Using Apple Find My Friends for continuous location tracking

Posted on October 18, 2011 by Sameer

At Fuse we like trying out new things and we always have very willing folks to sign up with. We started continuously monitoring each others locations 24×7 yesterday. As I came into work today it was great to see everyone converging into our workplace.

I have used other services like Glympse and many others which let me do this too but I never reached this type of critical mass so quickly so haven’t seen it across 10 people in real-time.

The cool thing is that this is integrated with Siri so I can just pick my phone and ask the question “Where is Flynn right now?” and the phone tries to track him down as best as it can and shows it to me:

In an ideal world this is awesome. But it’s a little involved to get off the grid when you want to and at least at this point it’s harder to remember that others could be seeing you.

Possible ways to make this better would be:
1. Notify me when a friend looks me up and views my current location – adds some level of symmetry.
2. Something at the level of a hardware button to easily turn off my location sharing
3. Get rid of the stitched leather

Other than that I think it’s designed pretty well and it’s clear they fought off many complicated considerations to come up with a solution that’s nuanced enough for something as sensitive as location sharing and still retains simplicity.

Facebook: stop worrying about sharing, live your life, leave the rest to us

Posted on September 23, 2011 by Sameer

Facebook launched the Like button 18 months ago and it has had a huge impact on how people browse and share information and form associations with other entities. Within days websites had integrated Facebook social plugins which made it super easy to feed stuff back to Facebook and share with your friends in a frictionless way. Though Facebook started collecting information about every webpage you went to as long as there was any social plugin on that page, you still had to take an additional step to decide if something was worth sharing with your friends or else they would never see it. Let’s take an example:

I visit the NYT webpage and read a couple of stories, say A and B. I then decide that story A is worth sharing and hit the “Recommend” button and it gets posted to my feed. My friend arrives on NYT and sees the headline for story B. He doesn’t know that I checked it out as well but he is interested in it and even clicks on it but he never shares it either. Then a third friend is now on NYT trying to decide what she should read. Given the old scenario, only story A would be recommended to her. The information about story B and two friends interacting with it has been lost.

Maybe it’s lost of for a good reason – it probably wasn’t worth sharing. One could argue it keeps the signal to noise ratio high. But the best way to deal with information overload is generating more information, not less. With enough training data, and meta information like time spent and other derived engagement metrics it won’t be too hard to use that lost information to come up with even better suggestions.

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iPhone vs Foursquare: comparing what they know about me

Posted on April 22, 2011 by Sameer

One of the biggest technology news this week has been the announcement made by Alasdair Allan and Pete Warden, researchers at O’Reilly, that theiPhone keeps a log of every location you have been to over the past one year and more. One could argue that it isn’t really news but it definitely is a rude surprise to most people. More so because the researchers also made a tool which makes it super easy for anyone to easily parse the contents of the file their own iPhone has been keeping on them.

Though I agree that saving an indefinite history of sensitive location data without explicit user notification is a terrible oversight at the least, I was also tempted to see what my own data held. So I went ahead and here’s what it looks like.

My iPhone faithfully recorded my road trip halfway across the country, my SXSW visit to Austin, Bay Area and LA trips and also my trip to Michigan and Ohio. I think it makes a very interesting sharing object at this level of zoom. Especially because I have been voluntarily giving that data to Foursquare anyway. Foursquare is a lot sparser than the iPhone data but it has more explicit knowledge of the exact business/venue I went to as opposed to the iPhone data that can only be used to make a reasonable guess. However, overall the data that the iPhone has been accumulating is obviously more exhaustive.

I am curious to run more detailed analysis on my own data, and possibly compare it with other people I know and other data sources I have to see what interesting stuff I can find. For example, it would be cool to see how much time my wife and I spend with each other and how it correlates to how many steps I took that day, what I ate, or what music I listened to.

Are we really as unique and different as we like to believe or are we just predictable dots on the map? At a higher aggregate level, data from cellphone carriers has already been used to find that we actually are quite predictable!

A week at work as a FUSE Labs PM

Posted on April 19, 2011 by Sameer

I am a Program Manager at FUSE Labs. If you were to ask me “What does a PM at FUSE Labs do?”, my short answer would be: whatever it takes to rapidly innovate on an idea and bring it to fruition. This often demands a very fluid set of tasks that span different skills. As PMs move along a project they also move along a spectrum of things to do. Often, while straddling multiple projects, there’s opportunity to exhibit a full spectrum within a very short time. In a recent week I ended up doing just that. This snapshot of that week is an illustrative example of what a PM does at FUSE Labs:

Monday
Spec writing. Formulate a development plan for a new project including goals, scenarios, implementation details, evaluation plan and schedule.

