Now you can get your own retouch transformation — should you so choose.

A new iOS app called Facetune helps edit pictures of people’s faces. Its tools can whiten teeth, smooth wrinkles, cover blemished skin, remove red-eye, apply makeup, add or remove hair, blur background objects and change the shape of a face.

There are tons of apps to help give mobile photos more contrast or sharper focus or a sepia tone. But many of those effects tend to be oriented toward landscapes and still lifes. Facetune is all about the faces.

Released last week by a small bootstrapped Jerusalem company called Lightricks, the app is currently the No. 1 paid photo and video app in the U.S., after being featured by Apple. It costs $1.99.

I played around with Facetune a bit, and it didn’t take long to notice that a light touch goes a long way — human faces are not a very forgiving canvas. I did appreciate that within the app there are explanations for every tool, as well as an ever-present option to compare what you’re working on to the original photo.

Other apps in this category include Philips Zoom (whitening teeth) and moreBeaute2 (smoothing skin tone). Nokia also developed an app called Glam Me, specifically for enhancing self-portraits taken with its Lumia devices.

Twitter announced on Monday that it would soon kill off a few versions of its TweetDeck product in the coming weeks, ending support for the Adobe AIR, iPhone and Android clients.

It’s been the death knell many have expected, considering Twitter’s lack of pushing out updates for the three versions over the past year.

“To continue to offer a great product that addresses your unique needs, we’re going to focus our development efforts on our modern, web-based versions of TweetDeck,” the company wrote in a blog post.

Most of the efforts going forward, as Twitter has made clear, will be on the company’s other existing clients: The TweetDeck found on the Web, the Chrome-based app, the Mac client and the PC client.

Knee-jerk reaction: It’s a bummer for anyone using TweetDeck on the three platforms being killed. And it isn’t immediately clear as to why it’s happening.

But it’s there, in the blog post. Just read between the lines.

“Over the past few years, we’ve seen a steady trend towards people using TweetDeck on their computers and Twitter on their mobile devices,” the post states.

That means that — in part, at least — perhaps continuing to support the iPhone and Android versions of TweetDeck just wasn’t worth it compared to the number of people using it. Not only that, but Twitter is investing loads of time and effort into its official Twitter app for iOS and Android. It’s been pretty obvious which apps Twitter wants its users to install on their phones.

But then why kill the desktop-based AIR app? Twitter doesn’t say anything about decreased usage in the AIR version of TweetDeck, and there’s no real explanation of this in the blog post.

My best guess: To be frank, the TweetDeck Adobe AIR app just plain sucked. It required updates often and was shaky in how well it functioned even when fully up to date. It also seemed to be a major resource hog on a computer’s operating system, and it wasn’t the most stable app in terms of crashing.

So perhaps Twitter wanted to rip the Band-Aid off a crummy user experience inside another supported app, and shift its users over to the PC and Mac versions if they still want a desktop client. Twitter does, after all, want everyone who uses the company’s products to have a positive experience with them. Probably doesn’t help to have a rogue AIR app act up for some, whatever size the user base is.

Then there’s the advertising display argument, of course. Twitter could be deep-sixing its AIR, Android and iOS apps to better control the way users see Twitter’s promoted suite of ad products. Can’t say for sure either way on that one.

Whatever the case, personally I’m a bit bummed. For its many faults (and believe me, there were many), I’ve used the TweetDeck AIR app as a power user for years. It’s been the best way to keep me abreast of what’s happening on Twitter in a given moment.

But now, I’m curious to see how my transition to the desktop version of TweetDeck will be. And perhaps more importantly, how other power users will take the news.

Sergey Nivens / Shutterstock.com

But that’s not to say that Apple hasn’t been preparing — quietly as always — for the kind of eventualities that tend to crop up when hackers and other digital miscreants are taken to probing your systems for vulnerabilities.

One visible sign of that preparation can be detected in the personnel that Apple has been hiring in the area of software and system security in recent years. Apple rarely if ever comments on any but its most senior hires. Nevertheless, several names have come to light. And while Apple generally doesn’t comment to confirm or deny the role that any of these people may or may not be playing in response to the latest incident, here are some people whose job at Apple involves security.

Craig Federighi: Senior vice president for software engineering, Federighi is in charge of all aspects of Apple’s operating system software, both on the Mac and the iOS platforms, and reports directly to CEO Tim Cook. He inherited responsibility for iOS after last year’s departure of Scott Forstal. He worked at Next Computer, the company Apple acquired in 1996 that brought Steve Jobs back to Apple after more than a decade. Later, Federighi spent a decade at Ariba, including a stint as its CTO. Everyone involved in OS security, whether for the iPhone, iPad or the Mac, reports to him.

