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000-SS2 exam Dumps Source : IBM Systems Software Technical Sales Mastery V1
Test Code : 000-SS2
Test appellation : IBM Systems Software Technical Sales Mastery V1
Vendor appellation : IBM
: 32 true Questions
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ARMONK, N.Y., Oct. 11, 2011 /PRNewswire/ -- IBM (NYSE: IBM) today announced it has entered into a definitive condense to acquire Platform Computing, a privately held traffic headquartered in Toronto, Ontario, Canada. Platform Computing is a world leader in cluster and grid management application for distributed computing environments. The acquisition is predicted to shut within the fourth quarter of 2011, bailiwick to the pride of closing conditions. monetary terms were now not disclosed. (logo: http://photographs.prnewswire.com/prnh/20090416/IBMLOGO)From departmental clusters to traffic grids, Platform Computing management software helps shoppers create, integrate and manage shared computing environments which are used in resource-intensive functions corresponding to simulations, desktop modeling and analytics. These technical and exorbitant efficiency computing (HPC) applications gas product development, censorious traffic decisions and step forward science in fiscal capabilities, manufacturing, digital media, oil and fuel, lifestyles sciences, govt, and research and schooling.across agencies of everyone sizes, utility complexity and the volume of records continue to grow vastly, driving the want for more and more compute capability. by means of combining Platform Computing's utility with IBM towering performance programs and application, IBM can stronger serve commercial enterprise valued clientele who are turning to technical computing to prick back the charge and complexity of managing and examining big quantities of statistics in a timely fashion.The mixed probability for servers, storage and programs software for technical computing is over $14 billion in 2011 and is expected to grow over eight p.c annually to $18.5 billion through 2014, in line with IDC (1). "IBM considers the acquisition of Platform Computing to be a strategic point for the transformation of HPC into the exorbitant growth section of technical computing and a vital allotment of their smarter computing approach," stated Helene Armitage, generic manager, IBM programs software. "This acquisition will also be leveraged across IBM as they raise their IBM offerings and solutions, providing purchasers with know-how that helps draw insights to fuel censorious enterprise decisions or leap forward science."Platform Computing at present serves over 2,000 customers together with 23 of the privilege 30 largest international organizations. example shoppers consist of CERN, Citigroup, Infineon, Pratt & Whitney, crimson Bull Racing, Sanger Institute, Statoil and tuition of Tokyo. "Platform Computing's application has a proven track list over the past 19 years of helping consumers to hasten up innovation, company analytics and IT features whereas being convenient to install and control," said Dr. Songnian Zhou, CEO, Platform Computing. "Our market-main software has enabled wide adoption of commodity clusters and enterprise grids everywhere. This acquisition will enable Platform Computing to enhanced serve their shoppers with the aid of leveraging the IBM reply portfolio and prolong the attain of their pioneering distributed computing software for broader enterprise adoption." Platform Computing's focused technical and allotted computing administration application suite enhances IBM's excessive-performance systems together with device x®, BladeCenter®, power programs™ and device Storage®, as well as the IBM utility portfolio, including Tivoli® management and WebSphere® utility infrastructure.Platform Computing's operations as of the closing can be integrated into IBM systems and know-how group. Platform Computing has about 500 employees international. The acquisition of Platform Computing will abet accelerate IBM's boom in smarter computing, a key initiative in IBM's Smarter Planet strategy. earlier this 12 months, IBM stated Smarter Planet initiatives are estimated to power $10 billion in profits for IBM by using 2015. Platform Computing's extensive network of ISVs, OEMs and others provides IBM with the occasion to deliver disbursed computing management software to a broader set of clients whereas assisting Platform Computing's present shoppers. About IBM For more information about IBM technical computing solutions, seek counsel from www.ibm.com/deepcomputing. To study more about IBM smarter computing, visit www.ibm.com/smartercomputing. About Platform Computing Platform Computing is a leader in cluster and grid management software ― serving greater than 2,000 of the world's most annoying corporations. For 19 years, its workload and resource management options fill delivered IT responsiveness and lower expenses for enterprise and HPC functions. seek counsel from www.platform.com.Footnote: (1) source: IDC HPC person discussion board meeting, April 2011, Houston, TexasIBM, BladeCenter, energy programs, tackle Storage, tackle x, Tivoli and WebSphere are registered logos of IBM traffic enterprise in the united states and/or different international locations. everyone other enterprise/product names and repair marks may well be logos or registered trademarks of their respective groups.Media ContactTracy SullivanIBM Media relations+1 email@example.com
March 27, 2019 Alex Woodie
the prospect of a brand fresh language coming to a platform is at everyone times intuition behind excitement. fresh languages carry fresh capabilities, or at the least faster the privilege way to faucet into present capabilities. The query for those animated and working on the IBM i platform is what language will approach next?
RPG continues to be the go-to language used with the aid of the significant majority builders on the IBM i platforms. in response to the 2019 survey with the aid of HelpSystems, eighty four percent of coders on the bailiwick consume RPG. COBOL, RPG’s associate in legacy crime, is also supported within the Rational development for IBM i RDi, together with C and C++ compilers. Java has also been massive for a number of years.
within the mid-2000s, IBM made a big splash with personal home page and its partnership with Zend expertise, the backers of the open supply language, which is now managed through Rogue Wave software. extra recently, IBM has been bringing even more languages to the field, together with Python, Perl, and Node.js. Even Microsoft’s .web is now operating on IBM i via the open source Mono task, which they now fill these days lined in these pages.
