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P2070-072 - IBM Content Collector Technical Mastery Test v1 - BrainDump Information

Vendor Name : IBM
Exam Code : P2070-072
Exam Name : IBM Content Collector Technical Mastery Test v1
Questions and Answers : 41 Q & A
Updated On : November 16, 2018
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P2070-072 exam Dumps Source : IBM Content Collector Technical Mastery Test v1

Test Code : P2070-072
Test Name : IBM Content Collector Technical Mastery Test v1
Vendor Name : IBM
Q&A : 41 Real Questions

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IBM IBM Content Collector Technical

right here's why software builders are worried about IBM's $34 billion acquisition of red Hat | killexams.com Real Questions and Pass4sure dumps

IBM just announced a massive deal to acquire pink Hat for a whopping $34 billion. or not it's good information for IBM within the cloud market, analysts say, but some utility builders are panicking.

Valued at $a hundred ninety a share, crimson Hat often is the third-biggest US tech acquisition ever, and IBM's largest deal in its 107-12 months background.

it be additionally an incredible bet on open supply, through which builders everywhere make contributions their time and potential to constructing free utility tasks giant and small for any one, anyplace, to make use of as they'd like. purple Hat was probably the most first businesses to show open supply into a viable enterprise model, and it is still a luminary within the area.

the upward thrust of open source looks to be a reoccurring theme in tech this 12 months. just last week, Microsoft formally bought GitHub, a platform for open-source coding tasks, for $7.5 billion. earlier this month, Cloudera and Hortonworks merged in a $5.2 billion deal. And prior this 12 months, Salesforce acquired MuleSoft for $6.5 billion.

nonetheless, the deal has raised some alarm bells in Silicon Valley and beyond, as some be troubled that IBM isn't the correct lengthy-time period home for pink Hat — and that the area of open source will suffer for it.

What does pink Hat do?

red Hat makes open-supply application for corporations. or not it's probably the most biggest distributors of Linux, an open-supply operating equipment commonly used to energy company information centers. Linux is an working device, corresponding to home windows and MacOS, that has been round for the reason that the '90s, however pink Hat mainly develops a customized version of Linux for businesses.

it's most reliable known for crimson Hat business Linux, a really good edition of the operating equipment. whereas downloading RHEL is free, crimson Hat expenses for software enhancements and the technical assist that enterprises want, akin to protection, help and setting up.

soon, different startups began following purple Hat's lead in this company approach — even today, sizzling startups like Docker and Mesosphere have adopted in crimson Hat's lead in finding the right way to use free application to generate profits.

What does IBM plan to do with purple Hat?

IBM plans to make use of crimson Hat's software to bridge these Linux-powered corporate facts facilities with the important cloud computing structures in a model known as "hybrid cloud." consumers running pink Hat software on their servers would get an easy path to flow some or all of their functions to the cloud, at their own pace, IBM says.

in addition to its personal IBM Cloud, IBM additionally plans to hold and nurture pink Hat's partnerships with other primary cloud providers like Amazon net capabilities, Microsoft Azure, Google Cloud, and Alibaba. To that end, IBM plans to run pink Hat as an independent subsidiary, in order to retain its neutrality among cloud structures.

furthermore, IBM has talked about it won't cease crimson Hat from contributing to open-supply tasks or from managing the everyday tasks it already maintains, just like the CentOS operating system or the Ansible IT automation tool.

Analysts are expecting this movement to have vast-reaching ramifications for the cloud landscape, and it would give IBM an facet to sustain with key players in the cloud computing market, similar to Amazon, Microsoft and Google. In other phrases, this acquisition keeps IBM crucial, even as its personal cloud lags in the back of Amazon's and Microsoft's.

nevertheless, no longer everyone is convinced that this deal might be an outstanding thing.

Why are people mad about it?

regardless of IBM's assurances that pink Hat will preserve its independence, and hold contributing to open supply, many apprehensive Linux builders (and at least one grownup claiming to be a pink Hat worker) see this as yet a different example of a tech massive gobbling up a liked open-supply application business.

"i am completely bowled over by using this information," mentioned one Reddit consumer who claims to work for purple Hat. "No indication that red Hat changed into going to be obtained. profits were respectable. Open source neighborhood became incredible. now not to point out, IBM is very nearly the anti-crimson Hat when it involves their values."

greater without delay, there is a feeling among fanatics of pink Hat's open-source application that the corporate subculture on the a good deal-higher IBM may have some kind of poor impact on its items.

these fans fret that it's simplest a be counted of time before IBM both mandates sweeping changes at crimson Hat or disassembles and absorbs it wholesale. These issues echo the furor after Microsoft announced it became paying for GitHub, the open-supply group hub, for $7.5 billion. That deal closed ultimate week.

"IBM has a protracted song record of buying exquisite agencies and wreaking havoc on their subculture," one Reddit person posted. "consider of it like corporate colonialism. on occasion it effects in an exodus of ability which severely affects future product updates and help."

What's extra, the tech industry has seen IBM as a corporation that has fallen at the back of the instances as one of the vital oldest tech businesses, and in contemporary years, IBM has struggled to gain footing within the cloud wars with Amazon and Microsoft. First headquartered in 1911, IBM has lost most of its popularity as an innovator.

"IBM's recognition with open source is quality basically; it be the leisure of their popularity i am involved about," another Reddit user posted.

causes to be optimistic

indeed, IBM and open supply go way returned, which consultants say might provide red Hat lovers motive to be positive.

"there's a lot of individuals announcing, here's going to be a problem for crimson Hat, and open supply should be bluewashed for IBM," Chris Gardner, a senior analyst at Forrester, told business Insider. "it be all this stuff that to me is in reality unhealthy analysis. IBM has had a lot of push into open supply within the closing decade or extra."

IBM has certainly in the past supported open-source tasks as an early supporter of Linux, and like pink Hat, or not it's one of the crucial top 10 contributors to Linux. It has invested billions of bucks in Linux and is a member of The Linux foundation. It even created a know-how center primarily for Linux.

