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C2090-549 IBM Certified System Programmer - IBM IMS

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C2090-549 exam Dumps Source : IBM Certified System Programmer - IBM IMS

Test Code : C2090-549
Test Name : IBM Certified System Programmer - IBM IMS
Vendor Name : IBM
Q&A : 103 Real Questions

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IBM IBM Certified System Programmer

Will AI achieve cognizance? incorrect question | killexams.com Real Questions and Pass4sure dumps

When Norbert Wiener, the daddy of cybernetics, wrote his e-book The Human Use of Human Beings in 1950, vacuum tubes have been nonetheless the primary digital constructing blocks, and there have been handiest a few actual computer systems in operation.

but he imagined the future we now contend with in impressive detail and with few clear errors. greater than every other early philosopher of synthetic intelligence, he identified that AI would no longer simply imitate—and exchange—human beings in lots of clever actions but trade human beings within the manner. “we're but whirlpools in a river of ever-flowing water,” he wrote. “We are not stuff that abides, however patterns that perpetuate themselves.”

When fascinating alternatives abound, as an instance, we are apt to be willing to pay a little and settle for some small, even trivial, cost-of-doing-business for access to new powers. And relatively quickly we develop into so elegant on our new tools that we lose the capacity to thrive devoid of them. options turn into necessary.

From "What do we Do?" through Daniel C. Dennett. tailored from possible MINDS: Twenty-five methods of AI edited with the aid of John Brockman, published by means of Penguin Press, an imprint of Penguin Publishing community, a division of Penguin Random residence LLC. Copyright © 2019 with the aid of John Brockman.

Penguin Press

It’s an historical, ancient story, with many ordinary chapters in evolutionary historical past. Most mammals can synthesize their personal vitamin C, but primates, having opted for a food plan composed largely of fruit, lost the innate means. The self-perpetuating patterns that we call human beings are actually stylish on clothes, cooked food, nutrition, vaccinations, credit score playing cards, smartphones, and the information superhighway. And—the next day if now not already nowadays—AI.

Wiener foresaw several problems with this incipient scenario that Alan Turing and other early AI optimists generally neglected. The real hazard, he pointed out, is

that such machines, notwithstanding helpless by means of themselves, may be used with the aid of a person or a block of human beings to increase their handle over the relaxation of the race or that political leaders may try to controltheir populations via capacity not of machines themselves but via political strategies as slender and indifferent to human possibility asif they had, definitely, been conceived mechanically.

bound ample, these dangers at the moment are pervasive.

In media, as an example, the innovations of digital audio and video allow us to pay a small rate (in the eyes of audiophiles and movie fanatics) after we abandon analog codecs, and in return provide convenient—all too easy?—copy of recordings with just about superb fidelity.

but there's an incredible hidden charge. Orwell’s Ministry of actuality is now a practical opportunity. AI thoughts for growing all-however-undetectable forgeries of “recordings” of encounters are now becoming obtainable, in an effort to render obsolete the tools of investigation we have come to take with no consideration in the last a hundred and fifty years.

Will we effectively abandon the quick Age of Photographic proof and return to the previous world by which human memory and have confidence offered the gold common, or will we improve new ideas of protection and offense within the arms race of truth? (we will imagine a return to analog movie-exposed-to-gentle, saved in “tamper-proof” methods unless proven to juries, etc., however how long would or not it's earlier than someone figured out a method to infect such techniques with doubt?

one of the vital disturbing classes of fresh journey is that the project of destroying a attractiveness for credibility is lots less costly than the assignment of conserving this kind of reputation.) Wiener noticed the phenomenon at its most regularly occurring: “[I]n the future, there is no distinction between arming ourselves and arming our enemies.” The guidance age is additionally the disinformation age.

What will we do? A key phrase, it appears to me, is Wiener’s virtually offhand observation, above, that “these machines” are “helpless through themselves.” As I have been arguing currently, we’re making equipment, no longer colleagues, and the terrific danger is not appreciating the difference, which we should attempt to accentuate, marking and defending it with political and prison innovations.

AI in its latest manifestations is parasitic on human intelligence. It somewhat indiscriminately gorges on anything has been produced by means of human creators and extracts the patterns to be found there—together with a few of our most pernicious habits. These machines do not (yet) have the goals or concepts or capacities for self-criticism and innovation to allow them to transcend their databases by means of reflectively thinking about their personal pondering and their own dreams.

they're, as Wiener says, helpless, no longer in the sense of being shackled brokers or disabled agents but within the experience of no longer being brokers at all—no longer having the potential to be “moved by causes” (as Kant put it) presented to them. it is crucial that we retain it that approach, so they can take some doing.

within the long run, “strong AI,” or normal artificial intelligence, is viable in principle however no longer appealing (extra on this later). The much more restrained AI that’s pretty much viable these days isn't necessarily evil. but it surely poses its personal set of dangers—mainly that it might be mistaken for effective AI!

The hole between today’s programs and the science-fictional systems dominating the ordinary imagination is still big, even though many folks, each lay and expert, be ready to underestimate it. Let’s believe IBM’s Watson, that could stand as a valuable landmark for our imaginations in the interim.

it's the influence of a really gigantic-scale R&D procedure extending over many grownup-centuries of clever design, and it makes use of hundreds of instances more energy than a human brain. Its victory in Jeopardy! turned into a genuine triumph, made possible by using the formulaic restrictions of the Jeopardy! guidelines, however to ensure that it to compete, even these guidelines had to be revised (one of those alternate-offs: you surrender a little versatility, a bit humanity, and get a crowd-appealing demonstrate).

Watson isn't good company, inspite of deceptive adverts from IBM that indicate a customary conversational potential, and turning Watson right into a plausibly multidimensional agent can be like turning a hand calculator into Watson. Watson could be a valuable core school for such an agent, however more like a cerebellum or an amygdala than a intellect—at most excellent, a unique-purpose subsystem that might play a huge aiding role, but now not remotely up to the task of framing applications and plans and constructing insightfully on its conversational experiences.