David Rice: Hired in 2011 as Apple’s global director of security, Rice is a graduate of the U.S. Naval War College and spent time at the National Security Agency. However, he’s best known for his 2007 book “Geekonomics,” in which he argued that software is a new kind of public infrastructure that when built badly amounts to a public hazard, and those who buy it become virtual crash test dummies who have to suffer with a software industry that is unaccountable for the results.

Window Snyder: Hired in 2010, Snyder lists her title as Senior Product Manager, Security and Privacy. She had previously headed up security operations at Mozilla, the open source software organization responsible for the Firefox Web browser. She has also held software security positions at Microsoft and @stake, a security firm that’s now part of Symantec. She’s listed as co-author, with Frank Swiderski, of a Microsoft-produced book called “Threat Modeling,” which focuses on looking at computer security from the point of view of an attacker.

Ivan Krstić: Hired in 2009, the Croatian-born Krstić is in charge of core OS security on the Mac. He previously ran security for the One Laptop Per Child program, where he came up with a method to secure programs in Linux called BitFrost that wrapped individual programs in their own virtual operating environments so that one couldn’t harm the other. The approach was considered so novel that some suggested incorporating it as a core feature of Linux.

Kristin Paget: Currently a Core OS Security Researcher, Paget is a Microsoft veteran who’s generally credited with “saving Windows Vista” by forcing a delay in that operating system’s release after demonstrating that it wasn’t as secure as previously thought, Paget joined Apple late last year as a Core OS security researcher. Her hiring was first reported by Wired.

Image: Sergey Nivens / Shutterstock.com

Previous investors including Atlas Venture, Flybridge Capital Partners and Menlo Ventures are back as well; DataXu has now raised $65 million.

DataXu started out in life as one of many “demand side platforms” that helped marketers place their ads in “real time” ad exchanges and took a cut of the media they bought.

Now CEO Mike Baker says the bulk of his revenues comes from software he licenses, which is supposed to let ad buyers navigate that world on their own.

DataXu’s giant round is one of many we’ve seen in the last year. Last month, for instance, ad platform AppNexus pulled down $75 million; in June, publisher platform PubMatic rounded up $45 million.

All of these companies play in different parts of the complicated ad tech landscape, but all of these big dollar bets are headed in the same direction: Their investors think they’re going to end up bulking up — via growth and M&A — and going public.

A lot of these guys have now raised so much that they don’t really have any other option. At one point investors were assuming that all sorts of acquirers would step in and snap these guys up, but aside from Google and Adobe, most would-be acquirers have sat on their checkbooks. But some optimists/bankers are hoping to entice Yahoo and/or Facebook to come to the table…

That’s dumb, says Adobe — which could make this argument about any TV ad spending. On the other hand, Adobe and the rest of the digital media business have been making that argument for a very long time, and TV ad rates keep going up.

The Los Angeles-based Rubicon Project has hired two execs to fill top spots at the digital advertising company, in what looks like preparations for an eventual public offering.

Greg Raifman, the founder, chairman and CEO of Dragon Media, will become president, reporting to Rubicon CEO and co-founder Frank Addante. And SocialVibe CEO Todd Tappin will take over in the role of COO/CFO, reporting to Raifman.

Founded in 2007 and armed with more than $50 million in funding, Rubicon is one of the larger real-time bidding platforms that allows automated buying and selling of global online ads.

“Greg and Todd are extremely intelligent and capable executives who have guided significant, publicly traded companies,” said Addante in a statement. “Both Greg and Todd have great relationships within our industry as well as on Wall Street. Their presence will enable me to focus on our overall vision and product strategy so we can take best advantage of the opportunities we see.”

Tappin is replacing Brian Barnum, who will leave the company, along with Chief Revenue Officer Nick Hulse. The pair only arrived less than two years ago, presumably to also help professionalize the organization.

In addition to the other exec moves, general counsel Victoria Von Szeliski will add the title of EVP of culture and business affairs and will also be adding 100 employees this year via organic growth and acquisition.

Rubicon said Raifman — who recently served as the executive chairman of video ad-serving company LiveRail, as well as being founding and running ad-serving pioneer Mediaplex — will “manage the day-to-day operations of the Rubicon Project as he ramps the company’s buy-side automation initiatives.”

