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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

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: 32 existent Questions

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IBM IBM Systems Software Technical

Is Nagios The route forward for Monitoring For IBM i? | killexams.com existent 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 pomp 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 exist 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 matter on. The software –backed by route of the obligatory recursive acronym “Nagios Ain’t Gonna Insist On Sainthood” – become in the genesis developed by using Ethan Galstad back in 2002 to rush and monitor Linux methods, which turned into simply genesis to do headway in enterprise facts facilities.

over the years, the C-primarily based program has been extended to lead an array of remonstrate kinds, including host components fancy 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 scope of Nagios brokers which bear prolonged the framework to an estimated 5,000 instruments.

Nagios is an open source tool 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 besides exist encrypted, and it additionally presents a plug-in that lets users create their own screens in lots of languages.

records collected by using dynamic 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 gawk at the Nagios dashboard on a telephone, a systems admins can descry if vital servers, method, and features are alive or useless.

The Nagios Core server software besides can labor 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 reckon graphs to descry efficiency traits. And with a puny setup ahead of time, Nagios can besides exist configured to immediately respond to hobbies as they occur, or multiply alerts to other individuals.

businesses that want more than what Nagios Core has to present can locate it from Nagios enterprises, the trade 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 besides brings a higher consumer journey with greater potent graphs and enhanced dashboards.

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

regrettably, Nagios companies doesn’t champion IBM i. but that you could net a Nagios distribution for IBM i from a puny 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 sunder facts aspects from IBM i servers, together with issues fancy CPU and disk utilization, ASP usage, number of energetic jobs, and lengthy-operating SQL jobs, amongst others. Some of those services are supported by route of SNMP, while others require the open source JTOpen Java toolbox to exist set aside in.

The Nagios server itself doesn’t rush on IBM i – at the least not yet. With the Nagios on IBM i plug-in, IBM provides users with instructions on the route to deploy Nagios Core or Nagios XI on a Linux server. Technically, there should exist 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 exercise of PASE – but that has no longer took location yet.

IBM makes the case for IBM i stores to do exercise 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 pomp IBM i metrics graphically.

Nagios, nonetheless, provides administrators and operators with a unique centralized view of utter IT belongings, Rowe and Yun write. moreover the core IBM i metrics that at the instant are accessible via the Nagios plug-in, IBM i clients can net 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 labor on IBM i. a brace of years ago, ShapPin Cheng launched a GitHub task called check_as400 that moved records from IBM i server logs into Nagios. seeing that the extensibility and openness of Nagios, it wouldn’t exist fanciful 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 exist shocked to gawk it eddy into a fully supported offering within the months to return, mainly considering the savor trade 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 trade red Hat for $34 billion | killexams.com existent 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 demand for mainframe servers.

IBM, which has a market capitalization of $114 billion, will pay $190 per partake in money for crimson Hat, a 63 % premium to Friday's closing partake 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 saturate 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 location customers using trade software are searching for to redeem money by means of consolidating their seller relationships.

IBM is hoping the deal will assist it trap up with Amazon.com Inc, Alphabet Inc and Microsoft within the utter of a sudden transforming into cloud enterprise. IBM shares bear 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 trade as imposing 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 bear covered synthetic intelligence and trade lines around Watson, named after the supercomputer it developed.

To exist 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 trade software maker Cognos in 2008 for $5 billion.

other massive expertise businesses bear 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 imposing wager on application and cloud computing two years ago, when it obtained records storage enterprise EMC for $67 billion. As a partake 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 nearby in the 2d half of 2019. IBM observed it planned to suspend its partake repurchase application in 2020 and 2021 to champion pay for the deal.

IBM spoke of purple Hat would proceed to exist led by route 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 descry the vigour of bringing these two corporations together, and are honored to recommend IBM and commit financing for this transaction," JPMorgan CEO Jamie Dimon spoke of in a statement.

(Reporting by Liana B. Baker and Greg Roumeliotis in imposing 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 lead 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 title : IBM Systems Software Technical Sales Mastery V1
Vendor title : IBM
: 32 existent Questions

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IBM-Bigdata-Analytics

There is a divergence 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 synthetic 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. inquire of Watson to apply to removing your appendix its lore of hundreds of medical questions and you’d exist disappointed and probably dead. That’s the problem with most analytics, which is why it can exist a difficult sell.

