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Meet this Bill from Microsoft.

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Meet Bill Thies , who’s products have a way of bridging the digital divide in rural areas.

He collected a clutch of degrees from MIT, completed his Ph.D. in Computer Science in 2009, began his career programming languages and compilers for multi-core processors and micro-fluidic chips, and joined Microsoft as a researcher in the Technologies for Emerging Markets Group. Here Bill Thies found his calling. His technology products have a way of leaning towards bridging the digital divide in rural areas, bringing life-needs like education and healthcare within the reach of people deprived of it, helping the less empowered face life with confidence, using only the cell phone as a weapon. He describes his work as “building Information and Communications Technologies (ICTs) that contribute to the socio-economic development of low-income communities — Information and Communication Technologies for Development (ICT4D).” Not surprisingly, his neatly-organised one-page digital mantelpiece is crammed with awards and citations.

A short-list of his — and his team’s — work: Interactive voice response (IVR) Junction that enables anyone with a basic mobile phone to participate in social media like Facebook, YouTube and the like. CGNet Swara, a voice portal for citizen journalism in rural India. A low-cost system for audience polling that uses computer vision and printed cards instead of electronic “clickers”. A project with Operation ASHA and Innovators in Health, on using biometrics to improve adherence to tuberculosis medications. Studies on how people respond to human-computer interaction and mobile crowdsourcing. Co-organising DataDev 2012 — the international workshop on mobile data collection in the developing realm. Teaching a course on building mobile services for emerging markets. Among projects in the pipeline is VidWiki, a system that makes it easy to translate videos into local languages (say, for online education) into a style called TypeRighting.

I ask Bill of his switch from core-tech to developing apps, primarily to help urban and rural disadvantaged groups. “I’ve always wanted to work on projects that could have a large social impact,” he says. Upon graduating, he decided to get closer to low-income communities in the developing countries, “to see if there was a role for technology to contribute to their health, education and well-being.” He had tech skills, he would train them towards projects meant “to address the most pressing problems” of the marginalised. He felt India was the place for him to match his skills with his dream.

In Bengaluru, the Microsoft office provides him with resources/equipment/personnel; walking outside, he can interact with people with limited literacy, “with people who have never touched a computer before”. Having both realms close-by presents opportunities to develop technology for social benefit quickly.

India, to him, is much more than a cold platform to practise his skills for the benefit of “low-income populations”. “I enjoy living and working in India. There is tremendous energy, diversity. I’m learning something new everyday. And as a vegetarian, I love the food as well!”

It is rewarding that his tech-apps help disenfranchised people in remote places, but what is truly heartening to him is how they “invent creative ways to use the tools”. The voice-forum where callers in rural areas can share cultural content, to his surprise, “found a large uptake amongst the visually-impaired populations… they testified this was the first medium where they could express themselves and people would listen”. He landed here hoping to stay for three to five years, but now has no plans to leave. India has become very special for this young techie. Apart from greatly enjoying his work, he found his wife here. “In fact, I got married to the girl in the office next to mine!”

 

This article first appeared on Nov, 21 on The Hindu. Its was written by Geeta Padmanabhan. 

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I called a Startup Idea Stupid, and it turned out to be Pinterest!

For some cruel reason, I keep finding myself in the position of being introduced to things in their infancy (often before they are even launched), dismissing them as stupid, and then watching them become unbelievably popular. This has happened to me at least four times. Each time I vow never to call anything stupid again, and then, invariably, it happens again.

I’m not sure if there’s any lesson here other than a warning against arrogance, but I have two stories to share.

The first was in late 2009. I received an email from a guy asking to meet about his new project. I was a designer at the time, and he was looking for some advice, so I agreed to meet with him at the quintessential startup meeting place in San Francisco, The Creamery.

“I want to make an app for browsing catalogs. It’s like a fashion catalog, but you can organize and share outfits,” he said. He pulled out his iPhone and showed me a prototype that barely worked. The user interface was decent but clunky; it had side-swiping navigation that only worked every few swipes. He showed me what seemed to be an endless series of women’s dresses. “Nice,” I said. But I had already dismissed the idea. How on Earth would this 20-something guy in Silicon Valley reach his target market of middle aged women? And would they even want such a thing? Did they even own iPhones? I think I asked a series of questions, but I don’t even remember the answers.

