By Charles King, Pund-IT, Inc.  October 17, 2018

Over the past decade or so, the IT industry has been in the thrall of what might be called the iPhone Effect, where vendors promote new technologies to consumers first, no matter how well or badly suited they are to consumer and home use cases. The strategy makes a certain sense given the impact Apple’s iPhone made—creating an essentially new market for web-enabled apps and content that eventually forced businesses to contend with mobility-obsessed employees via Bring Your Own Device (BYOD) initiatives and other efforts.

The problem is that other promising technologies have had serious problems in trying to catch the iPhone’s lightning in a bottle. So, strategies centering on consumer-focused products, like IoT (through Smart Home devices and services) and virtual reality (for home entertainment), have often faltered, sullying the reputations of the technologies and players involved. Some others—self-driving consumer cars are a good example—are growing in fits and starts, with vendors vying for position in markets that are years away from being commercially sustainable.

On the other hand, business-focused solutions leveraging many of these same technologies are proceeding apace. Industry-specific IoT and VR solutions are readily available, and autonomous systems for commercial transportation are evolving quickly. Why is that the case? Partly because enterprises are willing to invest in a new technology when they believe it can offer significant, even profound business benefits.

A good example is this week’s announcement from Intel and Rolls-Royce concerning the latter’s Ship Intelligence platforms and Intelligent Awareness System solutions for commercial shipping. The solution uses AI-enabled sensor-fusion and decision-making capabilities powered by Intel’s Xeon and 3D NAND-technologies to increase the intelligence, efficiency and safety of commercial ships. The two companies also believe that the Intelligent Awareness System will provide the foundation for future autonomous shipping systems.

Let’s consider this further. Continue reading →

By Charles King, Pund-IT, Inc.  October 17, 2018

That open technologies are still evolving and succeeding some two decades after the emergence of the pioneer Open Source Initiative and early commercial Linux distributions qualifies as, at the very least, a small miracle. Not only did open source products and standards challenge the orthodoxy of leading, seemingly indomitable vendors but many of those companies, including Microsoft, considered open source to be explicitly subversive and dangerous.

On the other hand, some vendors recognized and successfully exploited the potential value that open technologies offered to largely or entirely proprietary platforms. Those efforts were not without controversy. For example, IBM raised more than a few eyebrows by announcing that it would not just support Linux distributions but that the first platform to do so would be the company’s signature mainframe systems.

IBM’s open commitment didn’t begin and end with the mainframe. Over the past two decades, the company has continued to plow significant energy and billions of investment dollars into creating, developing and supporting a wide variety of open technology platforms and initiatives.

This week’s launch of IBM’s new AI OpenScale platform, its Multi-Cloud Manager and Security Connect services find the company breaking significant new ground while following a long familiar open technologies path. Let’s consider these new offerings and their implications for IBM and the broader market. Continue reading →

By Charles King, Pund-IT, Inc.  October 10, 2018

Strategic partnerships between IT vendors have existed for decades, and mostly followed conventional synergistic pitches: By combining the products/expertise of vendors A and B, you can get C, or even D or E.

Twenty years ago, those relationships mainly consisted of system vendors and specialty ISVs of various sizes and kinds. But the continuing rise of Intel x86-based servers changed the balance due to customers adopting Intel x86-based servers and their corresponding moves from proprietary operating environments, like HP’s HP-UX and Sun Microsystems’ Solaris to Microsoft Windows Server and Linux distributions.

Further shifts occurred with the appearance of once unimaginable (or, at least, unimaginably expensive), increasingly available and affordable technologies. Those included in-memory applications, hyperconverged infrastructure (HCI) solutions, and hybrid cloud computing operating environments, like Nutanix’s Enterprise Cloud OS.

Those changes required and inspired strategic partnerships to evolve, as well. Recent announcements by Lenovo about its longstanding relationships with Microsoft and SAP show how one vendor is pursuing those developments to its own, its partners’ and its customers’ betterment. Continue reading →

By Charles King, Pund-IT, Inc.  October 3, 2018

It’s no surprise that artificial Intelligence (AI) inspires reams of press releases and media coverage these days. The fact is that a confluence of IT trends and achievements have made AI more achievable and affordable than ever before.

At the same time, it’s wise to remember that companies’ announcements typically mirror their specific, if sometimes limited, talents and skills. So, in the case of AI, silicon vendors might focus on the importance of their products in machine learning performance. Or AI software vendors may tout the value their frameworks, algorithms and models bring to the AI table.

