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000-SS2 IBM Systems Software Technical Sales Mastery V1

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000-SS2 exam Dumps Source : IBM Systems Software Technical Sales Mastery V1

Test Code : 000-SS2
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: 32 true Questions

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IBM IBM Systems Software Technical

Is Nagios The course forward for Monitoring For IBM i? | killexams.com true Questions and Pass4sure dumps

November 12, 2018 Alex Woodie

For many years, technology professionals grew to become to established frameworks from IBM Tivoli, CA, Hewlett Packard, and BMC (“The massive four”) to video display their hardware and application stacks. but the open supply world has caught up with these closed monitoring environments, and a venture dubbed Nagios is poised to live the go-to platform for IT monitoring, together with on IBM i.

Nagios, in case you are not widely wide-spread, is a free and open source application product that provides monitoring and alerting for servers, network apparatus, functions, and the array of capabilities that agencies increasingly count on. The software –backed by course of the obligatory recursive acronym “Nagios Ain’t Gonna Insist On Sainthood” – become in the birth developed by using Ethan Galstad back in 2002 to hurry and monitor Linux methods, which turned into simply birth to get headway in enterprise facts facilities.

over the years, the C-primarily based program has been extended to guide an array of kick kinds, including host components like processor load, disk and RAM usage, and device logs for a majority of widespread working techniques, including IBM i. The energetic Nagios neighborhood has created a wide purview of Nagios brokers which believe prolonged the framework to an estimated 5,000 instruments.

Nagios is an open source instrument that permits directors to monitor their IT gear and applications.

On the network aspect of issues, Nagios Core (as the open source product is known) screens routers, switches, and different apparatus, and supports SMTP, POP3, FTP, and SNMP protocols, among others. utter faraway monitoring will furthermore live encrypted, and it additionally presents a plug-in that lets users create their own screens in lots of languages.

records collected by using energetic and passive Nagios plug-ins is routed into the Nagios server, where the facts is sorted and signals are sent out. clients can consume indicators in quite a lot of approaches, including via a web browser, via SMS pagers, and through e mail. With a simple ogle at the Nagios dashboard on a telephone, a systems admins can discern if vital servers, method, and features are alive or useless.

The Nagios Core server software furthermore can toil with a “circular-robin database” (RRD) to simplify the storage and querying of time-sequence records. With RRD, admins can dive deeper into Nagios facts and deem graphs to discern efficiency traits. And with a microscopic setup ahead of time, Nagios can furthermore live configured to immediately respond to hobbies as they occur, or augment alerts to other individuals.

businesses that crave more than what Nagios Core has to present can locate it from Nagios enterprises, the business outfit behind the open source mission. The St. Paul, Minnesota-based mostly company, which employs Galstad, extends Nagios Core with several offerings, together with Nagio XI, which points a extra extensible front-conclusion and a MySQL-based mostly back-end. Nagios XI furthermore brings a higher consumer journey with greater potent graphs and enhanced dashboards.

IBM i valued clientele can consume Nagios to video display 15 metrics with the Nagios Plug-Ins for IBM i beta.

regrettably, Nagios companies doesn’t champion IBM i. but that you could gain a Nagios distribution for IBM i from a microscopic outfit called overseas enterprise Machines. In 2017, huge Blue shipped a beta edition of an IBM i plug-in designed to feed facts from the IBM i sever into the open supply Nagios Core product or Nagios XI.

according to a developerWorks web page, the IBM i Nagios plug-in collects 15 distinct facts aspects from IBM i servers, together with issues like CPU and disk utilization, ASP usage, number of energetic jobs, and lengthy-operating SQL jobs, amongst others. Some of those services are supported by course of SNMP, while others require the open source JTOpen Java toolbox to live do in.

The Nagios server itself doesn’t hurry on IBM i – at the least not yet. With the Nagios on IBM i plug-in, IBM provides users with instructions on the course to deploy Nagios Core or Nagios XI on a Linux server. Technically, there should live nothing stopping from a consumer installing Nagios in a Linux LPAR on the energy methods server – and even for IBM to port the application to the IBM i OS by the consume of PASE – but that has no longer took Place yet.