The Linux groundwork, which oversees the construction of the operating device, has stepped as much as compliment the movement as a reflection of the value of open source.

"IBM's announcement that it's buying pink Hat items a major possibility for both agencies and highlights the value of open supply within the tech sector," Jim Zemlin, the director of The Linux basis, wrote in a statement on the acquisition. "IBM has been a major open supply recommend for over two a long time: advertising and defending Linux and open source at essential elements in its background."

around the time that Steve Ballmer, then the CEO of Microsoft, all however declared warfare on the concept of open supply, IBM boldly introduced its guide for Linux, embracing it wholeheartedly. more these days, Microsoft has made a a hundred and eighty-degree turn on its attitude towards open supply, however IBM has an extended historical past of aid.

bill Karpovich, a former govt for IBM Cloud who's now the government vice chairman of the open-source application company Sonatype, told enterprise Insider that IBM's pledging guide for Linux became a "main flow towards legitimizing this movement."

IBM, he mentioned, had "always had a business mannequin that supports open source. He added: "they're placing their funds the place their mouth is. With this acquisition, they definitely are inserting huge greenbacks on the open-source model."

still, Gardner has the same opinion that developer issues over the deal may have some advantage. both corporations do have very distinctive cultures: IBM is a century-ancient tech large with a bureaucratic lifestyle and the biggest of gigantic consumers, while the pretty more youthful purple Hat, centered in 1993, serves a generally smaller clientele and is greater geared toward taking dangers.

"there's abilities for problems right here," Gardner noted. "no longer dramatic life-amending issues, however there is a significant change in culture and how they address enterprise shoppers."

To make this acquisition work, he says, IBM should maintain red Hat with handiest a lightweight contact.

"It should enable pink Hat to do its factor," Gardner observed. "as long as IBM has that light touch, everything is superb. They are trying to override the subculture a little bit, and that is the reason not going to work."


Ancestry Adopts IBM Cloud, advanced Analytics to discover enterprise Insights | killexams.com Real Questions and Pass4sure dumps

ARMONK, N.Y., Nov. eight, 2018 /PRNewswire/ -- IBM (NYSE: IBM) introduced these days that Ancestry LLC, the area's biggest consumer DNA community, has chosen IBM Planning Analytics as-a-provider on the IBM Cloud for its enterprise planning and forecasting tactics, to take talents of the mixed answer's fast analytics, scalability and effectivity.

Ancestry has helped valued clientele unencumber hidden insights from historical records and genomic data considering 1983. nowadays the enterprise boasts more than 10 million AncestryDNA purchasers and greater than three million subscribers globally.

IBM, together with Data41, a utility developer and integrator of fiscal planning and reporting systems, worked with Ancestry to create a high-velocity analytics and forecasting solution on the IBM Cloud. With the brand new answer, Ancestry can analyze all fiscal statistics, from budgeting to labor costs, to the forecasting of subscriptions and earnings to help make extra counseled and strategic business decisions based on the latest insights.

"we've improved all of a sudden around the globe, so we required a system that helps our pace of boom," noted Curtis Tripoli, vice president, economic Planning & analysis, at Ancestry. "The analytics is a comprehensive answer, and since or not it's on the IBM Cloud we get the reliability as well as the effectivity and scale we were attempting to find."

"remarkable agencies like Ancestry take into account the cost that comes from leveraging superior technologies like analytics during the cloud to enrich issues like performance, scale and effectivity," spoke of Greg Adams, vice president, IBM business Analytics. "As these businesses develop and scale, Planning Analytics on the IBM Cloud can support them continue to now not most effective manipulate but extract helpful insights from their transforming into business."

For greater on this story, visit: IBM consider weblog

About IBM Cloud

For greater suggestions discuss with IBM Cloud.

For extra guidance talk over with IBM Analytics.           

About Ancestry

Bringing together science, expertise and self-discovery, Ancestry's market-leading products and features leverage facts and different content throughout household historical past and buyer genomics to supply consumers with beneficial insights into their lives. In 2017, Ancestry generated more than $1 billion in income, an annual raise of greater than 30 p.c. The enterprise has offered more than 10 million AncestryDNA kits to this point, reflecting a a hundred and fifteen% year-over-year increase in sales in 2017.

About Data41

Data41 develops company analytics options spanning information supply to visualization – helping groups easily prepare disparate records to make impactful, informed choices. As an IBM Gold partner, Data41's technical and business savvy pals help address enjoyable company targets in company performance administration so increase choices will also be in keeping with correct projections and information while enhancing performance across the business.

Contact

Michael ZimmermanIBM Media Relationsmrzimmerman@us.ibm.com(585) 698-9974 

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IBM Watson: The inside story of how the Jeopardy-winning supercomputer become born, and what it wants to do next | killexams.com Real Questions and Pass4sure dumps

IBM Watson wowed the tech industry and a corner of U.S. pop culture with its 2011 win against two of Jeopardy's superior champions. here's how IBM pulled it off and a look at what Watson's real career goes to be.

Between them, they'd racked up over $5 million in winnings on the television quiz display Jeopardy. They had been the premiere gamers the display had produced over its many years-lengthy lifetime: Ken Jennings had the longest unbeaten run at 74 successful appearances, while Brad Rutter had earned the largest prize pot with a complete of $3.25 million.

Rutter and Jennings have been Jeopardy-successful machines. And in early 2011, they agreed to an exhibition suit against an opponent who'd certainly not even stood at the back of a Jeopardy podium before.

however this Jeopardy unknown had spent years preparing to tackle both giants in the $1m match, taking part in a hundred games in opposition t past winners with a view to increase his possibilities of successful.