That’s all to the good since artificial intelligence is a very large pool with space for lots of talent. But keenly focusing on myriad, smaller elements often makes the AI market resemble the proverb of the blind men and the elephant. Do any vendors see, understand and effectively build out the bigger picture of AI? Absolutely, including IBM.

Broadly speaking, the company’s work in AI  goes back decades. But those efforts cover numerous of focus areas and specific vertical use cases. For example, IBM recently announced new Watson AI toolsets pretrained for nine industries and professions, including the Watson Decision Platform for Smarter Farms. Let’s look at that solution and consider how IBM’s work in global agriculture reflects its AI strategy and tactical plans.

Global farming – A growing concern outside and inside IBM

Before diving into the new IBM solutions, what sparked the company’s work in agriculture? As noted in a blog by Ulisses Mello, lab director, IBM Research-Brazil and Sriram Raghavan, VP of IBM Research-India & Singapore, agriculture is a $2.4 trillion industry that serves as a foundation for economies worldwide. However, it also faces significant serious issues, such as climate change, population growth and food security.

Any one of those three factors would be concerning but together they could lead to catastrophic results. Add in other uncertainties, from local and regional weather events to rapid shifts in market demand and crop prices and you can understand why agricultural players are keenly focused on protecting and improving crop yields.

IBM Watson, The Weather Company and agriculture

What can IBM do? Quite a lot, as it happens. The company’s Watson platform is the public face for decades and billions of dollars of investments in AI and advanced analytics. Following a longstanding strategy, IBM’s AI solution development focuses on practice areas that correspond with the company’s industry and market experts, including those in IBM Research.

The Watson Decision Platform for Smarter Farms also takes advantage of other IBM offerings, particularly The Weather Company assets that the company acquired in 2015 which provide access to terabytes of highly detailed, regularly updated global satellite data.

In turn, the IBM PAIRS GEOSCOPE platform is used to aggregate and analyze multi-layer geospatial-temporal data (maps, satellite, weather, drone, IoT) using machine learning and advanced analytics. Since PAIRS processes and serves as storage component in the current system, it can both store and run queries on geo-referenced data.

The Watson Decision Platform for Smarter Farms offers new APIs, including,

• Yield History and Forecast for Corn – uses big data and machine learning to predict yield for corn crops two to three months in advance with only a limited amount of data and computing power. The models can also be used to determine yields for past growing seasons, thus enhancing validation of agriculture insurance claims and risk, optimizing supply-and-demand chain logistics and predicting commodity prices.
• Disease & Pest Indicators for Corn – predicts the risks in corn production, leveraging hyper-local weather forecast details (temperature, relative humidity, precipitation, etc. from The Weather Company) and crop specific inputs (sowing date, growth stage, etc.) to model the outbreak probability of various pests and diseases.
• High Definition Normalized Difference Vegetation Index (HD-NDVI) for Crop Health Monitoring – uses geospatial and satellite data to identify crop type and crop growth stage at a high – 30 meters – resolution. The resulting insights could be used to assess crop health, determine fertilizer, pesticide and irrigation schedules, validate crop insurance clams, predict yield and reduce risk in commodity trading.
• High Definition Soil Moisture (HD-SM) – is a high resolution, real-time measurement tool that monitors soil moisture at multiple depths (up to one meter) using a combination of AI algorithms and physical models along with satellite and weather model data sets. Satellite data can be combined with terrain data (land/vegetation type, atmospheric parameters and solar radiation) to simulate changes in soil moisture.

Why Brazil and India?

Why did IBM Research teams in Brazil and India play key roles in developing the new platform? Consider that agriculture has long been a major part in Brazil’s economy, leading the country to become the largest global exporter of beef, coffee, soybeans and crop-based ethanol. With nearly 100,000,000 hectares (about 250,000,000 acres) of fertile land undeveloped – a territory larger than France and Spain combined – agriculture will remain be a critical concern for Brazil and the world.

Agriculture has been central to life in India for thousands of years and remains the country’s demographically broadest economic sector, accounting for about half of the overall workforce. Currently, India ranks second in worldwide farm outputs, with agriculture and allied areas, like fisheries and forestry accounting for 13.7% of the country’s gross domestic product (GDP). Like other populous countries in equatorial zones, India is acutely aware of and concerned with the effects of global warming on its food supply. Improving and securing crop yields is, for India, a matter of life and death.

The Smarter Farms Platform is merely one area where IBM Research professionals are bringing new ideas and capabilities to global agriculture. The team in Brazil just built a prototype, the AgroPad, which produces simple, real time soil and water chemical analysis. In India, IBM Research has developed a suite of capabilities aimed at small farmers, and is also partnering with NITI Aayog to develop an AI-based pest and disease prediction model and real-time advisory for farmers.