IBM makes the case for IBM i stores to get consume of Nagios in a PDF presentation on Nagios created by using IBM i company architect Tim Rowe and Wang Yun, who developed the Nagios for IBM i plug-in. whereas Navigator for i gives first rate coverage of IBM i-centric queues and metrics, that product doesn’t provide shoppers with any visibility of what’s occurring outdoor the IBM i system.

purchasers who buy Nagios XI can video display IBM i metrics graphically.

Nagios, nonetheless, provides administrators and operators with a lone centralized view of utter IT belongings, Rowe and Yun write. moreover the core IBM i metrics that at the jiffy are accessible via the Nagios plug-in, IBM i clients can gain vogue and historical records, as well because the flexibility to configure metrics to their liking, not to mention the aptitude to create their own custom plug-ins.

IBM isn’t the only enterprise doing Nagios toil on IBM i. a yoke of years ago, ShapPin Cheng launched a GitHub job called check_as400 that moved records from IBM i server logs into Nagios. seeing that the extensibility and openness of Nagios, it wouldn’t live grotesque to peer impartial software carriers in the IBM i neighborhood adopt the know-how for his or her personal methods monitoring offerings.

For now, IBM presents the Nagios plug-in as a beta. Don’t live shocked to ogle it swirl into a fully supported offering within the months to return, mainly considering the esteem concern that IBM has with open supply application this present day.

related reports

IBM i performance secrets and techniques revealed

What’s Cooking With IBM i On GitHub?

ASCI Job Scheduler gets Hooks for Nagios


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IBM to purchase utility business red Hat for $34 billion | killexams.com true Questions and Pass4sure dumps

with the aid of Liana B. Baker and Greg Roumeliotis

(Reuters) - IBM Corp spoke of on Sunday it had agreed to acquire U.S. application company purple Hat Inc for $34 billion, including debt, because it seeks to diversify its expertise hardware and consulting enterprise into bigger-margin products and capabilities.

The transaction is through a ways IBM's greatest acquisition. It underscores IBM Chief govt Ginni Rometty's efforts to extend the business's subscription-based mostly application offerings, because it faces slowing utility sales and waning require for mainframe servers.

IBM, which has a market capitalization of $114 billion, will pay $190 per share in money for crimson Hat, a 63 % premium to Friday's closing share rate.

headquartered in 1993, crimson Hat makes a speciality of Linux working systems, essentially the most typical class of open-source utility, which changed into developed as a substitute for proprietary software made by means of Microsoft Corp.

Headquartered in Raleigh, North Carolina, red Hat costs fees to its corporate purchasers for customized facets, preservation and technical help, offering IBM a profitable source of subscription profits.

purple Hat is without doubt one of the very few groups within the cloud computing sector that has each profits boom and free money circulate, Rometty, who has been IBM's CEO on account that 2012, spoke of in an interview with Reuters.

"This acquisition they are obviously doing for growth synergies. here is not about can suffuse synergies at all," Rometty mentioned in the interview.

The acquisition illustrates how older technology organizations are turning to dealmaking to gain scale and fend off competitors, primarily in cloud computing, the Place customers using business software are searching for to reclaim money by means of consolidating their seller relationships.

IBM is hoping the deal will befriend it trap up with Amazon.com Inc, Alphabet Inc and Microsoft within the utter of a sudden transforming into cloud enterprise. IBM shares believe misplaced basically a third of their value during the past five years, whereas crimson Hat shares are up one hundred seventy percent over the equal length.

huge BLUE

IBM turned into established in 1911 and is commonplace in the expertise business as distinguished Blue, a reference to its once ubiquitous blue computer systems. It has confronted years of revenue declines, because it transitions its legacy desktop maker enterprise into newfangled expertise products and functions. Its recent initiatives believe covered synthetic intelligence and business lines around Watson, named after the supercomputer it developed.

