Last year, Pell founded a company called Moon Express that is focused on building lunar landing craft. So his new venture, QuickPay, is a little more down to earth. [Ed. Note: Sorry, couldn't resist.] But what is it about parking or payments that got his attention? I passed along a few questions by email to see.

GigaOM: Why parking or payments? What is it about that particular market that attracted you to innovate on current services?

Barney Pell: I’m always thinking about how the basic things of life can be done better. Every time I look for parking, pay for parking, or worry about a parking ticket, I think that there must be a better way. Last year, I met another entrepreneur who had an initial product in this space and the opportunity totally captured my imagination.

GigaOM: What’s the market opportunity or focus of Quickpay? Are you looking to improve efficiency of the current system, reduce friction in payments or enable more users by taking away cash and making the technology mobile?

Barney Pell: All of the above, and much more. The market opportunity for QuickPay is massive. Parking in the US is a $26B industry (from end-user parking fees alone), but the parking operators know hardly anything about the people who park in their facilities, and parkers have little in the way of technology to help them carry out one of life’s daily activities. With QuickPay, we are bringing the parking industry to the age of the cloud and mobile devices. This brings benefits for parkers, parking operators, and facility owners, of efficiency, convenience, loyalty, rewards, dynamic pricing, and real-time data. QuickPay makes money in general on a per-transaction basis, with a market opportunity for just the payments piece >$3B per year.

GigaOM: What’s the buy-in from on-street (municipalities) or off-street (garages)? What exactly do you need to do to enable this technology to work with existing systems?

Barney Pell: QuickPay [is] getting a great response from municipalities and private parking operators. We are live in 80 locations in the Bay Area and have an active pipeline of national and regional players and municipal RFPs.

To onboard a new facility, we let the parking operators enter the lot information, such as location, open hours, and rate table, into our cloud-based system.

Then to work with their existing systems, we have a proprietary and inexpensive gate-arm kit that we install at each parking entrance and exit gate, which lets our cloud-based system raise the gate whenever a user scans the gate’s QR code with their mobile device. For ungated facilities and metered on-street parking, our system pushes the license plate of our parked users to the enforcement systems of the parking operators, so that our users don’t get tickets when they have paid to park with our system.

GigaOM: It seems like QuickPay is a bit of a departure from NASA or natural-language processing. What parallels can you draw between the technology you’re building now and some of the projects from your past?

Barney Pell: Actually, QuickPay is very closely related to my most recent work on Bing and, in particular, Bing Mobile and Local Search. Parking is largely a local and mobile search and commerce problem. You need to organize large amounts of structured data about users, prices, and locations, organize it, and deliver the data and transactions in vertically optimized user experiences. While at Powerset and Bing I identified major trends in search as Mobile, Local, Social, Personal, Contextual and Semantic, all supported by Cloud. It turns out that all these trends are directly relevant in the future of parking (in fact I’ve published some papers in parking magazines elaborating on all this).

GigaOM: Is parking just the first vertical that you hope to tackle with QuickPay? What other industries could this technology have the potential to disrupt?

Barney Pell: Parking is, in itself, a major vertical upon which we can build a great company. Parking extends naturally to transportation, such as fares for bus, trains, and tolls. But at the heart of it, our system is a cloud-based mobile wallet and payment system, so the possibilities are endless.

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The trio met as members of the board of Singularity University, which is based in the NASA Ames campus in Silicon Valley. A year ago, they started the company with some initial funding from Pell and Jain, but they have since raised a little bit of angel funding. With seven full-time employees and a handful of contractors, the company isn’t looking for big round of funding just yet. It is all in the future, Pell said.

Pell spent a large portion of his working life at NASA before leaving to work in Silicon Valley. He worked on projects for the Mars Exploration Rover mission along with several other projects related to autonomous systems. He was also involved in the development of one of the first artificial intelligence systems to fly onboard (and control) a deep space probe. “I’m still fully engaged with my day job at Bing, but this is definitely an exciting nights and weekends [almost literally moonlighting] job for me,” Pell wrote.
For now the company has a contract from NASA worth up to $10 million  “for the initial delivery order of the ‘Innovative Lunar Demonstration Data (ILDD)’ program.” The company is competing in the $30 million Google Lunar X PRIZE, “a competition to place a robot on the Moon’s surface that travels 500 meters and transmits high definition video, images and data back to Earth.”

Moon Express describes itself as a “lunar transportation and data services company created to establish new avenues for commercial space activities beyond Earth orbit” and “will be sending a series of robotic spacecraft to the Moon for ongoing exploration and commercial development.” What does that mean? “Our big play is to develop a robotic lander to transport things to (and from) the moon,” Pell said. And why would we do that?