Final analysis

The Decision Platform for Smarter Farms and eight other sets of new APIs for IBM Watson mirrors the company’s longstanding focus on vertical industry solutions. In fact, that substantial expertise in industry use cases is one of the reasons that IBM is so a valuable resource and partner for thousands of enterprise customers.

Along with spotlighting the skills and flexibility of IBM’s Research teams, the new agriculture solutions also underscore the critical importance of these markets to multiple groups and populations, from farmers, to equipment makers to seed and chemical suppliers to wholesalers and retailers to billions of individual consumers.

Are the new solutions perfect and complete? Not by any means but they mark a promising beginning for what is likely to become a larger set of Watson AI-enabled solutions for farmers and other agriculture professionals. In addition, they highlight IBM’s ability and willingness to tackle and find solutions for big, hard, seemingly intractable problems.

That skill is part and parcel of IBM’s depth of experience and the breadth of its technology portfolio, including solutions for artificial intelligence. When it comes to AI, the company will never be lost in the dark with the blind men and the elephant. Instead, IBM sees and understands the bigger picture in full light, in ways that provide consistent, consequential value to its customers and partners.

© 2018 Pund-IT, Inc. All rights reserved.

By Charles King, Pund-IT, Inc.  September 26, 2018

There are numerous reasons for IT industry vendors’ interest in and focus on artificial intelligence (AI) solutions and services. Though it has long been a goal for scientists and engineers of every stripe, advancements in foundational technologies have finally made AI commercially viable. Equally important is how AI can complement and support the solution of increasingly complex, thorny problems, meaning that it can be applied in numerous technical, industry, workplace and consumer scenarios.

In other words, effective AI-based solutions can be developed, and there’s plenty of work to be done. While that’s great news, critical AI-related trust and transparency issues have never been more important for vendors to address or their customers to understand. That’s especially true as vendors bring new AI solutions and services on line.

Recently in New York City, IBM executives outlined the state of the company’s AI efforts, the critical roles trust and transparency play in that process and the next steps needed to bring those projects in-line with the company’s multi-cloud strategy and vision.

Following those events, IBM announced new Trust and Transparency capabilities on IBM Cloud which automatically detect bias and explain how AI makes decisions, as decisions are being made, and can be applied to models built from machine learning frameworks and AI-build environments, including IBM Watson, Tensorflow, SparkML, AWS SageMaker, and AzureML.

Let’s consider the current and future state of IBM AI, along with why the company is focusing so much attention on related trust and transparency issues and solutions.

The role of trust and transparency in AI

It’s no wonder that players from tiny start-ups to Silicon Valley’s biggest global vendors are in the AI hunt. But how, how well and how effectively they are progressing is, to be kind, more than a little erratic.

Why is that the case? In part, it’s due to the industry’s increasing reliance on specialization—on companies that focus on solving incremental pieces of far bigger puzzles. That approach makes it hard to maintain a broad view or understanding of larger challenges. It can also be difficult for individuals to fully perceive or groups to reach a consensus when critical points arise, especially when answers could impact how they conduct their work and business.

Since AI has reached just such a juncture crossing over into common use, the value of specialty vendors with a myopic market view is likely to hit some speedbumps along the way. In contrast, those whose AI efforts span a broad range of technologies and use cases are better-positioned to maintain their balance while delivering measurable value to customers.

That’s a critical point since it’s difficult to think of a time when the perceptions of and trust in technology have been at a lower ebb. From elections influenced by groups successfully gaming massive social media platforms to the continual thefts of data from banks, credit agencies and retailers to many of those same “trusted” companies sitting on the evidence of data breaches for months before finally informing their customers.

If vendors are to have any chance of success with AI, they must respect, implement and maintain trust and transparency throughout their services. In addition, they need to provide customers the necessary tools to effectively monitor the accuracy of and correct bias in AI-related processes and solutions.

AI can’t be a black box

Why are trust and transparency so important to AI? You might call it the inevitable intersection of public values and business value. Recently on CNN’s Amanpour and Co., biographer Walter Isaacson asked IBM’s CEO Ginni Rometty about controversies concerning data ownership and whether, through their inaction, companies in Silicon Valley were risking government intervention and the imposition of stringent regulations.

