So here’s one of the main reasons I haven’t been blogging lately – the release of the next episode of “A Startup A Week”!   ASAW is an online reality show where we challenge a team of developers to build a startup in just one week.  For episode two, we’re trying something a little different by bringing together “A Startup A Week” with an event called “Incubation Week”.  Instead of working with just one team, Incubation Week brings together multiple teams of entrepreneurs for a caffeine-fueled week of coding, all leading up to a final presentation in front of a panel of experienced angel investors. 

For this video, I flew out to Boston to check out the initial Incubation Week event.  We definitely had a great time, check out the video to see if the teams were able to complete their apps in time for their presentations to the investors.

Who cares more about gaining web API share on the web, Amazon or Google?  Who cares more about gaining database share on the web, Amazon or Oracle?  Who cares more about gaining server share on the web, Amazon or Sun?  Who cares more about gaining developer mind share on the web, Amazon or Microsoft?

While web services are a great high-margin business for now, as these other large companies build out their could computing strategies, the competition will drive margins lower and lower.  What’s more, these existing platform companies can afford to offer these services at or below cost, in exchange for a greater share in their respective categories.  As these services become commoditized and the price drops lower and lower, at what point does Amazon’s web service strategy stop making good financial sense for them? 

Anyway, the point of the article is that the combination of a GPS-enabled iPhone along with a seamless way to download 3rd party apps (AppStore), a new development trend is about to begin:

The iPhone is a platform that lives in your pocket. So you can pull it out, check your options and make some decisions without all the overhead associated with laptop use. It’s this fundamental difference in the way we use the iPhone with “pants-based computing,” with a device that travels with us and knows where we are, that powers this paradigm shift. We’re sitting at the edge of a location-based computing revolution, and the iPhone is pulling us there. From our pockets.

So in honor of the forthcoming revolution and in homage to my previous blogging contributions, here are some ideas for three killer PBC apps.

          1. Stadiu.ms – A Temporary Social Network for Stadiums 

For people who are all gathered together in one very large venue (sporting events, concerts, etc..), Stadi.um is an app that would allow you to network with other people at the event and get extra add-on information about that event (for a baseball game, think detailed player stats for the specific batter at the plate, mini-games such as trivia or mini fantasy baseball games, etc..).  You could also chat with other fans in real-time about the event, or see a map of the stadium with little pins showing where each Stadiu.ms user was sitting.  The beauty of an app like this is you get around the whole chicken-and-egg problem inherent with most mobile..err, PBC-based social networks (need users, but users won’t use the service until other users are there).  You could simply buy out an ad at the beginning of the game to flash the info needed for people to get signed onto the app, and you’d instantly have enough users with the same basic interests who are in the same general geographic area to make the service immediately interesting and useful.

          2. TravelWithMe – A Portable Travel Blogging Tool

For travelers who are looking to capture more than just a few grainy photos of their overseas adventures, TravelWithMe offers an easy-to-use set of tools to share your travel with your friends and family back home.  Instead of relying on long blog posts or cumbersomely uploading a set of photos to a website, TravelWithMe would offer a Twitter-like ability to very quickly share thoughts, pictures and short videos.  Each time travelers share something, it is automatically tagged by time and by location, and uploaded to a website.  The site would display a dot on a map for each item that was uploaded, and based on the time the item was uploaded, lines would show the daily progress of the traveler.  Users who are following along on the website could post comments on each item, and the travelers could be notified of the new comments either directly through the app or via SMS alerts.

          3. BluLight – Distributed “Woot” for PBC

For stores that are looking to attract nearby customers and users who are looking for deals, BluLight is a woot-like system that allows retailers to advertise limited-time-only in-store deals.  Retailers could log into the BluLight system and post a deal, which would then be broadcast to all BluLight users who are currently within one mile of the store.  One advantage this system offers retailers is the scenario when customer traffic in the store is temporarily low, retailers could quickly post a deal to the system and use it to generate foot traffic on-demand to maximize their efficiency.  For customers, this would be a fun way to spontaneously get notified of amazing deals, which would create almost a real-life game-like buzz around the product.

Starting July 15 (and perhaps coinciding with the rollout of Facebook’s new site design), users will no longer see an installation screen (see below) when they access an application for the first time. Rather, they will see a new “login” screen that simply asks them whether they want to permit the application access to their information. This simply grants the application temporary access to your data so it can operate, without establishing any real footprint on your Facebook experience.

All I can say is wow.  With all of the recent changes to reduce the spamminess of Facebook apps, it’s been harder and harder for independent developers to get access to the same viral “magic formula” that launched so many of the early apps and created the gold rush mentality around the platform.  Now, not only are they greatly reducing yet another viral channel for app developers, they are also grandfathering in existing applications, which means the big guys will keep getting bigger, and the little guys are at a serious disadvantage. 