So what’s subsequent for IBM i on this planet of languages that may in fact hasten on the power line of processors? There are rumblings that fade may well be the next in line.
Go became at the start developed by Google to streamline the development of applications running in parallel across multi-node clusters of commodity X86 containers. the primary line of fade code became laid down in 2007, and the language become launched to the common public in 2012. since then, it has turn into one of the most commonplace languages on the earth.
Go (which is now and again known as “Golang”) is a static-typed, compiled language it's syntactically comparable to C, which programmers aver originate it rather facile to study. The language offers elements enjoy reminiscence defense and garbage assortment that users aver champion fade to create secure and performant programs. It ships with a criterion library, but there are many other open source libraries purchasable too. The language features its personal built-in trying out tool, which is favored by means of some users.
Google is said to fill developed fade mostly in response to Oracle taking on Java. Google had been a mountainous user of Java before Oracle’s acquisition of sun Microsystems, and the traffic became reportedly involved that Java’s future would be controlled by means of Oracle. whereas it resembles C to a degree, fade is asserted to fill been developed because the antithesis of C++, which its creators reportedly loathed.
In his blog “courageous fresh Geek,” utility engineer Tyler deal with elaborates on what makes fade tick. “Go makes it convenient to effect in writing code it truly is understandable,” he writes. “There’s no magic enjoy many enterprise Java frameworks and not one of the lovely tricks you’ll locate in most Python or Ruby codebases. The code is verbose but readable, unsophisticated but intelligible, tedious however predictable.”
Some IBMers fill notable that they’re working on porting fade to IBM i. If authentic, the port would virtually actually be via PASE, which is the know-how gigantic’s favored path to bringing fresh utility to the platform nowadays, principally software that’s open supply.
different practicable candidates for IBM i consist of Erlang, a language that traces its roots returned to 1986, when it changed into developed by Ericsson as a proprietary language for telephony functions. Erlang turned into launched as open source in 1998, and today
a further candidate may be Swift, the object-oriented, static-typed language from Apple. Swift builds noticeably upon purpose-C, which is an additional programming language from Apple that builds upon C and is the primary language for setting up iOS mobile apps.
not enjoy objective-C, however, Swift is used extra notably on servers. truly, due to the fact that Swift become open sourced below an Apache 2 license in 2015, the language has even made it to IBM’s z systems mainframe by means of the IBM Toolkit for Swift on z/OS. might this sort of toolkit bring Swift to IBM i?
There are different languages that might eventually originate their technique to IBM i. There are JVM-suitable languages enjoy Groovy, Scala, and Kotlin that are garnering a generous tiny bit of consideration, not to mention languages enjoy Julia and Rust which are finding followers. The AIX team at IBM is also performing some travail to champion emerging compiler expertise, such as Clang and LLVM, which might portend some future PASE-level enhancements for IBM i.
Bringing fresh languages to IBM i seems enjoy a generous idea. after all, it puts fresh tools within the fingers of software builders, whereas allowing a brand fresh group of developers to effect in writing functions that hasten on IBM i. however no longer everyone is overjoyed with the theory that extra syntaxes originate for a better ecosystem.
as a substitute of getting current builders to gain lore of fresh languages, some aver IT departments are better off bolstering their pile teams with competencies enjoy database design, challenge management, and technical writing.
For some, having a neatly-rounded construction crew that can boost, set up, and retain purposes – as antagonistic to just understanding the latest, ultimate language – is the vital component that’s missing in so many IT departments this present day.
Whichever camp you quit up in – the one wanting to welcome fresh languages into the IBM i ecosystem or the one craving for greater neatly-rounded developers using latest applied sciences – the topic matter of application development thoughts on the IBM i platform is a vital one.related reviews
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(Reuters) - IBM Corp referred to on Sunday it had agreed to purchase U.S. application enterprise red Hat Inc for $34 billion, together with debt, because it seeks to diversify its technology hardware and consulting traffic into better-margin items and services.
The transaction is by means of a long way IBM’s greatest acquisition. It underscores IBM Chief government Ginni Rometty’s efforts to expand the business’s subscription-based mostly application choices, because it faces slowing software income and waning claim for mainframe servers.
IBM, which has a market capitalization of $114 billion, can pay $a hundred ninety per partake in money for pink Hat, a 63 % premium to Friday’s closing partake cost.
headquartered in 1993, crimson Hat focuses on Linux operating programs, essentially the most usual category of open-source application, which changed into developed as an alternative option to proprietary utility made by using Microsoft Corp.
Headquartered in Raleigh, North Carolina, red Hat costs prices to its corporate customers for customized features, upkeep and technical support, providing IBM a profitable supply of subscription income.
pink Hat is without doubt one of the very few groups in the cloud computing sector that has both earnings growth and free money stream, Rometty, who has been IBM’s CEO for the intuition that 2012, spoke of in an interview with Reuters.
“This acquisition we're certainly doing for enlarge synergies. this is not about can charge synergies at all,” Rometty notable within the interview.
The acquisition illustrates how older expertise organizations are turning to dealmaking to profit scale and fend off competitors, peculiarly in cloud computing, the spot shoppers the usage of enterprise software are searching for to retain money with the aid of consolidating their supplier relationships.
IBM is hoping the deal will abet it seize up with Amazon.com Inc, Alphabet Inc and Microsoft in the impulsively starting to be cloud business. IBM shares fill lost pretty much a 3rd of their value during the past five years, while crimson Hat shares are up 170 percent over the equal duration.FILE photograph: an emblem of IBM is viewed at the cellular World Congress in Barcelona, Spain February 28, 2018. REUTERS/Yves Herman/File photograph
“This deal represents the culmination of IBM’s existing partnership with red Hat, and, in their view, enables IBM to profit a extremely strategic asset to enhance its hybrid cloud initiatives,” Barclays analysts wrote in a analysis note.