“There is eventually going to be a moon rush, because there are a lot of resources on the moon that we will need,” said Pell. Resources like platinum and other metals that are needed for fuel cells and the post-fossil fuel economy. “In the future we want to be able to land the payloads and machines and bring things back,” said Pell. ”We want to be the last mile to the moon.”

Crazy? Absolutely! Impossible? Probably not! There are a growing number of people who believe that with federal funding for our space program getting scarce, the future lies in private-public partnerships. Entrepreneur Elon Musk’s third job (after leading electric car company Tesla and acting as the Chairman of solar installer SolarCity) is heading up SpaceX, which was the first private company to successfully launch, orbit and recover a rocketship. Virgin’s Richard Branson has a similar private space venture.

Rare metals have suddenly become a hot commodity in products from hybrid vehicles batteries, to wind turbines, to compact fluorescent light bulbs to magnets for electric vehicle motors. Particularly now that China, which owns control of 95 percent of rare earth metals, decided to cut its exports of those metals.

Of course governments of China and other emerging economies like India and Brazil have had similar thoughts about tapping into moon’s resources and are spending billions of dollars.

When I asked Pell how he plans to compete with the seemingly unlimited resources of nations, he said that the company has a few tricks up its sleeve that he is going to be sharing at a later stage. And yes, they will be seeking funding, eventually.

Image courtesy of Flickr user peasap

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Lately, many people have been experimenting with Bing, Microsoft’s new search engine offering, which we covered here. I agree with the many people who are noting improvements that need to arrive in Bing, such as blog searching and more varied search results for basic keywords. However, not everyone realizes that Bing is built on a powerful search engine technology from an open source-focused company that Microsoft acquired last year: Powerset. As I covered in this post, the Powerset technology underlying Bing introduces some powerful features that many people aren’t trying. You may find them useful.

Powerset originally got noticed in the search community because it leveraged Hadoop, which is an open-source software framework that allows clusters of computers to make very quick work of mining large data sets. (Hadoop also powers Yahoo’s search engine.) Powerset’s idea was to leverage Hadoop to improve natural language searching, where you type in questions in sentence form instead of using keywords. If you’ve followed natural language searching,  you’ll know that it’s had a rocky, and generally unsuccessful, history.

Hadoop brought Powerset more speed at mining through the mountains of possibly relevant search returns that come back in natural language search engines. Powerset doesn’t underlie all of Bing, but this unique facility with natural language searching is in Bing, and you may find it useful if you haven’t tried it.

Here are some example queries to try at Bing.com, to get a sense for how it works:

• Which companies has Google acquired?
• Which Firefox extensions block online ads?
• What is the semantic web?
• How much was MySQL acquired for?

You’ll notice that many of the search results that come back in these types of searches at Bing are mined from Wikipedia, because Powerset has always specialized in Wikipedia search. Entries on Wikipedia aren’t always correct, so you have to take results with a grain of salt, but Microsoft has extended Bing’s facility with natural language search beyond just Wikipedia searches, and it can be quite good at providing quick answers to natural language questions.

What do you think of Bing’s natural language search capabilities?

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The good news is that the increased pressure from all sides has forced ISPs to come to terms with the reality of file-sharing and other forms of P2P video distribution, which is essentially: You can’t stop it, so you might as well find ways to make it run more smoothly on your network.
 

For most of the year, the spotlight in the debate about P2P and ISPs has been on Comcast, and the cable operator has subsequently provided us with lots of headline fodder. The company was caught blocking the upload of files through the BitTorrent protocol in late summer of 2007, but denied any such actions well into the spring of 2008. The FCC started to investigate Comcast’s actions in January, and the company reacted by paying people to “save seats” at public hearings.

The company finally did a complete turnabout in March, teaming up with BitTorrent and promising to stop the blocking that it had previously denied. Comcast also briefly championed an ill-fated “consumer’s bill of rights.” Many of these actions were obviously designed to appease the FCC and avoid any federal regulation, something that eventually proved to be futile. But they also forced Comcast and other ISPs to look at technical solutions for the ever-increasing amount of bandwidth used up by P2P applications that didn’t involve sabotaging their customers’ Internet use.

One of the solutions that quickly gained traction within the industry was an idea developed by a handful of Yale researchers. What if, they asked, ISPs could actually help P2P users find the closest link to other users downloading the same videos? What if a BitTorent user on Comcast’s network exchanged bits with another Comcast customer in the same city, as opposed to someone in Tokyo? And what if there was a system that allowed P2P applications to access this type of routing information across the networks of multiple ISPs?

