Software Licensing & Master Service Agreements : Chicago Software Licensing Lawyer & Attorney : Sam Conforti Law Firm : Master Service Agreements, Negotiations, Outsourcing : Cook County, Illinois

The hottest topic of the day is Data Mining. Unless you have been in a coma for the last few days, it has come to light that our government is involved in this activity. I staunchly try to stay away from any discussion about politics in this Blog and will do so here. However, as my readers know, I am a man who needs to have things defined. Once I know what I am dealing with, then I, and in this case the readers of this Blog, can make an informed decision.

In my research I was able to find a White Paper on the subject simply entitled Data Mining: What is Data Mining? The White Paper is somewhat technical in nature, but it does have the definitions that we need to get a foothold on the topic and it also has some good examples to help our understanding. In the spirit of Full Disclosure the author of this White Paper is not listed. Because we are dealing with definitions it is somewhat difficult to characterize these definitions in any words other than those in the White Paper. I will cut and paste these definitions and what I feel are the salient points from the White Paper into this posting. Therefore, the bulk of the remainder of this posting will be directly from the White Paper and not my own words. 

“Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.” Comment: It appears from this opening definition and from the examples given in this White Paper that the author is taking a business perspective on the topic. The activity of Data Mining can be applied to other activities such as those of interest to our government at the present time.

“Although data mining is a relatively new term, the technology is not. Companies have used powerful computers to sift through volumes of supermarket scanner data and analyze market research reports for years. However, continuous innovations in computer processing power, disk storage, and statistical software are dramatically increasing the accuracy of analysis while driving down the cost.” Comment: Again, this is from a business perspective. --- AND here is an application of the usefulness of this activity: For example, one Midwest grocery chain used the data mining capacity of Oracle software to analyze local buying patterns. They discovered that when men bought diapers on Thursdays and Saturdays, they also tended to buy beer. Further analysis showed that these shoppers typically did their weekly grocery shopping on Saturdays. On Thursdays, however, they only bought a few items. The retailer concluded that they purchased the beer to have it available for the upcoming weekend. The grocery chain could use this newly discovered information in various ways to increase revenue. For example, they could move the beer display closer to the diaper display. And, they could make sure beer and diapers were sold at full price on Thursdays.

Data

Data are any facts, numbers, or text that can be processed by a computer. Today, organizations are accumulating vast and growing amounts of data in different formats and different databases. This includes:

• operational or transactional data such as, sales, cost, inventory, payroll, and accounting

• nonoperational data, such as industry sales, forecast data, and macro economic data

• meta data - data about the data itself, such as logical database design or data dictionary definitions

Information

The patterns, associations, or relationships among all this data can provide information. For example, analysis of retail point of sale transaction data can yield information on which products are selling and when.

Knowledge

Information can be converted into knowledge about historical patterns and future trends. For example, summary information on retail supermarket sales can be analyzed in light of promotional efforts to provide knowledge of consumer buying behavior. Thus, a manufacturer or retailer could determine which items are most susceptible to promotional efforts.

Data Warehouses

Dramatic advances in data capture, processing power, data transmission, and storage capabilities are enabling organizations to integrate their various databases into data warehouses. Data warehousing is defined as a process of centralized data management and retrieval. Data warehousing, like data mining, is a relatively new term although the concept itself has been around for years. Data warehousing represents an ideal vision of maintaining a central repository of all organizational data. Centralization of data is needed to maximize user access and analysis. Dramatic technological advances are making this vision a reality for many companies. And, equally dramatic advances in data analysis software are allowing users to access this data freely. The data analysis software is what supports data mining. Comment: This sort of activity is what has been mentioned in the news lately.

What can data mining do?

Data mining is primarily used today by companies with a strong consumer focus - retail, financial, communication, and marketing organizations. It enables these companies to determine relationships among "internal" factors such as price, product positioning, or staff skills, and "external" factors such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction, and corporate profits. Finally, it enables them to "drill down" into summary information to view detail transactional data.

With data mining, a retailer could use point-of-sale records of customer purchases to send targeted promotions based on an individual's purchase history. By mining demographic data from comment or warranty cards, the retailer could develop products and promotions to appeal to specific customer segments.

