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M2090-743 - IBM Big Data and Analytics Sales Mastery v2 - BrainDump Information

Vendor Name : IBM
Exam Code : M2090-743
Exam Name : IBM Big Data and Analytics Sales Mastery v2
Questions and Answers : 20 Q & A
Updated On : February 15, 2019
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M2090-743 exam Dumps Source : IBM Big Data and Analytics Sales Mastery v2

Test Code : M2090-743
Test Name : IBM Big Data and Analytics Sales Mastery v2
Vendor Name : IBM
Q&A : 20 Real Questions

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Amazon internet functions Chosen For Guinness Six nations Rugby Championship, IBM and SAP Canada to seriously change Toronto Transit and Kofax Acquires Nuance doc Imaging shares mentioned: (NasdaqGS:AMZN) (NYSE:IBM) (NYSE:SAP) (NasdaqGS:NUAN)

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IBM (NYSE:IBM) and SAP Canada, a subsidiary of German software company SAP SE (NYSE:SAP), introduced their joint effort to transform the Toronto Transit commission's (TTC) internal payroll, finance and HR procedures, featuring the general public sector corporation with a contemporary, digitally advanced answer. part of this involves the implementation of SAP S/4HANA Finance, which is deployed on the SAP intelligent enterprise platform HANA, providing a groundwork to introduce desktop researching and artificial Intelligence equipment to aid the TTC enrich financial stewardship of its individuals, belongings and repair choices. Dave McCann, Canadian Public Sector chief, IBM services observed:

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software enterprise Kofax has close its acquisition of Nuance document Imaging (NDI), a division of Nuance Communications, Inc. (NasdaqGS:NUAN). With the sale of NDI to Kofax for $four hundred million, Nuance can focus the enterprise on its conversational AI- and cloud-primarily based solutions, whereas simplifying the corporation and enhancing its increase profile.

Sam Mowers, Investorideas.com

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IBM analysis Ai Hardware core to power next-era AI Chips | killexams.com Real Questions and Pass4sure dumps

An IBM chip comprising a number of Analog AI contraptions used for in-memory computing.

today IBM introduced an ambitious plan to create a worldwide research hub to advance subsequent-technology AI hardware and expand their joint analysis efforts in nanotechnology. As part of a $three billion commitment, the IBM research AI Hardware middle may be the nucleus of a brand new ecosystem of research and commercial partners collaborating with IBM researchers to further speed up the development of AI-optimized hardware innovations.

IBM headquarters for the AI Hardware center might be on the SUNY Polytechnic campus in Albany, manhattan, and the center will increase a number of technologies from chip-degree devices, substances and architecture to the utility assisting AI workloads. These efforts will push the boundaries of chip technology essential to fulfill the emerging demands of cloud computing, large records, and cognitive computing techniques.

The groundbreaking work that these engineers will behavior at SUNY Polytechnic Institute displays IBM’s lengthy-time period commitment to inventing the future of microelectronics,” pointed out Dr. John Kelly, Senior vice president, solutions Portfolio and analysis at IBM. “The IBMers working at SUNY Poly possess entertaining talents and capabilities, positioning our enterprise to drive construction of the subsequent era of chips and to gas a new era of computing.”

IBM analysis AI Hardware core is constructing a roadmap for 1,000x improvement in AI compute efficiency efficiency over the subsequent decade, with a pipeline of Digital AI Cores and Analog AI Cores.

The $three billion funding that IBM announced in July 2014 focuses on the building of basic materials science to make it feasible to cut back semiconductors to 7 nanometers and beyond, as well as support research into absolutely new areas beyond average silicon architectures, corresponding to synaptic computing, quantum instruments, carbon nanotubes, and photonics, that may radically change computing of every kind.

Partnerships inside an open ecosystem are key to advancing hardware and application innovation that are the basis of AI. New IBM research AI Hardware center partnerships introduced these days will aid in those continuing efforts. Samsung is a strategic IBM partner in each manufacturing and research. Mellanox technologies is a number one organization of excessive-efficiency, conclusion-to-end wise interconnect options that accelerate most of the world’s main AI and computer gaining knowledge of systems. Synopsys is the leader in utility systems, emulation and prototyping options, and IP for constructing the excessive-efficiency silicon chips and at ease software applications which are driving developments in AI.

