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C5050-280 - IBM Cloud Computing Infrastructure Architect V1 - BrainDump Information

Vendor Name : IBM
Exam Code : C5050-280
Exam Name : IBM Cloud Computing Infrastructure Architect V1
Questions and Answers : 98 Q & A
Updated On : March 18, 2019
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C5050-280 exam Dumps Source : IBM Cloud Computing Infrastructure Architect V1

Test Code : C5050-280
Test Name : IBM Cloud Computing Infrastructure Architect V1
Vendor Name : IBM
Q&A : 98 Real Questions

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IBM IBM Cloud Computing Infrastructure

After limping through chapter certainly one of cloud computing, IBM goals to personal chapter two | killexams.com Real Questions and Pass4sure dumps

In 2013, IBM Corp. received a wakeup call when it misplaced an important cloud computing deal on the critical Intelligence agency to Amazon net services Inc.

IBM protested the contract, exposing previously private particulars. In a high-profile resolution, judge Thomas Wheeler dominated in opposition t IBM regardless of the apparent bigger bid submitted by way of AWS. The final analysis: AWS’ cloud offering become considered as advanced to IBM’s.

below 24 months into her tenure as IBM’s chief government, Ginni Rometty (pictured) understood the necessary. IBM had to make a flow to get into the general public cloud video game or it might be disregarded in the cold, a lot like Hewlett Packard business Co., Cisco systems Inc., EMC Corp., VMware Inc. and other enormous tech enterprises on the time. IBM paid $2 billion to purchase SoftLayer and has on the grounds that transformed the platform into a doable offering from which it intends to rewrite the cloud narrative.

right here’s a paraphrase of the premise put forth by means of IBM’s chairman and CEO at this week’s IBM consider convention in San Francisco:  

Chapter probably the most cloud represented about 20 % of the workload opportunity. It became mostly about moving lots of new and client-facing functions to the cloud. Chapter two is in regards to the difficult stuff. It’s about scaling synthetic intelligence and developing hybrid clouds. It’s about bringing the cloud working mannequin to all these mission-essential apps and enabling purchasers to control records, workloads and apps and circulate them between distinctive clouds. this is one trillion-greenback chance and IBM intends to be No. 1.

IBM is not on my own in its aspiration. colossal businesses reminiscent of Cisco, VMware and even HPE have a little bit similar aspirations. As does ServiceNow Inc. and a host of smaller specialist companies. and naturally, the general public cloud giants, including AWS and Microsoft Corp., have their own ideas about chapter two of the cloud era.

To declare a management place in this subsequent chapter, IBM is spending $34 billion to purchase open-supply software chief pink Hat Inc. here is an immense move on the chessboard, underscoring that the IBM Cloud and a decade of trying to commercialize the AI-powered Watson equipment aren’t sufficient to win the day. quite, it sees open source, Kubernetes, containers, microservices and developers as a lynchpin to success within the subsequent chapter of cloud.

a brief evaluate of chapter one

There’s lots debate about who first created the term cloud computing. There’s little doubt, although, that AWS evangelist Jeff Barr’s weblog post in the summer of 2006, asserting AWS’ Elastic Compute Cloud, ushered within the modern period of cloud — chapter one. In his submit, Barr wrote:

With Amazon EC2, you don’t need to purchase hardware in increase of your wants. in its place, you effortlessly flip up the dial, spawning extra digital CPUs, as your processing wants grow.

His fact underscored the most fundamental price proposition of cloud: Pay only for what you use. This of path changed into the first of a large number of innovations and services — all available with the swipe of a credit card, to be dialed up on demand. Startups flocked and tapped world-class data middle features up to now obtainable handiest to enormous agencies.

The financial downturn of 2007-2009 led chief fiscal officers to mandate a shift from capital bills to working costs, and when the economic system grew to become up, companies realized that their cloud experience enabled a lot better agility. Shadow suggestions technology powered the subsequent section of growth and as “cloud creep” permeated the market. IT departments hopped on board and haven’t looked again.

notably, Microsoft modified itself to the cloud the usage of the method of: 1) An open-supply approach with alignment and support on open compute, Linux on .internet etc; 2) cloudifying all issues Microsoft and making Azure, not windows, the middle of its universe; and 3) bundling office 365 to demonstrate salary from not handiest infrastructure and a provider however application as a service.

