The teams have each accepted $1,000 to fund their efforts to create smartphone applications.
1) Toco Transducer and Tocodynomometer – with smart phone APP – will be used to help pregnant women in early labor determine when to get to the hospital. They hope to reduce false alarms and get help for women who really need it but may not realize it.
2) Binspace – an APP to help students find available study or meeting locations on campus.
Each team has an assigned IBM volunteer buddy who will act as coach or mentor.
Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. It has been the buzzword of the last couple years, and many businesses today want to “Get Started with Big Data”.
When I start discussing with clients what they want to do with big data, more often than not I get puzzled looks. It is important to have the preparedness to “get started with big data” by having:
- Pinpointed a line of business in the company to get started with the use cases
- Identified use cases that serves a true business needs within that line of business
- Verified that there’s indeed large amounts of meaningful data available to support the use cases
Above is the snapshot of the mindmap showing some sample use cases. You can download the original mindmap from the links at the original post.
Rahul Sainani (LinkedIn) is an Electronics Engineering student with a passion for developing Smart Applications. Tarun Sainani (LinkedIn) is an Entrepreneur in Knowledge Based Service Systems – Mobile Augmented Reality Solutions. Together they have helped Students for a Smarter Planet put up an app for service-science.us. Here is their website – World Around Me.
Here’s a short talk by Rahul telling what it’s like to be an entrepreneur.
Rahul is on Twitter.
Since you are reading this on an IBM official blog, I bet you would remember Deep Blue, the amazing chess player ‘trained’ by IBM. And of course, since you are such an IBM-fanatic, you would also know that Deep Blue is no ordinary human. It’s actually a machine; a chess-playing computer that supposedly beat former world champion Garry Kasparov in 1997. Either he was a sore loser or his Russian senses were tingling, Garry accused IBM of cheating by allowing human intervention during gameplay which was against the rules. Nobody really knows if that was true or not since IBM later tore down the machine before any real investigation could be initiated (There’s always something between Americans and Russians it seems…).
Earlier on in the late 18th century, a machine known as the Mechanical Turk (a predecessor to Deep Blue) was invented by Wolfgang von Kempelen to impress the Empress of Austria. After beating numerous chess players, however, it was uncovered as a hoax: a real human chess master was actually hiding inside it and making it looked as if the Mechanical Turk had a life of its own and an intelligence unparalleled by any human being.
But why all this talk about getting humans to perform the task of machines in a time where machines are supposed to be legitimately doing the work for humans? Well it turns out that there are some tasks that computers couldn’t do (I think I heard a loud resonating “WHAT?” in the background), and has to be done manually by humans. And this is what the Amazon Mechanical Turk (MTurk) is all about!
In essence, MTurk is an online crowdsourcing marketplace which allows job seekers (called workers) to earn money by doing tasks (posted by people known as requesters) that no computers can accomplish. These tasks usually include things like choosing the best picture for a particular theme or putting tags to pictures so that these pictures can show up when a person types in a particular keyword on Amazon (I believe this was how the MTurk was first conceived). Actually now you can also find tasks like transcribing or programming which may be accomplish-able by machines as well, but still seems to be have a better result if carried out by humans.
So just to give you an idea how much a task would pay from the perspective of a worker, copying text from a business card would be around $0.02 while answering a surveys would be like $0.16. Here’s a short list of tasks that may interest you:
Proofreading a real estate transaction: $0.10
Identifying companies from a photo: $0.01
Voicemail transcription: $30.00
Writing three 400-words articles about travelling: $12.00
Flagging pornographic content: $0.10 (this should be excellent for a lot of readers here)
No matter which tasks you choose, you can see that Service Thinking is applied at MTurk. Value is being co-created between the requesters and workers; a modular business structure is present where a requester can “outsource” tasks to a community of workers; a GLO-MO-SO platform is pretty obvious; you can refer to my earlier blog to think about how the other chevrons of Service Thinking is applied at MTurk.
As quoted from a reviewer who posted on Youtube, MTurk is not going to pay big bucks, but at the very least, it puts money in your pocket.
Yup yet another legit money-making website for you guys out there looking to pay your rent while you look for a full-time job.
IBM Intern; Hult International Business School