Tappin will be in charge of Rubicon’s operating and financial plan and also lead mergers and acquisitions for the company. Before running SocialVibe, a video real-time buying startup, he was founding CFO of Overture and helped sell the search automation company to Yahoo many years ago.

The exec roundelay — a not entirely uncommon thing for Rubicon over the years — is apparently part of a larger bid to eventually IPO the company. Rubicon had also been in recent preliminary discussions with several larger companies — Yahoo and Adobe — about being acquired. The ad tech space has heated up of late, with a range of startups, such as AppNexus, Pubmatic, Turn and others, looking to gain ground, get funding or sell out.

But with a large price tag and some strong growth over the last year, along with becoming profitable, Rubicon appears to now be aiming to remain independent. Over the last few years, the company has grown its business significantly — according to comScore, Rubicon Project reached 214.2 million monthly unique users.

Whether that is enough to keep up with powerful rivals such as Google is, of course, the big question, especially as the way publishers and marketers interact with the online ad market is changing quickly.

To understand how graphs address data complexity, we need first to understand the nature of the complexity itself. In practical terms, data gets more complex as it gets bigger, more semi-structured, and more densely connected.

We all know about big data. The volume of net new data being created each year is growing exponentially — a trend that is set to continue for the foreseeable future. But increased volume isn’t the only force we have to contend with today: On top of this staggering growth in the volume of data, we are also seeing an increase in both the amount of semi-structure and the degree of connectedness present in that data.

Semi-Structure

Semi-structured data is messy data: data that doesn’t fit into a uniform, one-size-fits-all, rigid relational schema. It is characterized by the presence of sparse tables and lots of null checking logic — all of it necessary to produce a solution that is fast enough and flexible enough to deal with the vagaries of real world data.

Increased semi-structure, then, is another force with which we have to contend, besides increased data volume. As data volumes grow, we trade insight for uniformity; the more data we gather about a group of entities, the more that data is likely to be semi-structured.

Connectedness

But insight and end-user value do not simply result from ramping up volume and variation in our data. Many of the more important questions we want to ask of our data require us to understand how things are connected. Insight depends on us understanding the relationships between entities — and often, the quality of those relationships.

Here are some examples, taken from different domains, of the kinds of important questions we ask of our data:

• Which friends and colleagues do we have in common?
• What’s the quickest route between two stations on the metro?
• What do you recommend I buy based on my previous purchases?
• Which products, services and subscriptions do I have permission to access and modify? Conversely, given this particular subscription, who can modify or cancel it?
• What’s the most efficient means of delivering a parcel from A to B?
• Who has been fraudulently claiming benefits?
• Who owns all the debt? Who is most at risk of poisoning the financial markets?

To answer each of these questions, we need to understand how the entities in our domain are connected. In other words, these are graph problems.

Why are these graph problems? Because graphs are the best abstraction we have for modeling and querying connectedness. Moreover, the malleability of the graph structure makes it ideal for creating high-fidelity representations of a semi-structured domain. Traditionally relegated to the more obscure applications of computer science, graph data models are today proving to be a powerful way of modeling and interrogating a wide range of common use cases. Put simply, graphs are everywhere.

Graph Databases

Today, if you’ve got a graph data problem, you can tackle it using a graph database — an online transactional system that allows you to store, manage and query your data in the form of a graph. A graph database enables you to represent any kind of data in a highly accessible, elegant way using nodes and relationships, both of which may host properties:

• Nodes are containers for properties, which are key-value pairs that capture an entity’s attributes. In a graph model of a domain, nodes tend to be used to represent the things in the domain. The connections between these things are expressed using relationships.
• A relationship has a name and a direction, which together lend semantic clarity and context to the nodes connected by the relationship. Like nodes, relationships can also contain properties: Attaching one or more properties to a relationship allows us to weight that relationship, or describe its quality, or otherwise qualify its applicability for a particular query.

The key thing about such a model is that it makes relations first-class citizens of the data, rather than treating them as metadata. As real data points, they can be queried and understood in their variety, weight and quality: Important capabilities in a world of increasing connectedness.

Graph Databases in Practice

Today, the most innovative organizations are leveraging graph databases as a way to solve the challenges around their connected data. These include major names such as Google, Facebook, Twitter, Adobe and American Express. Graph databases are also being used by organizations in a range of fields including finance, education, web, ISV and telecom and data communications.

The following examples offer use case scenarios of graph databases in practice.