Why would we need to create a pondering, creative agent out of Watson? most likely Turing’s amazing idea of an operational verify—the famous Turing examine—has lured us into a lure: the search to create at least the phantasm of a real grownup at the back of the display, bridging the “uncanny valley.”

The danger right here is that ever considering that Turing posed his problem—which became, in any case, a challenge to fool the judges—AI creators have tried to paper over the valley with cutesy humanoid touches, Disneyfication outcomes in order to enchant and disarm the uninitiated. Joseph Weizenbaum’s ELIZA, a very early chatbot, was the pioneer instance of such superficial phantasm making, and it become his dismay at the ease with which his laughably primary and shallow application could persuade individuals they have been having a major heart-to-coronary heart conversation that first despatched him on his mission.

He changed into right to be concerned. If there's one component we have realized from the restrained Turing look at various competitions for the annual Loebner Prize, it is that even very intelligent individuals who aren’t tuned in to the percentages and shortcuts of desktop programming are without difficulty taken in by using basic tricks.

The attitudes of americans in AI towards these strategies of dissembling on the “person interface” have ranged from contempt to party, with a commonplace appreciation that the hints don't seem to be deep however may also be amazing. One shift in attitude that might be very welcome is a candid acknowledgment that humanoid elaborations are false advertising—something to sentence, not applaud.

How may that be achieved? once we admire that individuals are starting to make lifestyles-or-demise selections largely on the groundwork of “counsel” from AI techniques whose inner operations are unfathomable in follow, we will see a superb explanation why those that in any manner inspire people to place more believe in these systems than they warrant should be held morally and legally dependable.

AI methods are very powerful equipment—so powerful that even consultants can have first rate reason not to have confidence their personal judgment over the “judgments” delivered with the aid of their equipment. but then, if these tool clients are going to improvement, financially or otherwise, from driving these equipment via terra incognita, they should be certain they comprehend how to try this responsibly, with maximum handle and justification.

Licensing and bonding the operators of those systems, simply as we license pharmacists, crane operators, and different experts whose blunders and misjudgments can have dire consequences, might, with power from coverage businesses and different underwriters, oblige creators of AI systems to go to impressive lengths to search for and display weaknesses and gaps of their items, and to coach those entitled to function them to monitor out for them.

one could think about a kind of inverted Turing check by which the judge is on trial; until he or she can spot the weaknesses, the overstepped boundaries, the gaps in a gadget, no license to operate may be issued. The intellectual training required to achieve certification as a choose should be traumatic. The urge to attribute human-like powers of thought to an object, our typical tactic every time we encounter what appears to be an clever agent, is almost overpoweringly strong.

indeed, the skill to face up to the attract of treating an obvious grownup as someone is an ugly skill, reeking of racism or species-ism. Many individuals would locate the cultivation of such a ruthlessly skeptical approach morally repugnant, and we are able to expect that even the most trained device clients would from time to time succumb to the temptation to “befriend” their tools, if handiest to assuage their discomfort with the execution of their tasks.

No rely how scrupulously the AI designers launder the phony “human” touches out of their wares, we are able to expect a flourishing of brief-cuts, work-arounds and tolerated distortions of the specific “comprehension” of both the programs and their operators. The comically lengthy lists of common facet effects of latest medicine advertised on tv might be dwarfed via the necessary revelations of the sorts of questions that cannot be responsibly answered via selected techniques, with heavy penalties for producers who “fail to see” flaws in their items. (it is commonly mentioned that a considerable part of the growing to be financial inequality in today’s world is due to the wealth accumulated by means of digital entrepreneurs; we may still enact law that places their deep pockets in escrow for the public first rate.)

We don’t want synthetic mindful agents. there's a surfeit of herbal aware agents, ample to handle whatever thing projects may still be reserved for such particular and privileged entities. We need intelligent equipment. equipment don't have rights, and should now not have feelings that could be harm, or be capable of reply with resentment to “abuses” rained on them by inept clients.

one of the motives for now not making synthetic conscious agents is that, besides the fact that children self sustaining they might turn into (and in precept, they can also be as autonomous, as self-enhancing or self-developing, as any grownup), they would no longer—without particular provision, which might possibly be waived—share with us natural mindful brokers our vulnerability or our mortality.

I as soon as posed a problem to students in a seminar at Tufts I co-taught on artificial brokers and autonomy: provide me the specs for a robotic that might signal a binding contract with you—now not as a surrogate for some human proprietor however by itself. This isn’t a query of getting it to remember the clauses or manipulate a pen on a bit of paper but of having and deserving criminal fame as a morally liable agent. Small babies can’t sign such contracts, nor can those disabled people whose prison status requires them to be below the care and responsibility of guardians of one kind or one more.

The difficulty for robots who might need to gain such an exalted reputation is that, like Superman, they're too invulnerable to be able to make a reputable promise. in the event that they were to renege, what would happen? What would be the penalty for promise breaking? Being locked in a cell or, extra plausibly, dismantled? Being locked up is barely an inconvenience for an AI except we first set up synthetic wanderlust that can not be overlooked or disabled by way of the AI on its own (and it will be systematically elaborate to make this a fool- proof answer, given the presumed cunning and self-expertise of the AI); and dismantling an AI (either a robotic or a bedridden agent like Watson) is not killing it if the information kept in its design and utility is preserved.

The very ease of digital recording and transmitting— the step forward that allows utility and statistics to be, in impact, immortal—removes robots from the world of the prone (at the least robots of the always imagined varieties, with digital software and recollections). If this isn’t obtrusive, feel about how human morality could be affected if we might make “backups” of individuals a week, say. Diving headfirst on Saturday off a high bridge devoid of advantage of a bungee wire would be a rush that you simply wouldn’t remember when your Friday night backup became put on-line Sunday morning, but you may benefit from the videotape of your apparent loss of life thereafter.

So what we're creating don't seem to be—should still now not be—mindful, humanoid agents however an entirely new type of entity, somewhat like oracles, with out a sense of right and wrong, no worry of demise, no distracting loves and hates, no personality (but all types of foibles and quirks that would little question be identified as the “character” of the system): packing containers of truths (if we’re lucky) pretty much actually contaminated with a scattering of falsehoods.