IBM analog AI cores are a part of an in-reminiscence computing method in efficiency efficiency which improves via suppressing the so-called Von Neuman bottleneck by way of disposing of information transfer to and from memory. Deep neural networks are mapped to analog pass element arrays and new non-risky fabric qualities are toggled to store network parameters in the pass aspects. find out how this technology works in our live interactive demo.

IBM and SUNY Poly have constructed a incredibly successful, globally identified partnership on the multi-billion greenback Albany NanoTech complex, highlighted via the institution’s core for Semiconductor research (CSR), a $500 million software that also contains the realm’s leading nanoelectronics corporations. The CSR is an extended-time period, multi-section, joint R&D cooperative application on future laptop chip technology. IBM changed into a founding member of Governor Andrew M. Cuomo’s international 450 Consortium. It continues to provide scholar scholarships and fellowships on the school to assist prepare the next generation of nanotechnology scientists, researchers and engineers.

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IBM cloud lands huge shoppers within the energy sector | killexams.com Real Questions and Pass4sure dumps

IBM Corp. could no longer elevate the equal sort of clout within the public cloud as competitors reminiscent of Amazon net functions Inc. and Microsoft Corp., however it’s managing to compete in certain area of interest industries the place its unique artificial intelligence and statistics analytics capabilities could make all the difference.

Such is the case with smart energy Water, which has simply agreed a multimillion-dollar deal to flow some of its most vital workloads to IBM’s cloud from one other main cloud platform. SEW, which offers client engagement, body of workers engagement and large statistics analytics services to energy and utilities companies, talked about it’s relocating to IBM’s cloud to be able to take expertise of huge Blue’s incredibly really good AI, statistics analytics and “information superhighway of issues” capabilities.

The thought is that it may tap into these features in an effort to help its consumers be sure that the energy they give is used more efficiently. To try this, SWE gives features to help businesses manipulate their energy grids more readily. It additionally sells smart meter equipment that assist consumers to hold tabs on their personal energy use extra comfortably.

IBM reckons its advantage is helpful to energy sector groups like SEW as a result of many are struggling to movement functions and workloads from on-premises environments to the clouds. That’s since the power business is among the most heavily regulated on the planet, and most corporations effectively don’t recognize where to begin, it talked about.

IBM’s claims are backed through the gigantic number of power organisations with which it has these days partnered. for example, it’s working with TenneT protecting B.V.’s subsidiary TenneT energy, which offers power to valued clientele in Germany and the Netherlands. IBM is helping TenneT to build a blockchain platform on its cloud that should be capable of control the company’s electrical energy grid extra conveniently, assisting it to in the reduction of the charge of providing power from fluctuating renewable energy sources.

different IBM partners in the energy business encompass Ista UK options Ltd., which makes use of its cloud to host an interactive power metering and billing platform. There’s additionally Hydro Ottawa maintaining Inc., which relied on IBM’s skills to abide by industry laws when migrating to its cloud platform.

to date this yr, IBM has signed more than $three billion value of latest cloud contracts, including new valued clientele corresponding to BNP Paribas S.A., Juniper Networks Inc. and the financial institution of the Philippine Islands.

photo: SEW/facebook since you’re right here …

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Intel Advances Next Phase of Big Data Intelligence: Real Time Analytics | killexams.com real questions and Pass4sure dumps

SANTA CLARA, Calif.--(BUSINESS WIRE)--To help companies in a variety of industries from retail and healthcare to banking and transportation turn data into actionable insights, Intel Corporation today introduced the Intel® Xeon® processor E7 v2 family.

Using analytics enables businesses to make decisions that improve top-line and bottom-line results. The Intel Xeon processor E7 v2 family delivers new capabilities to process and analyze large, diverse amounts of data to unlock information that was previously inaccessible.

“Organizations that leverage data to accelerate business insights will have a tremendous edge in this economy,” said Diane Bryant, senior vice president and general manager of Intel’s Data Center Group. “The advanced performance, memory capacity and reliability of the Intel Xeon processor E7 v2 family enable IT organizations to deliver real-time analysis of large data sets to spot and capitalize on trends, create new services and deliver business efficiency.”