Tuesday
Demo a project at a public event. This one, specifically, is where I demo Project Montage at the Hacks/Hackers event in Seattle.

Wednesday
I get down and dirty with HTML5 and Jquery as I code away on the project most of this day. The project would benefit from some additional development resources.

Thursday
Conduct discount usability study to identify usability issues in a project under development. I am formally trained as a User Experience Researcher and I am always looking for ways to get useful and timely evaluation in the cheapest way possible.

Friday
I receive a “Ship it” badge as a recognition for another project that was completed and brought to market in the past.

So in summary, my week = spec + demo + coding + usability study + recognition. This, actually, might be different for a different PM depending on their background, passion and project. In general, folks at FUSE are very versatile and multi-talented which makes the workplace a lot of fun!

New York subway map as an interactive string instrument

Posted on January 31, 2011 by Sameer

Alexander Chen from Creative Labs at Google has made this beautiful interactive string instrument out of the subway map of New York. And, of course, it’s all in HTML5.

Conductor: www.mta.me from Alexander Chen on Vimeo.

You can read more on his blog here. [via Gizmodo]

When iTunes lies: Finding the right Nusrat Fateh Ali Khan – Massive Attack song

Posted on January 18, 2011 by Sameer

In 1990, Nusrat Fateh Ali Khan collaborated with Michael Brook and released an album called Mustt Mustt. [You might know Michael Brook as the guy who invented the Infinite Guitar which was used for the haunting notes on U2's With or Without You] It combined a traditional Qawalli style song with guitar and produced a new kind of sound. The title song of that album was a big hit and inspired Massive Attack to remix it. This remix of the song became a smash hit and reached an even wider audience.

I was unaware of this song until 1996 when it was used in a Coca Cola commercial during the Cricket World Cup. It was an interesting ad and the sound went really well with it.

The Indian Cricket focused Coca Cola ad (1:04)

After I saw the ad, I tried to find out what this song was called (no SoundHounds or Shazams back then). Eventually I found the song through a friend who let me “borrow” the MP3. The file name on the song I got said ‘Nusrat Fateh Ali Khan – Mustt Mustt (Massive Attack Remix).mp3″. I had no idea that Massive Attack was actually a band and assumed it was some fancy name given to the remix. But I enjoyed the song and … Continue reading →

Religious stereotypes visualized using Web Seer

Posted on October 22, 2010 by Sameer

Blame it on the Voices covered a venn diagram published by reddit user prateekmi2 today which shows the search terms that people use for different religions on Google search. It exposes the different words associated with different religions and the common words are equally interesting.

venn diagram

Web Seer is another visualization tool built specifically for comparing and contrasting google search suggestions for two different search terms. I decided to augment the venn diagram above with the web seer visualization – it’s just another way to present the same information.

As you can see from the visualization, “stupid” is the most frequent word used on Google to complete the sentence “Why are muslims so …” that is also used to complete the sentence “Why are christians so …”. Other common words for both religions are “intolerant” and “hateful”. On the extremes,the words associated with Muslims are “angry” and “violent” while those associated with Christians are “judgmental” and “mean”.

muslims christians

Contrasted with the unique words associated with Muslims, those associated with Jews are “cheap”, “successful” and “smart”. However, the interesting common word for both Muslims and Jews implies “Why are Muslims and Jews so hated?”

muslim jews

According to this visualization, there is nothing in common between words associated with Jews and Christians, however, the original Venn diagram above found the word “annoying” to be common enough.

jews christians

Extra

India is a democratic country with separation of church and state. However, though it’s dominantly Hindu it still hosts one of the largest Muslim populations in the world in terms of absolute numbers. I was curious to see how the two religions compare on Google. There were zero search suggestions for the term “Why are Hindus so …” so for this case I shortened the search terms to “Why are Hindu” and “Why are Muslim”. Unfortunately, there were no words commonly associated with the two religions but it was interesting to see Hindus’ discontent with the movie Avatar and the color of the depictions of their gods.

muslims hindus

Are people really moving into Seattle?

Posted on June 18, 2010 by Sameer

Forbes recently published a visualization based on IRS data which shows where Americans moved between 2008 and 2009. You click on the city name that you are interested in and it shows you a dense sets of lines showing migration paths. Red lines show that there was a net number of people moving out whereas black lines show a net number of people moving in. It’s interesting to look at, but really really hard to read, and almost useless due to that. But that’s a different story.