It may be tough enough getting to know to are living with them devoid of distracting ourselves with fantasies concerning the Singularity through which these AIs will enslave us, literally. The human use of human beings will soon be changed—as soon as again—continuously, however we are able to take the tiller and steer between some of the risks if we take responsibility for our trajectory.

Daniel C. Dennett is the Austin B. Fletcher professor of philosophy and co-director of the center for Cognitive reports at Tufts tuition.

From "What can we Do?" with the aid of Daniel C. Dennett. adapted from viable MINDS: Twenty-five approaches of looking at AI edited through John Brockman, published through Penguin Press, an imprint of Penguin Publishing group, a division of Penguin Random condo LLC. Copyright © 2019 with the aid of John Brockman.

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internal The latest ALL400s report | killexams.com Real Questions and Pass4sure dumps

February 6, 2019 Alex Woodie

In early 2018, John Rockwell began a survey from his ALL400s web site in an attempt to glean more assistance concerning the state of midrange neighborhood. most of the questions are about which products IBM i gurus use, but the survey additionally digs into different facets of the relationships that americans and corporations have with the platform, including plans emigrate off IBM i.

in line with the newest ALL400s survey of the midrange group, extra IBM i stores say they don't have any plans to circulate off the platform. It turned into a small boost — from fifty seven.5 % last April who talked about they'd no plans to migrate off IBM i to fifty nine.three p.c reported in remaining month’s consequences – but it become a major change.

What’s extra, the January ALL400s report found that nearly 9.0 percent of respondents say their corporation has plans to circulate off the platform inside 5 years. That turned into down a little from 9.7 p.c said a year in the past who observed they'd a five-12 months migration plan. The percent of survey-takers who responded with a particular “probably” to the migration question remained virtually unchanged (about 14.7 percent), while these asserting they're going to “eventually” migrate dropped from 9.7 p.c a 12 months in the past to 8.6 percent this year.

The outcomes, while now not conclusive, are indicative of a strengthening put in base for IBM i, which is a storyline that’s been documented within the midrange put in base in recent years. The theory goes whatever like this: while there is all the time some degree of churn on any platform, agencies that were likely to migrate off the platform have already performed so, leaving the community with a more strong core of corporations that accept as true with within the way forward for the platform.

Most of Rockwell’s 25-query survey turned into committed to IBM i product usage across a few categories, together with GUI generation, security, backup and recuperation, excessive availability, and cloud internet hosting.

On the GUI entrance, the survey suggests that IBM-offered equipment continue to be very widely wide-spread (used by 20.6 %), adopted by using in-house developed equipment (used by using 10.three p.c). Rounding out the precise 10 are Fresche solutions‘ WebSmart and looksoftware (8.four percent), CNX‘s Valence (7.1 percent), Profound good judgment‘s Profound UI (6.1 %), Rocket‘s LegaSuite and Jwalk (5.7 %), Easy400‘s CGIDev2 (four.4 percent), LANSA (3.4 p.c) and Infor‘s Lawson tools (3.1 %).

The suitable 10 within the GUI category didn’t exchange from 2018 to 2019, although Profound logic moved past Rocket utility and CNX fell at the back of Fresche. interestingly, 25.3 % of All400’s survey takers suggested they nonetheless use eco-friendly screens and don't the use of any GUI. That became down rather just a little from last yr, when 27.eight % pointed out they had no GUI.

On the safety entrance, the percent of IBM i gurus announcing that they had no security utility – both homegrown or purchased from a 3rd celebration — decreased from 31.2 percent a year in the past to 27.6 % this year. this is a welcome trade. besides the fact that children, the guidance that multiple-quarter of IBM i shops don't seem to be invested in protection utility should still nevertheless be a major concern.

practically 17 % of survey-takers say they've developed their own security software in-apartment, a lessen from 20.5 % a year in the past. HelpSystems remained firmly in the number three slot, with 15.eight p.c of respondents saying they have got certainly one of HelpSystems security producdts (PowerTech, StandGuard, Halcyon, and so forth.), down somewhat from 17.1 percent a year in the past. About 6.three percent said they use IBM provided security tools, while 6.2 percent report the use of equipment from Syncsort (comparable to Enforcive, Cilasoft, or Townsend protection’s encryption software), up from about 5.8 % a year in the past. Raz-Lee, meanwhile, got here in with a 6.0 percent share, up from three.9 % a yr ago.

RPG is still the dominant programming language on the IBM i platform.

RPG ILE continues to be the dominant programming language in use on the IBM i platform, the place it’s used by 85.7 p.c of outlets, according to ALL400s survey, basically unchanged from a 12 months ago. Use of RPG Free ticked down slightly, from 74.0 percent to seventy three.0 %. SQL went up a hair, to sixty two.7 percent, while CL edged up 5 p.c to 49.0 p.c. Java and JavaScript use changed into basically unchanged at forty one.8 p.c and 36.4 p.c, respectively, whereas RPG III use edged down a percent to about 36.4 percent. personal home page changed into up about three p.c to 27.1 p.c, whereas .net become up about 1 percent to 18.5 percent. COBOL barely registered 10 percent, and was at the back of visible primary, Zebra barcoding, C/C++, RPG II, BASH, and C#.

Fewer IBM i retail outlets are writing their own trade administration utility, in accordance with the All 400s survey. A year in the past, 29.three % pointed out they rolled their own, while best 26.4 p.c observed they use homegrown today. About 3 percent extra (22.0 versus 19.1) say they use no exchange management utility. Rocket’s Aldon leads the third-party cost with a 16.9 percent share, followed by using UNICOM‘s SoftLanding (12.2 %), PTC‘s Implementer (7.9 percent), continue to be application‘s TD/OMS (3.3 p.c), Midrange Dynamics MDCMS (2.0 %), and ARCAD application (2.0 %). Use of open supply GIT has ticked up from 5.8 % to 6.1 percent.