Big data and the Internet of Things (IoT) are providing enormous opportunities for many organizations to grow as they create revenue-generating services from the information they are able to derive. The big data technology and services market is expected to grow 27 percent annually through 2017 to reach $32.4 billion4. A leading driver of this growth is the immense amount of data coming from connected devices making up the IoT, which is projected to grow to 30 billion devices by 20205. Investments in the highest performing technologies and analysis solutions can also deliver significant cost savings. For example, Intel’s IT organization expects to achieve cost savings and increased bottom-line revenue of nearly half a billion dollars through use of analytics solutions by 2016.

New Big Data Processing and Analytics Capabilities with Relentless Reliability

The Intel Xeon processor E7 v2 family has triple the memory capacity of the previous generation processor family, allowing much faster and thorough data analysis. In-memory analytics places and analyzes an entire data set – such as an organization’s entire customer database – in the system memory rather than on traditional disk drives. This method is gaining in popularity due to the increased need for more complex analytics. Industry analyst firm Gartner expects 35 percent6 of mid- to large-sized companies will adopt in-memory analytics by 2015, up from 10 percent in 2012 and predicts at least 50 percent of Global 2000 companies will use in-memory computing to deliver significant additional benefits from investments in enterprise resource planning (ERP).

eBay, one of the world's largest and most complex online marketplaces, handles massive data sets of more than 50 petabytes (PB) for more than 100 million users. Based on initial testing of the new Intel Xeon processor E7 v2 and SAP’s HANA* in-memory analytics software, eBay has seen greater performance7 and understanding of larger data sets that will help drive additional revenue opportunities for its customers.

Built for up to 32-socket8 servers, with configurations supporting up to 15 processing cores and up to 1.5 terabytes (TB) of memory per socket, the new processor family achieves twice the average performance of the previous generation3. These enhancements help businesses that run mission critical applications including business support systems (BSS), customer relationship management (CRM), and ERP to operate more efficiently, at lower cost and with faster response times2. For example, a sales team with these capabilities can maximize revenue by pinpointing the best time to sell a product, or let an oil and gas company better predict when its platforms require preventative maintenance.

To reduce data bottlenecks, the Intel Xeon Processor E7 v2 family features Intel® Integrated I/O, Intel® Data Direct I/O and support for PCIe 3.0*, achieving up to four times the I/O bandwidth over the previous generation9 and providing extra capacity for storage and networking connections.

System uptime and reliability also remains a key requirement for mission critical applications. The Intel Xeon Processor E7 v2 family continues Intel’s tradition of delivering world-class reliability, availability and serviceability (RAS). Intel® Run Sure Technology10 is designed for “five nines” solutions essential for business-critical data by reducing the frequency and cost of planned and unplanned downtime.

Extensive Industry Support

Starting today, 21 system manufacturers from around the world will announce more than 40 Intel Xeon processor E7 v2 family-based platforms. These manufacturers include Asus*, Bull*, Cisco*, Dell*, EMC*, Fujitsu*, Hitachi*, HP*, Huawei*, IBM*, Inspur*, Lenovo*, NEC*, Oracle*, PowerLeader*, Quanta*, SGI*, Sugon*, Supermicro*, Unisys* and ZTE*. Numerous analytics software vendors also support Xeon processor E7 v2 family-based platforms, including Altibase*, IBM*, Microsoft*, Oracle*, Pivotal*, QlikView*, Red Hat*, SAP*, SAS*, Software AG*, Splunk*, Sungard*, Teradata*, TongTech*, Vertica* and YonYou*.

About Intel

Intel (NASDAQ: INTC) is a world leader in computing innovation. The company designs and builds the essential technologies that serve as the foundation for the world’s computing devices. Additional information about Intel is available at newsroom.intel.com and blogs.intel.com.

Intel, Intel logo and Intel Xeon are trademarks of Intel Corporation in the United States and other countries.

*Other names and brands may be claimed as the property of others.

Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products.

Results have been measured by Intel based on software, benchmark or other data of third parties and are provided for informational purposes only. Any difference in system hardware or software design or configuration may affect actual performance. Intel does not control or audit the design or implementation of third party data referenced in this document. Intel encourages all of its customers to visit the websites of the referenced third parties or other sources to confirm whether the referenced data is accurate and reflects performance of systems available for purchase.