Joined by means of Google, which used its dominant global search infrastructure to stake its claim in cloud, the huge three lead the way for a new economic mannequin in line with scale, innovation and automation, making use of software economics to the theory of infrastructure deployment and management capabilities (figures under).

first-graph

second-graph

Key aspects in the charts:

  • historically, the marginal charge of of utility procedures zero while services have terrible economies of scale;
  • With cloud, infrastructure functions song greater carefully to utility economics, enabling huge scale (and profitability) for those with volume (AWS, Microsoft and GoogleLLC);
  • normal infrastructure agencies combat to grasp on to legacy put in bases;
  • Cloud companies with a SaaS portfolio (Oracle, IBM, Microsoft) have “up-the-stack” cost benefits they can use as a bulwark against commoditization of their groups.
  • IBM’s prospects for chapter two leadership count on statistics

    earlier than diving into the crimson Hat piece of the puzzle, we should factor returned to information. In our view, IBM is working intently with clients to construct a digital company material where records is still the underpinning of its approach to power a brand new period of analytics in line with AI. IBM sees statistics as a fundamental ingredient to bringing contextual relevance to company applications. What we’re seeing is because of IBM’s huge features enterprise and deep trade expertise it has earned the correct to assist customers construct digital networks and seriously change company fashions.

    IBM’s tremendous consumers have become this. They’re not trying to IBM to readily bring features or comfortable their infrastructure or promote them SaaS. reasonably, they’re trying to find IBM to support them radically change and bring new enterprise models. We’re seeing this in healthcare, financials features, agriculture, power, coverage and practically all industries wherein IBM has a presence globally.

    IBM’s opportunity as we see it's to aid organizations take note a way to make cash the use of statistics — not always by means of directly selling their statistics but deciding a way to monetize records. What we see IBM doing is taking what were largely piecemeal, statistics-oriented AI tasks and growing what Rometty calls “outside/In”: customer adventure oriented functions and “internal/Out” — that is, workflow and new the right way to work purposes — each which contribute to bottom-line outcomes. greater importantly, IBM desires to support shoppers fully radically change their business operations.

    to accomplish this, IBM is supplying a enterprise platform fueled via information and a laptop intelligence platform, which means tooling and capabilities to extract value from records and operationalize AI.

    Enter red Hat

    IBM didn’t free up any new details about red Hat at suppose, most likely on account of regulatory concerns. but with pink Hat, IBM can enable a new breed of application developers — for corporations — the usage of cloud-native tooling. records is the important thing ingredient to emerging business functions, and with red Hat in its portfolio, IBM can “cloudify” and “information-fy” organizations and position itself as contemporary and critical. extra importantly, it could actually dramatically scale crimson Hat’s business globally.

    red Hat for IBM emerges as a automobile for producing spinoff leverage out of IBM ecosystem application and trade potential. With RHEL, OpenShift and 8 million pink Hat developers, IBM can support its consumers modernize their application portfolios and transform company operations — creating a new breed of digital business developers.

    trust statements made by means of Rometty and purple Hat CEO Jim Whitehurst throughout their mini-roadshow after asserting the pink Hat acquisition. Rometty kept asserting, “This isn’t a backend-loaded deal.” What did she imply? In our view, she become virtually explaining the enterprise case for IBM paying a 60 percent-plus top rate over red Hat’s stock price earlier than the deal being announced. notably, IBM has an enormous installed base of services valued clientele (a $20 billion-plus captive chance in our estimate) at which it may element red Hat PaaS tooling to modernize application portfolios and construct the longer term digital company platform for and with shoppers.

    So out of the chute, IBM can immediately start scaling purple Hat’s company, marrying deep trade competencies, the sprawling IBM SaaS portfolio and the place relevant the IBM Cloud, AI-infused all over the place, and crimson Hat platform as a provider to join consumer information, workloads and functions to any cloud or on-premises setting up.

    Longer-term, IBM can, together with its valued clientele, absolutely adopt up to date application development practices to codify its deep business knowledge and construct out transformative business and AI systems to help incumbent companies compete in the digital era.

    The competitive landscape

    in case you don’t own a public cloud, you go complicated after multicloud. To wit: VMware exited public cloud after years of attempting to commercialize VCloud Air. It at last settled on a cope with AWS and sold off its public cloud. VMware is Dell’s ace within the gap for multicloud.

    Cisco lately announced its multicloud strategy at Cisco live Barcelona that comes at the difficulty from a powerful position in networking. As networks flatten, Cisco will also be the glue between clouds with a application administration and orchestration framework for networked data — now not a nasty approach. HP tried and failed within the public cloud online game and HPE is attempting to be a provider of multicloud features, nonetheless it’s generally relying on packaging its hardware, functions and some minimal software content.

    of those avid gamers, handiest Cisco has any meaningful presence with builders. IBM with pink Hat receives entry to eight million devs.

    in consequence, IBM has a more robust position than these players — albeit more complex. It owns a public cloud presence and though no longer nearly as giant as AWS in IaaS, IBM has a big SaaS portfolio. Like Oracle, it doesn’t need to compete for commodity enterprise towards AWS. reasonably it may well promote value “up the stack” using SaaS as a high-value play. As smartly, its AI runs within the cloud and it just introduced at think that it’s opening up Watson to run on any on-premises, public or hybrid cloud (a protracted overdue movement in our opinion). previously, if you desired Watson, you could best get it on IBM’s cloud.