The idea, cleverly branded P4P, has been championed by P2P vendor Pando, and initial field tests with a number of ISPs show very promising results. A lot of the details are still unclear, however, and some P2P users remain wary of any involvement of ISPs. If the industry starts to meddle with their downloads, they fear, then what stops them from just accelerating licensed P2P and in effect slowing down unlicensed content?

The answer is simple: Licensed P2P traffic is growing, but it’s still not anywhere near the amount of bandwidth eaten up by torrents from the Pirate Bay and similar sites. In fact, even optimistic market researchers estimate that in five years, piracy will still account for more than twice the amount of traffic as legal P2P. Any P4P solution that does not include unlicensed content would essentially have no effect on the health of the network.

But in the meantime, ISPs finally got real about P2P video. They realized that TV torrents won’t go away, and that the only way to effectively deal with this traffic is to optimize it, instead of trying to block it. That’s a big blow for content owners that were hoping for ISP-based anti-piracy filters, but it’s actually a boon for content owners that embrace P2P technology. Just as pirated torrents run more smoothly over P4P-assisted networks, so will downloads from NBC Direct.

As for bandwidth caps, well, that’s another story. But you can’t really expect company’s like Comcast to learn from all of their mistakes in the same year, can you?

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I’ve been unable to stop wondering why founder Barney Pell decided to take the money and run — after all, he used to turn blue in the face telling people how superior Powerset’s approach to search was. If it was so superior, Mike Masnick of Techdirt put it best when he wrote that “[T]he exit certainly falls well short of the hype around Powerset. If Powerset was actually seeing any traction at all it never would have agreed to sell at that price.”

To some extent, Mike is right, but I would add another reason: infrastructure, specifically how expensive it is to build. At our Hadoop meet-up earlier this year, Chad Walters, director of engineering at Powerset, noted that their search “requires 100 times more processing than simple keyword searching and indexing (about one second per sentence is required for processing).”

Powerset used some pretty nifty technologies to build out their system, but in order to really scale, they would have needed more money — a lot of it.

And Powerset would have had to scale; there’s no other way to compete with search’s 800-pound gorilla, Google. That’s why Microsoft is building a gigantic data center in the Chicago area focused almost entirely on search. (Which it can now use to help roll out Powerset’s search technology to a larger audience.)

This is an abject lesson for every startup looking to get into the business of search: No matter how good your algorithms are, you still have to deal with the cost of queries, which need to be low enough to be offset by some kind of advertising in order to make a profit. (The conspiracy theorist in me says that if your results are really good you won’t be able to generate enough inventory to serve up ads that bring in the dollars, but maybe I’m just too cynical.)

One of our readers believes that it is possible to build a search engine that surpasses Google’s. Nevertheless, as I’ve noted in the past, “[P]rocess-optimized infrastructure ensures that Google’s cost of executing a query keep going down” — and that allows the company to wring more dollars from the system.

Given all that, Powerset has done a good job of wringing a hundred million from Microsoft. Not that there’s anything wrong with that.

Bonus Link: Don Dodge of Microsoft explains the logic behind the deal.

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Powerset’s search technology uses the open-source, cluster-based technology Hadoop, which provides fast answers to queries by using the resources of many computers. Hadoop, a project from the Apache Software Foundation, is also behind Yahoo’s search.

Natural language search got a bad rap early on in the rise of the web as players such as AskJeeves stumbled, but clustered query technology like Hadoop’s may represent a game-changer. Microsoft, of course, has been desperately trying to catch up in search, where it is a distant third to Google and Yahoo. It won’t be surprising to see large portions of Microsoft’s LiveSearch start to depend on Powerset, and in so doing, depend on open-source upstart Hadoop.

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In this post, we compare Powerset results with those of a demo implementation from one such search engine, Cognition Technologies. And we compare them both with the current gold standard in web search, Google (again, limited to the Wikipedia data set).

Example 1: Powerset

There are some classes of queries in which Powerset shines, such as whenever the query involves extracting concepts or aggregation of data from a given data set.