That opponent did not smile, offered all his solutions in the same impassive tone, and would not take a seat within the identical room as his fellow contestants. He had to work too difficult at maintaining his cool and turned into so noisy, it turned into concept he became too disruptive to take the podium in grownup. He became saved in a lower back room, his answers piped into the studio.

You would not comprehend by way of looking at him what he was pondering - maybe you'll spot only a tinge of shade when he become complicated over a particularly tough question.

The contender started out with a run of profitable answers - he knew his Beatles songs, Olympic heritage, literary criminals. certain, he wasn't too usual along with his Harry Potter, however he stretched out a lead then again, leaving Rutter and Jennings trailing lots of greenbacks in the back of.

however questions about many years tripped him up, and Rutter fought again, piling up sufficient cash to unsettle anyone who'd guess on the result of the fit. by using the conclusion of the primary of the special exhibition in shape suggests, you'll have been challenging pushed to determine which become safest with your cash.

but then Double Jeopardy took place. The upstart powered in the course of the massive questions, successful even with guesses he become far from satisfied about, and inserting bizarre bets that got here first rate.

through the end of the second episode, the unknown had $25,000 more than his closest opponent, Rutter. Rutter and Jennings seemed increasingly uncomfortable as it begun to seem like they'd get a pasting from the new boy, bobbing in frustration as their opponent buzzed in earlier than them time and time once again.

"I, for one, welcome our new computer overlords" Ken Jennings' response to dropping to an exhibition Jeopardy suit to Watson

Jennings managed a late fightback in the third episode, however the new opponent step by step clawed lower back adequate money to make it a close run.

All three appropriately answered the remaining query 'William Wilkinson's 'An account of the principalities of Wallachia and Moldavia' inspired this writer's most noted novel' with 'who's Bram Stoker?' but Jennings appended his response with: "I for one welcome our new laptop overlords".

He, and Rutter, had misplaced to Watson - a room-sized beast of a computing device made by IBM and named after the company's founder Thomas J Watson.

Watson, which include ten racks of ten energy 750 servers, needed to be kept aside from the human contestants on account of the roar of its cooling gadget and turned into represented on the podium by means of an avatar of IBM's Smarter Planet brand, whose relocating strains would go green when Watson had cracked a thorny difficulty, orange when the reply changed into wrong.

while Watson had the questions delivered in textual content as opposed to by means of taking note of the quizmaster, he performed the online game like his human counterparts: puzzle over the question, buzz in, provide the answer it's surely to be correct, tot up some prize funds.

And Watson become appropriate a lot of the time. He gained the online game with $seventy seven,147 leaving Rutter and Jennings within the filth with $21,600 and $24,000 respectively.

It grew to become out that the true Jeopardy profitable machine become, neatly, a computing device.

Three nights, two americans, one machine and $1 million: the victory of IBM's Watson over two human contestants on Jeopardy was the primary, and perhaps only, time the machine impressed itself on the universal public's awareness.

watson-jeopardy

IBM Watson defeated two of Jeopardy's most fulfilling champions.

photo: IBM

however even before Watson secured its now-noted win, IBM become working on a way to turn the lovable quiz reveal-dominating computer into a serious company contender.

Watson started existence five years before its television appearance, when IBM research professionals have been looking for the subsequent "Grand problem" for the company. IBM periodically runs these Grand Challenges, selected projects that pit man towards machine, have international enchantment, are handy to grasp and entice individuals into working in science and maths fields. along with Watson, the Grand Challenges have spawned Deep Blue, the computing device that famously beat grand master Garry Kasparov at chess, and the Blue Gene supercomputer.

in the mid-2000s, IBM was looking for its next Grand challenge. Paul Horn, then director of IBM analysis, was in favour of attempting to enhance a desktop that could win the Turing check, a method to measure laptop intelligence through having a equipment attempt to fool a human into thinking that they are having a conversation with another adult.

As challenging as passing the Turing verify is - no computing device has yet finished it - it was felt that it would not possibly gentle up the general public's creativeness as other tasks had. but have been there any linked challenges that may still deliver these points of competing in opposition t humans and figuring out human speech together?

"They at the start observed no, or not it's a foolish venture to work on, it be too gimmicky, it's not a real desktop science verify, and we probably can't do it anyway" IBM researchers' first tackle constructing a laptop that could win Jeopardy

"Beating a human in Jeopardy is a step in that route - the questions are advanced and nuanced, and it takes a unique classification of desktop to have an opportunity of beating a human with the aid of answering those category of questions. i used to be running the analysis division and that i changed into bugging people in the agency, in selected [former EVP in IBM's software group] Charles Lickel," Horn pointed out.

Lickel turned into impressed to take on the problem of building a Jeopardy-successful computing device after having dinner with his group. "We had been at a steak apartment in Fishtail, new york. within the center of dinner, all of a sudden the whole restaurant cleared out to the bar - I turned to my crew and requested 'what's happening?'. It changed into very atypical. I hadn't actually been following Jeopardy, nonetheless it grew to become out it was when Ken Jennings was having his lengthy successful streak, and everybody wanted to discover if he would win once more that night, and they'd gone to the bar to see," Lickel talked about. Jennings received once once again that night, and nevertheless holds the longest unbeaten run on Jeopardy with seventy four appearances undefeated.

The conception of a quiz champion laptop did not automatically win his crew around, with lots of Lickel's most suitable team of workers asserting they did not believe a laptop may compete with, let alone beat, flesh and blood champions.

"They initially pointed out no, it's a foolish undertaking to work on, it's too gimmicky, it be not a true computer science verify, and we likely can not do it anyway," stated Horn.

on the other hand, a group sufficiently adventuresome to take on the challenge of building a Jeopardy winner become discovered.

It was nevertheless a small challenge and techniques of commercialisation weren't uppermost in any individual's mind - Grand Challenges have been demonstration projects, whose return for the enterprise become extra in the buzz they created than in a contribution to the final analysis. If commercialisation came about, great - but for now, Watson was just a bit of a moonshot for IBM.

because of the initial measurement of the hassle, it turned into funded from the analysis community's customary finances and did not require signal-off from large Blue's greater-ups, that means it might operate free of the business pressures of most projects.