    Microsoft clearly could have its say in chapter two of the cloud. With its acquisition of GitHub and its giant utility estate, combined with a leading cloud at scale, Microsoft holds a lot of playing cards. it's investing in AI and has a strong information perspective.

    Google Cloud is resetting with new administration and is playing the long game. It evidently has AI chops and a powerful information perspective.

    Then there’s AWS. Amazon’s announcement of Outposts suggests that it will possibly and may evolve and alter its spots. nowadays, AWS makes a powerful case for a single versus a multicloud strategy — arguing that multiple clouds are much less cozy, greater complicated and extra high priced. whereas credible in its place, the truth is multicloud is like multivendor. There’s now not a procurement czar interior every enterprise so as to dictate a single cloud. As such, if AWS sees a chance to manage varied clouds it will enter the house, in our view.

    ultimate suggestions

    the brand new “innovation cocktail” combines statistics + AI + Cloud. a typical statistics mannequin brings aggressive knowledge in a digital world. computing device intelligence, or AI, applied to statistics drives insights and cloud makes it possible for scale and attracts innovation via ecosystems. IBM is combining these three features to compete within the next chapter of expertise trade growth.

    IBM, like Microsoft, is cloudifying its choices to guide its valued clientele’ digital transformations. through bringing cloud to its products, building records networks with purchasers, making use of AI all over the place and leveraging purple Hat, it could catalyze a brand new type of company builders and go challenging after the multicloud chance that exists.

    We accept as true with, despite the fact, that the multicloud world might be messy. these days, multicloud is as a good deal a multivendor incidence as a deliberate method. then again, consumers will continue to opt for horses for courses — meaning the right cloud for the right workload — and so as to inevitably cause assorted clouds and opportunities for simplified administration, safety, governance and facts leverage.

    today, about half of IBM’s earnings comes from so-called Strategic Imperatives. That piece must develop sooner than the other half declines. in addition, about 60 % of IBM’s earnings comes from consulting and professional services. The first rate information there's that it offers IBM deep visibility and relationships into well-nigh all global industries. The downside is that enterprise doesn’t scale as neatly.

    As such, IBM’s choicest electricity is additionally its premiere challenge. The unique probability dealing with IBM is to codify that deep trade knowledge in application, using records because the key ingredient for new business purposes constructed on cloud native PaaS tooling and scaling to the cloud — any cloud.  

    this is a differentiating story and one that protects IBM from getting “Amazon’d” whereas at the equal time permitting the enterprise to pressure margin improvements over time. Rometty has spent the ultimate five to 6 years getting ready the business for this subsequent chapter. Now huge Blue should exhibit that elephants can dance, dash and run marathons.

    photo: IBM/livestream due to the fact you’re here …

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    evaluation: IBM CEO publicizes Chapter 2 of Cloud and AI at IBM believe 2019 | killexams.com Real Questions and Pass4sure dumps

    In 2013, IBM had a wakeup name.

    It lost a crucial cloud deal at the CIA to AWS. IBM protested the contract exposing in the past exclusive particulars. In a high profile resolution, decide Thomas Wheeler ruled in opposition t IBM regardless of the obvious bigger price bid submitted with the aid of AWS. The final analysis is AWS’ cloud providing become viewed as superior to IBM’s.

    less than twenty-4 months into her tenure as IBM’s CEO, Ginni Rometty understood the integral. IBM had to make a movement to get into the general public cloud video game or it would be overlooked within the bloodless, lots like HP, Cisco, EMC, VMware, and other tremendous tech organizations on the time. IBM paid $2B to purchase Softlayer and has due to the fact that changed the platform right into a achievable offering from which it intends to re-write the cloud narrative.

    here’s a paraphrase of the premise put forth by using IBM’s Chairman and CEO at this week’s IBM consider conference in San Francisco:  

    Chapter one of the cloud represented about 20% of the workload possibility. It became mostly about relocating lots of new and client-dealing with functions to the cloud. Chapter two is about the challenging stuff. It’s about scaling AI and growing hybrid clouds. It’s about bringing the cloud working model to all those mission-critical apps and enabling consumers to control statistics, workloads, and apps and flow them between diverse clouds. here is one thousand billion dollar chance and IBM intends to be #1.

    IBM is not by myself in its aspiration. gigantic corporations like Cisco, VMware, and even HPE have somewhat similar aspirations. As does ServiceNow and a bunch of smaller professional enterprises. and naturally, the public cloud giants including AWS and Microsoft have their personal ideas about Chapter 2 of the cloud period.