There wasn’t tons trade in ERP usage, which isn’t dazzling, considering that they could take years to put into effect and frequently are in place for a decade or more. Infor’s ERP LX (BPCS) remained the desirable third-celebration ERP product within the IBM i put in base, based on ALL400s survey, with a 7.5 percent share, followed by Infor’s ERP XA (MAPICS) at 7.3 p.c, Oracle‘s JD Edwards World at 5.5 percent, JD Edwards EnterpriseOne and SAP‘s business Suite tied at 4.5 p.c, and Infor’s gadget 21 and Infinium products tied at 3.three p.c. One-third of respondents report using in-house developed ERP application, whereas 14.9 percent say they use no ERP. That’s in most cases unchanged from closing 12 months, when forty eight.5 percent talked about they used in residence or none (Rockwell grouped them together).

When it involves system automation, about 29.7 percent of ALL400s survey-takers say they use custom classes or IBM’s WRKJOBSCDE command, which turned into down more than 5 p.c from final 12 months. HelpSystems was the proper-ranked third-birthday party systems automation enterprise, with a 27.4 percent share within the survey, up from 25.eight p.c remaining yr. utility Engineering of the united states (SEA) suggested a 3.1 % share, up from 2.0 % final 12 months.

Job scheduling had a similar breakdown, with forty two.4 p.c saying they use IBM’s native tools, and an extra 25.7 percent announcing they write custom programs or use WRKJOBSCDE. HelpSystems had a 24.7 percent share, while BMC application‘s control-M product had a 2.2 % share and SEA’s absScheduler 1.eight percent.

A majority of IBM i stores nevertheless use old building equipment, in keeping with ALL400s latest survey.

The percentage of survey respondents saying they use tapes plummeted from 56.5 p.c a 12 months in the past to 31.3 p.c in the most contemporary survey. It’s doubtful what led to the numbers to crash, even though it may be due to the enormous variety of abilities answers that are blanketed in the question. valued clientele said the use of every little thing from the BRMS utility and SAVF instructions to EVault and the Flashcopy command.

The high availability/disaster recovery category was a little more neatly-defined, with Syncsort’s MIMIX product leading the way with a 26.7 percent share, up a hair from last year. Syncsort’s iTera came it at 9.7 p.c, up half a percent from yr whereas short-EDD (now owned via Syncsort) edged up six-tenths of a % to 5.1 %. Maxava‘s share of the HA/DR market went from 2.four p.c to three.2 percent, whereas Rockee’s iCluster product dropped from 3.3 percent to 2.8 p.c, as the old vision options OMS/ODS product went from 2.1 p.c to 1.9 percent. IBM’s PowerHA increased from 0.9 p.c to 2.4 percent, whereas HelpSystems’ RobotHA dropped from 1.5 p.c to 1.3 % within the new survey. iSamBlue had 0.9 %, while defend superior options‘ HA4i providing dropped from 0.9 p.c to 0.7 %. The percentage saying they used nothing for HA/DR went from 24.9 percent in 2018 to twenty.four % in 2019.

On the cloud front, it’s no surprise that a majority (50.four percent) of respondents record using no cloud services by any means. youngsters, many IBM i retail outlets do, certainly, use public cloud solutions for x86 workloads, in addition to inner most clouds for some IBM i workloads. So it’s now not awesome that Amazon net features is used via 9.1 % of ALL400s survey respondents, followed by way of 5.9 percent who use either IBM’s cloud or the Microsoft Azure cloud. The Google Cloud additionally had a showing at 1.5 %.

among these offering IBM i capabilities, UCG technologies led the manner with 1.three % share, followed by five-manner tie 0.7 p.c that covered Maxava, Cloud400, Sirius, Connectria, and Infor’s system i cloud.

Rockwell updates his survey perpetually, featuring a working snapshot of the IBM i group and the products that the neighborhood makes use of.

“several of the sponsors have helped me get some facts in an effort to make a major raise in the measurement of the ALL400s business checklist. I’m within the system of including as a minimum 5,000 new companies to it, and many that were last proven in the 2004 – 2006 range had been re-proven this year. once I’m executed we’ll have at the least 13 percent of the AS/four hundred ecosystem on the checklist, the usage of IBM’s estimate of a hundred and twenty,000 companies on the platform as a e book. We were initially capturing to make it to the 13,000 business mark for the rolling three-year ordinary by the end of the yr (2017-2019) however with the brand new records we may still come closer to hitting the 20,000 mark.”

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Survey Paints a picture of IBM i community, Product usage


How Nat Prakongpan found His domestic on the Cyber range | killexams.com Real Questions and Pass4sure dumps

series: Voices of securityHow Nat Prakongpan found His home on the Cyber diversityFebruary eleven, 2019  |  by using protection Intelligence personnel Nat Prakongpan, senior manager at the IBM Integration and Threat Intelligence Lab

IBM

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while most children had been bickering with siblings and fawning over the latest toys, young Nat Prakongpan became building an commercial enterprise network for his college.

before he grew to become senior supervisor at the IBM Integration and threat Intelligence Lab and constructed a state-of-the-artwork cyber latitude from the ground up, Nat spent his childhood in Thailand surrounded through computers. He begun programming at age 5. At 13, he turned into certified in community protection by means of considered one of Thailand’s countrywide labs.

Such was his passion for computing that he stopped going to school in grade six to train himself at home and later earn a GED — even though Nat is quick to factor out that his old faculty let him hang around without attending category, so he changed into “socialized.”

“When every person was in class, i used to be constructing the desktop lab,” Nat laughs. “That’s how I won experience in constructing an business community when i used to be in grade seven.”

That’s right — Nat constructed his faculty’s complete network, deploying around 500 machines with everything an enterprise network essential at that time. however this was appropriate as the internet changed into starting to growth, and, of direction, the gadget was compromised.

“That’s how I right away pivoted to gaining knowledge of security,” says Nat. “I took extra certification courses when i was 15 and became eventually in a position to relaxed that community.”