Jeopardy's quirk is that as a substitute of the quizmaster surroundings questions and contestants providing the reply, the quizmaster offers the answers, called 'clues' in Jeopardy-speak, to which contestants give a question. not most effective would the computer need to be in a position to produce questions for the possible clues that may come its approach on Jeopardy, it might should be in a position to first pull apart Jeopardy's tricksy clues - figure out what turned into being requested - earlier than it may even provide the appropriate response.

trebeck-jeopardy

Jeopardy host Alex Trebeck and the IBM crew talk in regards to the exhibition in shape with Watson.

photo: IBM

For that, IBM developed DeepQA, a massively parallel utility architecture that examined herbal language content in each the clues set by using Jeopardy and in Watson's own stored information, together with looking into the structured guidance it holds. The component-based mostly gadget, built on a collection of pluggable accessories for browsing and weighting assistance, took about 20 researchers three years to reach a degree where it could address a quiz show efficiency and come out looking stronger than its human opponents.

First up, DeepQA works out what the question is asking, then works out some possible answers based on the tips it has to hand, creating a thread for each. each thread uses a whole lot of algorithms to examine the evidence, factors together with what the counsel says, what class of counsel it's, its reliability, and the way possible it is to be principal, then developing an individual weighting according to what Watson has up to now learned about how doubtless they're to be appropriate. It then generated a ranked listing of solutions, with evidence for every of its alternatives.

The suggestions that DeepQA would finally be in a position to question for Jeopardy turned into 200 million pages of advice, from loads of sources. all of the information had to be in the neighborhood saved - Watson wasn't allowed to connect with the information superhighway during the quiz - and understood, queried and processed at a fair clip: in a Jeopardy's case, Watson had to spit out an answers in a matter of seconds to make sure it turned into first to the buzzer.

"once I left IBM in end of 2007, Watson was an embryonic project," talked about Horn. "It had three individuals in Charles Lickel's area that acquired the facts from the historical Jeopardy programmes and had been starting to educate the computing device. It may barely beat a five year historic at the moment. The projection became 'god is aware of how lengthy it could take to beat an adult, not to mention a grand champion'. Then over time when it looked like they started to have an opportunity, Dave under the management of John Kelly grew the challenge into anything gigantic," observed Horn.

while there may be nonetheless debate over precisely when the concept of creating Watson pay its method at last took shape at IBM, when Watson took to the stage for its Jeopardy-successful performance, the exhibit featured IBM execs talking about possible makes use of for the system in healthcare, and moves to establish a Watson company unit began not long after the Jeopardy reveal aired.

IBM's then-CEO Sam Palmisano and its present CEO Ginni Rometty, below whose remit Watson fell on the time, started discussions within the weeks after the win, and the venture become moved from beneath the wing of IBM analysis and into the IBM application group.

In August of 2011, the Watson company unit suitable came into being, headed up by means of Manoj Saxena, who'd joined IBM some years prior when the company he worked for, Webify, turned into acquired via IBM.

Saxena changed into the unit's worker number one. within three months, he had been joined by means of 107 new Watson staffers, on the whole technologists within the fields of herbal language processing and computing device studying.

Healthcare had already been recommended as the first business Watson should still goal for business choices, but there were no plans to confine it simply to medication. Any guidance-intensive trade turned into reasonable video game, anywhere have been there were massive volumes of unstructured and semi-structured facts that Watson could ingest, be aware and system sooner than its human counterparts. Healthcare could be a starting point, but banking, insurance, and telecoms had been all within the firing line.

however how do you flip a quiz exhibit winner into anything more company-like? First job for the Watson group become to familiarize yourself with the computer they'd inherited from IBM research, take into account the forty one separate subsystems that went into Watson, and work out what necessary to be fixed up before Watson might placed on its suit and tie.

in the Watson unit's first yr, the gadget acquired speeded up and slimmed down. "We serialised the threads and the way the software worked and drove up the performance," Saxena referred to. "The equipment today compared to the Jeopardy equipment is approximately 240 % quicker and it is one-sixteenth the size. The equipment that turned into the size of a grasp bed room will now run in a gadget the measurement of the vegetable drawer to your double-drawer refrigerator."

an additional approach of taking a look at it: a single vigour 750 server, measuring nine inches high, 18 inches huge and 36 inches deep, and weighing in at around a hundred kilos. Having obtained the gadget to a extra manageable size for companies, it set about discovering shoppers to take it on.

IBM had healthcare pegged as its first vertical for Watson from the time of the Jeopardy win. despite the fact, whereas Jeopardy Watson and healthcare Watson share a standard heritage, they're distinctive entities: IBM forked the Watson code for its industrial incarnation.

"The device that became the measurement of a master bed room will now run in a system the measurement of the vegetable drawer on your double-drawer fridge" Watson VP Manoj Saxena on the shrinking Watson

Jeopardy Watson had one assignment - get a solution, bear in mind it, and locate the question that went with it. It changed into a single user gadget - had three quizmasters put three solutions to it, it might have thrown the machine right into a spin. Watson had to be retooled for a state of affairs where tens, a whole bunch, youngsters many, clinicians can be asking questions without delay, and not single questions either - advanced conversation with a number of connected queries one after the other, all requested in non-common codecs. And, of path, there become the English language itself with all its messy complexity.

"there were basic areas of innovation that needed to be finished to go past Jeopardy - there was a huge amount of pre-processing, publish-processing and tooling that we've delivered across the core engines," introduced Saxena. "it be the equal of getting a Ferrari engine then attempting to build an entire race vehicle around it. What we inherited changed into the core engine, and we observed 'k, let's construct a brand new element that does all sort of things the customary Jeopardy device wasn't required to do'."