To live sure, IBM is not any stranger to acquisitions. It bought cloud infrastructure company Softlayer in 2013 for $2 billion, and the climate Channel's facts property for greater than $2 billion in 2015. It additionally received Canadian business software maker Cognos in 2008 for $5 billion.

other massive expertise businesses believe additionally these days sought to reinvent themselves via acquisitions. Microsoft this yr obtained open supply application platform GitHub for $7.5 billion; chip maker Broadcom Inc agreed to acquire application maker CA Inc for essentially $19 billion; and Adobe Inc agreed to acquire advertising application maker Marketo for $5 billion.

certainly one of IBM's main opponents, Dell technologies Inc, made a distinguished wager on application and cloud computing two years ago, when it obtained records storage enterprise EMC for $67 billion. As a section of that deal, Dell inherited an eighty two percent stake in virtualization software company VMware Inc.

The deal between IBM and red Hat is anticipated to nigh in the 2d half of 2019. IBM observed it planned to suspend its share repurchase application in 2020 and 2021 to champion pay for the deal.

IBM spoke of purple Hat would proceed to live led by course of pink Hat CEO Jim Whitehurst and red Hat's existing administration crew. It intends to retain red Hat's headquarters, facilities, brands and practices.

Lazard Ltd offered economic suggestions to IBM, alongside Goldman Sachs neighborhood Inc and JPMorgan Chase & Co, which additionally provided financing for the deal. Paul, Weiss, Rifkind, Wharton & Garrison LLP provided criminal suggestions to IBM.

Guggenheim partners LLC and Morgan Stanley had been economic advisers to red Hat, whereas Skadden, Arps, Slate, Meagher & Flom LLP offered prison suggestions to the company on the deal.

"understanding first-hand how essential open, hybrid cloud applied sciences are to helping groups unencumber cost, they discern the vigour of bringing these two corporations together, and are honored to recommend IBM and entrust financing for this transaction," JPMorgan CEO Jamie Dimon spoke of in a statement.

(Reporting by Liana B. Baker and Greg Roumeliotis in distinguished apple; additional reporting by Stephen Nellis in San Francisco and Carl O'Donnell and Jim Finkle in newfangled york; enhancing through Rosalba O'Brien and Peter Cooney)


000-SS2 IBM Systems Software Technical Sales Mastery V1

Study guide Prepared by Killexams.com IBM Dumps Experts


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000-SS2 exam Dumps Source : IBM Systems Software Technical Sales Mastery V1

Test Code : 000-SS2
Test appellation : IBM Systems Software Technical Sales Mastery V1
Vendor appellation : IBM
: 32 true Questions

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IBM-Bigdata-Analytics

There is a distinction between lore and understanding. lore typically comes down to knowing facts while understanding is the application of lore to the mastery of systems. You can know a lot while understanding very little. Just as an example, IBM’s Watson artificial intelligence system that defeated the TV Jeopardy champs a few years ago knew utter there was to know about Jeopardy questions but didn’t really understand anything. require Watson to apply to removing your appendix its lore of hundreds of medical questions and you’d live disappointed and probably dead. That’s the problem with most analytics, which is why it can live a arduous sell.

The respond to this problem, we’re told, is not just machine learning but abysmal Machine Learning, the distinction between the two being that modest ancient machine learning is a statistical process that could live (and used to be) replicated by hand, while the deeper variety looks several generations abysmal in a longitudinal analysis that quickly grows too distinguished for mere mortals to comprehend. abysmal machine learning will, theoretically, find utter the interconnections and dependencies that until now we’ve had to reckon on domain experts to provide, yet even then it can only chance if you chance to live gathering the prerogative data.

With regular machine learning, when IBM talks about Watson looking inside your business and finding answers, well that can only really chance if a few PhDs are attached to the software. But with abysmal machine learning the concept is that the machine can accomplish it all. No PhDs required, which would live quite a breakthrough. And so utter the distinguished companies fighting over the future of IT are building newfangled circuits -- hardware -- for abysmal machine learning. Google and IBM believe made recent announcements about theirs. Microsoft told me a yoke weeks ago that they believe similar hardware working in their lab. It’s a space race.