    To claim a leadership position in Chapter 2, IBM is spending $34B to purchase crimson Hat. here's a big circulate on the chess board and underscores that the IBM Cloud and a decade of making an attempt to commercialize Watson aren’t sufficient to win the day. quite it sees open source, Kubernetes, containers, microservices, and builders as a lynchpin to success within the next chapter of the cloud.

    a brief overview of Chapter One

    There’s a great deal debate about who first created the term cloud computing. There’s little doubt although that Jeff Barr’s weblog publish in the summertime of 2006, announcing AWS’ Elastic Compute Cloud, ushered within the up to date era of cloud - so-known as Chapter 1. In his publish, Barr wrote:

    With Amazon EC2, you don’t deserve to acquire hardware in advance of your needs. as a substitute, you effortlessly flip up the dial, spawning greater virtual CPUs, as your processing needs develop.  

    His statement underscored essentially the most simple cost proposition of cloud - pay for under what you use model. This, of course, was the primary of a large number of innovations and features - all available with the swipe of a bank card, to be dialed up on demand. Startups flocked and tapped world-class information middle capabilities up to now best obtainable to gigantic groups.

    The financial downturn of 2007-2009 led CFOs to mandate a shift from Capex to Opex and when the economic climate became up, corporations realized that their cloud event enabled an awful lot enhanced agility. Shadow IT-powered the subsequent phase of increase and as “cloud creep” permeated the market - IT hopped on board and hasn’t looked returned.

    above all, Microsoft modified itself to the cloud using the components of: 1) An open supply attitude - alignment and help (open compute, linux on .internet, etc.); 2) Cloudify all issues Microsoft and making Azure, now not home windows, the core of its universe; and 3) bundling office 365 to show income from no longer simplest IaaS however SaaS.

    Joined by way of Google, which used its dominant world search infrastructure to stake its declare within the cloud, the large three paved the way for a new financial mannequin based on scale, innovation and automation, making use of utility economics to the conception of infrastructure deployment and administration services (See Figures 1 & 2 under).

    commercial enterprise IT Economics 1990-2010SiliconAngle.com

    business IT Economics 2010-2030SiliconAngle.com

    Key aspects within the Charts:

  • traditionally, the marginal can charge of utility procedures zero whereas services have negative economies of scale;
  • With cloud - infrastructure functions tune more intently to utility economics - enabling big scale (and profitability) for these with extent (i.e. AWS, Microsoft, and Google);
  • natural infrastructure corporations fight to grasp on to legacy put in bases;
  • Cloud agencies with a SaaS portfolio (Oracle, IBM, Microsoft) have “up-the-stack” value merits they can use as a bulwark against the commoditization of their groups.
  • IBM’s possibilities for Chapter 2 management depend on facts

    earlier than diving into the crimson Hat piece of the puzzle, we should point again to information. In our view, IBM is working intently with purchasers to build a digital business textile where facts remains the underpinning of its method to power a new era of analytics in line with AI. IBM sees records as a fundamental ingredient in bringing contextual relevance to enterprise purposes. What we’re seeing is because of IBM’s massive capabilities enterprise and deep industry expertise it’s earned the right to support valued clientele build digital networks and radically change business fashions. IBM’s tremendous valued clientele are getting this. They’re not trying to IBM to effectively deliver features or cozy their infrastructure or sell them SaaS - quite they’re hunting for IBM to support them seriously change and convey new business models. We’re seeing this in healthcare, financial features, agriculture, energy, assurance and pretty much all industries during which IBM has a presence globally.

    IBM’s probability as we see it's to aid groups take note a way to make money the use of statistics. no longer always via at once selling their information but deciding how to monetize statistics. What we see IBM doing is taking what has been mostly piecemeal, records-oriented AI initiatives and growing what Rometty calls “backyard / In” - i.e. client journey oriented purposes and “inside / Out” - i.e. workflow and new tips on how to work purposes - each which make a contribution to bottom line results. extra importantly, IBM desires to help the customer completely transform their company operations.

    to achieve this, IBM is supplying a company platform - fueled by facts, and a computing device intelligence platform - i.e. tooling and capabilities to extract value from records and operationalize AI.