To get Watson from Jeopardy to oncology, there were three processes that the Watson group went via: content adaptation, practising adaptation, and useful adaptation - or, to position it another method, feeding it medical assistance and having it weighted as it should be; trying out it out with some practice questions; then making any technical alterations essential - tweaking taxonomies, as an example.

The content adaptation for healthcare adopted the equal course as getting Watson up to velocity for the quiz exhibit: feed it assistance, show it what right seems like, then let it bet what right feels like and proper it if or not it's wrong. In Jeopardy, that intended feeding it with lots of question and answer pairs from the demonstrate, after which demonstrating what a appropriate response gave the look of. Then it changed into given simply the answers, and asked to get a hold of the questions. When it went wrong, it turned into corrected. through desktop studying, it would start to get a deal with on this answer-question aspect, and alter its algorithms as a consequence.

watson-on-phone

Watson has moved on to options that can power searches from smartphones. picture: IBM

"it would be fed many cases where the background turned into popular and relevant medicine turned into widely used, and then, analogous to training for Jeopardy, it be been given cases after which it suggests therapies," Kohn stated.

Some statistics came from what IBM describes as a Jeopardy-like online game known as medical professional's catch 22 situation, whose questions encompass 'the syndrome characterised with the aid of joint pain, belly pain, palpable purpura, and a nephritic sediment?'. (The reply, of route, is Henoch-Schönlein purpura.)

The working towards, says Kohn, "is an ongoing system, and Watson is unexpectedly enhancing its potential to make reasonably-priced recommendations the oncologists think are helpful."

through 2012, there were two healthcare companies that had begun piloting Watson.

Wellpoint, one of the vital US biggest insurers, changed into probably the most pair of companies that helped define the software of Watson in health. The different became Memorial Sloan-Kettering melanoma core (MSKCC), an employer IBM already had a relationship with and which is located not removed from each IBM's own Armonk headquarters and the analysis laboratories in York Heights, manhattan that nonetheless condominium the primary Watson.

And it changed into this relationship that helped spur Watson's first commercial movement into working in the box of cancer treatment options. whereas using Watson as a prognosis tool might possibly be its most obtrusive utility in healthcare, using it to assist in selecting the right therapy for a melanoma patient made even more feel. MSKCC became a tertiary referral centre - by the time patients arrived, they already had their prognosis.

So Watson become destined first to be an oncologist's assistant, digesting reams of statistics - MSKCC's own, medical journals, articles, sufferers notes and greater - along with sufferers' preferences to get a hold of information for medicine alternatives. every could be weighted accordingly, reckoning on how principal Watson calculated they were.

unlike its Jeopardy counterpart, healthcare Watson additionally has the capacity to go online - now not all its facts must be kept. And while Watson had two million pages of clinical records from 600,000 sources to swallow, it may still make use of the time-honored knowledge garnered for Jeopardy - particulars from Wikipedia, for instance. (What it does not use, however, is the city Dictionary. Fed into Watson late last year, it become reportedly eliminated after answering a researcher's query with the notice "bullshit". "We did locate some enjoyable responses, so we had to shut that down," Saxena noted diplomatically. "That isn't to be repeated, since it can be viewed as very unsuitable in certain cases, and we had to train Watson the correct business behaviour.")

watson-info-box

This chart, completed a year after Watson's Jeopardy win, indicates some of its rapid growth.

picture: IBM

As such, the sources are actually medical publications like Nature and the British medical Journal. And there are different security nets too.

"within the teaching section, a physician - a melanoma care professional during this case - sits down and asks questions of Watson and corrects the machine studying. The doctor and a data scientist are sitting next to each and every other, correcting Watson. Spurious cloth, or conflicted cloth or anything from a pharmaceutical business that the doctor feels could be biased - this is caught right through the practising cycle," introduced Saxena.

WellPoint and MSKCC used Watson as the foundation for techniques that could study and have in mind volumes of medical literature and different counsel - patients' medication and family histories, as an example, as well as clinical trials and articles in scientific journals - to aid oncologists via recommending courses of treatment.

A 12 months of working with both establishments has produced industrial items: Interactive Care Insights for Oncology, and the WellPoint Interactive Care e-book and Interactive Care Reviewer. Interactive Care Insights for Oncology offers advice for treatment plans for lung melanoma sufferers, whereas New WellPoint Interactive Care book and Interactive Care Reviewer reports clinicians' recommended remedies towards their sufferers' plans and is anticipated to be in use at 1,600 healthcare providers this yr.

Watson has bigger ambitions than a clinician's assistant, however. Its medical advantage is round that of a first year scientific scholar, in keeping with IBM, and the enterprise hopes to have Watson flow the usual medical licensing board tests in the not too distant future.

"Our work today is within the very early levels around follow of drugs, round continual care ailments. We're beginning with cancer and we can soon add diabetes, cardiology, mental health, other continual ailments. after which our work is on the fee aspect, where we are streamlining the authorisation and approval system between hospitals, clinics and assurance agencies," Saxena stated.

The premier intention for Watson is to be an aid to analysis - in place of simply suggesting cures for melanoma, as it does nowadays, it might aid doctors in selecting the ailments that convey people to the clinics in the first area.

before then, there is work to be finished. whereas large statistics vendors regularly trumpet the growth of unstructured facts and the abandoning of relational databases, for Watson, it be these older sources of facts that present more of a problem.

"Watson works principally with natural language - free textual content or textual content-like assistance - and that's the reason about 80 % of the large volumes of healthcare suggestions accessible to us," spoke of Kohn. "Then there's the 20 p.c that's structured records - really, numerical facts - or pictures, like MRIs, CAT scans, and so on. Watson does not procedure structured statistics at once and it would not interpret images. it might interpret the report attached to an image, but now not the picture itself."

additionally, IBM is engaged on making a broader healthcare providing that allows you to take it beyond its oncology roots.