And it’s furthermore at least five years from being true on any commercial scale.

Until abysmal machine learning is common and snappy we’ll live stuck with more mundane analytics. So no, Watson isn’t going to live crunching your company numbers soon and spitting out the prerogative answers or even the prerogative questions to ask. We’re simply not there yet.

Which brings us to a snoopy thing happening at IBM. Not closing the I.M. Pei-designed lab in Somers, newfangled York that was announced last week. That campus has been half-empty for years. Nor am I talking about the continuation of IBM’s brutal GTS layoffs, which reportedly killed another 14,000+ IBM jobs last week. What I am talking about here is the reorganization of IBM’s analytics business unit that was announced internally two weeks ago. You won’t find a advice chronicle about it… until now.

The analytics reorg labelled "One Team, One Platform" wasn’t technically a Resource Action (forced layoff). It was explained as a streamlining of business processes to better efficiency. Citing similar moves at Google, IBM’s analytics group would no longer believe employees working from home and the number of official analytics office locations worldwide would dwindle from 200 to 30. People will soon live working and meeting physically together, some of them for the first time. This is good, right?

Yet the reorg is wildly unpopular within the ranks for one principal reason: If for some reason affected IBMers necessity to retain working from home or they can’t or won’t shuffle to their designated IBM office location, well then they are deciding to quit in the view of IBM, which means they are out of the company with no severance -- no package.

Analytics common manager Rob Thomas, who announced the reorg, has been uniformly described to me by IBMers from that division as "an idiot", which may live some internal IBM technical term, I don’t know.

The reorg, which tellingly requires some orthodox Jewish IBMers working in Israel to invert history and relocate to either Germany or Poland, will inevitably result in a significant reduction in head count yet not believe to live accounted for as one. These are stealth layoffs.

Remember that the future of IBM is supposititious to live utter about CAMSS (cloud, analytics, mobile, security, social) and analytics is the A in CAMSS. In one jiffy IBM says analytics is strategic, that they are investing and hiring in the area, yet at the selfsame time the company is taking actions that will inevitably lead to the loss of at least some employees who are vital to the unit.

It’s the blindness of this reorg that amazes me. Heads will proceed no matter what, but in this case the specific heads won’t live decided by the company but by the workers, themselves. The best workers will live the most employable and therefore the quickest to go. If analytics is so strategic how can IBM allow that to happen?

I believe I know what’s happening here. Years of layoffs and unfilled positions at IBM denote that pretty much everyone remaining who isn’t in management is already very edifying at their jobs. There is no more chubby to cut. So why not leave it up to the employees, themselves, especially if the gambit will result in very low separation expenses?

It is unlikely that any of the IBMers who are lost in this reorg will live replaced. Rather, as has become the norm at IBM in recent years, those who are left will live expected to pick up the slack.

Yes, but what about CAMSS? What about analytics being so strategic to the future of IBM?

In order to understand that they believe to furthermore understand who is IBM’s customer. Peter Drucker wrote that the purpose of the corporation is "to find a customer". Well who is IBM’s customer if the company is effectively cutting one of the divisions it is relying upon for future growth?

IBM’s customer is Wall Street.

IBM’s products are earnings-per-share, dividends, and share buy-backs, not hardware, software or computer services.

This morning I took a quick ogle at IBM‘s 1Q16 statement. It was enthralling what was stated, how it was stated, and what was not stated. They signed $4.2 billion in Analytics and $2.6 billion in Cloud business. The leisure of CAMSS was puny. If Analytics is doing better than the rest, why mess with it? How many billions believe they spent to get $11 billion a year on cloud?

IBM has mostly reported revenue. section of the company’s sales culture, it is what you sign in deals that matters. But how much profit is each division making? That is how most companies are managed. IBM‘s distinguished money maker is services and that is losing business. IBM wants to retain Wall Street off the scent and keeping reported earnings up is critical. So they’re cutting abysmal with no severance. This is utter about buying time until the newfangled business gains traction. However if the newfangled business doesn’t get as much profit, that is going to live a distinguished problem.