As someone who works on the breadth developer strategy at Microsoft, I know firsthand the importance of creating a healthy developer ecosystem with a good mix of the new, smaller software companies and larger, established ones.  With this move, Facebook is essentially cutting off the oxygen supply to the broad base of developers.  This will likely not make an immediate impact to the platform, but once they start to see the erosion taking place, their bread-and-butter breadth developers will have moved on to a platform that gives them a better shot at making some real revenue.

Imagine if the NBA suddenly decided that the rookies in the league were causing too many problems, so to fix the problem, they stopped the draft.  The short term impact would be minor.  But long term?  Disastrous. 

Of course, maybe Facebook simply decided that their core product is good enough without the add-on apps, and this is one way to slowly cut their losses and move towards an even more closed down system.  Or maybe they just don’t really understand the ripple effect that could happen to their developer ecosystem as a result of all these changes.  Hopefully these guys know what they’re doing, ’cause I’m a huge fan of the FB platform and really would hate to see it die a slow and painful death.

Update: Check out the uproar on the official FB dev forums…obviously I’m not the only one who thinks this is a bad idea…

OK, so despite the fact I work for Microsoft, I couldn’t help but get way excited about this site.  Props to Mashable for posting this.  Now, if only someone could make a livesh.org…

One panelist said “Privacy doesn’t matter anymore. If it did, Facebook, MySpace, and YouTube wouldn’t exist. This is the “Full Monty” generation.” The trend is certainly in that direction, but the Facebook Beacon experience suggests we aren’t there yet.

Two very good points – so why would someone (like me) post many personal details out on the web but that same person (me again) be completely turned off by Beacon?  I’d argue that it all comes back to a simple question: what’s in it for me? 

When I post my personal email here on my blog (kleneway@hotmail.com), I’m sacrificing a tiny bit of my privacy for the chance that someone interesting will find my email and send me a nice note.  Same goes for the reasoning behind posting my favorite movie on my MySpace profile.  I love the movie Wayne’s World!  Do you?  Great, we have something in common, let’s talk!

However, when I used the CBS NCAA college football pool app on Facebook and clicked over to watch one of the games that was in progress, I got a Beacon message asking if I wanted to broadcast to my friends that I was watching a basketball game.  So why didn’t I want that to appear in my Facebook feed?  Because it was a Thursday afternoon and I probably should have been working!    I have lots of work contacts listed as friends on Facebook, and while they probably wouldn’t really care if I watched a few minutes of a game during a break between emails, it probably isn’t the best signal to send.  The “what’s in it for me” coefficient suddenly went negative, and I’ve turned off all future Beacon notifications ever since.

The truth is, we like to talk about scaling, but without steady growth and something people find compelling, all the scaling in the world won’t help you.

Don’t ask me why, but after reading this comment, I couldn’t help but draw comparisons to a typical high school prom.  Not sure how things operated when you were (or still are) in school, but for me, the prom queen was much more likely to be physically attractive as opposed to being just regular-looking with an amazing personality.  If the web held a prom, who do you think would be crowned the queen, Twitter or Grazr?

Don’t worry, Grazr.  I’ll save a spot next to me at the next math club meeting.

Phase 1: Grow a Rabid User Base

In order for FriendFeed to build up a index of the world’s conversations, they first needed to create a front end with two important components.  First, it needed to be as easy as possible for people to pull in their conversations from all over the web, and to do it in the most automated format possible.  Second, they needed to build in a viral distribution model that would allow them to build up their user base as quickly as possible.  My guess is that somewhere in the FriendFeed offices, they have a graph on the wall that shows two curves.  One is an exponential growth curve that represents their predicted growth (based on power laws and estimated viral coefficients) with a clearly defined upper threshold.  The other is a line showing the actual user activity.  The one thing FriendFeed should focus on in this initial phase is to ensure that their actual growth is showing a viral growth pattern and will reach their target threshold by a certain date.  Once they reach this threshold, they will have proven out their viral distribution model.  Take an exponential growth pattern and multiply that by an exponential content aggregation engine, and FF has the underpinnings of a massively powerful engine that can quickly build out the data needed to form the basis of their “conversation index”.

It will be pretty obvious when they hit their target threshold.  It will be approximately 2-3 weeks before they announce a pretty sizeable VC investment.  FF won’t be the only ones who are watching this growth curve very closely.   

Phase 2: Mine for Context

At this point, FF can use the new investment to build out a pretty sizeable server farm to handle the incredible amounts of data that will start flooding in.  You’ll probably also see some job postings on their site for PhD’s with backgrounds in data mining and contextual relevance.  Why?  Because unlike a traditional search engine that can do a pretty good job of indexing information just based on things like page rank and keywords, extracting value from conversations needs to take context into account before it can truly be valuable. 