"despite the fact that Watson is working with these two companies, what the designers and desktop scientists are focusing on [is] that anything they enhance is generalisable, it be not simply area of interest for cancer remedy and particularly for the several cancers we're working with. We're the use of it as a researching method to create algorithms and methodologies that could be without difficulty generalisable to any enviornment of healthcare. They won't have to have to say, appropriate, we've oncology below manage, now let's start once more with household practice or cardiology," Kohn observed.

ibm-citiback-ebrain

Citi and IBM had been collaborating on business systems on account that the days of the early mainframes.

image: IBM

Watson has additionally already found some activity in banking. Citi is using Watson to enhance client event with the bank and create new features. it's easy to peer how Watson may well be put to make use of, say, figuring out even if a borderline-risk company consumer is likely to repay the personal loan they've utilized for, or used to choose instances of fraud or id theft before customers can be conscious they may be going on.

Citi continues to be early in its Watson experiments. A spokeswoman stated the enterprise is presently just "exploring use circumstances".

From right here on in, in place of being standalone items, the next Watson offerings to hit the market could be embedded into products within the IBM Smarter Planet product line. they may be anticipated to appear in the 2nd half of the 12 months.

the first such Smarter Planet product looked in may also: IBM Engagement guide. The idea at the back of the Engagement advisor, aimed at contact centres, is that customer provider brokers can question their employers' databases and different advice sources the usage of natural language whereas they're conducting helpline conversations with their shoppers. one of the corporations trying out out the provider is Australia's ANZ financial institution, the place it will be assisting name centre team of workers with making monetary functions techniques to people who ring up.

watson-question-phone

Ask Watson goes some distance beyond what Apple's Siri can do, IBM believes.

photograph: IBM

Watson may presumably one day scour purchasable evidence for the most fulfilling time to discover a person able to talk and choose the communique channel without doubt to generate a positive response, or pore over social media for disgruntled customers and supply solutions to their issues in natural language.

There are also plans to alternate how Watson's delivered, too. as an alternative of simply interacting with it by the use of a call centre employee, shoppers will soon be able to become familiar with the Engagement marketing consultant. instead of have some name centre agent examine out Watson generated tips to a client with, say, a fault with their new washing machine or a inventory-trader looking counsel on updating their portfolio, the client and dealer may just quiz Watson without delay from their mobilephone or pill, via typing their query straight right into a business' app. Apps with Watson below the hood should be out in the latter half of this year, in keeping with Forbes.

IBM professionals have also up to now suggested that Watson might turn out to be a supercharged edition of Siri, the place individuals may be capable of talk directly into their mobile and pose a posh query for Watson to reply - a farmer protecting up his smartphone to take video of his fields, and asking Watson when to plant corn, as an example.

IBM is eager to spell out the modifications between Watson and Siri. "Watson is aware of what it knows - and by listening, gaining knowledge of and the use of human-like pondering capabilities uncovers insights from large information, Watson also quickly ascertains what it does not know. Siri, nonetheless, with no trouble looks for key words to go looking the internet for lists of alternate options that it chooses one from," the enterprise says. but, the evaluation holds: Watson could actually have a future as your infinitely knowledgeable very own assistant.

while adding voice-cognizance capabilities to Watson may still be no exquisite shakes for IBM given its current partnerships, the sort of movement would require Watson to be in a position to recognise pictures (anything IBM's already working on) that could require Watson to question all forms of sources of tips together with newspapers, books, photographs, repositories of statistics which have been made publicly accessible, social media and the internet at massive. That Watson should take on such a task in the coming years, mainly if the processing goes on in an IBM datacentre and never on the cellular itself, as you possibly can expect, is certainly within the nation-states of the feasible.

As IBM seeks to embed Watson's capabilities into more and more products, how some distance does the business feel Watson will spread in the coming years? it's going to only say gnomically, "as we continue to scale our capabilities, we intend to make Watson purchasable as a group of services in lots of industries." desire a higher answer? more suitable ask Watson.

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How to Diagnose Java Resource Starvation | killexams.com real questions and Pass4sure dumps

We can visualize resource starvation using an elaborate rendition of the Dining Philosophers Problem. This classic metaphor of resource allocation among processes was first introduced in 1971 by Edsger Dijkstra in his paper "Hierarchical Ordering of Sequential Processes." It's been a model and universal method for verifying theories on resource allocation ever since.

The metaphor goes like this: There are three well-known philosophers in an Asian bistro. Dinner is served but they are only given three chopsticks because the restaurant's supply truck has been stuck in a snow storm for a couple of days. Naturally each philosopher needs two chopsticks to eat his dinner and each is protected from interference while he uses a chopstick.

Plato skipped lunch that day and insists that he should have priority or else he'll faint. If he doesn't give up his chopsticks, the other philosophers won't be able to eat and eventually they'll starve. If Plato drops his chopsticks and immediately picks them up before the other philosophers can get them then they won't be able to eat and they'll eventually starve.

Dijkstra's Dining Philosophers Problem employed spaghetti and forks but I used chopsticks and Asian cuisine for a more realistic illustration since you can't eat spaghetti with a single chopstick (see Figure 1).

These are examples of resource starvation. You could also encounter deadlock. There are a couple of solutions like semaphores and monitors. But we won't think about solutions or deadlocks in this article. We'll focus on detecting resource starvation using IBM Thread and Monitor Dump Analyzer for Java.

What Is the IBM Thread and Monitor Dump Analyzer for Java?During the runtime of a Java process, some Java Virtual Machines (JVMs) may not respond predictably and often seem to hang up for a long time or indefinitely (until the JVM shuts down). It's sometimes very challenging to determine the root causes of these sorts of problems.

By triggering Java thread dumps or Javacores when a Java process doesn't respond, it's possible to collect diagnostic information related to the JVM and a Java application captured at a particular point during execution.