The TCO or other cost reduction scenarios described in this document are intended to enable you to get a better understanding of how the purchase of a given Intel product, combined with a number of situation-specific variables, might affect your future cost and savings. Nothing in this document should be interpreted as either a promise of or contract for a given level of costs.

1. Intel Xeon processor E7 v2 family provides the largest memory footprint of 1.5 TB per socket vs 1TB per socket delivered by alternative architectures, based on published specs.

2. Up to 80% leadership performance on Xeon E7 v2 over IBM Power* 7+ at ~80% lower TCO claim based on Intel estimated SPECint*_rate_base2006 results and pricing of comparable 4-socket rack server using Intel® Xeon® processor E7-4890 v2 (37.5M Cache, 2.8 GHz, 15-Cores) to IBM POWER*750 using POWER7+ (80M Cache, 4.0 GHz, 8-Cores) as of December 2013.

3. Up to double the average generational performance based on results of six key industry-standard workloads: SPECint*_rate_base2006+, SPECfp*_rate_base2006+, brokerage on-line transaction processing (OLTP) database workload, warehouse supply chain OLTP database workload, STREAM memory bandwidth and LINPACK GFLOPS. Configurations: 4-socket server using Intel® Xeon® processor E7-4890 v2 (new processor) vs. E7-4870 (previous generation processor). Learn more about Xeon E7 v2 performance at http://www.intel.com/content/www/us/en/benchmarks/server/xeon-e7-summary.html

4. Source: IDC WW Big Data Technology and Services 2013-2017 Forecast, Doc #244979, Dec 2013

5. Source: IDC Market Analysis Perspective: Worldwide Enterprise Servers, 2013 — Technology Market, Doc #245080

6. Source: Gartner "Top Technology Trends, 2013: In-Memory Computing Aims at Mainstream Adoption"

7. eBay’s test systems configurations are not disclosed but the observed results are consistent with Intel’s internal measurements from November 2013 showing 2x performance increase when using SAP HANA based on these configurations:Baseline 1.0x: Intel E7505 Chipset using four Intel Xeon processors E7-4870 (4P/10C/20T, 2.4GHz) with 256GB DDR3-1066 memory scoring 110,061 queries per hour. Source: Intel Technical Report #1347.New Generation 2x: Intel C606J Chipset using four Intel Xeon processors E7-4890 v2 (4P/15C/30T, 2.8GHz) with 512GB DDR3-1333 (running 2:1 VMSE) memory scoring 218,406 queries per hour. Source: Intel Technical Report #1347.

8. Requires node controller (available from 3rd party sources).

9. Up to 4X I/O bandwidth claim is based on Intel estimates on an internal bandwidth tool running the 1R1W test of the Intel Xeon processor E7-4890 v2 performance normalized against the improvements over dual-IOH Intel Xeon processor E7-4870.

10. No computer system can provide absolute reliability, availability or serviceability. Requires an Intel® Xeon® processor E7-8800/4800/2800 v2 product families or Intel® Itanium® 9500 series-based system (or follow-on generations of either). Built-in reliability features available on select Intel® processors may require additional software, hardware, services and/or an internet connection. Results may vary depending upon configuration. Consult your system manufacturer for more details.


IBM: 2 Important Verticals To Watch | killexams.com real questions and Pass4sure dumps

No result found, try new keyword!In 2012, the company made it clear it wants to focus on high value segments with fatter profit margins and earn 50% of sales from ... that deal with Big Data and are paranoid about data security. Runn...

Zacks Investment Ideas feature highlights: Microsoft, Amazon, IBM, NVIDIA and Salesforce.com | killexams.com real questions and Pass4sure dumps

For Immediate Release

Chicago, IL – March 10, 2017 – Today, Zacks Investment Ideas feature highlights Features: Microsoft (NASDAQ: MSFT – Free Report ), Amazon ( NASDAQ: AMZN – Free Report ) , IBM (NYSE: IBM – Free Report ), NVIDIA (NASDAQ: NVDA – Free Report ) and Salesforce.com ( NYSE: CRM – Free Report ) .

A.I. Deep Dive: NVIDIA, IBM and salesforce.com

Last June I wrote a special report for Zacks Confidential called "Big Economic Disruption: Big Data, AI, and Robotics."