“What a stupid idea,” I thought to myself.

As we finished our coffees, I think he sensed my apathy, and we parted ways. But just before I walked away, he asked a question:

“What do you think about the name we’ve been using? It’s called Pinterest.”

Then in 2012 I met a guy for dinner at an unassuming restaurant in New York. After we’d started eating, he handed me his phone and said, “I’m making an app that makes it easy to share video, kind of like Instagram.” The app was very well designed and engineered, especially for a prototype, but I’ve had a lot of experience with photography and video apps, and I knew the odds were hugely against him. The mobile video space is littered with the dead carcasses of previous attempts. How would this guy overcome all of the hurdles that the plethora of other attempts at mobile video have been unable to address?

The app had one awesome feature, though–it would only record when your finger was on the screen, so you could take a bunch of little videos through time and connect them together to build a story. But it was a self-contained app, with its own feed and no obvious viral mechanics. I couldn’t see it ever succeeding.

“What a stupid idea,” I thought to myself.

I liked the logo, though. It was a V on a green background, for the name “Vine.”

Thinking back on those meetings with Ben Silbermann, the founder of Pinterest, and Dom Hoffman, the founder of Vine, I am kind of disgusted by my reactions. Both of those guys are uniquely passionate and driven, and you can tell that within five seconds of meeting them. They saw the future and they built it. But for some reason, my reaction to their early attempts wasn’t to give them the benefit of the doubt—it was to immediately find problems with their ideas before dismissing them.

The future is extremely hard to see through the lens of the present. That’s why it’s so easy to dismiss an idea as something frivolous or useless, or call it a stupid idea.

Dustin Curtis is a developer, designer and blogger. He is the founder of Svbtle, a publishing and writing network.

I discovered it on Quartz. A version of this originally appeared on Dustin Curtis’s blog.

What the Hell is “Big Data”?

Big Data is THE biggest buzzwords around at the moment and I believe big data will change the world. Some say it will be even bigger than the Internet. What’s certain, big data will impact everyone’s life. Having said that, I also think that the term ‘big data’ is not very well defined and is, in fact, not well chosen. Let me use this article to explain what’s behind the massive ‘big data’ buzz and demystify some of the hype.

Basically, big data refers to our ability to collect and analyze the vast amounts of data we are now generating in the world. The ability to harness the ever-expanding amounts of data is completely transforming our ability to understand the world and everything within it. The advances in analyzing big data allow us to e.g. decode human DNA in minutes, find cures for cancer, accurately predict human behavior, foil terrorist attacks, pinpoint marketing efforts and prevent diseases. Take this business example: Wal-Mart is able to take data from your past buying patterns, their internal stock information, your mobile phone location data, social media as well as external weather information and analyze all of this in seconds so it can send you a voucher for a BBQ cleaner to your phone – but only if you own a barbeque, the weather is nice and you currently are within a 3 miles radius of a Wal-Mart store that has the BBQ cleaner in stock. That’s scary stuff, but one step at a time, let’s first look at why we have so much more data than ever before.

In my talks and training sessions on big data I talk about the ‘datafication of the world’. This datafication is caused by a number of things including the adoption of social media, the digitalization of books, music and videos, the increasing use of the Internet as well as cheaper and better sensors that allow us to measure and track everything. Just think about it for a minute:

  • When you were reading a book in the past, no external data was generated. If you now use a Kindle or Nook device, they track what you are reading, when you are reading it, how often you read it, how quickly you read it, and so on.
  • When you were listening to CDs in the past no data was generated. Now we listen to Music on your iPhone or digital music player and these devices are recording data on what we are listening to, when and how often, in what order etc.
  • Today, most of us carry smart phones and they are constantly collecting and generating data by logging our location, tracking our speed, monitoring what apps we are using as well as who we are ringing or texting.
  • Sensors are increasingly used to monitor and capture everything from temperature to power consumption, from ocean movements to traffic flows, from dust bin collections to your heart rate. Your car is full of sensors and so are smart TVs, smart watches, smart fridges, etc. Take my new scales (which I – as a gadget freak – love!), they measure (and keep a record of) my weight, my % body fat, my heart rate and even the air quality in our bed room. When I step on the scales they automatically recognize me, take all the measurement and then send them via Bluetooth to my iPhone which gives me stats on how my Body Mass Index etc. is changing. This information is then also synced with the data collected by my Up band, which tracks how many calories I have consumed and burnt in a day and how well I have slept at night.
  • Finally, combine all this now with the billions of internet searches performed daily, the billions of status updates, wall posts, comments and likes generated on Facebook each day, the 400+ million tweets sent on Twitter per day and the 72 hours of video uploaded to YouTube every minute.