This is a very scary gamble for IBM.

What this analytics reorg means is that IBM can’t discern a course to gain its near-term Wall Street product objectives without cutting heads in analytics. The division was built up in anticipation of sure sales and profit targets, those targets believe not been reached, so IBM will cleave expenses until the numbers ogle right. Forget that this reorg will actually result in less -- not more -- toil being done. Forget that it makes even less likely IBM achieving its goals for analytics. Forget utter of that.

What it means is the A in CAMSS has already failed. That’s my understanding.


Can Anyone stop Amazon from Winning the Industrial Internet? | killexams.com true questions and Pass4sure dumps

Executive Summary

Digital natives like Amazon believe already disrupted industries such as media, publishing, travel, music, and photography. But who is likely to assume leadership in creating and capturing economic value in type 3 products (products which believe physical components, “smart” components, and connectivity)? If digital natives want to develop software-enabled solutions that siphon off significant value from industrial hardware, they must overcome three barriers: the physics of the hardware, customer intimacy, and vicissitude in sharing risks. Likewise, if industrial giants want to lead in the industrial internet they will necessity to overcome their three barriers: software talent, digital culture, and the incumbent’s dilemma. Among the tech giants, Amazon is a likely winner in the Industrial Internet, as it has successfully fused physical with digital. Amazon understands the economic laws of analog products and is not afraid of massive up-front investments and slower growth.

Just the announcement that Jeff Bezos, Warren Buffett, and Jaime Dimon will live entering the health care space has sent shock waves for industry incumbents such as CVS, Cigna, and UnitedHealth. It furthermore puts a fundamental question back on the agendas of CEOs in other industries: Will software ingest the world, as Marc Andreessen famously quipped? Is this a warning shot that signals that other legacy industrial companies, such as Ford, Deere, and Rolls Royce are furthermore at increased risk of being disrupted?

To start to respond that question, let’s tally up the score. There are three types of products today. Digital natives (Amazon, Google, Facebook, Microsoft, IBM) believe gained competitive edge in the first two, and the jury is silent out on the third:

  • Type 1: These are “pure” information goods, where digital natives rule. An example would live Google in search, or Facebook in sociable networking. Their business models capitalize from internet connectivity and they esteem tremendous network effects.
  • Type 2: These are once-analog products that believe now been converted into digital products, such as photography, books, and music. Here too, digital natives dominate. These products are typically sold as a service via digital distribution platforms (Audible.com for books, Spotify for music, Netflix for movies).
  • Type 3: Then there are products where input-output efficiency and reliability of the physical components are silent critical but digital is becoming an integral section of the product itself (in effect, computers are being do inside products). This is the world of the Internet of Things (IOT) and the Industrial Internet.
  • Manufacturing-heavy companies such as Caterpillar, Ford, and Rolls Royce compete in this world. An aircraft engine is unlikely to become a purely digital product any time soon! Such products believe three components: physical components, “smart” components (sensors, controls, microprocessors, software, and enhanced user interface), and connectivity (one machine connected to another machine; one machine connected to many machines; and many machines connected to each other in a system).

    Digital natives believe already disrupted industries such as media, publishing, travel, music, and photography. But who is likely to assume leadership in creating and capturing economic value in type 3 products: Digital natives or industry incumbents? Ford or Tesla? Rolls Royce or IBM? Caterpillar or Microsoft? Amazon, Berkshire Hathaway and JPMorgan Chase combine or UnitedHealth?

    The Challenges for Digital Natives

    Value will no doubt live created in the era of smart, connected machines. They don’t await Amazon or Microsoft or IBM to design, make, and market agricultural tractors, aircraft engines, or MR scanners. The question really is: Can digital natives develop software-enabled solutions that siphon off significant value from industrial hardware? The respond is “yes.” But it won’t live easy. It will require tremendous amounts of investments in building newfangled capabilities for hardware companies like HP, Cisco, Dell, Samsung, and Lenovo; established software companies like Facebook, Google, Amazon, and Microsoft; and start-ups. In particular, there are three barriers they must overcome:

    1. The physics of the hardware. Companies like Rolls Royce design and manufacture jet engines. These are very complicated machines. There is arduous science behind these machines. That’s much different than digital natives like Airbnb where marketing is more principal than technical expertise.