Rometty replied, “Look, we’re builders of this stuff. We believe in the purpose of it … to augment mankind. Ownership of data (is critical) to whether people have trust. ‘Do I have to give you my data? Do you own my data?’ Even more important is that AI is about training (computational) engines. ‘Okay, that engine got trained. Who does that engine belong to now? Did you take it to my competitor?’”

Rometty continued, “We say we can guarantee (that) the way we built it, the … data used to train this will not go to the next guy. We also said that for trust, AI can’t be a black box; it has to be explainable.”

Rometty noted that the issue crystalized in IBM’s early work on Watson AI-based healthcare solutions. When the company would make recommendations, the first questions doctors asked were, “’How did you figure that out? What data went into it? Why?’ So, we had to build (Watson) so it can answer those kinds of questions. Explainability is a really big deal. You’ve got to believe in and live those kinds of principles for people to trust you.”

Trust and transparency: The next steps to AI on IBM Cloud

How enterprises feel about the issues Rometty detailed was highlighted in the recently released IBM Institute for Business Value AI 2018 Report. While 82% of enterprises and 93% of high-performing enterprises are considering or moving ahead with AI adoption, 60% fear liability issues and 63% lack the skills to harness AI’s potential.

What IBM is doing to prevent AI solutions from turning into the “black boxes” that Rometty described was a focal point of the company’s New York events, with presentations focusing on how trust and transparency qualify as a key step on “the ladder to AI.” To that end, IBM is introducing Trust and Transparency services for AI on IBM Cloud, a new service that supports key capabilities, including:

1. Automatically detects fairness issues at runtime and explains outcomes and recommendations in business terms
2. Can be programmed to monitor unique decision factors for any workflow, enabling it to be customized for specific organizations
3. Reduces bias by automatically recommending data to add to the model to mitigate detected bias
4. Supports auditability and traceability of predictions made in production applications so records of a model’s accuracy, performance and fairness, and the lineage of the AI systems can be easily discovered and recalled for customer service, regulatory or compliance reasons.
5. Is accessed through visual dashboards, enabling users of all sorts to understand, explain and manage AI-led decisions

Beth Smith, GM of Watson AI at IBM noted, “It’s time to translate principles (of trust and transparency) into practice. We are giving new transparency and control to the businesses that use AI and face the most potential risk from any flawed decision making.” That’s a strategically sensible approach for IBM, but it’s also easy to see how the new services will benefit its customers and end users.

Why is IBM Cloud so important to this process? The company has designed its cloud platform and services to provide highly accessible and dependable support for enterprise-critical workloads. IBM has further evolved its portfolio with solutions that seamlessly access private, hybrid and public cloud (multi-cloud) assets.

The company’s new IBM Cloud Private for Data is a prime example of this. It provides a single console for managing enterprise data wherever it resides, from private clouds enterprises managed on-premises to any public cloud. As Rob Thomas, GM of the IBM Analytics organization noted in New York, Cloud Private for Data qualifies as “the gateway for all your data” and thus “is a prerequisite for AI.”

In other words, there is no better place for the company’s new Trust and Transparency capabilities to reside than IBM Cloud. As AI continues to evolve and come into greater commercial use, IBM Cloud will be central to assuring that trust and transparency remain central to the company’s solutions and services, and that Watson AI never becomes a black box.

Final analysis

Though critically important, trust and transparency were just two of the AI issues IBM focused on during events in New York. Also discussed were the practical steps required to make data ready for AI, efficiently scaling AI workloads for enterprise customers, and how the company is leveraging IBM Cloud and solutions like SPSS to deliver business value to customers.

Several of those customers took the stage during IBM’s public event – “Changing the Game and Winning with AI” – to detail how and how well the company is delivering on its promises. Taken together, these discussions described the process and steps required for the company’s AI solutions to deliver dependable, replicable results.

How important are these issues for enterprise customers? The tremendous pressure that businesses face today speaks to the need for organizations to reinvent themselves. As IBM’s Thomas said, “AI can and will make all the difference. So, not having an AI strategy in 2018 is akin to not having an Internet strategy in 2000 or a mobile strategy in 2010.” But Thomas also noted that successfully executing an AI strategy “means doing the right things that may also be the hard things.”

Ensuring trust and transparency throughout AI processes is anything but simple. That’s where an innovative vendor like IBM, whose AI efforts span a broad range of technologies and use cases, can deliver measurable, dependable value. In fact, trust and transparency qualify as a sort of canopy across IBM’s AI continuum, ensuring that its solutions and services never become an impenetrable “black box” and assuring customers that their precious data assets are properly respected and secured.

Without trust and transparency, artificial intelligence is worth little or nothing. With them, individuals and organizations, including IBM, will find the ladder to successful artificial intelligence simpler and easier to climb.