For example, check out the beautifully presented results for the following queries that extract key information the user is looking for and provide it in summary format:

“military intelligence”

“teams in the NFL”

Example 2: Cognition Technologies

On the other hand, there are other types of queries — especially where hardcore semantic parsing is involved — where the Powerset algorithms get confused, and Cognition gives better results:

“rare wildlife of the Amazon”

“football players who went to jail”

Example 3: Google

There are still queries (especially when semantic parsing is not involved) in which Google results are much better than either Powerset or Cognition:

“helicopter carrier Iwo Jima class”

Here, surprisingly, Google has the best results. Powerset has related results, Cognition gets totally confused, but Google nails it!

Disambiguation

One area where both Powerset and Cognition improve on Google is the disambiguation of query terms. This is always a significant issue for search engines; for example, when a user types in the keyword Java, does she mean the island, the programming language, or the coffee?

Google has recently tried some experiments in this area, but these new search engines go one better.

When Powerset sees an ambiguous topic, it uses tabs to provide both sets of results:

Cognition handles it in a different way, by letting the user select from among different semantic meanings for each term:

User Impact

For most common searches, Google search works just fine. We’ve all gotten used to the ubiquitous “keyword-ese,” currently the universal language of web search. With Google’s unlimited resources, comprehensive index and formidable prowess in finding relevant results using the PageRank algorithm, it’s going to be difficult for any other search engine to match those results. Users may have to work just a little bit harder for unusual queries or specialized searches, but most users will accept that trade-off in return for using their familiar and beloved search engine. Indeed, the word Google has come to represent web search in the same way that the word Xerox had once come to symbolize the process of photocopying.

Future Competition

So what can Powerset (and Cognition) do to gain traction and capture users?

In their recent book, “The Innovator’s Solution,” Clayton Christensen and Michael Raynor discuss how upstart companies challenging market leaders and entrenched incumbents can position new technologies for a reasonable chance of success. One approach that they believe is guaranteed to fail is when these smaller upstarts try to make evolutionary improvements to get and stay ahead of the major players.

Instead, they suggest shaping the new technology into a disruptive innovation, along either of the following two major axes:

1. New-market strategy: Leveraging the innovation to attract users who do not typically participate in using the product or service, and thus growing the market as a whole.

2. Low-end strategy: If there are price-sensitive, over-served users who would be willing to trade some of the advanced functionality in return for a lower price point, then the smaller players have an opportunity to enter the market — that is, if they can figure out a way to make a profit.

In other words, the new players entering the market have to find profitable business opportunities in segments of the market that are not attractive to market leaders.

Using this model, it is apparent that a strategy of challenging Google head-on for control of the mainstream web search market has little hope of success, regardless of the new technologies or search innovations that are applied. Google would have no choice but to fight back with everything it’s got to catch up to or leapfrog this “better search” alternative.

Similarly, since Google search is free for users, there is really no viable low-end strategy, no way to outdo the existing search leader by offering a lower price point.

What about non-participant users? Practically everyone online already uses a web search engine (with Google being the overwhelming favorite). However, Google search follows a specific, consistent set of guidelines: simplicity of UI, speed of response, and relevance based on incoming links. These design parameters take top priority over all other considerations.

By challenging these assumptions, we can discover new use cases in search that are underserved (or not served at all) by Google. Some examples include:

1. UI Simplicity: Google’s minimal UI is trivially simple to use and ideal for a one-size-fits-all model, but it may be less than optimal for complex semantic searches. As Alex Iskold points out in his recent article on the myth and reality of semantic search, a richer user interface would allow power users to express semantically-rich search queries and get back better results. Notably, Powerset and Cognition excel at these types of queries.

2. Speed: For some types of advanced searches, users might be willing to wait, perhaps even as long as a day, in order to get back semantically complex results. Imagine a software agent that acts as a virtual search assistant – once the user specifies a query with multiple levels of complexity and dependency, the agent goes off and returns the next day with a list of possible results/options. Queries that require the coordination of complex tasks fall into this category, such as planning a trip that requires coordinating air travel, hotel and car, and minimizing the cost of the whole trip while taking some additional factors into consideration.

3. Relevance: Although all the mainstream search engines use similar criteria to evaluate relevance (mainly, the evidence of incoming links), other relevance algorithms are certainly feasible and may work better for certain classes of queries. Social relevance is an obvious example; reputable premium content is another.

This post is in no way meant to discredit Powerset — they’re in early beta and are doing a fine job of building semantic search. Instead, the examples above clearly demonstrate that the jury is still out on semantic search; other search engines are also contenders in this space, and the race is far from won.