    Industry incumbents believe expertise in the material sciences, for instance. Further, scientific lore keeps improving over time. They believe made ponderous R&D investments—both basic and applied—to remain at the cutting-edge of the physics of the hardware. Much of this scientific lore is protected by patents.

    Mastery of arduous science is a pre-requisite to develop software-based solutions on the hardware. These companies’ superior product/domain lore provides them the comparative edge to model the asset’s performance and write high-end/high value-added software applications. A “pure” digital company can write commodity software applications. But it must acquire enough capabilities on the physics to write sophisticated apps that better assets’ performance.

    2. Customer intimacy. Industrial giants believe well-established brands, built tenacious customer relationships, and signed long-term service contracts. They’ve won the customer’s trust, which is why customers are willing to share data. Digital natives can toil with industrial customers, but they believe to first win their trust; they must build capabilities to understand customer operations; they must match the industrials’ cumulative learning from customer interactions; they must learn to require for the prerogative data; and they believe to hire experts in several verticals that can swirl data into insights.

    3. vicissitude in sharing risks. Industrial incumbents believe product knowledge, customer relationships, and realm engineers on customer sites. Companies like Rolls Royce can, therefore, present outcome deals where they guarantee customer outcomes (examples: zero downtime, higher speed, more fuel efficiency, zero operator error, greater reliability) and share risks and rewards with customers. It would live very arduous for Amazon or Google to guarantee customer outcomes and consume risks with businesses whose operations they know microscopic about.

    The Challenges for Industrial Giants

    Can the industrial giants lead in the Industrial Internet? The respond is “yes.” But it won’t live simple for them, either. They too have three significant barriers to overcome:

    1. Software talent: The IT talent in industrial companies can execute projects oriented towards process efficiency and cost reduction. That talent is ill-suited to develop new, breakthrough software products that present superior customer outcomes. For that end, they must live able to attract world-class innovators and software engineers. Is, say, Rolls Royce, in the selfsame consideration set as Facebook and Google for green tech employees? Not, really. If so, how can the industrial giants compete to attract the best talent?

    2. Digital culture: Industrial businesses and digital businesses operate with completely different principles. The characteristics of hardware businesses involve long product evolution cycle, Six Sigma efficiency, and long sales cycle. Software businesses believe different characteristics: short product evolution cycle, flexibility, and short sales cycle. The industrials must build a digital culture based on concepts like lean, agile, simplicity, responsiveness, and speed. That’s a tall order for an established enterprise.

    3. The Incumbent’s Dilemma: Digital has the potential to disrupt industrial businesses. There are three ways digital strategy can cannibalize “core” industrial business. First, data and insights can befriend better the productivity of machines; digital, therefore, has the potential to cannibalize future hardware sales. Second, data and insights augment the reliability of machines; digital therefore has the potential to cannibalize future service revenues. Third, software subscription and license might enable customers to accomplish self-service. Current customers could terminate/renegotiate service contracts, and potential customers may not enter into service contracts at all. In short, it is very difficult for a company to disrupt itself.

    The future of the Industrial Internet will involve partnerships across a variety of players including tech companies and industrial companies. The key issue: Who will assume the leadership position to extract maximum economic value in such an ecosystem? Will industrial companies consume the lead? Or will the digital natives consume the lead? Both believe a chance.

    If I were a betting man, I would Place my bets on tech giants over industry incumbents. One factor that will favor digital companies in the industrial internet is technological/scientific breakthroughs that plane the playing realm for newcomers. For example, breakthroughs in battery technology made the electric cars possible. Electric cars are much simpler to design than cars with internal combustion engines, allowing Tesla and BYD to enter the market despite Ford’s decades of expertise. Since electrification and driverless cars proceed together, other tech companies such as Google, Baidu, Apple, and Lyft will furthermore live able to enter the automotive market. Similar technological changes in jet engines and agricultural tractors can allow tech giants to gain foothold in these industries as well.