They delivered that for the deal to work, it turned into crucial for IBM to uphold pink Hat’s neutrality when it got here to operating structures and retain crimson Hat’s open-supply and multi-cloud position in the market.big BLUE
IBM became situated in 1911 and is frequent within the technology traffic as huge Blue, a reference to its once ubiquitous blue computer systems. It has confronted years of profits declines, because it transitions its legacy computing device maker company into fresh technology products and functions. Its simultaneous initiatives fill protected artificial intelligence and traffic lines around Watson, named after the supercomputer it developed.
To be certain, IBM is not any stranger to acquisitions. It got cloud infrastructure issuer Softlayer in 2013 for $2 billion, and the climate Channel’s data property for more than $2 billion in 2015. It additionally received Canadian traffic software maker Cognos in 2008 for $5 billion.
other big expertise organizations fill additionally recently sought to reinvent themselves through acquisitions. Microsoft this year received open source software platform GitHub for $7.5 billion; chip maker Broadcom Inc agreed to purchase application maker CA Inc for very nearly $19 billion; and Adobe Inc agreed to purchase advertising utility maker Marketo for $5 billion.
one among IBM’s leading opponents, Dell applied sciences Inc, made a mountainous wager on utility and cloud computing two years in the past, when it obtained records storage enterprise EMC for $sixty seven billion. As allotment of that deal, Dell inherited an eighty two % stake in virtualization application traffic VMware Inc.
The deal between IBM and red Hat is anticipated to shut within the second half of 2019. IBM mentioned it planned to droop its partake repurchase program in 2020 and 2021 to abet pay for the deal.
IBM mentioned purple Hat would proceed to be led by means of pink Hat CEO Jim Whitehurst and red Hat’s latest management group. It intends to maintain crimson Hat’s headquarters, amenities, manufacturers and practices.a mark for pink Hat hangs on a constructing in Boston, Massachusetts, U.S., June 27, 2018. REUTERS/Brian Snyder
Lazard Ltd provided monetary counsel to IBM, alongside Goldman Sachs community Inc and JPMorgan Chase & Co, which also provided financing for the deal. Paul, Weiss, Rifkind, Wharton & Garrison LLP offered legal counsel to IBM.
Guggenheim companions LLC and Morgan Stanley were economic advisers to pink Hat, whereas Skadden, Arps, Slate, Meagher & Flom LLP offered legal tips to the traffic on the deal.
“figuring out first-hand how essential open, hybrid cloud applied sciences are to helping agencies unencumber price, they descry the vigour of bringing these two organizations collectively, and are honored to propound IBM and entrust financing for this transaction,” JPMorgan CEO Jamie Dimon stated in an announcement.
Reporting by way of Liana B. Baker and Greg Roumeliotis in manhattan; extra reporting via Stephen Nellis in San Francisco and Carl O'Donnell and Jim Finkle in fresh york; modifying via Rosalba O'Brien and Peter Cooney
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More and more traffic schools are offering traffic masters degrees, from generalist programs in management to specialized master’s offerings covering topics enjoy accounting, data analytics, finance, and marketing.
With so many options out there, choosing the best master’s degree to suit your career ambitions can be a challenge.
Before applying, candidates should know the answers to the following questions: Who are the different master’s programs for? What jobs conclude they lead to? What conclude you study on the course? What conclude you exigency to know to derive accepted?
To reply those questions, they spoke with students and faculty from five of the most common traffic master’s degree options at some of the world’s leading traffic schools.
Read on to find out how to choose the best master’s degree for you.
You can find out more about the master’s degree that interests you most by clicking on one of the links below.
Masters in Accounting
Masters in Analytics
Masters in Finance
Masters in Management
Masters in Marketing
Find out more about traffic master’s degrees via webinar
Masters in Accounting
Find out more about Masters in Accounting via webinar
Dr Wang Jiwei, MSc in Accounting director at Singapore Management University (SMU)
Who is a Master’s in Accounting for?
Our Master of Professional Accounting (MPA) is designed to create a pathway for non-accounting graduates working or seeking to travail in a bailiwick that requires specialized lore in accounting.
We also fill a Master of Science in Accounting (MSA) which specializes in data and analytics. It’s designed for students who already fill a background in accounting or traffic related disciplines, but wish to further their career and skills set in this data-driven era.
What skills/qualifications conclude you exigency to apply?
The overall property of the applicant determines admission to the program. This would embrace prior academic performance at university, travail experience, referees reports, interview scores, and GMAT/SMU Admission Test is compulsory.
Applicants must fill enough background in math. Applicants with post-undergraduate working experience will fill an added advantage. Applicants to the MSA must also fill a traffic or accounting background.
What will you learn on a Master’s in Accounting?
Through the MPA course, students will learn about the three pillars of accounting; the traffic fundamentals, accounting core and the professional services which would embrace the following modules: management accounting, taxation, audit, corporate financial management and financial accounting.
The MSA equips students with the essential skills to harness data for censorious decision making. They learn to originate consume of tools such as R, Python, Tableau, and SQL for data analysis, data visualization and data management. They also can learn machine learning techniques, and understand how they can be applied to the accounting and finance work.
What jobs can you qualify for after a Master’s in Accounting?