For example, Blockbuster Entertainment mines its video rental history database to recommend rentals to individual customers. American Express can suggest products to its cardholders based on analysis of their monthly expenditures.

WalMart is pioneering massive data mining to transform its supplier relationships. WalMart captures point-of-sale transactions from over 2,900 stores in 6 countries and continuously transmits this data to its massive 7.5 terabyte Teradata data warehouse. WalMart allows more than 3,500 suppliers, to access data on their products and perform data analyses. These suppliers use this data to identify customer buying patterns at the store display level. They use this information to manage local store inventory and identify new merchandising opportunities. In 1995, WalMart computers processed over 1 million complex data queries.

The National Basketball Association (NBA) is exploring a data mining application that can be used in conjunction with image recordings of basketball games. The Advanced Scout software analyzes the movements of players to help coaches orchestrate plays and strategies. For example, an analysis of the play-by-play sheet of the game played between the New York Knicks and the Cleveland Cavaliers on January 6, 1995 reveals that when Mark Price played the Guard position, John Williams attempted four jump shots and made each one! Advanced Scout not only finds this pattern, but explains that it is interesting because it differs considerably from the average shooting percentage of 49.30% for the Cavaliers during that game.

By using the NBA universal clock, a coach can automatically bring up the video clips showing each of the jump shots attempted by Williams with Price on the floor, without needing to comb through hours of video footage. Those clips show a very successful pick-and-roll play in which Price draws the Knick's defense and then finds Williams for an open jump shot.

How does data mining work?

While large-scale information technology has been evolving separate transaction and analytical systems, data mining provides the link between the two. Comment: The preceding sentence is key to this activity. Data mining software analyzes relationships and patterns in stored transaction data based on open-ended user queries. Several types of analytical software are available: statistical, machine learning, and neural networks. Generally, any of four types of relationships are sought:

• Classes: Stored data is used to locate data in predetermined groups. For example, a restaurant chain could mine customer purchase data to determine when customers visit and what they typically order. This information could be used to increase traffic by having daily specials.

• Clusters: Data items are grouped according to logical relationships or consumer preferences. For example, data can be mined to identify market segments or consumer affinities.

• Associations: Data can be mined to identify associations. The beer-diaper example is an example of associative mining.

• Sequential patterns: Data is mined to anticipate behavior patterns and trends. For example, an outdoor equipment retailer could predict the likelihood of a backpack being purchased based on a consumer's purchase of sleeping bags and hiking shoes.

Data mining consists of five major elements:

• Extract, transform, and load transaction data onto the data warehouse system.

• Store and manage the data in a multidimensional database system.

• Provide data access to business analysts and information technology professionals.

• Analyze the data by application software.

• Present the data in a useful format, such as a graph or table.

Different levels of analysis are available:

• Artificial neural networks: Non-linear predictive models that learn through training and resemble biological neural networks in structure.

• Genetic algorithms: Optimization techniques that use processes such as genetic combination, mutation, and natural selection in a design based on the concepts of natural evolution.

• Decision trees: Tree-shaped structures that represent sets of decisions. These decisions generate rules for the classification of a dataset. Specific decision tree methods include Classification and Regression Trees (CART) and Chi Square Automatic Interaction Detection (CHAID) . CART and CHAID are decision tree techniques used for classification of a dataset. They provide a set of rules that you can apply to a new (unclassified) dataset to predict which records will have a given outcome. CART segments a dataset by creating 2-way splits while CHAID segments using chi square tests to create multi-way splits. CART typically requires less data preparation than CHAID.

• Nearest neighbor method: A technique that classifies each record in a dataset based on a combination of the classes of the k record(s) most similar to it in a historical dataset (where k 1). Sometimes called the k-nearest neighbor technique.

• Rule induction: The extraction of useful if-then rules from data based on statistical significance.

• Data visualization: The visual interpretation of complex relationships in multidimensional data. Graphics tools are used to illustrate data relationships.

What technological infrastructure is required?

Today, data mining applications are available on all size systems for mainframe, client/server, and PC platforms. System prices range from several thousand dollars for the smallest applications up to $1 million a terabyte for the largest. Enterprise-wide applications generally range in size from 10 gigabytes to over 11 terabytes. NCR has the capacity to deliver applications exceeding 100 terabytes. There are two critical technological drivers:

• Size of the database: the more data being processed and maintained, the more powerful the system required.