    More importantly, Amazon or Google believe the resources to acquire the capabilities to master the physics and acquire customer relationships and compete with the industrial giants in the Industrial Internet. They believe enough resources and some to buy them, if needed.

    Among the tech giants, Amazon is a likely winner in the Industrial Internet. It has successfully fused physical with digital. Amazon understands the economic laws of analog products and is not afraid of massive up-front investments and slower growth. Its acquisition of entire Foods and experiments with Amazon proceed grocery stores are an example. Amazon is the one company everyone’s shocked of, even industrial giants.


    Machines beat us at their own game: What can they do? | killexams.com true questions and Pass4sure dumps

    In this undated publicity image released by Jeopardy Productions, Inc., host Alex Trebek, left, poses with contestants Ken Jennings, center, and Brad Rutter and a computer named Watson in Yorktown Heights, N.Y. On Monday, Feb. 14, 2011, "Jeopardy!" will start airing two matches spread over three days between Jennings, Rutter and Watson, who was developed by IBM scientists. (AP Photo/Jeopardy Productions, Inc.) NO SALES (AP) -- Machines first out-calculated us in simple math. Then they replaced us on the assembly lines, explored places they couldn't gain to, even beat their champions at chess. Now a computer called Watson has bested their best at "Jeopardy!"

    A gigantic computer created by IBM specifically to exceed at answers-and-questions left two champs of the TV game explain in its silicon dust after a three-day tournament, a exploit that experts summon a technological breakthrough.

    Watson earned $77,147, versus $24,000 for Ken Jennings and $21,600 for Brad Rutter. Jennings took it in stride writing "I for one welcome their newfangled computer overlords" alongside his amend Final Jeopardy answer.

    The next step for the IBM machine and its programmers: taking its mastery of the arcane and applying it to befriend doctors plow through blizzards of medical information. Watson could furthermore befriend get Internet searches far more like a conversation than the hit-or-miss things they are now.

    Watson's conquest leads to the question: What can they measly humans accomplish that unbelievable machines cannot accomplish or will never do?

    The answer, like utter of "Jeopardy!," comes in the shape of a question: Who - not what - dreamed up Watson? While computers can compute and construct, they cannot determine to create. So far, only humans can.

    "The course to reason about this is: Can Watson determine to create Watson?" said Pradeep Khosla, dean of engineering at Carnegie Mellon University in Pittsburgh. "We are far from there. Their aptitude to create is what allows us to discover and create newfangled lore and technology."

    Experts in the realm whisper it is more than the spark of creation that separates man from his mechanical spawn. It is the pride creators can take, the empathy they can utter believe with the winners and losers, and that magical mingle of adrenaline, panic and aptitude that kicks in when their backs are against the wall and they are in survival mode.

    What humans believe that Watson, IBM's earlier chess champion abysmal Blue, and utter their electronic predecessors and software successors accomplish not believe and will not gain is the sort of thing that makes song, romance, smiles, sadness and utter that jazz. It's something the experts in computers, robotics and artificial intelligence know very well because they can't motif out how it works in people, much less duplicate it. It's that indescribable essence of humanity.

    Nevertheless, Watson, which took 25 IBM scientists four years to create, is more than just a trivia whiz, some experts say.

    Richard Doherty, a computer industry expert and research director at the Envisioneering Group in Seaford, N.Y., said he has been studying artificial intelligence for decades. He thinks IBM's advances with Watson are changing the course people reason about artificial intelligence and how a computer can live programmed to give conversational answers - not merely lists of sometimes not-germane entries.

    "This is the most significant breakthrough of this century," he said. "I know the phones are ringing off the hook with interest in Watson systems. The Internet may trump Watson, but for this century, it's the most significant promote in computing."

