If you’re in the Bay Area, come join us at the 2011 ACM Conference on Electronic Commerce, June 5-9 in San Jose, CA, one of sixteen conferences that comprise the ACM Federated Computing Research Conference, the closest thing we have to a unified computer research conference.

The main EC’11 conference includes talks on prediction markets, crowdsourcing, auctions, game theory, finance, lending, and advertising. The papers span a spectrum from theoretical to applied. If you want evidence of the latter, look no further than the roster of corporate sponsors: eBay, Facebook, Google, Microsoft, and Yahoo!.

There are also a number of interesting workshops and tutorials in conjunction with EC’11 this year, including:

Workshops:

  • 7th Ad Auction Workshop
  • Workshop on Bayesian Mechanism Design
  • Workshop on Social Computing and User Generated Content
  • 6th Workshop on Economics of Networks, Systems, and Computation
  • Workshop on Implementation Theory

Tutorials:

  • Bayesian Mechanism Design
  • Conducting Behavioral Research Using Amazon’s Mechanical Turk
  • Matching and Market Design
  • Outside Options in Mechanism Design
  • Measuring Online Advertising Effectiveness

The umbrella FCRC conference includes talks by 2011 Turing Award winner Leslie G. Valiant, IBM Watson creator David A. Ferrucci, and CMU professor, CAPTCHA co-inventor, and Games With a Purpose founder Luis von Ahn.

Hope to see many of you there!

Cantor Gaming mobile device for in-running bettingLast January, a few friends and I visited the sportsbook at the M Casino in Las Vegas, one of several sportsbooks now run by Cantor Gaming, a division of Wall Street powerhouse Cantor Fitzgerald. Traditional sportsbooks stop taking bets when the sporting event in question begins. In contrast, Cantor allows “in-running betting”, a clunky phrase that means you can bet during the event: as touchdowns are scored, interceptions are made, home runs are stolen, or buzzers are beaten. Cantor went a step further and built a mobile device you can carry around with you anywhere in the casino to place your bets while watching games on TV, drink in hand. (Cantor also runs spread-betting operations in the UK and bought the venerable Hollywood Stock Exchange prediction market with the goal of turning it into a real financial exchange; they nearly succeeded, obtaining the green light from the CFTC before being shut down by lobbyists, er, Congress.)

Back to the device. It’s pretty awesome. It’s a Windows tablet computer with Cantor’s custom software — pretty well designed considering this is a financial firm. You can bet on the winner, against the spread, or on one-off propositions like whether the offensive team in an NFL game will get a first down, or whether the current drive will end with a punt, touchdown, field goal, or turnover. The interface is pretty nice. You select the type of bet you want, see the current odds, and choose how much you want to bet from a menu of common options: $5, $10, $50, etc. You can’t bet during certain moments in the game, like right before and during a play in football. When I was there only one game was available for in-running betting. Still, it’s instantly gratifying and — I hate to use this word — addictive. Once my friend saw the device in action, he instantly said “I’m getting one of those”.

When I first heard of Cantor’s foray into sports betting, I assumed they would build “betfair indoors”, meaning an exchange that simply matches bettors with each other and takes no risk of its own. I was wrong. Cantor’s mechanism is pretty clearly an intelligent automated market maker that mixes prior knowledge and market forces, much like my own beloved Predictalot minus the combinatorial aspect. Together with their claim to welcome sharps, employing a market maker means that Cantor is taking a serious risk that no one will outperform their prior “too much”, but the end result is a highly usable and impressively fun application. Kudos to Cantor.


P.S. Cantor affectionately dubbed their oracle-like algorithm for computing their prior as “Midas”, proving this guy has a knack for thingnaming.

March Madness is upon us and Predictalot, the crazy game that I and others at Yahoo! Labs invented, is live again and taking your (virtual) bets. Filling out brackets is so 2009. On Predictalot, you can compose your own wild prediction, like there will be exactly seven upsets in the opening round, or neither Duke, Kentucky, Kansas, nor Pittsburgh will make the Final Four. You’ll want your laptop out and ready as you watch the games — you can buy and sell your predictions anytime, like stocks, as the on-court action moves for or against you.

Predictalot v0.3 is easier to play. We whittled down the ‘Make Prediction’ process from four steps to just two. Even if you don’t want to wager, with one click come check out the projected odds of nearly any crazy eventuality you can dream up.

Please connect to facebook and/or twitter to share your prediction prowess with your friends and followers. You’ll earn bonus points and my eternal gratitude.