• Query complexity: the more complex the queries and the greater the number of queries being processed, the more powerful the system required.

Relational database storage and management technology is adequate for many data mining applications less than 50 gigabytes. However, this infrastructure needs to be significantly enhanced to support larger applications. Some vendors have added extensive indexing capabilities to improve query performance. Others use new hardware architectures such as Massively Parallel Processors (MPP) to achieve order-of-magnitude improvements in query time. For example, MPP systems from NCR link hundreds of high-speed Pentium processors to achieve performance levels exceeding those of the largest supercomputers.

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This is not the usual subject matter of my postings in this Blog. However, it is indirectly related to how we all function in a work environment and how we deal with personal interactions with our colleagues and that is why I placed it in the category of “Other Interesting Items”. 

“In 2011, salaries for the 200 top-paid CEOs rose 5 percent to a median $14.5 million per year, according to a study by compensation-data company Equilar.”

I was very intrigued by the article in The Huffington Post by Glenn Llopis entitled “The Most Successful Leaders Do 15 Things Automatically, Every Day”. I have owned a couple of businesses and had employees. I was interested to read when some of my actions and philosophy matched the author’s defined traits. I have carried over my Traits into my current position and use them in my negotiations with opposing counsel(s). 

In the introduction the author seems to be saying that Leaders are made and not born, in other words the identified traits of Leaders are an amalgam of that person’s life experiences. These life experiences eventually become so inculcated into that person’s decision making process that huge and very sensitive decisions that would cause most of us great difficulty can be made rapidly and on a daily basis. Llopis explains this is why most Leaders are comfortable going with their “gut-feel” when deciding complex issues. I still think there is a certain innate ability as part of this decision making process. You decide. Here are the 15 Traits with some brief commentary from me:

1.       Make Others Feel Safe to Speak-Up: Intimidation does not work. Be able to tap into the ideas of others.

2.       Make decisions: I’ve been in meetings where the discussions go on for hours but nothing gets decided. This breaks the rhythm of the enterprise and the frustration factor grows exponentially.

3.       Communicate Expectations: When you set expectations at the outset that are reasonable and achievable and remind others of these expectations periodically, things get done.

4.       Challenge People to Think: Once you learn your colleagues capabilities you can encourage them (not push them) to go a little further. I’ve always said that once a person becomes “comfortable” in business then it is just a matter of time when that complacency becomes counter-productive.

5.       Be Accountable to Others: The author explains that this is not succumbing to others, but rather having the ability to show that you are concerned with their success as well as your own.

6.       Lead by Example: This I think is self-explanatory.

7.       Measure and Reward Performance: Never take consistent performers for granted.

8.       Provide Continuous Feedback: And making it reciprocal builds trust.

9.       Properly Allocate and Deploy Talent: Delegation of duties should be your mantra.

10.   Ask Questions and Seek Counsel: ALL THE TIME.

11.   Avoid Procrastination: See bullet #2 above.

12.   Positive Energy and Attitude:  Set the right tone and you will motivate people.

13.   Be a Great Teacher: I love this one --- full disclosure --- I was an Assistant Professor in my younger days.

14.   Invest in Relationships: Don’t be territorial. Open up to others and seek out people that can broaden your perspective.

15.   Genuinely Enjoy Responsibilities: Not for the power, but rather for the meaningful and purposeful impact you can have on others. Serve others ….

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Confidentiality is one of the key items negotiated in Contracts dealing with Software Licensing, and the Consulting Services necessary to implement the software package, and any Outsourcing or Hosting arrangements that may also be desired. Both parties, the Licensor and the Licensee, have valuable information that each wish to be kept secret and yet must be shared in order to go forward with the deal. In fact the sales cycle should begin with a signed Confidentiality Agreement. One might assume that this is furnished by the vendor, and in many cases that is correct. However, I have been involved in many negotiations with buyers big and small who provide their own version of their Confidentiality Agreement. The areas of concern for both parties are many and include such issues as reverse engineering, trade secrets, research, development, business activities, customer lists, products, services, technical knowledge, written or descriptive material, drawings, videotapes, operational data, blueprints, descriptions, or other papers or documents and any derivative works created from the confidential information disclosed.