While researching and talking about science-fiction technologies like machine learning and artificial intelligence is always fun, I began that report with a more important and sobering premise: why tens of millions of jobs globally were about to be eliminated in the next decade.

This assertion came from research published in January of 2016 by Citi and the Oxford Martin School exploring the varying impact that automation would have on jobs and economies in major countries around the world.

Here's what I wrote last June...

Technology at Work v2.0: The Future Is Not What It Used to Be builds on 2013 research by Carl Benedikt Frey and Michael Osborne which found that 47 per cent of US jobs were at risk of automation over the next two decades.

The 156-page report provides in-depth analysis of the vulnerabilities of countries and cities to job automation, explores what automation will mean for traditional models of economic growth, and considers how governments can prepare for the potentially disruptive impacts of job automation on society.

Key areas of analysis in the new report include this startling projection right at the outset:

Risks of job automation in emerging economies such as China and India are as high as 77% and 69% over the next two decades.

That's a lot of emerging markets workers put out of work in a fairly short time.

And it challenges what I had long believed: that China and India would make steady progress in their efforts to bring over 1 billion people collectively into the ranks of the global middle class.

That assumption was based on the efficient ability and desire of corporations to move manufacturing and service jobs to those countries and thereby balance the global market for goods and labor with the most cost-efficient choices available.

But the reality is that automation trends -- broadly defined as those involving cloud computing, business intelligence (Big Data analytics), artificial intelligence, and robotics -- will create far more disruption for capital and labor sources than most are imagining.

It's not just about the select company going out of business because a new technology or software solution -- like 3-D "printed" parts -- just replaced what their 50 employees did for far less money. It's about entire industries getting turned inside-out. In short, the industrial revolutions of China and India could be over sooner than many would like.

Here's how the Citi-Oxford report summed it up...

"While manufacturing productivity has traditionally enabled developing countries to close the gap with richer countries, automation is likely to impact negatively on their ability to do this, and new growth models will be required.

"The impact of automation may be more disruptive for developing countries, due to lower levels of consumer demand and limited social safety nets. With automation and developments in 3D printing likely to drive companies to move manufacturing closer to home, developing countries risk ‘premature de-industrialisation.’

"Digital industries have not created many new jobs. Since 2000, just 0.5% of the US workforce has shifted into new technology industries, most of which are directly associated with digital technologies."

This amount of disruption should not be taken lightly. Massive changes are coming to industry that will have deep impacts for economies and workers.

I think every citizen should be studying these changes and impacts on an ongoing basis to find the best ways to position their career, their business, and their investments.

(end of excerpt from my June Zacks Confidential report)

That report ended, as all ZCs do, with actionable investment ideas.

Tasked to answer the question "How does one invest to capitalize on these megatrends?" I came up with 4 stocks you had to own for the long term.

Here's how I answered...

So this brings me back to my top 4 picks for the future of work. And they will all be involved in robotics and additive manufacturing (3-D "printing") in some form, whether providing the software to design, build, and operate the machines, or the cloud-AI-machine learning data to drive their "intelligence."

1) Microsoft (NASDAQ: MSFT – Free Report ) : I believe buying this stock near $50 virtually guarantees a chance to beat the market over the next 5-10 years. Stifel Nicolaus analysts recently met with Microsoft management to talk about cloud and BI initiatives. Here's what they said: "The meetings served to reinforce our view the company's commercial cloud strategy is on track to hit the $20B FY18 goal and should be a source of solid growth for the next several years. Azure (the BigData platform) should also continue to close the gap with AWS as Microsoft expands its product offering and is able to exploit its existing customer relationships to create unique hybrid scenarios." They maintain a $58 12-month price target on MSFT shares.

2) Amazon (NASDAQ: AMZN – Free Report ) : Much like Page, Jeff Bezos has a vision of the future and find ways to be a part of it. It's no wonder both of them are involved in space rocketry too. But Bezos is more practical, ensuring steady sales. He is credited with once saying something to this effect: "Everybody wants to focus on how the future will be different. We try to ask 'How will it be the same?' and then those are the businesses we want to be in."