The odds start off at our own prior estimate based on seeds and (new this year) the current scores of ongoing games, but ultimately settle to values set by “the crowd” — that means you — as predictions are bought and sold.

Yahoo! Labs Predictalot version 0.3 overview tab screenshot

For the math geeks, Predictalot is a combinatorial prediction market with over 9 quintillion outcomes. Prices are computed using an importance sampling approximation of a #P-hard problem.

What kind of information can we collect that a standard prediction market cannot? A standard market will say that Texas A&M is unlikely to win the tournament. Our market can say more. Yes, A&M is unlikely to reach the Final Four and even more unlikely to win apriori, but given that they somehow make it to the semifinals in Houston, less than a two hour drive from A&M’s campus, their relative odds may increase due to a home court advantage.

Here’s another advantage of the combinatorial setup. A standard bookmaker would never dare to offer the same millions of bets as Predictalot — they would face nearly unlimited possible losses because, by tradition, each bet is managed independently. By combining every bet into a single unified marketplace, we are able to limit the worst-case (virtual) loss of our market maker to a known fixed constant.

Applications for Yahoo!’s third annual Key Scientific Challenges Program are due March 11. Our goal is to support students working in areas we feel represent the future of the Internet. If you’re a Ph.D. student working in one of the areas below, please apply!

We are thrilled to announce Yahoo!’s third annual Key Scientific Challenges Program. This is your chance to get an inside look at — and help tackle — the big challenges that Yahoo! and the entire Internet industry are facing today. As part of the Key Scientific Challenges Program you’ll gain access to Yahoo!’s world-class scientists, some of the richest and largest data repositories in the world, and have the potential to make a huge impact on the future of the Internet while driving your research forward.

THE CHALLENGES AREAS INCLUDE:

- Search Experiences
- Machine Learning
- Data Management
- Information Extraction
- Economics
- Statistics
- Multimedia
- Computational Advertising
- Social Sciences
- Green Computing
- Security
- Privacy

KEY SCIENTIFIC CHALLENGES AWARD RECIPIENTS RECEIVE:

- $5,000 unrestricted research seed funding which can be used for conference fees and travel, lab materials, professional society membership dues, etc.

- Access to select Yahoo! datasets

- The unique opportunity to collaborate with our industry-leading scientists

- An invitation to this summer’s exclusive Key Scientific Challenges Graduate Student Summit where you’ll join the top minds in academia and industry to present your work, discuss research trends and jointly develop revolutionary approaches to fundamental problems

CRITERIA: To be eligible, you must be currently enrolled in a PhD program at any accredited institution.

We’re accepting applications from January 24th – March 11th, 2011 and winners will be announced by mid April 2011.

To learn more about the program and how to apply, visit http://labs.yahoo.com/ksc.

Yahoo! India Predictopus logo

I’m thrilled to report that Predictalot had an Indian makeover, launching as Predictopus* for the ICC Cricket World Cup. The Yahoo! India team did an incredible job, leveraging the idea and some of the code base of Predictalot, yet making it their own. Predictopus is not a YAP — it lives right on the Yahoo! Cricket website, the official homepage for the ICC Cricket World Cup. They’re also giving away Rs 10 lakhs — or about $22,000 if my calculations are correct — in prizes. Everything is bigger in India, including the crowds and the wisdom thereof. It will be great to see the game played out on a scale that dwarfs our college basketball silliness in the US.

The Y! India team reused some of the backend code but redid the frontend almost entirely. To adapt the game to cricket, among other chores, we had to modify our simulation code to estimate the starting probabilities that any team would win against any other team, even in the middle of a game. (How likely is it for India to come back at home from down 100 runs with 10 overs left and 5 wickets lost? About 25%, we think.) These starting probabilities are then refined further by the game-playing crowds.

It’s great to see an experiment from Labs grow into a full-fledged product run by a real product team in Yahoo!, a prime example of technology transfer at its best. In the meantime, we (Labs) are still gunning for a relaunch of Predictalot itself for March Madness 2011, the second year in a row. Stay tuned.

2011/02/24 Update: An eye-catching India-wide ad campaign for predictopus is live, including homepage, finance, movies, OMG, answers, mail, everywhere! Oh, and one of the prizes is a Hyundai.

predictopus ad on Yahoo! India homepage 2011/02/24


* Yes, that’s a reference to legendary Paul the Octopus, RIP.

The US National Science Foundation’s Small Business Innovation Research program provides grants to to small businesses to fund “state-of-the-art, high-risk, high-potential innovation research proposals”.

In their current call for proposals, they explicitly ask for “I2b. Tools for facilitating collective intelligence”.