    Enter crimson Hat  

    IBM didn’t unlock any new details about purple Hat at consider, presumably as a result of regulatory concerns. but with red Hat, IBM can enable a new breed of application builders - for organizations - the use of cloud-native tooling. facts is the important thing ingredient to emerging company purposes and with red Hat in its portfolio, IBM can “cloudify” and “records-fy” businesses and position itself as modern and vital. more importantly, it may well dramatically scale purple Hat’s company globally.

    red Hat for IBM emerges as a vehicle for producing spinoff leverage out of IBM ecosystem software and trade knowledge. With RHEL, OpenShift and eight million purple Hat builders, IBM can support its purchasers modernize their application portfolios and transform business operations...developing a new breed of digital company builders.

    trust statements made by means of Ginni Rometty and Jim Whitehurst all over their mini roadshow after announcing the pink Hat acquisition. Ginni saved saying “this isn’t a backend loaded deal.” What did she suggest? In our view, she became virtually explaining the enterprise case for IBM paying a 60%+ top rate over crimson Hat’s inventory price prior to the deal being announced. particularly, IBM has an important put in base of features consumers (a $20+B captive probability in our estimate) at which it could aspect pink Hat PaaS tooling to modernize utility portfolios and construct the future digital business platform for/with consumers.

    So out of the chute, IBM can immediately begin scaling red Hat’s business, marrying deep industry knowledge, the sprawling IBM SaaS portfolio, the IBM Cloud (the place applicable), AI infused in all places and red Hat PaaS to join customer records, workloads, and functions to any cloud or on-prem installing.

    long term, IBM can, along with its shoppers, absolutely undertake modern application development practices to codify its deep trade skills and construct out transformative company and AI systems to help incumbent groups compete in the digital period.

    The aggressive landscape

    in case you don’t own a public cloud, you go tough after multi-cloud. To wit: VMware exited public cloud after years of trying to commercialize VCloud Air. It at last settled on a contend with AWS and sold off its public cloud. VMware is Dell’s ace in the hole for multi-cloud. Cisco lately announced its multi-cloud strategy at Cisco reside Barcelona which comes on the issue from a strong place in networking. As networks flatten - Cisco may also be the glue between clouds with application administration and orchestration framework for networked information-- no longer a foul method. HP tried and failed within the public cloud game and HPE is trying to be a issuer of multi-cloud services but is largely counting on packaging its hardware, functions and a few minimal application content material.

    of these players, handiest Cisco has any meaningful presence with developers. IBM with purple Hat gets entry to eight million devs.

    As such, IBM has a more robust place than these players-- albeit greater complicated. It owns a public cloud presence and whereas not almost as big as AWS in IaaS, IBM has a large SaaS portfolio. Like Oracle, it doesn’t have to compete for commodity business against AWS, somewhat it will possibly promote price “up the stack” using SaaS as a high-price play. As neatly, it’s AI runs on the cloud and it just introduced at suppose that it’s opening up Watson to run on any on-prem, public or hybrid cloud (an extended past due flow in our opinion). previously, in case you wanted Watson you could handiest get it on IBM’s cloud.

    Microsoft naturally can have its say in Chapter 2 of the cloud. With its acquisition of GitHub and big software property, mixed with a leading cloud at scale, Microsoft holds lots of playing cards. it is investing in AI and has a robust facts angle.

    Google Cloud is resetting with new management and is taking part in the long game. It clearly has AI chops and a robust statistics angle.

    Then there’s AWS. Amazon’s announcement of Outposts suggests that it can and will evolve and alter its spots. these days, AWS makes a strong case for a single versus a multi-cloud approach - arguing that distinct clouds are much less cozy, extra complicated and greater costly. while credible in its place, the reality is multi-cloud is like multi-seller. There’s now not a procurement czar inside of each company as a way to dictate a single cloud. As such if AWS sees an opportunity to control distinctive clouds it's going to enter the area in our view.

    ultimate recommendations

    the brand new “innovation cocktail” combines statistics + AI + Cloud. a typical statistics mannequin brings a competitive advantage within the digital world. computing device intelligence (AI) utilized to statistics drives insights and cloud permits scale and attracts innovation through ecosystems. IBM is combining these three aspects to compete in the next chapter of expertise industry boom.

    IBM, like Microsoft, is cloudifying its offerings to help its consumers’ digital transformations. through bringing the cloud to its products, constructing facts networks with valued clientele, making use of AI everywhere and leveraging pink Hat, it will probably catalyze a brand new classification of business developers and go tough after the multi-cloud possibility that exists.

    We consider, despite the fact, that the multi-cloud world should be messy. nowadays, multi-cloud is as much a multi- (cloud) supplier prevalence versus a deliberate strategy. even so, patrons will proceed to select horses for lessons - that means the appropriate cloud for the correct workload - and in order to inevitably cause distinctive clouds and alternatives for simplified management, protection, governance, and facts leverage.

    nowadays, about half of IBM’s revenue comes from so-called Strategic Imperatives. That piece needs to grow sooner than the different half declines. furthermore, about sixty p.c of IBM’s salary comes from consulting and knowledgeable services. The decent news there is it gives IBM deep visibility and relationships into basically all international industries. The downside is that company doesn’t scale as smartly. As such IBM’s most useful strength is its most excellent challenge. The exciting possibility dealing with IBM is to codify that deep trade capabilities in application, the use of statistics because the key ingredient for brand new business applications constructed on cloud-native PaaS tooling - and scaling to the cloud, any cloud.  

    that is a differentiable story and one that protects IBM from getting Amazon’d while at the identical time enabling the business to power margin advancements over time. IBM’s Rometty has spent the remaining 5-6 years making ready the company for this subsequent chapter.