Screen shot 2010-06-18 at 9.12.08 PM

I found it interesting to compare this data with the temperature heatmap of that day. We have had an awfully cold spring but this heatmap really drives in the point. That week, the Pacific Northwest was the coldest region in the country! Makes one wonder, if people really are moving to Seattle in hordes, do they really know what they are getting into?

I average 4 dreams a night – what’s the shape of your sleep?

Posted on May 22, 2010 by Sameer

Every night, we surrender ourselves to the most enigmatic aspects of our reality – sleep. We voluntarily (or involuntarily) enter this dormant state of being for 1/3rd of our life, each time waking up hours later to face the remaining 2/3rd of of the day.

What exactly happens when we are unconscious? You can always go to a sleep lab and have all sorts of machines monitoring your brain frequencies and other vitals so that you can learn more about how you sleep. But if you want the convenience of doing it yourself, you can try this $0.99 app for the iPhone called Sleep Cycle.

The setup

You start Sleep Cycle, leave it running, and place the iPhone face down on the mattress, somewhere near your head area. SleepCycle uses the accelerometer in an iPhone to detect motion as you sleep. This motion is interpreted as a proxy for how active your brain is at that time. When you wake up the next day, you can see a graph of your sleep activity the past night.

Certain levels of activity are associated with different stages of sleep. Lowest activity corresponds to deep slumber when we have no dreams. Some activity corresponds to the stage of Rapid Eye Movement when we have all of our dreams. And high activity corresponds to light sleep – the kind that leaves you tired when you wake up.

Sleep graphs

I have been monitoring my sleep this way for a couple of months now. I have noticed that on average I seem to have 4 instances of REM like activity levels. Does that mean I have as many distinct dreams each night? Most research points out that this is in fact close to the average number of dreams humans have. However, I rarely remember my dreams; so this is insightful for me to understand that my brain is being creative while I am unconscious

And then there are some days where I have interesting variations. For example, the two graphs below are quit extreme when compared to each other. According to the first one I plunged straight into deep sleep as soon as I lied down. But within an hour I was almost awake. I stayed in the high activity area dipping twice to catch 2-3 quick dreams but was pretty much sleeping lightly for the rest of the night. I am guessing it’s one of those nights when your dreams take input from what’s actually happening outside and distorts it into a fantasy dream world experience. Unfortunately, I don’t remember what I dreamt that night so I have no way of validating this.

The one on the right, however, suggests that I stayed in deep sleep for most of the night. I only had a dream around 5:00 am before going back to deep sleep. Is this one of the nights where I actually remember what I dreamt since there was only one? I am not sure because I really couldn’t remember what I dreamt.

Waking up at the “right” time

If you look closely at all the graphs there is one thing in common to almost all of them. They all end on an uptick in my sleep graph – did you notice that? This is no co-incidence. This is the second feature in this app which makes it an awesome alarm clock. You set the time you want to wake up and then use the app as described earlier. Around 30 minutes before your wake up time the app starts looking for increase in activity. As soon as it notices your body’s activity level going up, it triggers the alarm even if it’s 10s of minutes before your desired wake up time. The theory is that if you are woken up at a time when your body is naturally trending towards being active then you wake up feeling more active and less groggy.

I am not sure I can say for certain that this helped me – it’s really hard to notice difference in grogginess – and I am never super happy to wake up And that’s the other problem with the app – there’s no snooze button. So if I don’t want to wake up, I have to quit the app to shut the alarm. Then it stops recording consequent activity, though, so the graphs are not true to the actual time you wake up in case you snoozed.

Augmented mindfulness

At SXSW this year, Robert Fabricant of Frogg Design described Augmented Mindfulness. It’s the idea of collecting information about yourself, processing it, reporting it and then reflecting on it to effect change in yourself.

Augmented Mindfulness.jpg

Sleep Cycle is a great app for the curious and I highly recommend trying it out. However, this data can’t be exported, nor can it be analyzed or visualized in other ways. So it’s limited in how much it can help you in making deeper insights into yourself. It would be great if I could correlate this data with other data about me. For example, I could look at my tweets or social updates of the preceding day to analyze my sentiment and derive my mood and then find correlations with my sleep patterns and how I was feeling that day. Or I could compare it with the food I ate that day that I capture in my food journal.

My Fitbit finally got delivered today. It also lets you monitor your sleep and helps you reflect on your data. It will be interesting to compare how the data differs across the two systems. I will find out soon!

Sameer Halai