These are grants of up to US$150,000 with opportunity for more later I believe. The deadline is December 3, 2010! Good luck and (not so) happy Thanksgiving to anyone working on one of these proposals. I’m glad to help if I can.


The deadline for another US government program has passed, but should yield interesting results and may lead to future opportunities. In August, the Intelligence Advanced Research Projects Activity (IARPA, the intelligence community’s DARPA), which “invests in high-risk/high-payoff research programs” in military intelligence, solicited proposals for Aggregative Contingent Estimation, or what might be called wisdom-of-crowds methods for prediction:

The ACE Program seeks technical innovations in the following areas:

  • Efficient elicitation of probabilistic judgments, including conditional probabilities for contingent events.
  • Mathematical aggregation of judgments by many individuals, based on factors that may include past performance, expertise, cognitive style, metaknowledge, and other attributes predictive of accuracy.
  • Effective representation of aggregated probabilistic forecasts and their distributions.

The full announcement is clear, detailed, and well thought out. I was impressed with the solicitors’ grasp of research in the field, an impression no doubt bolstered by the fact that some of my own papers are cited ;-) . Huge hat tip to Dan Goldstein for collating these excerpts:

The accuracy of two such methods, unweighted linear opinion pools and conventional prediction markets, has proven difficult to beat across a variety of domains.2 However, recent research suggests that it is possible to outperform these methods by using data about forecasters to weight their judgments. Some methods that have shown promise include weighting forecasters’ judgments by their level of risk aversion, cognitive style, variance in judgment, past performance, and predictions of other forecasters’ knowledge.3 Other data about forecasters may be predictive of aggregate accuracy, such as their education, experience, and cognitive diversity. To date, however, no research has optimized aggregation methods using detailed data about large numbers of forecasters and their judgments. In addition, little research has tested methods for generating conditional forecasts.

2 See, e.g., Tetlock PE, Expert Political Judgment (Princeton, NJ: Princeton University Press, 2005), 164-88; Armstrong JS, “Combining Forecasts,” in JS Armstrong, ed., Principles of Forecasting (Norwell, MA: Kluwer, 2001), 417-39; Arrow KJ, et al., “The Promise of Prediction Markets,” Science 2008; 320: 877-8; Chen Y, et al., “Information Markets Vs. Opinion Pools: An Empirical Comparison,” Proceedings of the 6th ACM Conference on Electronic Commerce, Vancouver BC, Canada, 2005.

3 See, e.g., Dani V, et al., “An empirical comparison of algorithms for aggregating expert predictions,” Proc. 22nd Conference on Uncertainty in Artificial Intelligence, UAI, 2006; Cooke RM, ElSaadany S, Huang X, “On the performance of social network and likelihood-based expert weighting schemes,” Reliability Engineering and System Safety 2008; 93:745-756; Ranjan R, Gneiting T, “Combining probability forecasts,” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2010; 72(1): 71-91.

[Examples:]

  • Will the incumbent party win the next presidential election in Country X?
  • Will the incumbent party win the next presidential election in Country X?
  • When will Country X hold its next parliamentary elections?
  • How many cell phones will be in use globally by 12/31/11?
  • By how much will the GDP of Country X increase from 1/1/11 to 12/31/11?
  • Will Country X default on its sovereign debt in 2011?
  • If Country X defaults on its sovereign debt in 2011, what will be the growth rate in the Eurozone in 2012?

Elicitation – Advances Sought
The ACE Program seeks methods to elicit judgments from individual forecasters on:

  • Whether an event will or will not occur
  • When an event will occur
  • The magnitude of an event
  • All of the above, conditioned on another set of events or actions
  • The confidence or likelihood a forecaster assigns to his or her judgment
  • The forecaster’s rationale for his or her judgment, as well as links to background information or evidence, expressed in no more than a couple of lines of text
  • The forecaster’s updated judgments and rationale

The elicitation methods should allow prioritization of elicitations, continuous updating of forecaster judgments and rationales, and asynchronous elicitation of judgments from more than 1,000 geographically-dispersed forecasters. While aggregation methods, detailed below, should be capable of generating probabilities, the judgments elicited from forecasters can but need not include probabilities.