The confess to this problem, we’re told, is not just machine learning but abysmal Machine Learning, the divergence between the two being that plain ancient machine learning is a statistical process that could exist (and used to be) replicated by hand, while the deeper variety looks several generations abysmal in a longitudinal analysis that quickly grows too imposing 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 occur if you occur to exist gathering the privilege data.

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

And it’s besides at least five years from being existent on any commercial scale.

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

Which brings us to a nosy thing happening at IBM. Not closing the I.M. Pei-designed lab in Somers, newfangled York that was announced ultimate 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 ultimate week. What I am talking about here is the reorganization of IBM’s analytics trade unit that was announced internally two weeks ago. You won’t find a word 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 trade processes to better efficiency. Citing similar moves at Google, IBM’s analytics group would no longer bear employees working from home and the number of official analytics office locations worldwide would decrease from 200 to 30. People will soon exist 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 famous reason: If for some judgement affected IBMers necessity to retain working from home or they can’t or won’t bolt 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 universal manager Rob Thomas, who announced the reorg, has been uniformly described to me by IBMers from that division as "an idiot", which may exist 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 matter yet not bear to exist accounted for as one. These are stealth layoffs.

Remember that the future of IBM is hypothetical to exist utter about CAMSS (cloud, analytics, mobile, security, social) and analytics is the A in CAMSS. In one instant 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 retract no matter what, but in this case the specific heads won’t exist decided by the company but by the workers, themselves. The best workers will exist 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 spell that pretty much everyone remaining who isn’t in management is already very genuine at their jobs. There is no more corpulent 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 exist replaced. Rather, as has become the norm at IBM in recent years, those who are left will exist 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 bear to besides 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 partake buy-backs, not hardware, software or computer services.

This morning I took a quick gawk at IBM‘s 1Q16 statement. It was challenging 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 ease of CAMSS was puny. If Analytics is doing better than the rest, why mess with it? How many billions bear they spent to do $11 billion a year on cloud?

IBM has mostly reported revenue. partake of the company’s sales culture, it is what you token in deals that matters. But how much profit is each division making? That is how most companies are managed. IBM‘s imposing 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 trade gains traction. However if the newfangled trade doesn’t do as much profit, that is going to exist a imposing problem.

This is a very scary gamble for IBM.

What this analytics reorg means is that IBM can’t descry a route to compass its near-term Wall Street product objectives without cutting heads in analytics. The division was built up in anticipation of inevitable sales and profit targets, those targets bear not been reached, so IBM will chop expenses until the numbers gawk right. Forget that this reorg will actually result in less -- not more -- labor 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 desist Amazon from Winning the Industrial Internet? | killexams.com existent questions and Pass4sure dumps

Executive Summary

Digital natives fancy Amazon bear 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 kind 3 products (products which bear 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 fearful of massive up-front investments and slower growth.

Just the announcement that Jeff Bezos, Warren Buffett, and Jaime Dimon will exist entering the health custody space has sent shock waves for industry incumbents such as CVS, Cigna, and UnitedHealth. It besides puts a fundamental question back on the agendas of CEOs in other industries: Will software devour 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 besides at increased risk of being disrupted?

To start to confess that question, let’s tally up the score. There are three types of products today. Digital natives (Amazon, Google, Facebook, Microsoft, IBM) bear 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 case would exist Google in search, or Facebook in sociable networking. Their trade models benefit from internet connectivity and they Enjoy tremendous network effects.
  • Type 2: These are once-analog products that bear 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 partake of the product itself (in effect, computers are being set aside 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 bear 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 bear 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 kind 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 exist 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 confess is “yes.” But it won’t exist easy. It will require tremendous amounts of investments in building newfangled capabilities for hardware companies fancy HP, Cisco, Dell, Samsung, and Lenovo; established software companies fancy Facebook, Google, Amazon, and Microsoft; and start-ups. In particular, there are three barriers they must overcome:

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

    Industry incumbents bear expertise in the material sciences, for instance. Further, scientific lore keeps improving over time. They bear made heavy 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 difficult 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 bear well-established brands, built stout customer relationships, and signed long-term service contracts. They’ve won the customer’s trust, which is why customers are willing to partake data. Digital natives can labor with industrial customers, but they bear to first rate their trust; they must build capabilities to understand customer operations; they must match the industrials’ cumulative learning from customer interactions; they must learn to inquire of for the privilege data; and they bear to hire experts in several verticals that can eddy data into insights.