From Wunderkind to community safety skilled

So how does a Thai child genius end up in Atlanta tinkering with IBM protection items to get them to consult with every different? if you ask Nat, it became a “complete fluke” — in fact, he stated tons of his grownup lifestyles is constituted of a sequence of satisfied accidents that led him to construct IBM’s Cyber latitude from the floor up.

the way Nat tells it, he had a number of months between finishing his domestic-education and starting university, so he came to the U.S. to dwell along with his brother-in-legislations (who became then incomes his grasp’s diploma on the institution of Florida) and attend an English-language faculty. His mom inspired him to apply on the equal university and, a whole lot to Nat’s surprise, he become authorized, so he stayed for the 5 years it took to earn his diploma in computing device engineering.

Like a lot of his classmates, he struggled to land an excellent job right out of faculty. Cue the next chuffed accident: a pal dragged him alongside to an advice session by means of cyber web protection systems (ISS) at his alma mater. He had a chat with the crew, and that they called him at 7 a.m. tomorrow and asked him to are available for an interview “now.” He got the job and moved to Atlanta.

In an alternate universe, Nat would have led a really distinctive lifestyles.

“i would likely have long past to a technical college somewhere in Thailand and worked at some organization,” he says. “The U.S. and the job I’m in at the moment is more analysis and construction, however lots of jobs in Thailand or in Asia are more product clients — attempting to find products to buy versus what we should build to make things take place. it could be a whole lot less entertaining.”

home on the Cyber latitude

in its place, Nat ended up at IBM safety following IBM’s acquisition of ISS. still in Atlanta, he now leads the team that ensures the entire particular person products from IBM safety can work with and talk to each and every other to give seamless end-to-conclusion security for shoppers.

“We write the glue for those items that makes them work collectively,” he says. “None of them work together out of the container, however my group has the advantage across all their areas of competencies to make one story from end to conclusion.”

but Nat’s proudest fulfillment is the IBM Cyber latitude in Cambridge, Massachusetts, the primary-ever commercial cyber simulator offering a digital environment through which businesses can interact with precise-world eventualities to bolster their possibility coverage and response capabilities. It’s his baby; he architected the expertise, received the funding and designed the eventualities. Nat’s crew then created a fictional global employer with round 3,000 digital laborers, built an enterprise network and invented threats. The fruits is a completely immersive simulation developed totally to help groups and people find out about disaster instances and improve their incident response talents.

“The working towards within the Cyber range is the ideal success that I have to date: to be capable of teach people and circulate on the advantage of optimum practices,” he says.

Nat may be among the few who built the facility, but he actually isn’t the just one who acknowledges its value. With the Cambridge vicinity now booked greater than half a yr out, the IBM group set about its next problem: taking the cyber simulator experience on tour.

IBMer Nat Prakongpan Found His Home on the Cyber Range

IBMer Nat Prakongpan Found His Home on the Cyber Range

Taking the range on the road

“some of the things we’ve realized is that our consumers invest a lot of time and components to return though the Cyber latitude in Cambridge,” Nat reflects. “it's complicated for a shopper to bring all its high-degree executives into the identical area on the identical day.

“We were also having a hard time finding out which IBM office will be the host of our subsequent cyber range.”

At this point, the team all started exploring greater flexible alternatives that could allow the superior number of individuals to advantage from the cyber simulation adventure. eventually, Nat and his colleagues built the primary-of-its-kind IBM X-force Command Cyber Tactical Operations core (C-TOC).

The C-TOC is not just a state-of-the-art cyber simulation on wheels — Nat proudly explains that it is “a real security operations core (SOC) able to serve reside pursuits comparable to high profile conferences and wearing events.” And to true all of it off, the C-TOC is designed to respond to a reside assault.

“we can power up to a shopper’s site and be in a position to computer screen the attack, in addition to perform forensic investigation on systems and networks,” Nat says.

Bringing the C-TOC from a dream to fact worried most of the equal technical challenges as growing the Cambridge Cyber range. The C-TOC, however, is a cellular unit constructed from the ground up, and Nat’s crew therefore had a number of extra concerns to account for, together with substances, lights, electrical, aircon, ventilation and more. And to accurate it all off, they had to preserve compliance with motor automobile rules in the U.S. and Europe and confirm that all the technology deployed in the unit would be capable of live to tell the tale the twists and turns of the highway.

Nat remembers the primary time he heard the C-TOC conception outlined by means of IBM protection VP Caleb Barlow.

“most likely my first idea turned into that this is an excellent theory and there are such a lot of probabilities for what we will do with this mobile platform,” he remembers. “My second notion, after I had a little more time, changed into, ‘Wow, i am going to be liable for making this all happen!'”

To the surprise of none of his teammates, Nat overcame the boundaries associated with the challenge, and the C-TOC rolled into action in October 2018. This month, the cell cyber range will begin a tour of Europe, bringing true-world cyber incident practising across the continent.

For Nat, the most beneficial point of his involvement with both the Cambridge Cyber range and the C-TOC has been the responses from IBM customers.

“The excitement we now have seen over these tasks was exceptional,” he says. “I consider the C-TOC certainly also conjures up the subsequent era of children and school students to peer what’s viable in cybersecurity and the way they may also be involved.”

Meet X-drive Command core artistic Director Allison Ritter

Tags: commercial enterprise security | IBM Cyber range | network insurance policy | probability Intelligence protection Intelligence staff

safety Intelligence team of workers

safety Intelligence strives to be the main web page for technical and business-focused security content. protection is... 224 Posts continue studying What’s new
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    IBM's Information Management System: Then and Now | killexams.com real questions and Pass4sure dumps

    This chapter covers the history of IBM's Information Management System (IMS) from its beginnings at NASA in 1969 to its current incarnation, and explains why IMS is still relevant to customers today.

    This chapter is from the book 

    This chapter presents IMS's past and discusses IMS as a strategic part of today's computing environment.

    In This Chapter:

  • "History of IMS: Beginnings at NASA"
  • "Is IMS Still Strategic for Customers and IBM?" on page 4
  • IMS has been an important part of world wide computing since its inception.

    On May 25, 1961, United States President John F. Kennedy challenged American industry to send an American man to the moon and return him safely to earth. The feat was to be accomplished before the end of the decade, as part of the Apollo program. American Rockwell won the bid to build the spacecraft for the Apollo program and, in 1965, they established a partnership with IBM to fulfill the requirement for an automated system to manage large bills of material for the construction of the spacecraft.