4) IBM (NYSE: IBM – Free Report ) is relevant and affordable again near $150 (11X next year's $13.75 EPS). Their powerful Watson Cognitive Analytics platform is appealing to many industries at the enterprise level, from medical research and diagnostics to manufacturing and marketing predictive capabilities. And they did a beautiful thing by putting a "human" voice on Watson to attract the interest and fascination of young people everywhere in the power of data. It's their future after all.

I recommended IBM shares in 2010 as the "safe" big cap Tech stock to outperform the market over 3 years and it did just that, rising from $125 to over $200 in 2013, with Warren Buffett joining the party at $175 as he finally found a Tech stock he could love. My buy then was based on their European contracts in the "smart energy grid" which I believed carried lower risk than most businesses since they were serving, and embedded in, the infrastructure of municipal power.

IBM will find a way to "embed" Watson in the Business Intelligence and cognitive/predictive analytics of many corporations who will come to depend on their superior commitment to data science R&D. Hopefully, they can use Watson to redesign the IBM corporate strategy for lower costs and higher sales and remain relevant to investors for another 50 years.

And here was their performance from June 6 up to the election, and since:

MSFT: +16.3% to the election and +7.4% since

GOOGL: +11.2% to the election and +5.2% since

AMZN: +8.4% to the election and +7.96% since

IBM: +1.6% to the election and +15.65% since

S&P 500: +12% from June 6 to March 9,2017

It's nice to see that you would have done nearly as well owning IBM as GOOGL or AMZN in this full period since June 6. And nothing has changed in my view about any of these stocks, although I would wait for pullbacks in all of them before initiating new positions. (I've had a bet since the beginning of the year with another investor about whether GOOGL or AMZN gets to $1,000 first. They've been trading neck-and-neck around $850 and my money is on the latter.)

But I am adding 2 more stocks to the mix. And, beyond fascinating, both of them have partnered with IBM since my original thesis.

The NVIDIA Connection

I am going to try and tell you this important story without mentioning those fancy action games my son plays till all hours. I hearNVIDIA (NASDAQ: NVDA – Free Report ) makes chips and graphics solutions that satisfy a gamer's "need for speed" (and parallel processing) too. But this story will be about the technology applied to more important tasks.

In September, NVIDIA joined forces with IBM to launch a new type of server built for machine learning based on NVIDIA's GPU semiconductor solutions. This is not a new partnership as the companies had been working together for several years and you can get some background from this 2014 NVIDIA blog post...

Story continues

NVIDIA and IBM Bring Supercomputing to Big Data Analytics

GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate deep learning, analytics, and engineering applications. From the NVIDIA website, a crystal clear explanation...

"A simple way to understand the difference between a GPU and a CPU is to compare how they process tasks. A CPU consists of a few cores optimized for sequential serial processing while a GPU has a massively parallel architecture consisting of thousands of smaller, more efficient cores designed for handling multiple tasks simultaneously."

Massively Parallel Architecture (MPA)

Yeah, that's what is needed to do machine learning and anything close to artificial intelligence.

In the early 1990's I read a book by physicist Heinz Pagels called The Dreams of Reason: The Computer and the Rise of the Sciences of Complexity. His understanding of how "big data" crunching would change both science and business was powerfully prescient nearly 30 years ago (published in 1988).

As chip innovations shrunk computing power into ever smaller machines, amazing tasks suddenly became affordable to average researchers, technologists and nerds in general. Heinz wasn't predicting which companies would make money off of this trend. But he knew it would have large impacts on society, science, and commerce.

It was in his book that I first learned about "parallel processing" that makes so much technology possible today. IBM has been playing with the "massively" component for a while, ala Deep Blue, the world's top chess computer. NVIDIA has taken it to new levels since 2007. Together, they are a force.

Here was Ian Buck writing on the NVIDIA blog on September 8, 2016 about the new venture with IBM...

Data center workloads are changing. Not long ago these systems were primarily used to handle storage and serve up web pages, but now they’re increasingly tasked with AI workloads like understanding speech, text, images and video or analyzing big data for insights.

Billions of consumers want instant answers to a multitude of questions, while enterprise companies want to analyze mountains of data to better serve their customers’ needs. Where do those answers come from? Data centers.