    Now massive Blue must exhibit that Elephants can dance, sprint and run marathons.

    follow all the IBM suppose 2019 are living video coverage right here: https://www.thecube.net/ibmthink2019

    send us feedback on Twitter @furrier @dvellante


    The #AI Eye: SEW signals contract to make the most of IBM ( $IBM) Cloud, Accenture ( $ACN) to Open Facility in South Africa | killexams.com Real Questions and Pass4sure dumps

    factor Roberts, WA and Vancouver, BC - February 6, 2019 (Investorideas.com Newswire) Investorideas.com (www.investorideas.com), a global investor news source masking artificial Intelligence (AI) brings you modern edition of The AI Eye - observing stock information, deal tracker and advancements in artificial intelligence.

    listen to modern podcast:

    https://www.investorideas.com/Audio/Podcasts/2019/020619-AI-Eye.mp3

    The #AI Eye: SEW signals settlement to make the most of IBM ( $IBM) Cloud, Accenture ( $ACN) to Open Facility in South Africa

    Hear Investor ideas Podcasts on iTunes

    modern Column - The AI Eye - watching stock information, deal tracker and developments in synthetic intelligence

    global Spending on NLP to attain $forty three.four Billion USD with the aid of 2025

    A contemporary file from market intelligence enterprise Tractica finds that international spending on herbal Language Processing (NLP) utility, hardware and features will attain $forty three.3 billion USD via 2025. An excerpt from the document abstract reads:

    The most efficient promise of NLP expertise is intent-primarily based computing. When machines can understand and communicate with people in herbal (human) language, it democratizes information science, enabling humans to use commonplace regularly occurring language to finished a wide latitude of projects from the fundamental and mundane reminiscent of auto-completing an internet form to the most complicated, comparable to writing application or optimizing a data network. NLP is a critical technology for extracting insights and evaluation from an enormous amount of prior to now unindexed and unstructured records; mining video and audio files, emails, scanned files, and more.

    SEW signals agreement to make the most of IBM Cloud, Accenture to Open Facility in South Africa and Datametrex AI partners With Empower shares discussed: (NYSE:IBM) (NYSE:ACN) (TSXV:DM) (CSE:EPW)

    global energy and water cloud platform provider smart power Water (SEW) has signed a multi-million dollar settlement with IBM (NYSE:IBM). in the course of the contract, SEW will leverage the IBM Cloud to scale its functions and supply a standard world infrastructure for their business internet and cellular purposes. Brad Gammons, global managing director, IBM power, environment and Utilities, talked about:

    "sensible energy Water is awaiting the major have an effect on related technologies can have on their clients company. through investing in statistics, their employees can do their job stronger than ever before and valued clientele could have entry to self-carrier capabilities that may aid enhance client carrier."

    Accenture (NYSE:ACN) plans to launch a brand new utilized Intelligence Studio for Mining in Johannesburg, South Africa. in keeping with the press release, "the studio will apply the latest in records science and synthetic intelligence applied sciences with new statistics sources for precise-time co-advent of inventive digital options that can support mining businesses resolve some of their hardest analytical problems". Rachael Bartels, a senior managing director who leads Accenture's mining enterprise globally, defined:

    "volatile commodity fees, rising input charges and changing world demand for commodities require mining corporations to rethink their recommendations and enterprise fashions to continue to be aggressive. they are more and more trying to follow superior analytics to reimagine approaches, liberate trapped price, and drive operational excellence in their businesses today and position themselves for growth tomorrow."

    Datametrex AI limited (TSXV:DM) has partnered with Empower Clinics Inc. (CSE:EPW) throughout the former's subsidiary Canntop AI Inc. on the creation of a pilot software the use of synthetic Intelligence to research and profit insights about Empower affected person facts, doctor treatment techniques and overall lengthy-term efficacy of affected person care. Empower Chairman and CEO Steven McAuley observed:

    "We consider the use of AI tools to investigate the massive amounts of information in the Empower database and the further records from the currently announced proposed sun Valley acquisition could make Empower a knowledge science chief within the cannabis trade. The results of our AI efforts with Datametrex are really going to position the business as an tutorial leader and we plan to collaborate with the industry to sooner or later increase affected person care."

    Sam Mowers, Investorideas.com

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    IBM is all-in on hybrid cloud | killexams.com real questions and Pass4sure dumps

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    Following its blockbuster $33 billion acquisition of the open source Linux company Red Hat last year, IBM has clearly set out its strategy for the future, and it is all about the hybrid cloud.