    In 1966, 12 members of the IBM team, along with 10 members from American Rockwell and 3 members from Caterpillar Tractor, began to design and develop the system that was called Information Control System and Data Language/Interface (ICS/DL/I). During the design and development process, the IBM team was moved to Los Angeles and increased to 21 members. The IBM team completed and shipped the first release of ICS in 1967.

    In April 1968, ICS was installed. The first "READY" message was displayed on an IBM 2740 typewriter terminal at the Rockwell Space Division at NASA in Downey, California, on August 14, 1968.

    In 1969, ICS was renamed to Information Management System/360 (IMS/360) and became available to the IT world.

    Since 1968, IMS:

  • Helped NASA fulfill President Kennedy's dream.
  • Started the database management system revolution.
  • Continues to evolve to meet and exceed the data processing requirements demanded by today's businesses and governments.
  • IMS as a Database Management System

    The IMS database management system (DBMS) introduced the idea that application code should be separate from the data. The point of separation was the Data Language/Interface (DL/I). IMS controls the access and recovery of the data. Application programs can still access and navigate through the data by using the DL/I standard callable interface.

    This separation established a new paradigm for application programming. The application code could now focus on the manipulation of data without the complications and overhead associated with the access and recovery of data. This paradigm virtually eliminated the need for redundant copies of the data. Multiple applications could access and update a single instance of data, thus providing current data for each application. Online access to data also became easier because the application code was separated from data control.

    IMS as a Transaction Manager

    IBM developed an online component to ICS/DL/I to support data communication access to the databases. The DL/I callable interface was expanded to the online component of the product to enable data communication transparency to the application programs. A message queue function was created to maintain the integrity of data communication messages and to provide for scheduling of the application programs.

    The online component to ICS/DL/I ultimately became the Data Communications (DC) function of IMS, which became the IMS Transaction Manager (IMS TM) in IMS Version 4.


    Will AI Achieve Consciousness? Wrong Question | killexams.com real questions and Pass4sure dumps

    When Norbert Wiener, the father of cybernetics, wrote his book The Human Use of Human Beings in 1950, vacuum tubes were still the primary electronic building blocks, and there were only a few actual computers in operation.

    But he imagined the future we now contend with in impressive detail and with few clear mistakes. More than any other early philosopher of artificial intelligence, he recognized that AI would not just imitate—and replace—human beings in many intelligent activities but change human beings in the process. “We are but whirlpools in a river of ever-flowing water,” he wrote. “We are not stuff that abides, but patterns that perpetuate themselves.”

    When attractive opportunities abound, for instance, we are apt to be willing to pay a little and accept some small, even trivial, cost-of-doing-business for access to new powers. And pretty soon we become so dependent on our new tools that we lose the ability to thrive without them. Options become obligatory.

    From "What Can We Do?" By Daniel C. Dennett. Adapted from POSSIBLE MINDS: Twenty-Five Ways of Looking at AI edited by John Brockman, published by Penguin Press, an imprint of Penguin Publishing Group, a division of Penguin Random House LLC. Copyright © 2019 by John Brockman.

    Penguin Press

    It’s an old, old story, with many well-known chapters in evolutionary history. Most mammals can synthesize their own vitamin C, but primates, having opted for a diet composed largely of fruit, lost the innate ability. The self-perpetuating patterns that we call human beings are now dependent on clothes, cooked food, vitamins, vaccinations, credit cards, smartphones, and the Internet. And—tomorrow if not already today—AI.

    Wiener foresaw several problems with this incipient state of affairs that Alan Turing and other early AI optimists largely overlooked. The real danger, he said, is

    that such machines, though helpless by themselves, may be used by a human being or a block of human beings to increase their control over the rest of the race or that political leaders may attempt to controltheir populations by means not of machines themselves but through political techniques as narrow and indifferent to human possibility asif they had, in fact, been conceived mechanically.

    Sure enough, these dangers are now pervasive.

    In media, for instance, the innovations of digital audio and video let us pay a small price (in the eyes of audiophiles and film lovers) when we abandon analog formats, and in return provide easy—all too easy?—reproduction of recordings with almost perfect fidelity.

    But there is a huge hidden cost. Orwell’s Ministry of Truth is now a practical possibility. AI techniques for creating all-but-undetectable forgeries of “recordings” of encounters are now becoming available, which will render obsolete the tools of investigation we have come to take for granted in the last 150 years.

    Will we simply abandon the brief Age of Photographic Evidence and return to the earlier world in which human memory and trust provided the gold standard, or will we develop new techniques of defense and offense in the arms race of truth? (We can imagine a return to analog film-exposed-to-light, kept in “tamper-proof” systems until shown to juries, etc., but how long would it be before somebody figured out a way to infect such systems with doubt?

    One of the disturbing lessons of recent experience is that the task of destroying a reputation for credibility is much less expensive than the task of protecting such a reputation.) Wiener saw the phenomenon at its most general: “[I]n the long run, there is no distinction between arming ourselves and arming our enemies.” The information age is also the disinformation age.

    What can we do? A key phrase, it seems to me, is Wiener’s almost offhand observation, above, that “these machines” are “helpless by themselves.” As I have been arguing recently, we’re making tools, not colleagues, and the great danger is not appreciating the difference, which we should strive to accentuate, marking and defending it with political and legal innovations.

    AI in its current manifestations is parasitic on human intelligence. It quite indiscriminately gorges on whatever has been produced by human creators and extracts the patterns to be found there—including some of our most pernicious habits. These machines do not (yet) have the goals or strategies or capacities for self-criticism and innovation to permit them to transcend their databases by reflectively thinking about their own thinking and their own goals.

    They are, as Wiener says, helpless, not in the sense of being shackled agents or disabled agents but in the sense of not being agents at all—not having the capacity to be “moved by reasons” (as Kant put it) presented to them. It is important that we keep it that way, which will take some doing.

    In the long term, “Strong AI,” or general artificial intelligence, is possible in principle but not desirable (more on this later). The far more constrained AI that’s practically possible today is not necessarily evil. But it poses its own set of dangers—chiefly that it might be mistaken for Strong AI!