• Adobe Systems currently leverages a graph database to provide social capabilities to its Creative Cloud — a new array of services to media enthusiasts and professionals. A graph offers clear advantages in capturing Adobe’s rich data model fully, while still allowing for high performance queries that range from simple reads to advanced analytics. It also enables Adobe to store large amounts of connected data across three continents, all while maintaining high query performance.
• Europe’s No. 1 professional network, Viadeo, has integrated a graph database to store all of its users and relationships. Viadeo currently has 40 million professionals in its network and requires a solution that is easy to use and capable of handling major expansion. Upon integrating a graph model, Viadeo has accelerated its system performance by more than 200 percent.
• Telenor Group is one of the top ten wireless Telco companies in the world, and uses a graph database to manage its customer organizational structures. The ability to model and query complex data such as customer and account structures with high performance has proven to be critical to Telenor’s ongoing success.

An access control graph. Telenor uses a similar data model to manage products and subscriptions.

• Deutsche Telekom leverages a graph database for its highly scalable social soccer fan website attracting tens of thousands of visitors during each soccer match, where it provides painless data modeling, seamless data model extendibility, and high performance and reliability.
• Squidoo is the popular social publishing platform where users share their passions. They recently created a product called Postcards, which are single-page, beautifully designed recommendations of books, movies, music albums, quotes and other products and media types. A graph database ensures that users have an awesome experience as it provides a primary data store for the Postcards taxonomy and the recommendation engine for what people should be doing next.

Such examples prove the pervasiveness of connections within data and the power of a graph model to optimally map relationships. A graph database allows you to further query and analyze such connections to provide greater insight and end-user value. In short, graphs are poised to deliver true competitive advantage by offering deeper perspective into data as well as a new framework to power today’s revolutionary applications.

A New Way of Thinking

Graphs are a new way of thinking for explicitly modeling the factors that make today’s big data so complex: Semi-structure and connectedness. As more and more organizations recognize the value of modeling data with a graph, they are turning to the use of graph databases to extend this powerful modeling capability to the storage and querying of complex, densely connected structures. The result is the opening up of new opportunities for generating critical insight and end-user value, which can make all the difference in keeping up with today’s competitive business environment.

Emil is the founder of the Neo4j open source graph database project, which is the most widely deployed graph database in the world. As a life-long compulsive programmer who started his first free software project in 1994, Emil has with horror witnessed his recent degradation into a VC-backed powerpoint engineer. As the CEO of Neo4j’s commercial sponsor Neo Technology, Emil is now mainly focused on spreading the word about the powers of graphs and preaching the demise of tabular solutions everywhere. Emil presents regularly at conferences such as JAOO, JavaOne, QCon and OSCON.

“Behance will play a key role in Adobe’s efforts to serve the creative world in the years to come and will accelerate our efforts to enable a more open and collaborative creative community,” said David Wadhwani, general manager at Adobe.

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The list of licensees for the patents is a dozen-long and includes not only Apple Inc. and Google Inc., but also Facebook Inc., Amazon.com Inc. and China’s Huawei Technologies.

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Marc Benioff, who is famous for declaring that “Software Is Dead,” may face a similar fate with his recent bets on Buddy Media and Radian6. These applications provide data to people who must then analyze, prioritize and act — often at a pace much slower than the digital world. Data, content and platform insights are too massive for mere mortals to handle without costing a fortune. Solutions that leverage big data are poised to win — freeing up people to do the strategy and content creation that is best done by humans, not machines.

Big data is too big for humans to work with, at least in the all-important analytical construct of responding to opportunities in real time — formulating efficient and timely responses to opportunities generated from your marketing cloud, or pursuing the never-ending quest for perfecting search engine optimization (SEO) and search engine marketing (SEM). The volume, velocity and veracity of raw, unstructured data is overwhelming. Big data pioneers such as Facebook and eBay have moved to massive Hadoop clusters to process their petabytes of information.

In recent years, we’ve gone from analyzing megabytes of data to working with gigabytes, and then terabytes, and then petabytes and exabytes, and beyond. Two years ago, James Rogers, writing in The Street, wrote: “It’s estimated that 1 Petabyte is equal to 20 million four-door filing cabinets full of text.” We’ve become jaded to seeing such figures. But 20 million filing cabinets? If those filing cabinets were a standard 15 inches wide, you could line them up, side by side, all the way from Seattle to New York — and back again. One would need a lot of coffee to peruse so much information, one cabinet at a time. And, a lot of marketing staff.