Challenges include:

  • Some forecasters will be unaccustomed to providing probabilistic judgments
  • There has been virtually no research on methods to elicit conditional forecasts
  • Elicitation should require a minimum of time and effort from forecasters; elicitation should require no more than a few minutes per elicitation per forecaster
  • Training time for forecasters will be limited, and all training must be delivered within the software
  • Rewards for participation, accuracy, and reasoning must be non-monetary and of negligible face value (e.g., certificates, medals, pins)

Our first prototype of Predictalot was written mainly in Mathematica with a rudimentary web front end that Dan Reeves put together (with editable source code embedded right on the page via etherpad!). It proved the concept but was ugly and horribly slow.

Screenshot of pre-alpha Predictalot: Mathematica + etherpad + web

Dan and I built a second prototype in PHP. It was even uglier but about twice as fast and somewhat useable on a small scale (at least by user willing/able to formulate their own propositions in PHP). Yet it still wasn’t good enough to serve thousands of users accustomed to simplicity and speed.

Screenshot of alpha Predictalot: PHP + YAP

The final live version of Predictalot was not only pleasing to the eye — thanks to Sudar, Navneet, and Tom — but pleasingly fast, due almost entirely to the heroic efforts of Mridul M who wrote a mini PHP parser inside of java and baked in a number of datbase and caching optimizations.

Screenshot of live beta Predictalot: Java + Javascript + YAP


It seems that high-level programming languages haven’t climbed high enough. To field a fairly constrained web app that looks good and works well, we benefit greatly from having at least three specialists, for the app front end, the app back end, and the platform back end (apache, security, etc.).

Here’s a challenge to the programming language community: anything I can whip up in Mathematica I should be able to run at web scale. Math majors should be able to create Predictalot. Dan and I can mock up the basic idea of Predictalot but it still takes tremendous talent, time, and effort to turn it into a professional looking and well behaved system.

The core market math of Predictalot — a combinatorial version of Hanson’s LMSR market maker — involves summing thousands of ex terms. Here we are in the second decade of the new millenium and in order for a sum of exponentials to execute quickly and without numeric overflow, we had to work out a transformation to conduct all our summations in log space. In other words, programming still requires me to think about how my machine represents my number. That shouldn’t qualify as “high level” thinking in 2010.

I realize I may be naively asking too much. Solving the challenge fully is AI-complete. Still, while we’re making impressive strides in artificial intelligence, programming feels much the same today as it did twenty years ago. It still requires learning specialized tricks, arcane domain knowledge, and optimizations honed only over years of experience, and the most computationally intensive applications still require that extra compilation step (i.e., it’s still often necessary to use C or Java over PHP, Perl, Python, or Ruby).

Some developments hardly seem like progress. Straightforward HTML markup like border=2 has given way to unweildy CSS like style=”border:2px solid black”. In some ways the need for specialized domain knowledge has gone up, not down.

Visual programming is an oft-tried, though so far largely unsuccessful way to lower the barrier to programming. Pipes was a great effort, but YQL proved more useful and popular. Google just announced new visual developer tools for Android in an attempt to bring mobile app creation to the masses. Content management systems are getting better and broader every day, allowing more and more complex websites to be built with less time touching source code.

I look forward to the day that computational thinking can suffice to create the majority of computational objects. I suspect that day is still fifteen to twenty years away.

It’s true.

More people are playing Predictalot today than Mafia Wars or Zynga Poker… On Yahoo!, that is.

In fact, Predictalot is the #1 game app on Yahoo! Apps by daily count. By monthly count, we are 5th and rising.

A prediction is being made about every three minutes.

Come join the fun.

predictalot most popular game app on yahoo 2010-06-12

In 2003, we wrote a paper titled 1 billion pages = 1 million dollars? Mining the web to play Who Wants to be a Millionaire?. We trained a computer to answer questions from the then-hit game show by querying Google. We combined words from the questions with words from each answer in mildly clever ways, picking the question-answer pair with the most search results. For the most part (see below), it worked.

It was a classic example of “big data, shallow reasoning” and a sign of the times. Call it Google’s Law. With enough data nothing fancy can be done, but more importantly nothing fancy need be done: even simple algorithms can look brilliant. When in comes to, say, identifying synonyms, simple pattern matching across an enormous corpus of sentences beats the most sophisticated language models developed meticulously over decades of research.

Our Millionaire player was great at answering obscure and specific questions: the high-dollar questions toward the end of the show that people find difficult. It failed mostly on the warm-up questions that people find easy — the truly trivial trivia. The reason is simple. Factual answers like the year that Mozart was born appear all over web. Statements capturing common sense for the most part do not. Big data can only go so far.*

That was 2003.

In the paper, our clearest example of a question that we could not answer was How many legs does a fish have?. No one on the web would actually bother to write down the answer to that. Or would they?