    3. vicissitude in sharing risks. Industrial incumbents bear product knowledge, customer relationships, and field engineers on customer sites. Companies fancy Rolls Royce can, therefore, tender outcome deals where they guarantee customer outcomes (examples: zero downtime, higher speed, more fuel efficiency, zero operator error, greater reliability) and partake risks and rewards with customers. It would exist very difficult for Amazon or Google to guarantee customer outcomes and lift risks with businesses whose operations they know puny about.

    The Challenges for Industrial Giants

    Can the industrial giants lead in the Industrial Internet? The confess is “yes.” But it won’t exist easy 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 tender superior customer outcomes. For that end, they must exist able to attract world-class innovators and software engineers. Is, say, Rolls Royce, in the selfsame consideration set as Facebook and Google for young 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 bear different characteristics: short product evolution cycle, flexibility, and short sales cycle. The industrials must build a digital culture based on concepts fancy 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 assist better the productivity of machines; digital, therefore, has the potential to cannibalize future hardware sales. Second, data and insights multiply the reliability of machines; digital therefore has the potential to cannibalize future service revenues. Third, software subscription and license might enable customers to achieve 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 lift the lead? Or will the digital natives lift the lead? Both bear a chance.

    If I were a betting man, I would location my bets on tech giants over industry incumbents. One factor that will favor digital companies in the industrial internet is technological/scientific breakthroughs that smooth the playing field 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 retract together, other tech companies such as Google, Baidu, Apple, and Lyft will besides exist 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 bear 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 bear 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 fearful of massive up-front investments and slower growth. Its acquisition of total Foods and experiments with Amazon retract grocery stores are an example. Amazon is the one company everyone’s alarmed of, even industrial giants.


    Machines beat us at their own game: What can they do? | killexams.com existent 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 originate 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 net 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 outstrip at answers-and-questions left two champs of the TV game argue in its silicon dust after a three-day tournament, a achievement that experts convoke 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 remedy Final Jeopardy answer.

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

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

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

    "The route to believe 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 learn and create newfangled lore and technology."

    Experts in the field direct 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 bear with the winners and losers, and that magical mix of adrenaline, alarm and aptitude that kicks in when their backs are against the wall and they are in survival mode.

    What humans bear that Watson, IBM's earlier chess champion abysmal Blue, and utter their electronic predecessors and software successors achieve not bear and will not net is the sort of thing that makes song, romance, smiles, sadness and utter that jazz. It's something the experts in computers, robotics and synthetic intelligence know very well because they can't device 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 synthetic intelligence for decades. He thinks IBM's advances with Watson are changing the route people believe about synthetic intelligence and how a computer can exist 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 advance in computing."

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

    "I descry human intelligence consuming machine intelligence, not the other route 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 sustain the world and lift in an colossal 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 achieve that."

    The aptitude of a machine to learn is the essence of the field of synthetic intelligence. And there bear been Great advances in the field, but nothing near human thinking.

    "I've been in this field for 25 years and no matter what advances they make, it's not fancy 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 achieve to bring computers to human intelligence. I'm not positive we'll ever really net there."

    Bart Massey, a professor of computer science at Portland situation University, quipped: "If you want to build something that thinks fancy a human, they bear a Great route to achieve that. It only takes fancy nine months and it's really fun."

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

    Nyberg said it is silly to believe that Watson will lead to an remain or a lessening of humanity. "Watson does just one task: confess questions," he said. And it gets things wrong, such as proverb grasshoppers devour kosher, which Nyberg said is why humans won't eddy 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 remedy response was Chicago, but Watson weirdly wrote, "What is Toronto?????"

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

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

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

    "We are headed toward a world where you are going to bear a conversation with a machine," Saffo said. "Within five to10 years, we'll gawk back and roll their eyes at the strategy 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 do lots of decisions that reckon on lots of data.

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

    IBM isn't proverb how much money it spent building Watson. But Doherty said the company told analysts at a recent meeting that the device 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 exist launching a robot to the moon as partake of Google challenge. When it lands, the robot will do utter sorts of key and crucial real-time decisions - fancy Neil Armstrong and Buzz Aldrin did 42 years ago - but what humans can achieve that machines can't will already bear been done: Create the total 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 exist published, broadcast, rewritten or redistributed.



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