These Confidentiality Agreements, also known as Nondisclosure Agreements, contain language describing what confidential and/or proprietary information will not fall under the terms of the Agreement, such as information already known to the receiving party or information already in the public domain. Disclosure by a valid court order is also allowed. And usually the parties agree that any violation of the restrictions on disclosure would cause the other party irreparable injury and thus allows such party to seek an injunction to prevent such release.

As our society and technology has advanced and methods of accessing such information have emerged, other issues in need of secrecy have developed such as HIPAA requirements and other Non-Public Personal Information, such as social security numbers, compensation, and drug testing results. As a practitioneer, I have had to deal with these issues and concerns as they developed and were presented for negotiation and also need to keep abreast of all new issues as our society and technology progress.

From time to time some of my readers have sent to me articles they have written and consider relevent to the stated purposes and goals of this blog. One such person, Gillian Holmes, has contacted me and pointed out a extremely important and relevent article in BACKGROUNDCHECK.ORG entitled “The Legislation of Privacy: New Laws That Will Change Your Life”.  The article is current and provides the reader a list of the new Privacy Laws that we as practitioneers and also US Citizens need to be made aware. The layout of the article is well done. There is a brief synopsis of the new law, its name, and legislative sponsor. This description is followed by two brief subsections; one entitled “How It will Affect You” (this is self-explanatory), and the second is entitled “Timeline” and lays out when the new law was passed or when it is expected to become law. In addition to a DIGITAL COMMERCE section with pertinent legislation for the purposes of this Blog, such as:

·         A bill of rights for consumers and a report entitled, “Consumer Data Privacy in a Networked World: A Framework for Protecting Privacy and Promoting Innovation in the Global Digital Economy”,

·         The GPS Act providing guidelines to when and how geolocation information can be accessed and used, and

·         Cyber intelligence Sharing and Protection Act (“CISPA”), and

·         The newly updated HIPAA entitled “Health Information Technology for Economic and  Clinical Health” (“HITECH”)

This article also includes information on:

·         Online predators with “The Protecting Children from Internet Pornographers Act of 2011”, and

·         Amendments to COPPA “Children Online Privacy Protection Act”, and

·         “Social Media Privacy Act” which addresses privacy boundaries crossed when potential employers require applicants to turn over passwords to social media accounts.

The article seems to be thorough and one that I highly recommend to be on your must read list.

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A February 28, 2013 article in bizcloud by razavi entitled “Hosted Private Cloud Services to Surpass $24 Billion in 2016” reports on International Data Corporation’s (“IDC”) optimistic outlook for Hosted Private Cloud (“HPC”) services in the near future. IDC predicts a compounded annual growth of more than 50% for the next 5 years. IDC predicts that the coming growth of HPC will transform how IT providers for outsourcing and hosting will provide their services.

The two types of deployment models for Cloud Services are:

1.       Public Cloud:  Opened to an unrestricted number of users who share services, and

2.       Private Cloud: Where a single Enterprise has defined users restrictions on access and level of allocated resources.

HPC is a hybrid of the private cloud services model and this hybrid can be further broken down into 2 models:

1.       Dedicated Private Cloud - Focus is on the needs of one enterprise with significant customer control over the contracted resources.

2.       Virtual Private Could – Contains shared virtualized resources with a wider range of customer controls and security options.

Robert Mahowald, Research Vice President at IDC and leads the SaaS and Cloud Services practice stated, “IDC anticipates that virtual private cloud will be the predominant operational model for companies wanting to take advantage of the speed and lower capital costs associated with cloud computing …”

As current IT buyers with an aging infrastructure look to the cost savings available from the Cloud, they will recognize the need to centralize their management of their cloud capabilities. These buyers are more likely to be Virtual Private Cloud customers. Enterprises with existing outsourcing and hosted environments will be looking for relief in the asset management and operational reliability area. These enterprises will probably be the Dedicated Private Cloud purchasers. Large incumbent packaged software providers and equipment providers, global systems integrators, professional services firms, and telecommunications service providers will be the beneficiaries as the Dedicated Private Cloud grows. Conversely, a new crop of vendors will benefit if the Virtual Private Cloud becomes the dominant model as IDC predicts.