I was recently explaining all this to a colleague. To make my point, we Googled that question. Lo and behold, there it was: asked and answered — verbatim — on Yahoo! Answers. How many legs does a fish have? Zero. Apparently Yahoo! Answers also knows the number of legs of a crayfish, rabbit, dog, starfish, mosquito, caterpillar, crab, mealworm, and “about 133,000″ more.

Today, there are way more than 1 billion web pages: maybe closer to 1 trillion.

What’s the new lesson? Given enough time, everything will be on the web, including the fact that hungry poets blink (✓). Ok, not everything, but far more than anyone ever imagined.

It would be fun to try our Millionaire experiment again now that the web is bigger and search engines are smarter. Is there some kind of Moore’s Law for artificial intelligence as the web grows? Can sentience be far behind? :-)

__________
* Lance agreed, predicting that IBM’s quest to build a Jeopardy-playing computer would succeed but not tell us much.

Sunday I returned from a trip to Bangalore, India, where I gave a talk on “The Automated Economy” about how computers can and should take over the mechanical aspects of economic activity, optimizing and learning from data in the way people cannot, with detailed case studies in online advertising and prediction markets. You can read the abstract, watch archive video of the talk, view my talk slides, browse the official pictures of the event, or see my personal pictures of the trip.

Some say everything’s bigger in Texas (most vociferously Texans). They haven’t been to India. My talk is part of Yahoo!’s Big Thinkers India series — four talks a year from (so far) Yahoo! Research speakers. If the Thinking isn’t Big, the crowds certainly are — the events can draw close to 1000 attendees from, apparently, all over India. Duncan Watts says its the largest crowd he’s spoken too; me too. This time they disallowed Yahoo! employees to attend the main event and the hotel ballroom still filled to capacity.

Here is a linked-up version of my journal entry for the trip, a kind of windy and winded thank you letter to Bangalore. If you’re not interested in personal details, you might skip to Thoughts on Bangalore.

Getting there

The Philadelphia airport international terminal is dead empty. I breeze through security — the only one in line. I’m inside security two hours early thinking that either the recession is still in full force or traveling internationally on a Monday night out of Philadelphia is the best ever. Maybe not. Get on plane. Wait two hours on tarmac. Apparently a two hour layover isn’t enough leeway on international flights. Miss my connecting flight in Frankfurt by a few minutes. Team up with a fellow passenger in the same boat. We are rebooked via Dubai. Fly directly over Bagdad. Dubai is an impressive airport. Endless terminals lined with upscale shopping. Packed with Asians, Europeans at midnight and beyond. From there, Emerites Air to Bangalore. Only 9 hours behind schedule. Sneezing fits begin after 28 hours of airplane air.

Day 0: Yahoo! internal practice talk

Driver right there outside baggage claim, nice guy. Takes me to hotel. Over an hour. Traffic. Time for shower, NeilMed nasal rinses (bottled water), Sudafed, but not sleep. Call home. Yahoo! Messenger with Voice doesn’t roll off the tongue like ‘Skype’, but it rocks. Super clear and dirt cheap. Lauren and the girls are so sweet. Miss them. To Yahoo! office. Meet Anita, Mani. Time for Yahoo! internal version of Big Thinkers talk. Nose is still running. Drips and wipes during my talk. Talk goes well but I run out of time for prediction market section and this seems what people are most interested in. I’m glad I had the practice run to work out the kinks and rebalanced the talk. Back to hotel. Call home again for a recharging dose of home. I missed Ashley’s graduation from pre-school: she did great: they sang six songs and she knew them all. She was dressed up in a yellow cap and gown. I’m upset I had to miss such an adorable milestone but am proud of my little girl (and dismayed she is rapidly becoming not so little!). More NeilMed. Room service. (Called “private dining” here — sounds illicit.) Sleep! For a few hours at least. Wake up in the middle of the night since it’s NY daytime. Finally get back to sleep again.