I am sure you are getting the point. The volume of data is growing at a freighting rate. Google’s executive chairman Eric Schmidt brings it to a point: “From the dawn of civilization until 2003, humankind generated five exabytes of data. Now we produce five exabytes every two days…and the pace is accelerating.”

Not only do we have a lot of data, we also have a lot of different and new types of data: text, video, web search logs, sensor data, financial transactions and credit card payments etc. In the world of ‘Big Data’ we talk about the 4 Vs that characterize big data:

  • Volume – the vast amounts of data generated every second
  • Velocity – the speed at which new data is generated and moves around (credit card fraud detection is a good example where millions of transactions are checked for unusual patterns in almost real time)
  • Variety – the increasingly different types of data (from financial data to social media feeds, from photos to sensor data, from video capture to voice recordings)
  • Veracity – the messiness of the data (just think of Twitter posts with hash tags, abbreviations, typos and colloquial speech)

So, we have a lot of data, in different formats, that is often fast moving and of varying quality – why would that change the world? The reason the world will change is that we now have the technology to bring all of this data together and analyze it.

In the past we had traditional database and analytics tools that couldn’t deal with extremely large, messy, unstructured and fast moving data. Without going into too much detail, we now have software like Hadoop and others which enable us to analyze large, messy and fast moving volumes of structured and unstructured data. It does it by breaking the task up between many different computers (which is a bit like how Google breaks up the computation of its search function). As a consequence of this, companies can now bring together these different and previously inaccessible data sources to generate impressive results. Let’s look at some real examples of how big data is used today to make a difference:

  • The FBI is combining data from social media, CCTV cameras, phone calls and texts to track down criminals and predict the next terrorist attack.
  • Facebook is using face recognition tools to compare the photos you have up-loaded with those of others to find potential friends of yours (see my post on how Facebook is exploiting your private information using big data tools).
  • Politicians are using social media analytics to determine where they have to campaign the hardest to win the next election.
  • Video analytics and sensor data of Baseball or Football games is used to improve performance of players and teams. For example, you can now buy a baseball with over 200 sensors in it that will give you detailed feedback on how to improve your game.
  • Artists like Lady Gaga are using data of our listening preferences and sequences to determine the most popular playlist for her live gigs.
  • Google’s self-driving car is analyzing a gigantic amount of data from sensor and cameras in real time to stay on the road safely.
  • The GPS information on where our phone is and how fast it is moving is now used to provide live traffic up-dates.
  • Companies are using sentiment analysis of Facebook and Twitter posts to determine and predict sales volume and brand equity.
  • Supermarkets are combining their loyalty card data with social media information to detect and leverage changing buying patterns. For example, it is easy for retailers to predict that a woman is pregnant simply based on the changing buying patterns. This allows them to target pregnant women with promotions for baby related goods.
  • A hospital unit that looks after premature and sick babies is generating a live steam of every heartbeat. It then analyses the data to identify patterns. Based on the analysis the system can now detect infections 24hrs before the baby would show any visible symptoms, which allows early intervention and treatment.

And these examples are just the beginning. Companies are barely starting to get to grips with the new world of big data. In conclusion then, big data will change the world. In terms of language I prefer to talk about the ‘datafication of the world’ in relation to the ever-growing amounts of data and ‘large-scale analytics’ (or simply ‘analytics’ because what is large now will be normal tomorrow) in relation to our ability to analyze and harness big data.

 

This article was written by Bernard Marr, an Enterprise Performance expert and appeared first on LinkedIn

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