Robert Mahowald stated:

“Not even the largest technology incumbents can sustain IT market leadership without achieving leadership in cloud services. Quite simply, vendor failure in cloud services will mean stagnation. Vendors need to be doing everything they can – today – to develop a full range of competitive cloud offerings and operating models optimized around those offerings.”

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James Staten, Vice President and Principal Analyst serving Infrastructure & Operations professionals for Forrester, has written an article entitled “2013 Cloud Predictions: We’ll Finally Get Real About Cloud” . In his article he and his team state that Enterprise IT departments have finally accepted the realities of the Cloud. Enterprise use will continue to grow through 2013 as Enterprises begin budgeting for Cloud services and development of private clouds as they prepare to deploy applications in the cloud.

Staten and his team put together what they expect will happen to Cloud Computing in the coming year. Here is a very brief synopsis of their top ten predictions:

1.       Enterprises will shake the idea that all must go into the Cloud: IT professionals will get a handle on what does and what does not belong in the Cloud based on the relative stengths and weaknesses of the platforms and how they differ with traditional methods and hosting.

2.       Cloud and Mobile will become one:  Mobile applications will connect to Cloud based back-end-services and not to your datacenter. This will shield your data from the voluminous requests from mobile clients.

3.       Cloud Service Level Agreements will change: The ability to recover quickly from setbacks (i.e. resiliency) will be built into the application itself. This avoids the need to negotiate an ironclad SLA for the Cloud when such protections are only needed for specific apps.

4.       ROI from Cloud Services and Platforms requires Cost Modeling: Model the costs to the specific applications. There are Cloud-Monitoring tools available and also the vendors use cost reporting tools.

5.       Infrastructure and Operations accepts the Cloud: In-House Developers will be using the Public Cloud and Infrastructure and Operations teams will accept this fact and use it to promote better communication regarding security and oversight.

6.       Use of the Cloud for Back-up and Disaster Recovery: Cloud computing and its pay-per-use pricing model lets you pay for long-term data storage while only paying for servers when testing or declaring a disaster.

7.       Stop thinking the Cloud is a Comodity: Even though Cloud services are highly standardized they are beginning to be backed-up by different and high-end hardware. Vendors will begin to offer these choices to meet specific market demands.

8.       Amazon Web Services will begin to lose market share: Amazon’s 70% market share will begin to erode from competitors such as Microsoft, Google, and other new entrants to the market.

9.       Virtulization does not mean the Cloud: A Virtual Environment usually does not offer self-service to the developer, fully-automated provisioning, standardized services, or cost transparency. The Infrastructure and Operations teams will learn to live with both types of enviroments.

10.  Development is not different in the Cloud:  Developers will realize that the majority of languages, frameworks, and development methodologies used in the enterprise are also in use in the cloud. There are no cloud-specific or cloud-best languages

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Julie Bort has an interesting article in Business Insider entitled “This Exec Has An Outrageous Plan To Make SAP Bigger In Mobile Than Apple”. In it she interviews Sanjay Poonen, head of SAP’s mobile division and responsible for SAP’s analytics, database, and technology products. Poonen’s plan is get to 1 billion users for the SAP software in the next 2 years. You can read her interview with Poonen in her article, but here is his plan in brief:

• “SAP is revamping a lot of its enterprise apps to run on mobile devices. It particularly wants to reach field workers who never used PCs.

• SAP is building a few consumer apps, too, such as fantasy fan apps for the NFL (Jets and Giants) and the NBA.

• SAP is "eating its own dog food"—an industry expression for relying on its own software—and is one of the largest users of iPads, too. Its deployed over 14,000 iPads and lets Apple's enterprise sales group use it as a case study. SAP is also pushing its apps onto Android, too.

• Through its $155 million venture capital fund, SAP is investing in mobile startups—with a preference for startups writing mobile apps that use its Hana database, Poonen said.

• SAP is on the prowl for mobile companies to buy or partner with.

• Although mobile-app users will make up most of the half billion users it expects to grab, some of them will also come from its Web-based human-resources software, SuccessFactors, and the social tools it is baking into it.”

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In my September 25^th posting in this Blog in the article entitled “Not yet Convinced? Here is Cloud Computing 101” I mentioned a case study of a company called Box in the Harvard Business Review I had been reading. The case study touted the advantages and efficiencies that Cloud Storage can provide to a global enterprise.