    "IBM will become the world's number one hybrid cloud provider, offering companies the only open cloud solution that will unlock the full value of the cloud for their businesses," IBM CEO Ginni Roomette said at the time of the acquisition, making a clear statement regarding IBM's hybrid-led strategy. Furthermore, she told CNBC this week that hybrid cloud is a "trillion dollar market and we'll be number one".

    During the company's flagship Think event in San Francisco this week, the vendor firmed up these plans with a raft of announcements aimed at practically helping customers move to a hybrid cloud model, from a new integration platform to an army of consultants focused on helping customers go hybrid.

    Read next: IBM is buying Red Hat for $33 billion

    First, a quick refresh. Hybrid cloud is an enterprise IT strategy that involves operating certain workloads across different infrastructure environments, be it one of the major public cloud providers (Amazon Web Services (AWS), Microsoft Azure or Google Cloud Platform (GCP), a private cloud, or on-premise, typically with a homegrown orchestration layer on top. Multi-cloud is a similar idea but tends to not involve private cloud or on-premise infrastructure.

    This architecture allows companies to diversify their spend and skills, build resiliency and cherry pick features and capabilities depending on where they see a vendor's strengths.

    That last part is particularly pronounced in the area of AI and machine learning, where companies like HSBC and the Telegraph Media Group have selected GCP for its AI features alone (The Telegraph has since gone 'all in' on GCP).

    Santander bank also announced this week during Think that it will be investing $700 million over five years to place IBM as "one of Santander Group's main transformation partner -- helping Banco Santander to implement their hybrid cloud strategy."

    IBM is supporting the bank with its "methodologies and processes to accelerate that transformation journey. Additionally, the bank is using a range of technologies including IBM devops solutions and IBM API Connect, aimed to develop, iterate and launch new or upgraded applications and digital services much more rapidly," according to a press release.

    Banking, with all of its legacy technology, seems the most naturally inclined industry to turn to hybrid cloud. Regulatory and security concerns leave them wanting to keep key data and workloads on-premise, but newfound competition from agile fintechs means they need to move to the sort of faster deployment cycles that can only be achieved in a cloud environment. IBM boasts of BNP Paribas, Westpac, Lloyds Banking Group, Credit Mutuel, Krungsri, Royal Bank of Canada, and Mizuho Bank all turning to them for hybrid cloud solutions.

    In fact, a recent report from 451 Research found that 60 percent of EMEA and North American financial services businesses expect to run a multi-cloud architecture within the next two years.

    The two major announcements made by IBM this week focused on first helping customers go hybrid, and secondly opening up its cognitive IBM Watson services to run across the major public cloud providers' infrastructure.

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    IBM preps Watson AI services to run on Kubernetes | killexams.com real questions and Pass4sure dumps

    Two of IBM’s Watson-branded collection of machine-intelligence services will be available to run as standalone applications in the public or private cloud of your choice. IBM is delivering these local Watson services atop IBM Cloud Private for Data, a combined analytics and data governance platform that can be deployed on Kubernetes. 

    Ruchir Puri, CTO and chief architect for IBM Watson, said this was driven by customer demand for machine learning solutions that could be run where customer data already resides, typically a multicloud or hybrid cloud environment (see related interview).

    “Rather than trying to move the data to a single cloud, and create a lockin in this open compute-environment-driven world, we are making available AI and moving it to the data,” Puri said. The concept follows how Hadoop and other mass data-processing systems perform work on data in place, rather than moving the data to the processing.

    Currently, only two services—Watson Assistant and Watson OpenScale, which Puri described as “flagship products”—will be offered to customers as standalone applications. Watson Assistant is used to build “conversational interfaces” such as chatbots; Watson OpenScale provides “automated neural network design and deployment,” or a way to train, deploy, and oversee machine learning models and neural networks in an enterprise setting.

    IBM Cloud Private for Data is composed of preconfigured microservices that run on a multinode, Kubernetes-based IBM Cloud Private cluster. Puri said the customer is expected to perform their own integration between IBM Cloud Private for Data and its local data stores; such integration isn’t handled by IBM directly. 

    Puri made it clear these local Watson incarnations do not just forward API calls from a local proxy into IBM-hosted Watson. The customer runs its own local incarnation of the service, delivered atop IBM Cloud Private and running in the environment of choice. Supported environments include Amazon Web Services, Google Cloud, Microsoft Azure, and Red Hat OpenShift. Local Watson services are API-compatible with Watson services running in IBM Cloud.

    What’s likely to change is the results delivered from local Watson incarnations versus the master version of Watson, because the local versions needs to be periodically updated. Puri could not provide a specific timeline for how often new versions of local Watson services will come down the pike (quarterly, annually, etc.), but he did affirm that it will be updated “on a relatively regular basis.”