Nitin Karandikar writes about Web 2.0, Internet search and semantic web on his blog, Software Abstractions

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By now it’s time to address the latest, and arguably the most powerful, networking tool in any founders’ arsenal: Twitter. It’s simple. If you’re not “tweeting,” you’re missing half the conversation. Just ask Sarah Lacy. (How different Lacy’s now-infamous SXSW interview of Facebook’s Mark Zuckerberg might have been had she been plugged into the tweets flying around the conference room floor!) Don’t know how to use Twitter? No sweat. Here are my 8 Tips for How to Work a Twitter Party.
(Photo credit: News.com. SXSW Tweeters celebrating before the ill-fated Zuckerberg interview.)

First things first: For founders, the goal of Twittering isn’t to tell people what we ate for lunch, but to get technology influencers — like Dave McClure, Mike Arrington or Guy Kawasaki — to read and respond to our Twitter feeds. In Twitter nomenclature, this is called “following.”

1. Don’t be afraid to Tweet above your head. McClure is an Alpha Tweeter. One tweet from Dave is like a TechCrunch link two years ago. But you’re no one, so you’ll have to tweet Dave five times to get him to reciprocate, and do something really interesting for him to “follow” your feed. Reciprocity is also a must. Guy Kawasaki, a top Twitter-er, takes this to the extreme, following every Tweeter who follows him. So do I. Use text message updates to keep tabs on those tweeting you.

2. Watch your Twitter ratios. Spammers have a bad follower-to-following ratio, so don’t randomly follow 20, 200 or 2,000 people without some Twittering under your belt. Similarly if you’re twittering a little too substantively, or have a banal topic, then expect to have a horrible updates-to-follower ratio. (my updates-to-followers ratio is bad because I tweet about FICO scores, a topic so dull that my “ABC News” segment on YouTube only has 12 views.)

3. Leverage what’s going on. If you knew HP would buy EDS a week ago or a month ago, then tweet and claim credit. I’m not joking, people. Do this. Did you walk in on a powerSet 2.0 pitch at Peet’s on University Ave.? Twitter that too.

4. Move your Twitter conversation(s) off-line. Good meet-ups can start with Twitter marketing. Good examples include Startup School or Sarah’s book-signing in San Francisco. Twitter loves Y Combinator and vice versa! Tweet your friends to organize a pre-party (like a breakfast at Fraiche) and voila! One day prior to your event, and the RSVP list on Facebook is 50 percent over capacity.

5. Migrate your real-world conversation to Twitter. At ad-tech, I was with Oren Michels, Scott Rafer, Owen Thomas and others. During post-conference parties, people tweeted back-and-forth other constantly. What does this do? It stimulates more face-to-face conversation! Indeed, working the Twitter party makes the real party you’re at better, bigger and better-documented.

6. Time your tweets. A great man once told me: “Be a vacation in your interactions with people.” He meant: “Don’t tax your conversation partners.” Is reading your Twitter feed a part-time job, or a little beach break that people can take from right inside their cube at work? For maximum impact, release your tweets with the time of day in mind. News-related tweets fly in the morning. Post-lunch tweets should be on the lighter side.

7. Pre-write some of your material. There is nothing wrong with pre-composing a few impromtu tweets. Think improv comedians don’t prepare? So don’t post stream of consciousness to your Twitter. And whatever you do, don’t tweet with a buzz on.

8. Work the Twitter Room for product development. A product manager for pbWiki, Kris, was recently using Twitter to collect ideas for product tweaks. So I chimed in with a tweet requesting that updates to my company’s 400 pbWiki pages be distributed via email, but only to those who’ve actually edited those pages. Hey Dave Weekly (founder of pbWiki), did you know your employees work the Twitter Party for your benefit?

Written by Larry Chiang, founder of duck9.com, which helps college students improve their credit ratings. He is also a frequent contributor to Found|READ.

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That said, Powerset faces an uphill climb, especially when it comes to consumer mindshare. I think Google has become so synonymous with search that it is virtually impossible for a newcomer to establish a toehold. Powerset’s approach is different, and its tactic of applying its technology to specific content repositories such as Wikipedia is smart. But will they (web searchers) come and use Powerset?

At our recent GigaOM PM event, Chad Walters, director of engineering, search and platform at Powerset, gave a talk about how his company was using Hadoop and other clever technologies to meet its immense infrastructure needs. Here are some bits from OStatic’s live blog coverage of the event:

Powerset applies deep natural language processing (based on technology licensed from Xerox PARC), which means the company needs 100 times more processing horsepower than a simple keyword searching and indexing. Powerset uses a distributed database system called HBase in tandem with Coral, its Document Processing System. Coral uses Hadoop as its job control machine. Powerset uses 92 eight-core machines to do processing.

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