    The gap between today’s systems and the science-fictional systems dominating the popular imagination is still huge, though many folks, both lay and expert, manage to underestimate it. Let’s consider IBM’s Watson, which can stand as a worthy landmark for our imaginations for the time being.

    It is the result of a very large-scale R&D process extending over many person-centuries of intelligent design, and it uses thousands of times more energy than a human brain. Its victory in Jeopardy! was a genuine triumph, made possible by the formulaic restrictions of the Jeopardy! rules, but in order for it to compete, even these rules had to be revised (one of those trade-offs: you give up a little versatility, a little humanity, and get a crowd-pleasing show).

    Watson is not good company, in spite of misleading ads from IBM that suggest a general conversational ability, and turning Watson into a plausibly multidimensional agent would be like turning a hand calculator into Watson. Watson could be a useful core faculty for such an agent, but more like a cerebellum or an amygdala than a mind—at best, a special-purpose subsystem that could play a big supporting role, but not remotely up to the task of framing purposes and plans and building insightfully on its conversational experiences.

    Why would we want to create a thinking, creative agent out of Watson? Perhaps Turing’s brilliant idea of an operational test—the famous Turing test—has lured us into a trap: the quest to create at least the illusion of a real person behind the screen, bridging the “uncanny valley.”

    The danger here is that ever since Turing posed his challenge—which was, after all, a challenge to fool the judges—AI creators have attempted to paper over the valley with cutesy humanoid touches, Disneyfication effects that will enchant and disarm the uninitiated. Joseph Weizenbaum’s ELIZA, a very early chatbot, was the pioneer example of such superficial illusion making, and it was his dismay at the ease with which his laughably simple and shallow program could persuade people they were having a serious heart-to-heart conversation that first sent him on his mission.

    He was right to be worried. If there is one thing we have learned from the restricted Turing Test competitions for the annual Loebner Prize, it is that even very intelligent people who aren’t tuned in to the possibilities and shortcuts of computer programming are readily taken in by simple tricks.

    The attitudes of people in AI toward these methods of dissembling at the “user interface” have ranged from contempt to celebration, with a general appreciation that the tricks are not deep but can be potent. One shift in attitude that would be very welcome is a candid acknowledgment that humanoid embellishments are false advertising—something to condemn, not applaud.

    How could that be accomplished? Once we recognize that people are starting to make life-or-death decisions largely on the basis of “advice” from AI systems whose inner operations are unfathomable in practice, we can see a good reason why those who in any way encourage people to put more trust in these systems than they warrant should be held morally and legally accountable.

    AI systems are very powerful tools—so powerful that even experts will have good reason not to trust their own judgment over the “judgments” delivered by their tools. But then, if these tool users are going to benefit, financially or otherwise, from driving these tools through terra incognita, they need to make sure they know how to do this responsibly, with maximum control and justification.

    Licensing and bonding the operators of these systems, just as we license pharmacists, crane operators, and other specialists whose errors and misjudgments can have dire consequences, could, with pressure from insurance companies and other underwriters, oblige creators of AI systems to go to extraordinary lengths to search for and reveal weaknesses and gaps in their products, and to train those entitled to operate them to watch out for them.

    One can imagine a sort of inverted Turing Test in which the judge is on trial; until he or she can spot the weaknesses, the overstepped boundaries, the gaps in a system, no license to operate will be issued. The mental training required to achieve certification as a judge will be demanding. The urge to attribute human-like powers of thought to an object, our normal tactic whenever we encounter what seems to be an intelligent agent, is almost overpoweringly strong.

    Indeed, the capacity to resist the allure of treating an apparent person as a person is an ugly talent, reeking of racism or species-ism. Many people would find the cultivation of such a ruthlessly skeptical approach morally repugnant, and we can anticipate that even the most proficient system users would occasionally succumb to the temptation to “befriend” their tools, if only to assuage their discomfort with the execution of their duties.

    No matter how scrupulously the AI designers launder the phony “human” touches out of their wares, we can expect a flourishing of short-cuts, work-arounds and tolerated distortions of the actual “comprehension” of both the systems and their operators. The comically long lists of known side effects of new drugs advertised on television will be dwarfed by the obligatory revelations of the sorts of questions that cannot be responsibly answered by particular systems, with heavy penalties for manufacturers who “overlook” flaws in their products. (It is widely noted that a considerable part of the growing economic inequality in today’s world is due to the wealth accumulated by digital entrepreneurs; we should enact legislation that puts their deep pockets in escrow for the public good.)

    We don’t need artificial conscious agents. There is a surfeit of natural conscious agents, enough to handle whatever tasks should be reserved for such special and privileged entities. We need intelligent tools. Tools do not have rights, and should not have feelings that could be hurt, or be able to respond with resentment to “abuses” rained on them by inept users.

    One of the reasons for not making artificial conscious agents is that, however autonomous they might become (and in principle, they can be as autonomous, as self-enhancing or self-creating, as any person), they would not—without special provision, which might be waived—share with us natural conscious agents our vulnerability or our mortality.

    I once posed a challenge to students in a seminar at Tufts I co-taught on artificial agents and autonomy: Give me the specs for a robot that could sign a binding contract with you—not as a surrogate for some human owner but on its own. This isn’t a question of getting it to understand the clauses or manipulate a pen on a piece of paper but of having and deserving legal status as a morally responsible agent. Small children can’t sign such contracts, nor can those disabled people whose legal status requires them to be under the care and responsibility of guardians of one sort or another.

    The problem for robots who might want to attain such an exalted status is that, like Superman, they are too invulnerable to be able to make a credible promise. If they were to renege, what would happen? What would be the penalty for promise breaking? Being locked in a cell or, more plausibly, dismantled? Being locked up is barely an inconvenience for an AI unless we first install artificial wanderlust that cannot be ignored or disabled by the AI on its own (and it would be systematically difficult to make this a fool- proof solution, given the presumed cunning and self-knowledge of the AI); and dismantling an AI (either a robot or a bedridden agent like Watson) is not killing it if the information stored in its design and software is preserved.