On some platforms, a Javacore is known as "javadump." The code that creates a Javacore is part of the JVM. One can control it by using environment variables and runtime switches. By default, a Javacore occurs when the JVM terminates unexpectedly. A Javacore can also be triggered by sending specific signals to the JVM. Although a Javacore or javadump can occur in Solaris JVMs, much of the content of the Javacore is added by IBM and, so, is present only in IBM JVMs.

IBM Thread and Monitor Dump Analyzer for Java analyzes thread dumps/Javacores and diagnoses monitor locks and thread activities to identify the root causes of hangs, deadlocks, and resource contention or monitor bottlenecks. It can analyze IBM, Solaris, and HP-UX Java thread dumps from Java Virtual Machine 1.3.1, 1.4.x, 5.0, and 6.0

More than three years ago, I created IBM Thread and Monitor Dump Analyzer for Java as a garage project and spent thousands of hours during weeknights, weekends, and vacations to provide my clients and colleagues with something that can help diagnose these problems easily, motivated by the same reasons as my other garage projects like IBM HeapAnalyzer, IBM Pattern Modeling and Analysis Tool, and IBM Performance Analyzer for Java for Windows. All the algorithms used have been filed with the U.S. Patent and Trademark Office.

The widgetry was introduced to the public about two years ago through alphaWorks where it's been one of the top downloads for 30 consecutive months. It's recorded 23,296 downloads so far and it's been used by more than 14,600 companies, government agencies, research facilities, and universities worldwide (these statistics are good as of October 2008).

What Is a Thread Dump?A Java thread dump is the one of the traces/dumps that JVM provides to help diagnosis a hang, deadlock, or monitor contention issue. It contains diagnostic information related to the JVM and a Java application captured at a point during execution. For example, the information can be a list of all the threads that run on a Java virtual machine. Usually thread dumps have more than just thread information. Thread dumps can produce information about the operating system, application environment, threads, stacks, locks, and memory. IBM Thread Dumps/Javacores provide much more information like core interface, data conversion/unicode, class, diagnosis, execution management/thread management, lock, execution engine, mixed mode interpreter, JIT (Just-in-Time compiler), storage/JVM heap, and hardware portability interface/extended hardware portability interface.

The contents and formats of Java thread dumps depend on the platform you're running on and the JVM provider.

Since a thread dump's format isn't a part of the SDK specification, each SDK vendor provides a unique thread dump format and its own JVM information. Currently IBM Thread and Monitor Dump Analyzer for Java understands IBM, Solaris, and HP-UX Java thread dump formats.

By default, IBM JVM thread dumps occur when the JVM terminates unexpectedly. A thread dump can also be triggered by sending specific signals to the JVM. Thread dumps are usually human readable text. In an IBM JVM, the thread dump is often called a Javadump or Javacore. Javacore is NOT the same as a core file, which is generated by a system dump.

Before IBM Thread and Monitor Dump Analyzer for Java was introduced, people had to manually check hundreds of threads in the thread dumps using their favorite editors. With IBM Thread and Monitor Dump Analyzer for Java, we can easily diagnose a variety of issues without reading through hundreds of thread stack traces.

Usually thread dumps aren't as large as heap dumps. Usually its size is around 1MB or less unless you have large number of threads or classes. It's not a big deal to manually review thread dumps if you only have a handful of threads running on your JVM. If you have hundreds of threads with dozens of Java monitors, it gets complicated.

How Does It Work?This technology analyzes the information in each thread and provides diagnostic information, such as current thread information, the signal that caused the Javacore/Java heap information (maximum Java heap size, initial Java heap size, garbage collector counter, allocation failure counter, free Java heap size, and allocated Java heap size), number of runnable threads, total number of threads, number of monitors locked, native memory usage of each JVM component, and deadlock information.

IBM Thread and Monitor Dump Analyzer for Java also provides you with the recommended size of the Java heap cluster (applicable only to IBM SDK 1.4.2 and 1.3.1 SR7 or above) based on a heuristic analysis engine.

It compares each Javacore and provides process ID information for threads, a time stamp of the first Javacore, a time stamp of the last Javacore, the number of garbage collections a minute, the number of allocation failures a minute, the time between the first Javacore and the last Javacore, the number of hang suspects, and a list of hang suspects.

This technology also compares all monitor information in a Javacore and detects deadlock and resource contention or monitor bottlenecks, if there are any.

Let's Get StartedWe can simulate a starvation problem with a simple Java application.

In DiningPhilosophers.java, we created three chopsticks, c1, c2, and c3 with the names, chopstick 1, chopstick 2, and chopstick3. Then we created three philosophers, p1, p2, and p3 with the names, Socrates, Plato, and Aristotle. You might have noticed that each philosopher's name has a suffix that represents a priority since we want to give Plato more of a chance to eat. Besides a name and priority, each philosopher is also given a left chopstick and a right chopstick. We start with each philosopher, p1, p2,  and p3 as shown in Listing 1. (Download Listings 1-6 here.)

In Chopstick.java, we just create a constructor, a getter, and a setter for the name of chopstick as shown in Listing 2

In Philosopher.java, we create a constructor, getters and setters for right and left chopsticks, and the philosopher's name. We also override the run() method in which we acquire Java's built-in monitors for left and right chopsticks and call the eat() method. In each () method, we pause for two seconds to simulate eating with the sleep() method but keep in mind that the philosopher is eating, not sleeping in the eat() method. See Listing 3.

Now let's put all the classes in a subdirectory, compile, and run them.

Compiling classes on a Unix platformjavac com/ibm/Jinwoo/starvation/DiningPhilosophers.java

Compiling classes on a Windows platformjavac com\ibm\jinwoo\starvation\DiningPhilosophers.java

I used the latest release of IBM Java virtual machine 6.0 (build jvmwi3260-20080816_22093 VM build 20080816_022093_lHdSMr) and another vendor's latest release of a Java virtual machine 6.0 when I wrote this for a fair comparison.