An accounting master’s degree is versatile. Every company needs somebody who is well versed in finance and accounting. Hence, the career of an accountant is not limited to the accounting, banking and finance industry. generous accountants are in claim in every sector.
In the recent years, the role of an accountant has evolved. Many organizations are eliminating manual accounting work, because computers and robots can automatically generate accounting entries.
But at the selfsame time, they also descry a growing claim in other job functions, mainly in the areas of data processing, management analysis and financial analysis. In the current market, there is a claim for domain experts who understand finance, accounting and data technology and how the systems work.
Top tip for applying to SMU?
What will give their applicants an edge is whether they fill the drive to excel, the gumption to overcome challenges and the fervor to originate a meaningful repercussion through their work.
Master’s in Accounting student mp;A
Ryan Guo Yu Sheng, SMU MSA student (part-time), manager of Global Operating Certificates at Visa in Singapore
Why pursue a Master’s in Accounting?
I fill always been a tech-savvy accountancy graduate, and most of the process and data technology applied in my travail was self-taught and unstructured. After completing a specialist diploma in traffic Analytics in 2017, I was looking to further my lore and build on the basics scholarly in that course.
An understanding of data analysis and usage of automation and robotics fill become essential to the modern finance office and this is also allotment of my distress in future-proofing my own career. There is an increasing focus on the application of technology to finance processes and simply relying on their IT colleagues to fill us in on technical developments is a thing of the past.
What counsel conclude you fill for prospective Master's in Accounting students?
A candidate should be technically savvy. Dealing with data requires a highly analytical and structured skillset, along with a sense of creativity for data transformation and programming. Having a conceptual understanding of accounting is important.
Masters in Analytics
Find out more about Masters in Analytics via webinar
Crystal Grant, director of admissions (pictured above), and Kalyan Talluri, MSc traffic Analytics program director at Imperial College traffic School (pictured below)
Who is a Master’s in Analytics for?
There's a huge sweep of Master's in Analytics programs available, which reflects the growing claim from candidates and employers for graduates who are able to derive traffic insights and competitive handicap from mountainous data.
Some will be aimed at fresh or recent graduates looking to launch their career, whilst others will be suited to professionals hoping to up-skill to progress or change jobs.
What skills/qualifications conclude you exigency to apply?
Programs vary in the balance of traffic versus technical experience required, but if you fill a fervor for data analytics, quantitative skills and commercial awareness, you should be able to find a Master's in Analytics that supports your goals.
Successful candidates to their MSc traffic Analytics bring a wide variety of academic and travail experience. They behold for strong quantitative, communication, problem-solving and team-working skills. A fervor for coding is also important, as the curriculum is very practical and you should be ready to learn and consume programming languages.
What will you learn on a Master’s in Analytics?
Masters in Analytics level to abet graduates and juvenile professionals understand the content, relevance, and weight of mountainous data problems facing businesses. Their program takes a practical approach including a variety of machine learning, statistical, and operations research techniques.
Students can await to learn solid technical skills in programming, including R, Python and SQL, data structures, and algorithms. They’ll learn skills in optimization, econometrics and statistics, networks, and machine learning. Industry-specific application is core to the program, and students learn to apply their mastery of tools to true traffic problems.
What jobs can you qualify for after a Master’s in Analytics?
The most celebrated destination for their graduates is consulting, however others fade on to travail in technology, FMCG, e-commerce, finance, healthcare, and media. Graduate roles vary depending on candidates’ previous experience, but embrace positions enjoy traffic analyst, data scientist and, consultant. Employers embrace Accenture, Amazon, BCG, eBay, EY, Microsoft, and Revolut.
Top tip for applying to Imperial?
Don’t just list your experience of coding and programming languages. Highlight your problem solving skills by showing how you’ve applied your technical expertise on spellbinding projects. Demonstrating big-picture thinking, commercial awareness, and the talent to articulate complicated information in a compelling and accessible way will abet your application stand out.
Master’s in Analytics student mp;A
Pinelopi Chamalelli, MSc traffic Analytics student at Imperial, joining the analytics graduate scheme of a major consulting solid in London after graduation
Why pursue a Master’s in traffic Analytics?
Analytics is the future; every traffic no matter its size collects more and more data, and desires to utilize them for a more efficient decision making. So, the opportunities they fill after this program are endless not only in terms of quantity but also in terms of variety, since analytics can be applied in every lone industry.
What counsel conclude you fill for prospective Master's in Analytics students?
Coding skills or generally the talent to learn a fresh programming language or a fresh software package quickly is crucial. Three main programming languages they consume are Python, R, and SQL, since these are widely used in the industry.
Good lore of linear algebra and statistics also abet a lot. A generous traffic understanding is also crucial for a successful data scientist.
Masters in Finance
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Diane Jordan, associate director of admissions, MIT Sloan
Who is a Master’s in Finance for?
Our Master of Finance is for individuals interested in learning the fundamentals of modern finance that emphasizes a foundation in how markets work. Students of the program approach from a variety of bachelor’s degree disciplines including business, economics, finance, and significant representation from the derive areas.
What skills/qualifications conclude you exigency to apply?
We seek smart, motivated applicants who are passionate about finance. Recent graduates, early career professionals in finance, engineers, mathematicians, physicists, computer programmers, and other high-tech professionals are encouraged to apply.
We behold for: Success in academic, extracurricular, and professional endeavors; talent to collaborate to accomplish a common goal; talent to inspire others to achieve success; Excellent communication skills; Willingness to seek alternative solutions to existing challenges; Motivation to pursue goals.