Of course, we have computers that do the perusing for us, but as big data gets bigger, and as analysts, marketers and others seek to do more with the massive intelligence that can be pulled from big data, we risk running into a human bottleneck. Just how much can one person — or a cubicle farm of persons — accomplish in a timely manner from the dashboard of their marketing cloud? While marketing clouds do a fine job of gathering data, it still comes down to expecting analysts and marketers to interpret and act on it — often with data that has gone out of date by the time they work with it.

Hence, big data solutions leveraging machine learning, language models and prediction, in the form of self-learning solutions that go from using algorithms for harvesting information from big data, to using algorithms to initiate actions based on the data.

Yes, this may sound a bit frightful: Removing the human from the loop. Marketers indeed need to automate some decision-making. But the human touch will still be there, doing what only people can do — creating great content that evokes emotions from consumers — and then monitoring and fine-tuning the overall performance of a system designed to take actions on the basis of big data.

This isn’t a radical idea. Programmed trading algorithms already drive significant activity across stock markets. And, of course, Amazon, eBay and Facebook have become generators of — and consummate users of — big data. Others are jumping on the bandwagon as well. RocketFuel uses big data about consumers, sites, ads and prior ad performance to optimize display advertising. Turn.com uses big data from consumer Web behavior, on-site behaviors and publisher content to create, optimize and buy advertising across the Web for display advertisers.

The big data revolution is just beginning as it moves beyond analytics. If we were building CRM again, we wouldn’t just track sales-force productivity; we’d recommend how you’re doing versus your competitors based on data across the industry. If we were building marketing automation software, we wouldn’t just capture and nurture leads generated by our clients, we’d find and attract more leads for them from across the Web. If we were building a financial application, it wouldn’t just track the financials of your company, it would compare them to public filings in your category so you could benchmark yourself and act on best practices.

Benioff is correct that there’s an undeniable trend that most marketing budgets today are betting more on social and mobile. The ability to manage social, mobile and Web analysis for better marketing has quickly become a real focus — and a big data marketing cloud is needed to do it. However, the real value and ROI comes from the ability to turn big data analysis into action, automatically. There’s clearly big value in big data, but it’s not cost-effective for any company to interpret and act on it before the trend changes or is over. Some reports find that 70 percent of marketers are concerned with making sense of the data and more than 91 percent are concerned with extracting marketing ROI from it. Incorporating big data technologies that create action means that your organization’s marketing can get smarter even while you sleep.

Raj De Datta founded BloomReach with 10 years of enterprise and entrepreneurial experience behind him. Most recently, he was an Entrepreneur-In-Residence at Mohr-Davidow Ventures. Previously, he was a Director of Product Marketing at Cisco. Raj also worked in technology investment banking at Lazard Freres. He holds a BSE in Electrical Engineering from Princeton and an MBA from Harvard Business School.

After a brief trading halt, Adobe shares climbed to $37.65 following the company’s report of fiscal fourth-quarter adjusted earnings of 61 cents a share. Analysts polled by FactSet had, on average, forecast earnings of 56 cents a share.

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According to sources close to the situation, Facebook is looking seriously at purchasing Microsoft’s Atlas Solutions ad-serving platform.

Sources said the social networking giant has been conducting due diligence on the media measurement platform, part of its efforts to create its own advertising network for third-party Web sites to compete with Google’s DoubleClick offering.

Atlas has been quietly on the market for some time and has been looked at by a number of companies, such as Adobe, said sources. But the effort to sell it got a jumpstart with recent interest from Facebook, which had been debating buy-versus-build options.

While there are some technological issues in taking over Atlas, sources said the prospect of starting from scratch was more daunting than picking up a platform that already delivers billions of ad impressions a day.

Atlas was acquired by Microsoft as part of its 2007 purchase of aQuantive for $6 billion. The new price for Atlas will be substantially lower, said sources, but could involve a more complex advertising agreement between Facebook and Microsoft.

Facebook declined comment and I am awaiting a response from Microsoft.

(Business Insider is also reporting that the pair are in talks.)

Google could be forgiven for fumbling tech that’s further away from its search business — if, say, its Wildfire acquisition goes sour. But if anyone should have figured out SEM, it should be Google. What’s going wrong?

To answer that question, you need to start with Google’s peculiar relationship with SEM — and with marketing software generally.

For advertisers and agencies, SEM software exists to make search buying more efficient. But from Google’s standpoint, SEM tools serve a different purpose entirely. They’re automated pipes that drive advertiser spend into search engines — including into Google search. Additionally, they’re ways to offer upsell off of Google’s existing ad network.