For example, compare the view of Twitter posts on the Twitter public feed to the view of Twitter posts on Twistori.  This is a very crude example of type of analysis needed to pull a signal out of the noise.  Once the algorithms have been created to extract the context, FF just has to sit back and wait for their index to grow to a point where they are able to provide statistically significant results for search queries.  Which, of course, brings us to the start of phase 3.

Phase 3: Search v2

And here’s the real value of FF gets unlocked – search.  Scoble actually touched on this a few weeks back (see #3), but here’s my take on it.  Imagine you’re looking to buy a new laptop.  You go to FF and ask the question “What laptop should I buy?”.  The results will come back in two forms.  First, a list of posts from your friends displaying their opinions on their favorite laptops.  Note that unlike the search that is on FF now, these contextual results will filter out any noise such as conversations about problems they are having with their laptops, posts that have the word “laptop” but are not specifically about laptops, etc..  Second, a list of posts from all users displaying information about their favorite laptops.  Again, this will be a filtered list, and it could also be aggregated in a format like “120 people like the MacBook Air, 75 people like Dell Latitude D820, etc..”.  Of course, you could click into any of these lists to see the details of the conversational threads.  And finally, if you didn’t get a satisfactory answer from your search, you could simply post your search query as a message post to your followers, and get a special notification back once people start responding.  This goes one step beyond anything a traditional search engine can do, and really takes a best-of-both-worlds (mechanical vs personal) approach to finding the information you’re looking for.

In addition, there’s one more killer application of this new way to search.  Imagine you’re in downtown Seattle and you’re looking for a place to eat.  You pull out your phone, do a search for “best restaurants in Seattle” (or click on the “Restaurant” icon on the FF mobile app), and get the same FF search outlined above for both your friends and everyone – filtered to show only opinions from people from within 1 mile of your current location. 

I’m not in charge of the budgets at G, M, or Y – but if I was, I don’t think it’s too crazy to think that a service like that tied into my advertising platform might be worth a pretty nice chunk of change.

What do you guys think?  Am I drinking way too much of the Web 2.0 Kool-Aid, or is FF really on to something here?  I’d love to hear your thoughts in the comments below.

Update: Jeremiah Owyang just posted an interesting analysis on FF that’s worth a read as well. 

Update #2: TechCrunch is reporting on FF’s hockey-stick growth.  Now it’s time to keep an eye on their “We’re hiring!” pages… 

“A team at the university of Pittsburgh has finally advanced a 2002 technology enough for use in prosthetic limbs, the targeted application all along. Training computer models to the firing patterns of the neurons in the parts of the brain that control motion, they are able to project the intentions of a monkey to a robotic arm, which follows the will of the animal. The sad thing about the articles is that the beauty of the mathematics used to create and train the models is totally ignored.”

I’m way interested in this stuff, as back in 2001 I worked on a project called the “Direct Brain Interface Project” at UM where I built out a little computer game that would be used to train the underlying computer model that would detect brain waves for a given stimulus.  I loved that project, it’s great to see that there’s some real progress being made in this area seven years later.

Tier 2 – Local Sensations

Your Local Sensation startup has survived the first six months to a year, and is beginning to build up a loyal community of users. Some people recognize the value of the service you are providing, but you either still have a ways to go to unseat the leader in your space, or your startup concept is so niche or so new that many people have been slow to sign up. Most of your users are either part of the Silicon Valley echo chamber or are geographically located in the country in which you are based.

Reputation: For the particular service you provide, you are recognized as a player in this space, but not the leader. Your startup may only be well known only in the country in which it is based. Your startup’s name is recognizable by roughly half of the Web 2.0 evangelists and early adopters, but almost none of your friends outside of the IT industry. Your friend’s mom has never heard of your service before.

Adoption: You may have anywhere from 1000 to 10,000 active registered users, most of which are based in your home country. Some Web 2.0 evangelists and early adopters may use your service for a bit to see if you are bringing anything new to the table.

Buzz: Your startup may be mentioned once or twice on either FriendFeed, Twitter, Techmeme, Digg, Reddit, or Slashdot. You are likely to have been mentioned on TechCrunch or other Silicon Valley evangelist blogs like Robert Scoble’s or Louis Gray’s.

Monetization: You may or may not have a business plan in place to make money. However, it’s still waaaaay too early to talk about monetization now. Let’s get even more users first!

Mulligans: If your startup is unstable and shows scalability or usability problems at this stage, it’s game over. Most early adopters will not bother giving you a second chance and will jump ship to your competitor instead.

Examples: Polyvore, SharedCopy, Twine

Where does your startup land?