Trying out LucidCam and the YouTube VR180 Format

I’ve been playing with a LucidCam recently as part of my work. LucidCam’s is a really easy way to start taking 180 degree VR content, both with photos and videos. Just turn it on, choose a media mode, and then point and press the “shutter” button to shoot. There’s no viewfinder, though you can enable one through your phone if you tether it to the camera via a direct wifi connection.

The 180 degree lenses basically takes away the need to focus – as LucidCam says, you can “capture moments from your perspective”, which just means you can capture everything (technically more) your eyes see, so there’s no need to spend time framing a shot.

Below is a playlist of some bike rides I took this week in the South Bay (you can view in 180 degree 3D with a VR headset like the Google Daydream one). The first set of videos is from an evening commute ride from Apple in Cupertino to Mountain View, the second set is an early morning ride through Palo Alto and Los Altos.

After Millions of Dollars, Microsoft Bing is Just as Smart as…Las Vegas [When Data Fails]

At Kellogg, we learned that people in aggregate tend to be quite correct (for example, say you have a random amount of jelly beans inside a big jar. Ask people to guess the amount of beans. When you average all the guesses, it will come out quite close to the real number, even if the real number is large and random, like 1,724).

According to How Microsoft got so good at predicting who will win NFL games, Microsoft Bing is an awesome prediction guru of human intelligence, machine learning, and big data:

Bing Predicts is run by a team of about a half dozen people out of Microsoft’s Redmond, Washington headquarters. It uses machine learning and analyses big data on the web to predict the outcomes of reality TV shows, elections, sporting events, and more.

How Microsoft got so good at predicting who will win NFL games

In 2014, Bing was 67% accurate predicting NFL winners.

In all, the Bing Predicts model considers hundreds of these different signals, or data points, for each event, like an election or game, Sun said.

So far this year[2015 to game three], Bing is about 60% accurate in predicting NFL matchups.

Sounds great, right? However, my first thought was, who cares about winners? I can’t bet on winners, this is why the spread exists, to create (theoretical) 50/50 bets that bookies can make stable revenue from.

My next question is, in this awesome model built from millions of dollars in labor and computing power, are the prediction results better, hopefully at a statistically significant (p = .05) level, than information I could get free from a public resource? How little can I spend to get reasonably close results to aid in my for-profit wagering?

Let’s look at Las Vegas betting spreads.

Booking Odds

According to Inpredictable.com and its 2013 article Is the NFL Betting Market Getting More Efficient?, the answer is NO, Bing’s modeling is no better than me looking at the latest odds online.

From 1989 to 2013, Las Vegas favorites were correct 66.8% of the time. With a sample size of 15 years, and looking at the chart above, I can say that Vegas is pretty good.

1 signal – Vegas odds – versus hundreds of signals – Microsoft Bing = the same result.

Great work, Microsoft.