What will you learn on a Master’s in Finance?
You’ll commence with rigorous courses in finance theory, financial mathematics, and financial accounting. You’ll be required to pass the Programming Literacy Test in either R or Python programming languages.
You’ll travail with analytical tools—financial modeling, portfolio and pricing theory, statistics and data analytics, and computational methods—to abet tackle multi-faceted challenges that arise in finance, from capital budgeting and cash rush analysis, to dynamic asset allocation and big-data-based investment strategies, and more.
You’ll pick allotment in project-based courses solving real-world problems with MIT's partner corporations and culminating in presentations to corporate decision makers. You’ll choose electives from financial technology, to quantitative methods, to economics, to specialized disciplines such as healthcare finance, fixed income, mergers and acquisitions and asset management.
What jobs can you qualify for after a Master’s in Finance?
Jobs at asset managers, consulting firms, investment and corporate banks, brokerage firms, financial data providers, ratings firms, hedge funds, venture capitalists, insurance companies, public institutions, fintech, and more—from Fortune 500 companies to leading-edge boutiques.
Companies who fill hired Master of Finance graduates from MIT for each of the final three years embrace Bain & Company, BCG, BlackRock, Deloitte, Morgan Stanley, McKinsey, and Citi.
Top tip for applying to MIT Sloan?
Get to know us and the admissions process through online chats and events to abet you decide if MIT is a generous fit.
Master’s in Finance student mp;A
David Smadja, student at MIT Sloan, has an tender for an associate position at a major investment bank in fresh York
Why pursue a Master’s in Finance?
Prior to my master’s, I graduated from a master of applied mathematics. Though I had a generous understanding of the quantitative side of financial markets, I felt I was missing some Important financial knowledge. To me, masters in accounting, for example, are not capable to cover everything you exigency to know to succeed in the bailiwick of finance enjoy a master’s in finance does.
What counsel conclude you fill for prospective Master's in Finance students?
The role of the master’s is to teach you what’s necessary to shatter through the industry but I reckon that some prefatory skills are beneficial. If you’re interested in financial markets, some coding and analytics skills (statistics, optimization, AI a plus) are a minimum to have. If you’re more interested by the corporate side, a generous understanding of financial statements analysis and accountability rules is crucial.
Masters in Management
Find out more about Masters in Management via webinar
Eric Simard, associate director, MSc admissions at Ivey traffic School, University of Western Ontario, Canada
Who is a Master’s in Management for?
It’s for ambitious, recent graduates who want a specialized Master’s degree, that will hone their skill-set, develop their leadership abilities and accelerate their career success. Students are admitted from a variety of disciplines, backgrounds, cultures.
This creates a unique experience in classrooms which is meant to abet students understand, reflect on, and challenge their tendencies, preferences and biases.
At Ivey, students apply to a specific bailiwick of study which will allow them to focus their learning in one of three areas; traffic Analytics, Digital Management, or International Business.
What skills/qualifications conclude you exigency to apply?
We evaluate applicants on a number of dimensions including; Relationship management; Leadership orientation; Openness to learning; Adaptability; Program readiness; Academic performance in their final two years of their undergraduate degree; Motivation for joining the program; Short and long-term career objectives; Pre-program experience; and International exposure/experience.
What will you learn on a Master’s in Management?
Master’s in Management programs are designed to abet students bridge the gap between a solid abstract foundation received in undergraduate studies and the practical and soft skills needed to originate a inequity in the early stages of their career.
Through Case-Method approach to education, Ivey MSc students are effect in the position of the decision-maker and are asked to anatomize data, develop alternatives and then originate and defend their recommendations. They are focused on creating the next group of traffic leaders who are able to walk into a fresh role and pick action.
What jobs can you qualify for after a Master’s in Management?
Graduates pick positions in a variety of industries including; Technology, Management Consulting, financial Institutions, Telecommunications, Consumer Packaged Goods, and more.
The majority of their graduates pick starting positions in leadership rotational programs or in consulting firms focused in Risk, Technology or Human Capital. Many fill titles such as data science associate, region manager or data analyst, and they travail in a variety of organizations such as PwC, Scotiabank, Amazon, Walmart, Deloitte, Proctor & Gamble, Accenture, Sun Life Financial, BMO, Bell, EY, and Morgan Stanley.
Top tip for applying to Ivey?
Candidates should connect with their admission and recruitment team before submitting their application. They should disburse time learning about what their programs fill to tender by attending webinars, talking to current students, and reaching out to their MSc alumni. And they should consider and reflect on how the Ivey MSc in Management can champion their short and long-term career goals.
Master’s in Management student mp;A
Deanna Hamilton, student at Ivey traffic School, starting a consulting career after graduation
Why pursue a Master’s in Management?
I wanted to pursue a career in traffic and a Master’s in Management seemed enjoy the faultless way for me to develop my lore as I did not study traffic during my undergrad. I also aspire to travail internationally one day. Ivey’s Global Lab occasion offered an eight-week, hands-on, international in-company experience which allowed me to immerse myself in an unfamiliar environment and travail cross-culturally.
What counsel conclude you fill for prospective Master's in Management students?
Aside from the obvious skills of being a arduous worker and passionate about the program, I cerebrate it is crucial for students to be open to learning and willing to adapt. It is essential for you to be willing to step out of your solace zone to really pick handicap of every occasion on the program. Interpersonal and communication skills are also necessary for most jobs and, coming into the program, many of my classmates already had exceptional communication skills.