Day 1: Meetings

Hard to wake up at 9am = midnight. Shower. Feel 1000% better. Driver takes me to the Yahoo! office. It’s in a complex with Microsoft, Google, Target, Dell, and many other US brands. Once you’re inside it’s like every other Yahoo! office except the food — built essentially to corporate spec. Meet with Anita, Raghu, and Rajeev: go over PR angles and they brief me on the media interviews. These guys and gal are on top of things. Meet with Mani and her team: great group. Skip intern pizza talks because I can’t eat cheese, going for the cafeteria instead. Mistake. Order a veggie grill thinking that since it’s grilled, it’s cooked enough. I only take a few bites of this before thinking it’s too risky. I eat some bread and Indian mixtures. Not sure what the culprit is but something doesn’t sit well in my stomach. Give prediction markets portion of my talk to a few interested people in labs. Very sharp group. Meet with Dinesh and Sachin, their intern, and one other. Interesting work. Meet with Chid and Preeti on Webscope. Back to hotel. Call Lauren. Good to hear her voice. Ashley wants to say hi. She’s so adorable. She finds it hilarious that I am about to have dinner while she is eating breakfast. I can hear her laughing uncontrollably at the thought. Sarah says hi too and even ends our conversation without prompting with a “bye, love you”. I go down to the restaurant for dinner. Have a chicken Indian dish with paratha (is it lachha paratha?) bread. Spicy (sweat inducing) yet so delicious. The bread is fantastic — round white with flaky layers. Back to room. TV. CNN. CNBC. ESPN. Hard to sleep. There is an incredible thunderstorm with torrents of rain. I open my balcony door briefly to catch its power. I find out later that monsoon season is just beginning. I also find out that it rained so hard and so long that the roads flooded to the point of becoming impassible. In fact, Anita, the Bangalore PR lead, had a near-disastrous experience in the rapidly flooding streets on her way home and had to turn back and check into a hotel before going home briefly in the morning and then back to Yahoo! for our am meeting. Finally get to sleep.

Day 2: My talk!

Hard to wake up at 8:30am too. Talk’s today! Nerves begin. Media interviews are first! Even worse. Turns out they went fine. Two nice/sharp reporters, especially the second one who really knows her stuff and spoke to us (Rajeev and I) for 1.5 hours. She’s especially interested in the prediction market stuff since that is something new. She may write two articles (for Business World India). Lunch, then a bit of time to rest and freshen up. Stomach is not doing well. Pepto to the rescue. Back down to lobby. They take my picture in the courtyard. Then into the ballroom. Miked. Soundchecked. They accept a final last minute change to my slides: hooray! Room starts filling. 100 people. 200. 300. Now 500. It’s time to start! Rajeev gives a very nice intro. I walk up the stairs onto the stage. I’m miked, in lights, speaking in front of 500 people expecting a Big Thinker. Here I go! “Four score and seven years…” Ha ha. Actually: “Thanks Rajeev, and thanks everyone for your time and attention. I am happy and honored to be here. I’m going to talk about trends in automation in the economy…”

David Pennock speaking at Yahoo! Big Thinkers India June 2009Audience at Yahoo! Big Thinkers India June 2009

65 minutes later “Thank you very much.” Applause. I think it went well: one of my better talks. I covered everything, including the prediction market stuff. It turns out, like at Yahoo!, and like the journalists, the audience is more interested in prediction markets than advertising. Lots of questions. Some I follow, some I can’t parse the words, others I hear the words but just don’t understand. I do my best. Several people mention they follow my blog: gratifying. After the official Q&A session ends, there is a line up of folks with questions or comments and business cards. It’s the closest I’ll ever be to a rock star. A handful of people wait patiently around me while I try to get to everyone. Eventually the PR folks rescue me and take me to a “high tea” event with Yahoo! Bangalore execs and some recruiting targets. Relief and euphoria kick in. It’s over. I talk with a number of people. I make my exit. Private dining. Call home. Lauren has explained to Ashley that I am on the other side of the world, so when she has the sun, I have the moon. So I can hear Ashley asking in the background, “does Daddy have the moon?” I do. She can’t stop laughing. A repeat of game 6 of the Stanley Cup is on Ten Sports India. I watch it, getting psyched for Game 7. I check online for Ten Sports schedule. Game 7 will be on at 5:30am! I can’t miss that! Set my alarm. Try to sleep. Can’t sleep. Try to sleep. Can’t sleep. Try with TV on. Can’t sleep. Try with TV off. Can’t sleep. Finally fall asleep… Alarm!

Day 3a: Penguins win the Stanley Cup!