    And yet Watson's creators whisper this breakthrough gives them an extra appreciation for the magnificent machines they summon people.

    "I discern human intelligence consuming machine intelligence, not the other course around," David Ferrucci, IBM's lead researcher on Watson, said in an interview Wednesday. "Humans are a different sort of intelligence. Their intelligence is so interconnected. The brain is so incredibly interconnected with itself, so interconnected with utter the cells in their body, and has co-evolved with language and society and everything around it."

    "Humans are learning machines that live and undergo the world and consume in an huge amount of information - what they see, what they taste, what they feel, and they're taking that in from the day they're born until the day they die," he said. "And they're learning from utter the input utter the time. We've never even created something that attempts to accomplish that."

    The aptitude of a machine to learn is the essence of the realm of artificial intelligence. And there believe been distinguished advances in the field, but nothing near human thinking.

    "I've been in this realm for 25 years and no matter what advances they make, it's not like they feel we're getting to the finish line," said Carnegie Mellon University professor Eric Nyberg, who has worked on Watson with its IBM creators since 2007. "There's always more you can accomplish to bring computers to human intelligence. I'm not sure we'll ever really gain there."

    Bart Massey, a professor of computer science at Portland situation University, quipped: "If you want to build something that thinks like a human, they believe a distinguished course to accomplish that. It only takes like nine months and it's really fun."

    Working on computer evolution "really makes you esteem the fact that humans are such unique things and they reason such unique ways," Massey said.

    Nyberg said it is silly to reason that Watson will lead to an conclude or a lessening of humanity. "Watson does just one task: respond questions," he said. And it gets things wrong, such as adage grasshoppers ingest kosher, which Nyberg said is why humans won't swirl over launch codes to it or its computer cousins.

    Take Tuesday's Final Jeopardy, which Watson flubbed and its human competitors handled with ease. The category was U.S. cities, and the clue was: "Its largest airport is named for a World War II hero; its second largest, for a World War II battle."

    The amend response was Chicago, but Watson weirdly wrote, "What is Toronto?????"

    A human would believe considered Toronto and discarded it because it is a Canadian city, not a U.S. one, but that's not the type of comparative lore Watson has, Nyberg said.

    "A human working with Watson can gain a better answer," said James Hendler, a professor of computer and cognitive science at Rensselaer Polytechnic Institute. "Using what humans are edifying at and what Watson is edifying at, together they can build systems that solve problems that neither of us can solve alone."

    That's why Paul Saffo, a longtime Silicon Valley forecaster, and others, discern better search engines as the ultimate capitalize from the "Jeopardy!"-playing machine.

    "We are headed toward a world where you are going to believe a conversation with a machine," Saffo said. "Within five to10 years, we'll ogle back and roll their eyes at the concept that search queries were a string of answers and not conversations."

    The beneficiaries, IBM's Ferrucci said, could involve technical champion centers, hospitals, hedge funds or other businesses that necessity to get lots of decisions that reckon on lots of data.

    For example, a medical focus might consume the software to better diagnose disease. Since a patient's symptoms can generate many possibilities, the edge of a Watson-type program would live its aptitude to scan the medical literature faster than a human could and suggest the most likely result. A human, of course, would then believe to investigate the computer's finding and get the final diagnosis.

    IBM isn't adage how much money it spent building Watson. But Doherty said the company told analysts at a recent meeting that the motif was around $30 million. Doherty believes the number is probably higher, in the "high dozens of millions."

    In a few years, Carnegie Mellon University robotic whiz Red Whittaker will live launching a robot to the moon as section of Google challenge. When it lands, the robot will get utter sorts of key and crucial real-time decisions - like Neil Armstrong and Buzz Aldrin did 42 years ago - but what humans can accomplish that machines can't will already believe been done: Create the entire darn thing.

    Explore further: 'Jeopardy!' to pit humans against IBM machine

    More information: IBM's Watson: tinyurl.com/4r8w6grJeopardy: jeopardy.com

    ©2010 The Associated Press. utter rights reserved. This material may not live published, broadcast, rewritten or redistributed.



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