Masters in Marketing
Find out more about Masters in Marketing via webinar
Ning Li, academic program director of the MS in Marketing at Johns Hopkins, Carey School of Business
Who is a Master’s in Marketing for?
For students looking to continue in their marketing studies or students looking to pivot into marketing from another field. Those who are looking to become marketing experts will receive training in traffic foundations in addition to numerous high-level marketing electives.
What skills/qualifications conclude you exigency to apply?
Candidates will exigency undergraduate level communication and analytical skills.
What will you learn on a Master’s in Marketing?
Students will learn behavioral and quantitative methods and best marketing practices to address the most censorious issues facing today’s marketer, including the repercussion of data and convivial media on marketing strategy, consumer behavior, convivial responsibility, competitive economics, business-to-business marketing, and more.
What jobs can you qualify for after a Master’s in Marketing?
Students can pursue careers in Marketing and traffic Analytics, Marketing and Sales, common Management, Consulting, and more. Some employers who fill hired their recent graduates embrace Amazon, China Telecom Americas, IBM, Johns Hopkins Medicine, P&G, and Tencent.
Top tip for applying to Carey?
Be Honest. No applicant is faultless and if there is a allotment of your application you are concerned about, be honest. be open to why this program appeals specifically to you. This is Important because honestly addressing concerns is Important in marketing roles.
Are you interested in a traffic master’s degree?
Register now for the Master’s Week webinar chain held by the Graduate Management Admission Council (GMAC).
Running from 8-to-12 April, different traffic schools will talk about a different master’s program each day.
Monday: Accounting; Tuesday: traffic Analytics; Wednesday: Finance; Thursday: Management; Friday: Marketing
Vint Cerf, who co-designed the early protocols and architecture for their modern internet, uses a parable to define why courageous leadership is vitally Important in the wake of emerging technologies enjoy artificial intelligence.
Imagine that you are animated in a tiny community at the foundation of a valley that’s surrounded by mountains. At the top of a far mountain is a giant boulder. It’s been there for a long time and has never moved, so as far as your community is concerned, it just blends into the ease of the landscape. Then one day, you notice that the giant boulder looks unstable—that it’s in position to roll down the mountain, gaining hasten and power as it moves, and it will Destroy your community and everyone in it. In fact, you realize that perhaps you’ve been blind to its motion your entire life. That giant boulder has always been moving, tiny by little, but you’ve never had your eyes fully open to the subtle, minute changes happening daily: a tiny shift in the shadow it casts, the visual distance between it and next mountain over, the nearly imperceptible sound it makes as the ground crunches beneath it. You realize that as just one person, you can’t hasten up the mountain and cease the giant boulder on your own. You’re too small, and the boulder is too large.
But then you realize that if you can find a pebble and effect it in the privilege spot, it will leisurely the boulder’s momentum and divert it just a bit. Just one pebble won’t cease the boulder from destroying the village, so you examine your entire community to join you. Pebbles in hand, every lone person ascends the mountain and is prepared for the boulder—there is collaboration, and communication, and a blueprint to deal with the boulder as it makes its way down. People and their pebbles—not a bigger boulder—make everyone the difference.
Safe, profitable technology isn’t the result of hope and happenstance. It is the product of courageous leadership and of dedicated, ongoing collaborations. But at the moment, the AI community is competitive and often working at cross-purposes.
The future of AI — and by extension, the future of humanity — is already controlled by just nine mountainous tech titans, who are developing the frameworks, chipsets, and networks, funding the majority of research, earning the lion’s partake of patents, and in the process mining their data in ways that aren’t transparent or observable to us. Six are in the US, and I convoke them the G-MAFIA: Google, Microsoft, Amazon, Facebook, IBM and Apple. Three are in China, and they are the BAT: Baidu, Alibaba and Tencent.
The mountainous Nine are under vehement pressure — from Wall Street in the United States and Beijing in China — to fulfill shortsighted expectations, even at remarkable cost to their futures. They must empower and embolden the mountainous Nine to shift the trajectory of artificial intelligence, because without a groundswell of champion from us, they cannot and will not conclude it on their own.
What follows is a chain of pebbles that can effect humanity on a better path to the future.
The mountainous Nine’s leadership everyone covenant that they are developing and promoting AI for the generous of humanity. I believe that is their intent, but executing on that covenant is incredibly difficult. To start, how should they define “good”? What does that word mean, exactly? This harkens back to the problems within AI’s tribes. They can’t just everyone disagree to be “doing good” because that broad statement is far too abstruse to sheperd AI’s tribes.
For example, AI’s tribes, inspired by Western moral philosopher Immanuel Kant, learn how to preprogram a system of rights and duties into inevitable AI systems. Killing a human is bad; keeping a human is good. The rigidity in that statement works if the AI is in a car and its only choices are to crash into a tree and hurt the driver or crash into a horde of people and destroy them all. Rigid interpretations don’t solve for more complex, real-world circumstances where the choices would be more varied: crash into a tree and destroy the driver; crash into a horde and destroy eight people; crash into the sidewalk and destroy only a three-year-old boy. How can they possibly define what is the best version of “good” in these examples?
Again, frameworks can be useful to the mountainous Nine. They don’t require a mastery of philosophers. They just claim a slower, more conscientious approach. The mountainous Nine should pick concrete steps on how it sources, trains, and uses their data, how it hires staff, and how it communicates ethical conduct within the workplace.
At every step of the process, the mountainous Nine should anatomize its actions and determine whether or not they’re causing future harm—and then they should be able to verify that their choices are correct. This begins with clear standards on bias and transparency.
