security with its cryptography-based decentralized system as well as the plethora of possible uses retailers could exploit in the near future. In a world of increasing cyberattacks, internet fraud and online hacking, blockchain comes as a breath of fresh air. With its encrypted data and decentralized network system, it's a thorn in every hacker's side. Generally being associated with the finance sector, blockchain is now taking retail by storm. It's on a course that will change the retail industry as we know it. But how exactly is it going to achieve such a feat?
In an attempt to put the patient first in healthcare, Congress and President Obama in 2015 approved a bipartisan bill for United States healthcare reform. The bill is known as “Medicare Access and CHIP Reauthorization Act of 2015,” or MACRA. Among the major provisions of MACRA is the Quality Payment Program. Under the Quality Payment Program, physicians and nurses receive positive, neutral or negative Medicare payment adjustments based upon a “Patient Satisfaction Score,” that is, patient satisfaction scores have a direct impact on how physicians, physician assistants, nurses, and hospital’s g...
The high barrier to entry prevents many companies from tapping into the full potential of machine learning. But what if you could make it more accessible? We’re in the midst of a data explosion, with today’s enterprises amassing goldmines of information (25 quintillion bytes of data every day, according to some reports). But what exactly are they doing with this data? Considering the volume of data being collected is quickly becoming unmanageable, now is a good time to shift from manual machine learning to a cognitive approach. This enables businesses to better capitalize on their data and fa...
The “Internet of Things” is an exciting area of tech, one in which industry experts estimate there will be more than 30 billion connected IoT devices by 2020. IoT is the inter-networking and instrumentation of physical devices – everything from streets, cars, factories, power grids, ice caps, satellites, and clothing to phones, microwaves, milk containers, planets, human bodies, etc. IoT creates an opportunity to measure, collect and analyze an ever-increasing variety of behavioral statistics. That being said, data, and more importantly insight into the data, is key for enhanced business val...
Our work, both with clients and with tools, has lead us to wonder how it is that organizations are handling compliance issues in the cloud. The big cloud vendors offer compliance for their infrastructure, but the shared responsibility model requires that you take certain steps to meet compliance requirements. Which lead us to start poking around a little more. We wanted to get a picture of what was available, and how it was being used. There is a lot of fluidity in this space, as in all things cloud. The fact that DevOps Security plays into the cloud compliance model – particularly in dynamic ...
Gaining visibility in today’s sprawling cloud infrastructure is complex and laborious, involving drilling down into tools offered by various cloud services providers. Enterprise IT organizations need smarter and effective tools at their disposal in order to address this pertinent problem. Gaining a 360 - degree view of the cloud costs requires collection and analysis of the cost data across all cloud infrastructures used inside an enterprise.
The 22nd International Cloud Expo | 1st DXWorld Expo has announced that its Call for Papers is open. Cloud Expo | DXWorld Expo, to be held June 5-7, 2018, at the Javits Center in New York, NY, brings together Cloud Computing, Digital Transformation, Big Data, Internet of Things, DevOps, Machine Learning and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit your speaking proposal today!
The goal of Microservices is to improve software delivery speed and increase system safety as scale increases. Microservices being modular these are faster to change and enables an evolutionary architecture where systems can change, as the business needs change. Microservices can scale elastically and by being service oriented can enable APIs natively. Microservices also reduce implementation and release cycle time and enables continuous delivery. This paper provides a logical overview of the Microservices Reference Architecture that highlights various sub systems needed to support Microservic...
The notion of improving operational efficiency is conspicuously absent from the healthcare debate - neither Obamacare nor the newly proposed GOP plan discusses the impact that a step-function improvement in efficiency could have on access to healthcare (through more capacity), quality of healthcare services (through reduced wait times for patients) or cost (through better utilization of scarce, expensive assets).
Most of us understand that artificial intelligence (AI) offers opportunities for productivity improvements in the form of speed, automation, standardized actions and responses, plus the opportunity for continuous improvements via machine learning. These opportunities are enabled by data inputs that are analyzed and processed through AI algorithms that execute a desired decision and action. For all of the great capabilities and benefits that AI can provide, there is also a potential dark side. AI solutions can easily codify our prejudices, bias, gender stereotypes and promote injustices intenti...