Executing classesjava com.ibm.jinwoo.starvation.DiningPhilosophersPlato priority9 is eating with chopstick 3 and chopstick 1Plato priority9 is eating with chopstick 3 and chopstick 1Plato priority9 is eating with chopstick 3 and chopstick 1Plato priority9 is eating with chopstick 3 and chopstick 1Plato priority9 is eating with chopstick 3 and chopstick 1

Most of the time Plato will be eating and the other two philosophers will have less of a chance to eat. We can generate thread dumps by sending signal 3 to the process. On the Windows platform, you can use keyboard combinations like Ctrl-Break to send signal 3 to a process running in a command line window. Listing 4 has the results from the IBM Java virtual machine.

We used another vendor's Java virtual machine and redirected output to a file.

Generating thread dumps with another vendor's Java virtual machinejava com.ibm.jinwoo.starvation.DiningPhilosophers 1> sun.log

Now let's talk about thread dump a little more. In most Java platforms, thread dumps are generated when the JVM terminates unexpectedly because of an operating system signal or when the user enters a reserved key combination control-break on Windows, say. We can also generate thread dumps with IBM's JavaDump API: com.ibm.jvm.Dump.JavaDump() if you're running a IBM Java virtual machine.

You can use the kill command on most Unix systems:

  • SIGQUIT[3] : JVM will not terminate
  • For example, kill -3 $PID

  • SIGSEGV[11] : JVM will terminate
  • For example, kill -11 $PID

    On the IBM WebSphere Application Server 5/6 environment, you can use wsadmin script to generate thread dumps:

    wsadmin.sh -conntype SOAP -port <port number>> set jvm [$AdminControl completeObjectName type=JVM,process=server1,*]> $AdminControl invoke $jvm dumpThreads


    Highlights from Linux Kongress | killexams.com real questions and Pass4sure dumps

    This article brought to you by LWN subscribers

    Subscribers to LWN.net made this article — and everything that surrounds it — possible. If you appreciate our content, please buy a subscription and make the next set of articles possible.

    September 27, 2006

    This article was contributed by Stacey Quandt

    The 13th annual International Linux System Technology Conference, also known as Linux Kongress, took place September 5 - 8 in Nürnberg, Germany. As a technical Linux event Linux Kongress is smaller in scale than the Ottawa Linux Symposium and linux.conf.au. Still the conference sessions and tutorials included a number of quality talks from familiar members of the Linux and open source communities such as Heinz Mauelshagen, Lars Mueller, Theodore Ts'o, Volker Lendecke, Alan Robertson, and Daniel Phillips.

    A few of the talks stood out. One such talk was Felix von Leitner's presentation titled "Benchmarking, round 2: I/O Performance", in which he tested file system performance on Linux, Windows, OpenSolaris, NetBSD, FreeBSD, and OpenBSD in order to better understand the scalability of different operating systems and IP stack throughput. Based on von Leitner's benchmarking methodology Linux has the fastest file system - reiser4.

    The testing theme continued with Poornima Bangalore, whose presentation was on the topic of "Best Practices in Linux Kernel Testing." Her talk detailed many of the key differences between traditional and open source testing. She pointed out that mainline kernel testing is more challenging than testing many other open source projects because of the rapid development and the different sub trees in the kernel: the stable kernels are released every 6 weeks or so, release candidate (-rc) kernels are available every week, and experimental (-mm) kernels are available every few days. Poornima shared best practices regarding kernel configuration, hardware configuration, test automation, test coverage, and first failure data capture.

    Heinz Mauelshagen gave a talk on device-mapper architecture features and the related target feature set. In the talk "Linux as a Hypervisor," Jeff Dike discussed the evolution of the hypervisor support in the Linux kernel and how capabilities such as ptrace, AIO and O_DIRECT make a difference to virtual machines. He also talked about the implications of FUSE (filesystems in userspace) and the manageability benefits of exporting a UML filesystem to the host. Lars Marowsky-Bree's presentation on Heartbeat 2 and Xen explored Heartbeat's ability to manage Xen guests. He expanded on Heartbeat's architecture and its integration with Xen to enable resource reallocation, globally ordered recovery actions, and data center automation policies using the Cluster Resource Manager (CRM).

    Mattias Rechenburg's presentation on "Using Enterprise Data Centers with OpenQRM" showcased the state of OpenQRM an open source project to achieve high-availability, scalability, and deployment, service and server virtualization on a variety of operation system. In spite of OpenQRM's pluggable architecture, the audience focused on the fact that it depends on a binary module which requires support from Qlusters. The general sentiment from the audience was they were not interested if they couldn't get support from Red Hat, IBM, Hewlett-Packard etc.

    In "Real-Time Approaches to Linux," Ted Ts'o shared his perspective on enterprise real-time computing and how it differs from so-called traditional real-time computing. He emphasized the changing requirements in enterprise software and how high throughput is not enough because customers increasingly also require latency guarantees, especially in particular military applications and trading systems. It was interesting to hear about the benefits and tradeoffs of different approaches to enterprise real-time including RTAI and Ingo Molnar's CONFIG_PREEMPT_RT.

    Ted suggested that guidelines outlined by his colleague Paul McKenney can be used to evaluate the different approaches to enterprise real-time. This includes quality of service, the amount of code inspection required when a new feature is added, the API provided to applications, the relative complexity, fault isolation, and supported hardware and software configurations.

    Although IBM presently has only one customer that plans to deploy enterprise real-time computing, the ability to support large SMP systems, TCP/IP, commercially available middleware, and databases makes it an area to watch in the future. Ted also elaborated on the features of IBM's real-time JVM/SDK (aka IBM Websphere Real-Time v1.0) such as RTSJ (Real-time specification for Java), the Metronome real-time garbage collector, and AOT (Ahead of Time Compilation). The talk emphasized that there are many new applications for real-time operating systems, and in particular enterprise real-time Linux.

    Maddog provided the final keynote on having fun with open source in his own inimitable way.

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