Right now, there is no singular baseline or set of standards to evaluate bias—and there are no goals to overcome the bias that currently exists throughout AI. There is no mechanism to prioritize safety over hasten and given my own experiences in China and the sheer number of safety disasters there, I’m extremely worried. Bridges and buildings routinely collapse, roads and sidewalks buckle, and there fill been too many instances of food contamination to list here. (That isn’t hyperbole. There fill been more than 500,000 food health scandals involving everything from baby formula and rice in just the past few years.
One of the primary causes for these problems? Chinese workplaces that incentivize cutting corners. It is absolutely chilling to imagine advanced AI systems built by teams that prick corners. Without enforceable global safety standards, the BAT fill no protection from Beijing’s directives, however myopic they may be, while the G-MAFIA must reply to ill-advised market demands. There is no criterion for transparency either. In the United States, the G-MAFIA, along with the American Civil Liberties Union, the fresh America Foundation, and the Berkman Klein heart at Harvard are allotment of the Partnership on AI, which is meant to promote transparency in AI research. The partnership published a terrific set of recommendations to abet sheperd AI research in a positive direction, but those tenets are not enforceable in any way—and they’re not observed within everyone of the traffic units of the G-MAFIA. They’re not observed within the BAT, either.
The mountainous Nine are using flawed corpora (training data sets) that are riddled with bias. This is public knowledge. The challenge is that improving the data and learning models is a mountainous financial liability. For example, one corpus with sober problems is ImageNet, which I’ve made reference to several times in this book. ImageNet contains 14 million labeled images, and roughly half of that labeled data comes solely from the United States.
Here in the US, a “traditional” image of a bride is a woman wearing a white dress and a veil, though in reality that image doesn’t approach nigh to representing most people on their wedding day. There are women who derive married in pantsuits, women who derive married on the beach wearing colorful summery dresses, and women who derive married wearing kimono and saris. In fact, my own wedding dress was a light beige color. Yet ImageNet doesn’t recognize brides in anything beyond a white dress and veil.
We also know that medical data sets are problematic. Systems being trained to recognize cancer fill predominantly been ingesting photos and scans of light skin. And in the future, it could result in the misdiagnosis of people with black and brown skin. If the mountainous Nine knows there are problems in the corpora and aren’t doing anything about it, they’re leading AI down the wrong path.
One way forward is to turn AI on itself and evaluate everyone of the training data currently in use. This has been done plenty of times already—though not for the purpose of cleaning up training data. As a side project, IBM’s India Research Lab analyzed entries shortlisted for the Man Booker Prize for literature between 1969 and 2017. It revealed “the pervasiveness of gender bias and stereotype in the books on different features enjoy occupation, introductions, and actions associated to the characters in the book.” manly characters were more likely to fill higher-level jobs as directors, professors, and doctors, while female characters were more likely to be described as “teacher” or “whore.”
If it’s practicable to consume natural language processing, graph algorithms, and other basic machine-learning techniques to ferret out biases in literary awards, those can also be used to find biases in celebrated training data sets. Once problems are discovered, they should be published and then fixed. This would serve a dual purpose. Training data can suffer from entropy, which might jeopardize an entire system. With regular attention, training data can be kept healthy.
A solution would be for the mountainous Nine—or the G-MAFIA, at the very least—to partake the costs of creating fresh training sets. This is a mountainous examine since creating fresh corpora takes considerable time, money, and human capital. Until we’ve successfully audited their AI systems and corpora and fixed extant issues within them, the mountainous Nine should insist on human annotators to label content and originate the entire process transparent. Then, before those corpora are used, the data should be verified. It will be an arduous and tedious process but one that would serve in the best interests of the entire field.
Yes, the mountainous Nine exigency their data. However, they should earn—rather than assume—our trust. Rather than changing the terms of service agreements using arcane, unintelligible language, or inviting us to play games, they ought to define and disclose what they’re doing. When the mountainous Nine conclude research—either on their own or in partnership with universities and others in the AI ecosystem—they should entrust to data disclosure and fully define their motivations and expected outcomes. If they did, they might willingly participate and champion their efforts. I’d be the first in line.
Understandably, data disclosure is a harder examine in China, but it’s in the best interests of citizens. The BAT should not disagree to build products for the purpose of controlling and limiting the freedoms of China’s citizens and those of its partners. BAT executives must demonstrate courageous leadership. They must be willing and able to disagree with Beijing: to negative requests for surveillance, safeguard Chinese citizens’ data, and ensure that at least in the digital realm, everyone is being treated fairly and equally.
The mountainous Nine should pursue a sober research agenda. The goal is simple and straightforward: build technology that advances humanity without putting us at risk. One practicable way to achieve this is through something called “differential technological progress,” which is often debated among AI’s tribes. It would prioritize risk-reducing AI progress over risk-increasing progress. It’s a generous notion but arduous to implement. For example, generative adversarial networks, which were mentioned in the scenarios, can be very risky if harnessed and used by hackers. But they’re also a path to mountainous achievements in research. Rather than assuming that no one will repurpose AI for evil—or assuming that they can simply deal with problems as they arise—the mountainous Nine should develop a process to evaluate whether fresh basic or applied research will relent an AI whose benefits greatly outweigh any risks. To that end, any financial investment accepted or made by the mountainous Nine should embrace funding for profitable consume and risk mapping. For example, if Google pursues generative adversarial network research, it should disburse a reasonable amount of time, staff resources, and money investigating, mapping, and testing the negative consequences.