So while standalone SEM platforms such as Kenshoo or Adobe’s Efficient Frontier have to work very hard to make advertisers happy, Google doesn’t really need to work too hard to achieve its own goals in SEM (namely, increased revenue and higher share of spend). Google’s mammoth share of search queries fairly guarantees it a lion’s share of search budgets, with or without good marketing tools. Plus, a bevy of other search marketing providers already provide great automation to help advertisers spend more money in search, including within Google search itself. Google’s chief goals for SEM are already largely achieved by the rest of the market. Doing beyond the bare minimum amounts to duplicating efforts — which means wasting Google resources.

The goal of providing a pipe into Google search even creates a disincentive for Google to help advertisers spend money outside of Google ad networks. It’s no surprise that Forrester notes how DoubleClick Search “supports biddable buys on fewer media outlets than its competitors.” Kenshoo, by comparison, goes so far as to provide integration into Facebook, while IgnitionOne “supports 11 display networks and can programmatically create mobile-device-specific ad versions.” As channel-agnostic and network-agnostic buys become increasingly critical to marketers, failure to provide good cross-outlet support can really hinder advertisers using Google products. But from Google’s perspective, effectively supporting channel-agnostic buys means helping advertisers take ad spend away from Google — which is bad business.

Forrester does “hope that [Google’s] plan to integrate DoubleClick Search into a comprehensive Google online advertising suite will solve this platform’s shortfalls.” I’m less optimistic, because mediocrity runs across a lot of Google’s tech stack beyond search. Michael Greene, a senior analyst at Forrester, has rightly pointed to Google as a prime example of “media and technology behemoths … making credible runs at the end-to-end ad tech stack, even if some of their stacks suffer from a mix of ‘best-in-class’ and ‘just good enough.’” But that’s not a surprise. If Google’s aims for the tech stack are just to provide a system of pipes that support Google Advertising, then building a tech stack out of cheap parts is really all that’s required in most instances. Going above and beyond that is, again, counterintuitive.

Which is why the marketing community really needs to ask if Google is the best business to provide the end-to-end tech stack that marketers want. For Google’s tech stack competitors which don’t have ad inventory to sell (Adobe, for example), the chief reason to create a tech stack is to provide marketers with a suite of useful, integrated products, and to make money in the process. That’s a setup for a win-win (pending good execution, of course). But Google has its own agenda. And if that agenda gets in the way of creating good products so close to Google’s core business, how can we expect Google to provide better than ho-hum technology across the entire marketing spectrum? If Google wants the marketing world’s technology business — and not just its ad dollars — then it’s a question the company needs to answer, soon.

Bill Wise is CEO of marketing systems provider Mediaocean.

I am a college student in the market for a non-clunky laptop. I have a pretty limited budget, $500 or less. I will be using it primarily for research and writing Word documents for school. I’m not into editing videos or pictures or downloading games and such but I do want one that can play DVDs, and don’t want something with too small or too large of a screen.

A:

Your price range eliminates Macs and the least “clunky” Windows laptops, but there are plenty of choices among Windows PCs around the $500 range. With a budget-driven purchase like this, it’s best to go to a store and actually eyeball the machines, to see which ones have screens and keyboards you favor. I’d also try to stick with name brands, like Acer or Toshiba, Hewlett-Packard or Lenovo. But bear in mind that to get the most out of the new Windows 8 operating system that comes on nearly all laptops now, you will want a touchscreen.

Q:

We would like to purchase a laptop for our 16-year-old to do school work, surf the Internet and play games. I also want to trade in my five-year-old desktop for a Windows laptop for my home business that will run Microsoft Office and surf the Internet. I’m concerned about switching over to Windows 8 as the reviews have been very mixed and I don’t have time or patience to learn a whole new way of performing basic tasks. We welcome any advice.

A:

You can still buy a Windows 7 laptop, which will be much more familiar to operate, from places like Amazon.com or Best Buy’s Web site.

Q:

I was hoping Microsoft’s new Surface tablet would include my two must-haves: a place for a flash drive and the ability to run Adobe Acrobat. It has the USB port for flash drives, so I can carry work files, but can the Adobe software be downloaded to a flash drive and used with the Surface tablet?

A:

Whether it resides in the Surface’s internal storage or on a flash drive, Adobe Acrobat won’t run on the current Surface, formally called Surface RT, unless and until Adobe creates a so-called new-style Windows 8, tablet-like version of the program. However, in January, Microsoft is expected to introduced a Surface Pro tablet which will be able to run traditional Windows programs like Acrobat. The downside: It will be heavier and possibly costlier.

Email Walt at mossberg@wsj.com.