    The amount of system resources needed to devote to a Watson service instance varies depending on the workload. Some SLAs for the offered products include a prescription for the computing environment (memory, cores, GPUs) required for the desired performance, Puri said. Both virtualized and bare-metal deployments are supported.

    Other Watson services will be made available locally atop IBM Cloud Private later. IBM plans later in 2019 to deliver Watson Knowledge Studio, which “discovers meaningful insights from unstructured text without writing any code,” and Watson Natural Language Understanding, an automatic metadata extraction tool. The latter, Puri said, is already used in Watson Assistant as an internal microservice, so most of the work to port it to a local incarnation has already been done.

    This new incarnation of Watson services provides a glimpse into some of the motives around IBM’s acquisition of Red Hat. IBM Cloud Private can use the Kubernetes-powered OpenShift as its base, and Watson’s services were reworked over a three-year period around Kubernetes and containers, Puri said. Once Red Hat is fully under IBM’s umbrella, it seems likely that Red Hat’s infrastructure expertise will unlock cloud portability for future IBM data-centric services, Watson and otherwise.


    Power Couple: IBM Joins PowerAI Hardware with Watson; Launches Multi-Hybrid AI Services | killexams.com real questions and Pass4sure dumps

    source: IBM

    As IBM kicked off its annual Think conference, a high-production extravaganza this week in San Francisco, the company this morning made a series of AI-related announcements, including the merging of its PowerAI integrated CPU-GPU server line with its cognitive computing flagship IBM Watson, to create what it calls the Watson Machine Learning Accelerator (WML Accelerator), which Big Blue claims accelerates machine learning training 46X.

    The objective of the Watson-Power marriage, IBM said, is to create a converged, integrated AI solution “that brings together the best software for AI, Watson, with the best hardware for AI, IBM Power Systems” – the ultimate goal being to ease enterprise AI adoption. As part of that strategy, the company this week will demonstrate new benchmarks for SnapML, IBM’s ML framework for simplified model selection and hyper-parameter tuning, which usually requires the specialized skills of data scientists.

    “By scaling out across a cluster, as well as scaling up across many-core CPUs and powerful modern GPUs, SnapML is capable of identifying a highly accurate model and its hyper-parameter configuration extremely quickly,” said Sumit Gupta, VP of AI and HPC, IBM Cognitive Systems, in a blog.

    Like many other AI-related vendor announcements over the past year, IBM’s Power AI-Watson convergence is aimed at easing the AI related skills shortage, cited by 54 percent as a barrier to AI adoption in a recent Gartner CIO survey, along with a skills scarcity related to integrating AI into existing infrastructures, cited by 27 percent of those in the Gartner surveyed by Gartner. WML Accelerator is designed to help enterprises train and deploy ML models built in IBM Watson Studio and monitored with Watson OpenScale.

    IBM's Sumit Gupta

    At IBM Think last year, the company demonstrated the SnapML library running on Power Systems servers and reported that it beat Google Cloud running ML on an advertising-focused dataset by 46x. Since then, the company has integrated new automation features that scale out across a cluster and scale up across many-core CPUs and GPUs, making “SnapML… capable of identifying a highly accurate model and its hyper-parameter configuration extremely quickly.”

    “Many users don’t realize how vast the open source machine learning catalogue is, and it can be quite challenging to identify the right tool for your particular data or desired outcome,” said Simon Thompson, Research Computing Infrastructure Architect at the University of Birmingham. “The automated model and library selection capabilities of SnapML greatly reduce the time required to parse through all of these tools, allowing users to begin ML training much more quickly.”

    In addition, IBM announced a pan-environment AI capability with IBM Cloud Private for Data (ICP for Data) on IBM Power Systems with IBM Storage, enabling Watson services, including Watson Assistant (for building conversational interfaces into applications and devices) and Watson OpenScale (an open AI platform for managing multiple instances of AI regardless if where they were developed) to run on premises or any private, public or hybrid multi-cloud, according to the company. IBM said ICP for Data “enable(es) businesses to apply AI to data wherever it is hosted. Businesses will be able to infuse AI into their apps, regardless of where they reside. The flexibility this affords can remove one of the major obstacles to scaling AI, since businesses can now leave data in secure or preferred environments and take Watson to that data.”

    “Businesses have largely been limited to experimenting with AI in siloes due to the limitations caused by cloud provider lock-in of their data,” said Rob Thomas, GM, IBM Data and AI. “With most large organizations storing data across hybrid cloud environments, they need the freedom and choice to apply AI to their data wherever it is stored. By breaking open that siloed infrastructure we can help businesses accelerate their transformation through AI.”

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