As a leader in server systems, IBM saw this trend coming several years ago, and partnered with us to accelerate new data center workloads. After four years of development, IBM today introduced its Power System S822LC for High Performance Computing powered by NVIDIA Tesla P100 GPUs and NVLink to facilitate high-performance analytics and enable deep learning on ever increasing mountains of data.

The system couples two of IBM’s POWER8 CPUs with four NVIDIA Tesla P100 GPUs connected via our NVLink high-speed interface. This is a custom-built GPU accelerator server, where the NVLink interface is routed on the motherboard and uses our Tesla P100 SXM2 GPU.

This tight coupling of IBM and NVIDIA technology enables data to flow 5x faster than over PCIe, accelerating time to insight for many of today’s most critical applications, like advanced analytics, deep learning and AI.

“The user insights and the business value you can deliver with advanced analytics, machine learning and artificial intelligence is increasingly gated by performance,” says Doug Balog, general manager of IBM Power Systems. “Accelerated computing that can really drive big data workloads will become foundational in the cognitive era. Based on OpenPOWER innovations from partners such as NVIDIA, our new OpenPOWER Linux servers with POWERAccel set a new standard for these workloads.”

And the two companies followed-up this powerful coup against Intel's X86 line of core processors with this news release on November 14...

IBM and NVIDIA Team Up on World’s Fastest Deep Learning Enterprise Solution

Michael Feldman, writing for the Top500.org, summed up the news this way...

"IT soul mates IBM and NVIDIA are at it again, this time collaborating on a deep learning (DL) toolkit, known as PowerAI, optimized for IBM’s Power S822LC for High Performance Computing platform. The integration of the toolkit and the IBM hardware is being aimed at what NVIDIA and IBM believe to be a burgeoning market in enterprise AI."

GPU accelerators now powering energy-efficient data centers in government labs, universities, enterprises, and small-and-medium businesses around the world. They play a huge role in accelerating applications in platforms ranging from artificial intelligence to cars, drones, and robots.

And the IBM-NVIDIA tag-team will be a powerful alliance in these computing markets.

See? I did it. Got through that whole story without mentioning that questionable use of time ("video games") at all. Except just there.

The Salesforce Connection

Last month, I wrote another Zacks Confidential about software. This one was titled "The SaaSy Nature of the Global Economy." My thesis was that software innovations were often the best indicators of trends in business because after the game-changing smartphone, the explosion of the app universe kept creating new categories of services and entirely new business models (Uber, Airbnb, Snapchat, etc) that required ever-further innovations in software.

My top stock pick for that report was Salesforce.com (NYSE: CRM – Free Report ) . Here's what I said...

The $57 billion giant of customer engagement software is certainly not a takeover candidate -- but then who thought LinkedIn was either? In either case, CRM is still seen as the preeminent leader in the industry, both by Wall Street analysts and research firm Gartner.

The stock is expensive on a P/E basis but I expect innovations in this space to come from CRM at the expense of the competition as they "stack" features and value for their corporate clients. The average price target on the Street is $93, while Goldman Sachs bumped theirs higher to $96 at the start of February.

CRM reports on Tuesday 2/28 and I would buy this Zacks #2 Rank on any weakness in the $70s.

I barely mentioned the company's latest innovation, Einstein, because I didn't fully understand it yet. It was only formally launched in late February.

I also made a video where I briefly explained the high-level feud between CRM and MSFT, especially after LNKD: SaaSy B2B Sales Are in the Clouds.

I bought CRM shares last week for the Zacks TAZR Trader service after another strong earnings report and guidance on February 28. Two years ago, CEO Marc Benioff was boasting about having become the fastest “software” company to $6 billion in revenue, and set on becoming the fastest to $10 billion.

Given that 2016 closed with $8.4 billion -- 26% annual growth -- and they are guiding the current fiscal year to $10.2 billion (+21% annual growth), it seems they are on their way.

During the company's October analyst day, Salesforce updated the size of its TAM (total addressable market) to about $70 billion in 2016 and projected a CAGR of 11 percent to reach $105 billion by 2020. They have plenty of potential to grab more of that market share.

And while the valuation is a headwind for the stock -- trading at over 6X sales -- the premier position in enterprise CRM is undisputed. If anybody can grab more of that TAM, it's CRM.

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