    The very ease of digital recording and transmitting— the breakthrough that permits software and data to be, in effect, immortal—removes robots from the world of the vulnerable (at least robots of the usually imagined sorts, with digital software and memories). If this isn’t obvious, think about how human morality would be affected if we could make “backups” of people every week, say. Diving headfirst on Saturday off a high bridge without benefit of a bungee cord would be a rush that you wouldn’t remember when your Friday night backup was put online Sunday morning, but you could enjoy the videotape of your apparent demise thereafter.

    So what we are creating are not—should not be—conscious, humanoid agents but an entirely new sort of entity, rather like oracles, with no conscience, no fear of death, no distracting loves and hates, no personality (but all sorts of foibles and quirks that would no doubt be identified as the “personality” of the system): boxes of truths (if we’re lucky) almost certainly contaminated with a scattering of falsehoods.

    It will be hard enough learning to live with them without distracting ourselves with fantasies about the Singularity in which these AIs will enslave us, literally. The human use of human beings will soon be changed—once again—forever, but we can take the tiller and steer between some of the hazards if we take responsibility for our trajectory.

    Daniel C. Dennett is the Austin B. Fletcher professor of philosophy and co-director of the Center for Cognitive Studies at Tufts University.

    From "What Can We Do?" By Daniel C. Dennett. Adapted from POSSIBLE MINDS: Twenty-Five Ways of Looking at AI edited by John Brockman, published by Penguin Press, an imprint of Penguin Publishing Group, a division of Penguin Random House LLC. Copyright © 2019 by John Brockman.

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    How to save money on IBM MLC software with soft capping, LPAR groups | killexams.com real questions and Pass4sure dumps

    If you choose IBM's Monthly License Charge software payment option, implement soft capping and LPAR groups to manage...

    CPU usage without performance glitches.

    Monthly License Charge software

    IBM licensing structures are, to be generous, arcane. IBM has many types of billing, some designed to lure people into the mainframe world, others supporting customers with fleets of Z processors and millions of lines of COBOL code.

    IBM customers have the option to pay an amount determined by CPU consumption each month. This pricing, which encompasses IBM's trademark software products, such as z/OS, DB2, CICS and IMS, comes under the umbrella of Monthly License Charge (MLC) software. MLC applies to IBM's Parallel Sysplex License Charges (PSLC), not One Time Charge (OTC) or subscription-based software.

    Within the MLC software pricing model, IBM charges according to the Millions of Service Units (MSUs) consumed by a logical partition (LPAR), or instance of the operating system. While MSUs roughly correspond to the traditional Millions of Instructions per Second (MIPS) metric for processor capacity, IBM does sometimes manipulate the MSU rating of a machine to encourage customers onto new processors with discounts. This is sometimes called the technology dividend. IBM's Resource Management Facility collects both software MSU and hardware MSU values.

    MLC licenses in action

    With MLC agreements, IBM charges based on the highest four-hour rolling average MSUs used by each LPAR for a month. The four-hour average only applies to the software that actually ran on the LPAR.

    IBM keeps track of what software runs where with type 89 Systems Management Facility records. A utility in z/OS tracks MLC products as they run and cuts a record for each, usually at 15-minute intervals. Each record contains labels identifying the software along with CPU consumption.

    The MLC billing cycle runs from the second of the month to the first of the next month. At the end of the cycle, customers feed the type 89 records through IBM's Subcapacity Reporting Tool (SCRT). The SCRT produces a usage report and a comma separated value (CSV) file suitable for sending to IBM. Mapping the type 89 records to the usage report isn't always straightforward, as SCRT uses transformation rules for accumulating the usage statistics into product report buckets. In some cases, you'll have to do extensive research to figure out exactly what's going into the individual product categories.

    Before sending the CSV file, you can adjust the report for extenuating circumstances, as outlined in your software contract, but IBM requires at least 95% of the type 89 records to be in the report. If you fail to meet that requirement, be prepared to pay software charges for the entire capacity of the box.

    With IBM's MLC payment methodology, some MSUs are cheaper than others. For instance, an enterprise running four LPARs may decide to confine CICS to half of the z/OS instances. The MSUs on the non-CICS machines are suddenly cheaper because they don't include charges for the transaction server. The CICS bill may go down, as the company is now billed only on the CPU that CICS consumes.

    Soft capping an LPAR

    Hard capping an LPAR can cut software costs, but can also risk performance degradation during an unexpected workload surge. The Processor Resource/System Manager (PR/SM) hypervisor enables soft capping as well, wherein systems programmers assign each LPAR a defined capacity in MSUs. Soft capping lets LPARs momentarily exceed their software caps in case of workload bursts or sudden online demand.

    With the cap in place, Workload Manager (WLM) watches the four-hour rolling average as the LPAR's workload waxes and wanes. When the LPAR's four-hour rolling average exceeds its assigned defined capacity, WLM asks PR/SM to manage the partition's processor usage until the average moves below defined capacity. PR/SM's throttling keeps an installation from paying more for MLC software than the LPAR's defined capacity. If the LPAR never reaches its limit, the software charges will be even lower.

    LPAR capacity groups

    For additional flexibility, capacity planners can put LPARs into capacity groups. The systems programmer assigns a defined capacity to the group; each LPAR's share is governed by the partition's PR/SM weight value. An LPAR can belong to only one group, though you can define more than one group per Central Electronic Complex (CEC). None of the LPARs in the group can have dedicated processors and a group may not span CECs.

    Though usage may vary between the individual LPARs, the group as a whole cannot exceed its cap. The LPARs share the CPU as needed, until the group reaches its cap, whereupon the LPAR with the highest weight will get its share and lower-weight LPARs will be limited.

    About the author:

    Robert Crawford spent 29 years as a systems programmer, covering CICS technical support, Virtual Storage Access Method, IBM DB2, IBM IMS and other mainframe products. He programmed in Assembler, Rexx, C, C++, PL/1 and COBOL. Crawford is currently an operations architect based in south Texas, establishing mainframe strategy for a large insurance company.

    captainwhacks@yahoo.com



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