Really hard to wake up at 5:30am. Actually maybe not quite as hard since it’s 8pm in my head. Game on! Nerves are racked up. Can’t sit down: bad luck. Pacing. No score first period. Tons of commercials, all for Ten Sports programming: wrestling, cricket, tennis. Every commercial repeats three times. Is period two coming? Yes, it’s back on! Pens score first! Fist pumping and muted cheering. Can they really do this? No sitting rule in full effect. Pacing. Pens score again! Talbot second goal. Wow, is this real? Can it be? Don’t think about it yet. Don’t celebrate to soon. Plenty of time left. Period two end at 2-0. Unbelievable. All the same commercials come back, three times each. Period three begins. Stand up. Pace. Clock ticks. Pens are playing too defensive: not taking shots, just throwing the puck out of their zone. This isn’t good. Detroit is getting tons of chances. Fleury is awesome. Five minutes left. I let myself think about winning the cup. Mistake! Detroit scores! It’s 2-1! Nerves are ratcheted up beyond ratcheting. I think about it all slipping away. How awful that would feel. If Detroit ties it up, imagine the let down, the blown opportunity. Clock ticks. More chances. More saves. More defense. It’s working! Detroit pulls their goalie. Pressure. Final seconds. Faceoff in our zone. Detroit wins control. Shot. Rebound. Right to a Red Wing — Nick Lidstrom — in perfect position. He shoots. Fleury swings around. He saves it! It’s over! Pens win the Cup! Super fist pumping, jumping around, dancing, muted cheering. They did it! How amazing it feels after last year’s loss to the same team. After falling behind 2-0 and 3-2 in the series. They came back! A delicious payback with the same but opposite script as last year: a two goal lead cut in half in the waning minutes, a flurry of attempts at the end including a few-inch miss of the tying goal in the last seconds. These guys are young and have the potential to rule hockey for several years if they’re lucky. Mario Lemieux is on the ice. How sweet. Twice as player, now as owner, the one who saved hockey in Pittsburgh. What a year for Pittsburgh sports! Two nail biter games, two comebacks, two championships. City of Champions again. Too bad the Pirates have no shot to join them in a trifecta. Back to sleep.

Day 3b: Sightseeing

Phone rings at 11am — my driver is here. Off to do some whirlwind sightseeing. Everyone here who finds out I have a day off recommends I leave Bangalore — Bangalore is just not that nice, nothing really to see, they say. They all recommend Mysore, 3.5 hours away, but that is too far for my comfort level given that my flight is late tonight and it’s supposed to thunderstorm. We start with some souvenir shopping on “MG Road”. My driver takes me to a store and waits in the car outside. I walk in an instantly there are people greeting me and showing me things. One aggressive man takes over and remains my “tour guide” through the whole store. The fact that I reward his aggressiveness by following along and eventually buying stuff will only bolster him to do more of the same in the future. Annoying but clearly it works. I do negotiate him down, but I leave still feeling I didn’t bargain hard enough and with a bit of distaste in my mouth that I fueled and validated the pushy tactics. Next we drive past parliament and the courthouse. Impressive, large, old buildings. But I can just gaze and take photos from the car — can’t go inside. Next we drive past Cubbon Park — tree lined paths and flower gardens in center city. Next is ISKCON temple. But it’s closed. So one more round of shopping at a place called Cottage Industries. I’m wary given the last experience, but go anyway. This one is better. Again one person escorts me around but I feel less pressure. Plus I’m more prepared to say no and negotiate harder. I leave with what seems like a fair amount of value in goods. I recommend Cottage Industries to future visitors: more professional, more familiar (items have price tags), lower pressure, greater variety, and higher quality than at least the first shop I visited. Now we’ve killed enough time and the ISKCON temple is open. It’s a giant Hare Krishna temple. The parking lot is full. I tell the driver it’s ok — we don’t need to go. He says “you go, you go”. “Ok” I say. We drive around again to the same full parking lot. The attendant waves at us to leave, blowing a whistle. My driver is talking to him. They are talking quite heatedly. The attendant in his official looking uniform is waving us on vigorously. Although I can’t understand the words, he is clearly telling us the lot is full and we must leave immediately — we are holding up traffic. My driver is getting more insistent. They are yelling back and forth. I have no idea what he says but it works. The guard let’s us in. Meanwhile another car sees our success and tries to argue his way in too but to no avail. I ask my driver what he said: he simply replies “don’t talk”. Indeed once we’re in, there is an empty spot. We put all my bags in my suitcase in the trunk and cover my backpack. We take off our shoes and my driver leads me to the temple. He knows the back entrance and is guiding me to cut in front of lines everywhere. We walk past the main attraction: the altar with some people on the floor worshiping. Then the line weaves past a gift shop of course: I buy a crazy looking book (Easy Journey to Other Planets). We need to kill some time. We go to the gardens again to walk around. We walk into the public library. Most books are in English. Most seem old and worn. The attendant says the library is 110 years old. We start walking through the garden but I am paranoid about mosquitoes/malaria so we turn around early to return to the car. We go to UB City where I meet Rajeev. It’s a thoroughly modern office tower half owned by Kingfisher of Kingfisher Airlines. The building is full of high-end shopping like almost any upscale western mall with all the same brands. Here is the Apple Store. Here is Louis Vuitton. We have dinner at an Italian restaurant that could be anywhere in the western world, owned by an Italian expat. The only seating is outside and I remain worried about mosquitoes but don’t see any. The food is good and the conversation is good.