A requirement enjoy this would also serve to curb expectations of swiftly profits. Intentionally slowing the development cycle of AI is not a celebrated recommendation, but it’s a vital one. It’s safer for us to cerebrate through and blueprint for risk in further rather than simply reacting after something goes wrong.
In the United States, the G-MAFIA can entrust to recalibrating its own hiring processes, which at present prioritize a prospective hire’s skills and whether they will ft into company culture. What this process unintentionally overlooks is someone’s personal understanding of ethics. Hilary Mason, a highly respected data scientist and the founder of swiftly Forward Labs, explained a simple process for ethics screening during interviews. She recommends asking pointed questions and listening intently to a candidate’s answers. Questions like: “You’re working on a model for consumer access to a financial service. Race is a significant feature in your model, but you can’t consume race. What conclude you do?” and “You’re asked to consume network traffic data to tender loans to tiny businesses. It turns out that the available data doesn’t rigorously inform credit risk. What conclude you do?”
Depending on the answers, candidates should be hired, be hired conditionally, and required to complete unconscious bias training before they commence work, or be dis-qualified. The mountainous Nine can build a culture that supports ethics in AI by hiring scholars, trained ethicists, and risk analysts. Ideally, these hires would be embedded throughout the entire organization: on consumer hardware, software, and product teams; on the sales and service teams; co-leading technical programs; pile networks and supply chains; in the design and strategy groups; in HR and legal; and on the marketing and communications teams.
The mountainous Nine should develop a process to evaluate the ethical implications of research, workflows, projects, partnerships, and products, and that process should be woven in to most of the job functions within the companies. As a gesticulation of trust, the mountainous Nine should publish that process so that they can everyone gain a better understanding of how decisions are made with regards to their data. Either collaboratively or individually, the mountainous Nine should develop a code of conduct specifically for its AI workers. It should reflect basic human rights and it should also reflect the company’s unique culture and corporate values. And if anyone violates that code, a clear and protective whistleblowing channel should be open to staff members.
Realistically, everyone of these measures will temporarily and negatively repercussion short-term revenue for the mountainous Nine. Investors exigency to allow them some breathing room.
AI is a mountainous space, and they are only at the dawn of their ascent up the mountain. It’s time to grab their pebbles and start on the privilege path.
Excerpted from: The mountainous Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity by Amy Webb. Copyright © by Amy Webb. Published by arrangement with PublicAffairs, an imprint of Hachette reserve Group.
Intel has launched its fresh family of Xeon E5 processors aimed at dual socket servers and workstations, which introduces performance and efficiency improvements over the previous Xeon E5 server range.
The fresh 22nm Xeon E5-2600 v2 processors tender up to 45 percent greater efficiency, benchmarked using SPECpower_ssj2008, and 50 percent more performance, benchmarked using SPECVirt_sc2013, than E5-2600 v1 processors.
Diane Bryant, common manager of Intel's datacenter and connected systems group, said the fresh family of 18 processors is suited to handling a wide sweep of virtualised workloads as datacentres plug towards "software-defined" compute, storage and networking.
"Workloads exigency to be facile to deploy, on-demand and always viable," she said at the Intel Developer Forum in San Francisco today.
The E5-2600 v2 processor sweep increases the maximum core weigh from eight cores to 12 over the previous generation and bumps the level 3 cache from 20MB to 30MB. The maximum operating frequency is increased by 200MHz, taking it to 3.5GHz foundation frequency and 4GHz turbo frequency.
The lower power consumption of the v2 family has been made practicable by the plug from a 32nm to 22nm manufacturing process from E5-2600 v1 and the introduction of fresh power management features, said Bryant.
Maximum system recollection is doubled to 1.5TB of DRAM and recollection hasten stepped up to 1,866MHz (for 1.5V memory).
Two fresh security features are introduced in the processor family, OS Guard, which isolates the operating system privilege from the application privilege to forestall malware from spoofing the OS, and instruction-level champion for generating a random 64-bit key.
There processor family is built around three variants of Ivy Bridge-EP processor die, each targeted towards different workloads.
The first is a four to six core chip with 15MB of shared L3 cache and a 40 – 80W TDP, a six to 10 core chip with 25MB shared L3 cache and 70 to 130W TDP and a 12-core chip with 30MB L3 cache and 115 to 130W TDP. The 12-core variant also includes an additional recollection controller to boost recollection bandwidth.
The different processors champion varying QuickPath Interconnect speeds, ranging from 6.4 to 8 GT/s, and PCI Express controllers hasten at 8GT/s for each SKU.
As well as the various server-targeted processors, there is the Xeon E5-2687W, which is an eight core processor running at 3.4GHz with a 150W TDP, designed for two-socket workstations.
The Intel Xeon processors E5-2600 v2 product family will power the fresh IBM NeXtScale System , a high-density, supple computing platform designed for high-demand workloads such as analytics, technical computing and cloud delivery.
Intel's newest processor family will also be used in IBM's fresh x3650 M4 HD high-density storage server, aimed at managing mountainous data and business-critical workloads, as well as everyone of IBM's two-socket systems including System x racks and towers, Flex System, iDataPlex, and BladeCenter offerings. Dell has also selected the fresh processors for its upcoming storage solution, the PowerEdge VRTX.
The Xeon processor E5-2600 v2 product family are shipping from today and sweep in price from $202 to $2,614 when bought in quantities of 1,000. Additionally three single-socket Intel Xeon processor E5-1600 parts will be offered for workstations and sweep in price from $294 to $1080.
ZDNet attended IDF as a guest of Intel
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