Recently I came across an interview of the Box CEO, Aaron Levie, conducted by James Temple of the San Francisco Chronicle’s SFGate entitled “Box CEO on growth, rivals and the inevitable IPO”. It’s a good interview. Temple asks the right questions covering a wide range of issues and does so in a non-restrictive manner which allows Levie to expound a bit in his responses. Levie’s answers gives us a bit more insight into the workings and future plans of what is sure to be one of the leaders in this new emerging area. Here are some of the highlights:

Regarding Growth: Levie explains, that in the evolving computing world as enterprises move from on-premise systems to more on-line applications and use more products like i-Pad and other handheld devices, the need for new ways to manage content will evolve. Levie states that Box is sitting at the confluence of this evolution, and mobility, and the cloud.

How will Box differentiate itself among its competitors if storage is basically a commodity: Levie explains that he will compete with the likes of Google Drive and Apple’s iCloud by creating value on top of the storage. He explains, “As you add more content into Box, Box gets smarter about your information. We can do much better things around analyzing that content and helping you discover more relevant information.”  Box’s research and development will be targeted at allowing information sharing and collaboration thus allowing the enterprise to leverage its intellectual property.

What’s the next new thing from Box:  Levie described their customers’ needs to have their data accessible across all applications from anywhere on the globe. Customers want to avoid reproducing the same data in different environments.   Box is anticipating the “post-PC enterprise”.

Is there an IPO in the offing: Temple asked the obvious since this summer, Box closed a $125 million funding round that reportedly valued the company at $1.2 billion. Levie, the consummate CEO, handled this adroitly.

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Article in bizcloud by Razavi entitled “Cloud Maturity Study Reveals Top 10 Issues Eroding Cloud Confidence” reports on a recent study conducted by ISACA and the Cloud Security Alliance which shows what is holding back C-Level executives from adopting Cloud Computing. Razavi reports that the  business leaders in the enterprise are still not yet as sufficiently involved with Could Computing and lack the understanding of its business advantages as their technical counter-parts in the enterprise and this seems to be holding back the adoption of the cloud. Yves LeRoux, a member of CSA and the ISACA Guidance and Practices Committee stated:

“Results show that CIOs and IT management understand cloud best and are most involved in driving cloud innovation in their organizations. This limits cloud maturity and innovation since cloud continues to be viewed as a technical solution and not as a business enabler”

Here are the top 10 concerns C-Level executives have regarding the cloud. The survey ranks the confidence from 0 to 5 with 0 as least confident and 5 as most confident:

“1. Government regulations keeping pace with the market (1.80)

2. Exit strategies (1.88)

3. International data privacy (1.90)

4. Legal issues (2.15)

5. Contract lock in (2.18)

6. Data ownership and custodian responsibilities (2.18)

7. Longevity of suppliers (2.20)

8. Integration of cloud with internal systems (2.23)

9. Credibility of suppliers (2.30)

10. Testing and assurance (2.30)”

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Brian Womack reports for Bloomberg in his article entitled “Google Passes Microsoft’s Market Value as PC Loses to Web” that in the afternoon on Monday October 1, 2012 Google’s price per share equated to a Market Capitalization close to $250 Billion, surpassing Microsoft’s Market Capitalization of around $247 billion. Apple with a Market Cap north of $618 Billion still leads all technology enterprises. The current sales of Apple’s iPhones and iPads can lay claim in large part to the recent success of the company. But for the first time we have a technology company providing computing over the internet topping a software company more focused on installing software on your desktop computer. As Womack states, the rise in Google’s valuation “…reflects the ascension of the Internet as the delivery channel for more of the software and computing tasks that were once left to the Microsoft-dominated PC industry.”

Here are some of the raw facts as reported in Womack’s article:

·         Google is #1 in the US Search Market with 66%

·         Google will soon pass Facebook as the #1 outlet for advertising

·         Google is #1 in US Mobile Apps

·         Google is #1 in US in software powering smartphones (i.e. Android software) with 64% of the market.

Can Microsoft rebound? The latest commercials out there touting the late October release of the next version of Windows, state that it is “designed for touch- screen technology in tablets and will power handheld devices.”

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