Gone are the days when application development was the daunting task of the highly skilled developers backed with strong IT skills, low code application development has democratized app development and empowered a new generation of citizen developers. There was a time when app development was in the domain of people with complex coding and technical skills. We called these people by various names like programmers, coders, techies, and they usually worked in a world oblivious of the everyday priorities of the business world. However, with the passage of time, this scenario is much more democr...
It’s conference season and, as you might expect, Jason and I have been on the road covering a bunch of them. It’s always great to see what the disruptive players in the market are doing — and this year did not disappoint. But there is one thing that repeatedly happens that just gets under my skin: transformation-washing. As Jason explained in a Forbes article over a year ago, ‘washing’ is when a vendor (or pundit) applies a buzzword loosely in an overt attempt to attach themselves to its buzz. And transformation-washing is rampant.
Networks have become large, complex entities that are increasingly difficult to manage and control. Security, audit, risk and compliance professionals know that their organizations rely on them for effective risk management, control and governance processes that are essential to the safety of their network environment. Yet compliance and security are more challenging than ever before as additional layers are added to this environment. One of the challenges lies in the fact that there is an ongoing, huge access gap in network security and compliance – and it has been residing within the enviro...
Some journey to cloud on a mission, others, a deadline. Change management is useful when migrating to public, private or hybrid cloud environments in either case. For most, stakeholder engagement peaks during the planning and post migration phases of a project. Legacy engagements are fairly direct: projects follow a linear progression of activities (the “waterfall” approach) – change managers and application coders work from the same functional and technical requirements. Enablement and development mirror one another, progressing from proof-of-concept planning to final product delivery. Exce...
Fingerspitzengefühl: A German word used to describe the ability to maintain attention to detail in an ever-changing operational and tactical environment by maintaining real-time situational awareness. The term is synonymous with the English expression of "keeping one's finger on the pulse". The problem with fingerspitzengefühl traditionally, in addition to pronouncing it, has been it is hard for an individual to scale up. Today that is changing. In a world of sensors, AI and mobile devices, having real-time situational awareness is far easier than ever before. In fact, today the challenge i...
Making informed network investment decisions about emerging technologies such as network function virtualization (NFV) and software-defined networking (SDN) can help evolve the network to keep pace with the innovations of the devices and people it’s connecting. As you work with business leaders to make decisions about upgrading your infrastructure with these networking developments, it’s important to understand the similarities, differences, and benefits of dual NFV and SDN implementation. With their ability to offer a new way to design, deploy, and manage the network and its services, NFV a...
For DevOps teams, the concepts behind service-oriented architecture (SOA) are nothing new. A style of software design initially made popular in the 1990s, SOA was an alternative to a monolithic application; essentially a collection of coarse-grained components that communicated with each other. Communication would involve either simple data passing or two or more services coordinating some activity. SOA served as a valid approach to solving many architectural problems faced by businesses, as applications could be developed by more teams working in parallel and more productively by reusing orig...
Many IT organizations have come to learn that leveraging cloud infrastructure is not just unavoidable, it’s one of the most effective paths for IT organizations to become more responsive to business needs. Yet with the cloud comes new challenges, including minimizing downtime, decreasing the cost of operations, and preventing employee burnout to name a few. As companies migrate their processes and procedures to their new reality of a cloud-based infrastructure, an incident management solution can and should be adopted to help overcome these challenges. This is particularly true when larger ...
We’re seeing an emerging trend in the cloud computing world. I’ve been referring to it as cloud fatigue, but it’s more commonly known as repatriation, or moving workloads from the cloud back to on-prem locations. According to a recent 451 Research report, over 21 percent of organizations have plans to pull back from the cloud and return to an on-prem infrastructure in 2017. Considering the vast growth of cloud adoption over the last several years, what’s behind this trend?