© 2018 Pund-IT, Inc. All rights reserved.

By Charles King, Pund-IT, Inc.  September 13, 2018

Strategic partnerships are common cause in the IT industry. There are numerous practical reasons for this, including the inherent complexity of modern computing solutions, and single vendors’ inability to effectively address the subtleties of myriad specific markets.

But however well-intentioned, the fact is that some of these efforts fail utterly. Why so? Some are built on faulty assumptions or are ineffectively crafted. Others founder due to the partners’ alterations in course or their inability to deal with changing circumstances.

But many strategic collaborations do succeed. Those tend to include partners that are well-matched from the get-go, that share common goals and pursue individual efforts that, paired, deliver highly synergistic results.

The strategic partnership between Lenovo and NetApp announced today at Lenovo’s Transform 2.0 conference in New York City is likely to fall into the category of successful collaborations. Let’s look at the details of the announcement and consider why the companies’ outlooks are so bright. Continue reading →

By Charles King, Pund-IT, Inc.  September 12, 2018

As I was preparing to attend VMworld 2018 a couple of weeks ago, I realized how much history the company and I share. VMware was founded the year before I became an IT industry analyst. A few months after I started that job, a pair of VMware reps on their first analyst “tour” briefed us to explain and promote the company’s technology and strategy.

Further along, I was covering EMC in 2004 when it bought VMware, a deal spearheaded by EMC CEO Joe Tucci that still qualifies as one of the tech industry’s all-time best corporate acquisitions. In 2016, I was covering both EMC and Dell when the latter announced its plans to acquire the former, along with its 85% stake in VMware.

Both VMworld 2017 and 2018 took pains to emphasize synergies between the company and its new parent but for slightly different reasons. Continue reading →

By Charles King, Pund-IT, Inc.  September 5, 2018

The Internet of Things (IoT) gets more than its fair share of media and other attention but has also tended to deliver considerably less substance to date than some vocal evangelists have promised. Why is that the case?

Two reasons spring immediately to mind. First, enterprise IoT is often unfairly saddled with the baggage of scores of so-called Smart Home consumer devices that have come and mostly gone. In fact, compelling and commercially sustainable IoT market opportunities mostly reside in vertical industry use cases.

More importantly, effective IoT solutions are far more complicated and require greater knowledge and expertise than any single vendor possesses. As a result, developing effective IoT offerings requires great technologies and integration skills, plus the ability to develop and manage relationships with partners with special expertise.

One vendor that has been able to avoid the former issue and successfully tackle the latter is Dell Technologies. Continue reading →

By Charles King, Pund-IT, Inc.  September 5, 2018

Vendors’ routes to commercial opportunities take many forms but for some markets and situations strategic partnerships make great good sense. That’s particularly true in the case of edge computing and analytics where a Tier 1 vendor provides the core infrastructure platform and components that specialist partners use as a foundation for their own software and hardware offerings.

Lenovo has long followed this strategy so the company’s new partnership with Pivot3 to develop smart city solutions comes as no surprise. However, the companies’ individual strengths and expertise suggest that their common offerings should be valuable and robust. Let’s consider that more closely. Continue reading →

By Charles King, Pund-IT, Inc.  August 29, 2018

Following Gamescom 2018 where Dell announced refreshed Alienware desktop systems and new gaming monitors, the company introduced a raft of new and updated solutions for consumers and small businesses. They include:

• Inspiron 2-in-1s with enhanced performance via Intel’s new 8th Generation Core processors, sophisticated design points and value pricing
• Dell’s first premium consumer Chromebook, a 14-inch 2-in-1 solution that combines upscale Inspiron design and features, including 8th Gen Core CPUs, with the simplicity of the Chrome OS
• XPS 13 2-in-1s with 8th Gen Core processors, plus updated XPS 13 with i3 offerings
• Vostro 5000 laptops for small businesses with Intel’s latest Core CPUs
• Dell Mobile Connect now provides enhanced support for iOS apps, texts and calls
• The Dell 27 USB-C Ultrathin monitor combines aesthetic design points with functional dependability

Pricing and availability details are available at dell.com.

Partner advancements

When considering PCs and other devices, it’s important to keep in mind how much these products depend on innovative and fruitful collaboration. Sure, PCs carry the brand and imprimatur of a primary vendor. But like other complex products, ranging from the smallest consumer electronics devices to the latest digitally-enhanced automobiles, scores of partners contribute their own efforts and innovations to the mix. Continue reading →