This place is the closest I’ve seen of the future of Bangalore. In the center of town, a gorgeous building filled with gleaming shops and tantalizing restaurants and bars, with apartments and condos within walking distance, and a palm-tree-lined street leading to the central town circle and the park. As Rajeev says, though, whereas New York has hundreds of similar scenes, Bangalore has one. For now.


Thoughts on Bangalore

Bangalore is a city of jarring contradictions, a hard-to-fathom mix of modernity and poverty. Signs with professional logos and familiar brands are set askew on dilapidated shacks and garages lining the road. While many live on dollars and day and others beg, the majority are smartly dressed (men invariably in button-down shirts), have mobile phones, and are intelligent and friendly. There are gleaming office towers indistinguishable from their western counterparts, yet a strong rain can flood the roads to the point of become impassible for hours and day-long blackouts aren’t uncommon. Many billboards are in English, sporting familiar brands and messages. Others, like sexy stars promoting a Bollywood film, are entirely familiar, English or not. Others are impenetrable. Still another advertises a phone number to learn why Obama quoted the Koran.

BMWs and Toyotas join bikes, motorcycles, pedestrians, aging trucks and buses, and colorful open-air motorized rickshaws in a sea of disorganized line-ignoring sign-ignoring traffic. People drive here the way New Yorkers walk sidewalks: weaving past one another in a noisy self-organized tangle that somehow — mostly — works. You can eat outside in a restaurant bar next to upscale shops, a fountain, and smiling yuppies, yet worry that a malaria-infected mosquito lurks nearby or that a washed vegetable will turn a western-coddled stomach deathly ill. When two people ride a motorcycle, as is common, only the driver wears a helmet — the passenger clinging on behind does not: new and old rules on display atop a single vehicle. And the traffic. Oh, the traffic. Roads are clogged nearly every hour of every day. My Saturday of sightseeing was as bad or worse than weekday rush hour. The extent of congestion itself illustrates Bangalore’s two faces: so many people with youth (India is one of the youngest countries in the world), energy, purpose, and the means and intelligence to accomplish it overtaxing a primitive infrastructure. Buildings are going up according to western specs, but under old-time rules where corruption reins and bribery is an accepted fact of life by even the western-educated aspirational class (about 20% and growing, according to Rajeev).

Thoughts on Yahoo! Labs Bangalore

The folks I met are impressive. Rajeev has done a great job hiring talented, driven folks. Mani‘s group of research engineers is fantastic. One is headed to Berkeley for grad school and asks great questions about CentMail. Another proposes an attack on Pictcha. Another (Rahul Agrawal) has read up deeply on prediction markets, including Hanson’s LMSR.

Thoughts on the Yahoo! Big Thinkers India program

The whole event was organized to precision. Anita, the PR lead, was incredible. I especially appreciated the extra “above and beyond” touches like having someone pick up Yahoo! India schwag for my family and send it to my hotel after I forgot: so nice. Raghu, who arranged the media interviews, is supremely organized and on top of his game. The fact that the event draws such a large crowd shows that there is great thirst for events like this in Bangalore. I’m not sure whose idea it is, but it’s a brilliant one: great marketing and great for recruiting.

Thank you Bangalore

In sum, thanks to the people of Bangalore for a fascinating and rewarding trip. Thanks to Rahul at the travel desk whose instant replies about the driver arrangements calmed my nerves on the stressful day of my departure. Thanks to the Yahoo! folks who arranged and organized my talk, and the Yahoo! Labs members for seeding an exceptional science organization. Thanks to my driver who got me everywhere — including into full parking lots, back entrances, and fronts of lines — with efficiency, safety, and a smile (when I tipped him, I tried to think wwsd and wwdd: what would Sharad or Dan do?). Thanks to those who attending my talk and whom I met afterward: it’s gratifying and invigorating to see your level of interest and enthusiasm (and your numbers). And thanks Bangalore chefs for keeping any stomach upset relatively mild and brief.

At the airport on the way out, the flight is overbooked and they are offering close to US$1000 plus hotel to leave tomorrow. Not a chance. It’s been fun and an adventure but my nerves are on high and I miss my family: it’s time to make the 20+ hour journey home.

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