Description: Algorithms make predictions more accurate—but they also create risks of their own, especially if we do not understand them.
Date: Jan 1, 2016
High-profile examples abound. When Netflix ran a million-dollar competition to develop an algorithm that could identify which movies a given user would like, teams of data scientists joined forces and produced a winner. But it was one that applied to DVDs—and as Netflix’s viewers transitioned to streaming movies, their preferences shifted in ways that didn’t match the algorithm’s predictions.
Another example comes from social media. Today many sites deploy algorithms to decide which ads and links to show users. When these algorithms focus too narrowly on maximizing user click-throughs, sites become choked with low-quality “click-bait. Read the Rest of the Story
1. Discuss the pros and cons of ALGORITHMS in managing a business.
2. List some examples of algorithm successes in business, education, or government.
Description: No matter how many times I ask Apple TV’s Siri for shows starring “Bea Arthur,” it only hears “be Arthur.”
Date: Nov 3, 2015
Siri is one of the new Apple TV’s most important features. It can stumble over proper names (“Keanu” took multiple tries but it nailed “Fassbender”), and Apple has saddled it with some key limitations. But ultimately, Siri is a neat way to surf TV.
In addition to the Siri upgrade, the new gadget includes a fancy touchpad remote control, beautiful interface and an all new app store. Apple (AAPL, Tech30) calls it the “future” of television.
The product upgrade, the first in three years, is a huge leap forward for Apple. And after spending a few days watching TV (for journalism), I think it’s very much the TV of our time. Read Rest of Story
Questions for discussion:
1. Are you an Apple TV user? Why or why not?
2. Does this product look like something you would adopt? Why or Why not?
3. What do you think the chances are for success with this product? Dexribe
Description: Last night Netflix hosted a gathering at its spa-like headquarters for 200 or so members of the Clouderati—the engineers building out the computing infrastructure on which businesses will someday run. Netflix (NFLX) has a reputation for pushing the limits of cloud computing, running much of its movie streaming business on Amazon.com’s cloud rental system.
Date: March 14, 2013
When it comes to infrastructure technology, we live in absurd times. Netflix—like Facebook (FB), LinkedIn (LNKD), Twitter, Yahoo (YHOO), and other Web celebs—open sources much of the software that underlies its operations. Put more bluntly, they fight for the right to heap money on the smartest engineers, then give away their work so that others can build on top of it. Together, all these companies are forging the cutting-edge cloud computing technology that mainstream companies will use in the years to come.
At its event, Netflix looked to turbocharge the process. The company announced $100,000 in prizes—$10,000 for 10 different awards—for volunteer coders who can develop interesting tools based on Netflix’s open-source code over the next six months. (Rules here.) The revelation of these prizes was met with great applause. Now the race is on for people who don’t work at Netflix to improve the company’s infrastructure. READ REST OF STORY
Questions for discussion:
1. What is the model that Netflix is using to develop a technology infrastructure? How is it different from say companies like Microsoft and IBM?
2. DO you feel that Netflix’s model is the way IT development will happen in the future or do you see this as just a fad?
3. What are the strengths and weaknesses of this model?