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Can a supercomputer pick out a good wardrobe: Best of the Web

While computers have always been great at anything relating to logic and maths, as anyone who has tried to have a conversation with Siri will attest, there are many problems humans find easy to solve that computers struggle with. One example from MITโ€™s Technology Review is a challenge most people deal with daily โ€“ choosing […]
Andrew Sadauskas
Andrew Sadauskas
Can a supercomputer pick out a good wardrobe: Best of the Web

While computers have always been great at anything relating to logic and maths, as anyone who has tried to have a conversation with Siri will attest, there are many problems humans find easy to solve that computers struggle with.

One example from MITโ€™s Technology Review is a challenge most people deal with daily โ€“ choosing a matching outfit:

If youโ€™ve ever puzzled over what to wear in the morning, you might also have wondered whether you could leave the choice to an algorithm that could recommend a decent combination of clothes.

The short answer is no. Various groups have studied the problem of automated fashion advice without anybody really nailing it.

The latest tech team to have a go at this everyday challenge come from eBayโ€™s San Jose Research Labs:

Today, it is the turn of Anurag Bhardwaj and pals from eBay Research Labs in San Jose. These guys have developed two different fashion recommendation systems and then crowdsourced opinions about whether the recommendations they provide are any good.

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The first algorithm, which Bhardwaj and pals call the deterministic fashion recommender, evaluates the colors in the top and compares them to the colors in the skirts. It then gives each combination a rating that can be compared to other top-bottom combinations. (Exactly how this rating is calculated, they donโ€™t say.)

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The second algorithm uses the predefined rule that patterned clothing coordinates well with clothing that has a solid color. โ€œIn other words, having busy patterns in both top and bottom clothing is less popular,โ€ say Bhardwaj and co.

Can good fashion sense really be expressed in algebra? Read the rest of the article to find out!

The new Uber-rich

Cloud-based ride-sharing app and service Uber has been in the headlines a fair bit recently in its quest to overturn the taxi industry.

Its latest round of financing valued the startup at an incredible $US17 billion.

As Erin Griffith at Fortune explains, itโ€™s made some people Uber wealthy:

As Fortune noted in February, Uberโ€™s first angel round of investmentโ€“a $1.5 million deal led by First Round Capitalโ€“came with a $4 million valuation. Investors in that round, assuming reasonable dilution, saw their investments grow to between 400x and 600x in the round that valued Uber at $3.5 billion. At $17 billion, theyโ€™re worth around 2,000x, according to people familiar with the deal.

That means even a tiny little $20,000 angel investment is now worth around $40 million. Even investors from the $3.5 billion round have now almost quintupled their money in less than a year.

In the piece, Griffith profiles a number of the early investors, including Mitch Kapor, Chris Sacca, Naval Ravikant and Alfred Lin. Theyโ€™re names I suspect we could all be hearing a lot more of in the future.

Big Data wonโ€™t change the world

Over at Scientific American, John Horgan has a bucket of cold water for the hype surrounding big data:

Is Big Data going to revolutionize science and help us make a better world? Not based on what itโ€™s done so far.

Horgan says much of the hype about the benefits of โ€˜unlocking dataโ€™ is similar to some of the rhetoric surrounding previous major discoveries in fields such as genetics:

Take genetics. The Human Genome Project was completed in 2003 in less time and for less money than had been expected because of advances in computers and other technologies. The costs of extracting and analyzing genetic data from humans and other organisms has continued to plummet.

But all this progress has produced disappointingly few medical advances. At this writing, not a single gene therapy has been approved for commercial sale in the U.S.; only one has been approved in Europe. The war on cancer has been a bust, as has the effort to find specific genes underpinning complex behavioral traits and disorders.

According to Horgan, just as geneticists now have more data than they could ever dream of, we are no closer to unpacking what it means to be human, let alone some of the big benefits the Human Genome Project promised.

How Android is killing Internet Explorer

Finally, Gregg Keizer at Computer World has some browser market share figures:

According to the Adobe Digital Index (ADI), a measurement of browser usage based on tracking visits to the average U.S. website, Google’s desktop and mobile browsers — Chrome on both platforms, the aging Android browser on the latter only — slipped past Microsoft’s Internet Explorer (IE), which retained its premier position on the desktop but had little to show for its effort on smartphones.

The underlying cause of Google, at the expense of Microsoft and Firefox maker Mozilla, boils down to Android:

The rise of Google’s browsers, and to a lesser extent Apple’s Safari, and the corresponding declines of both IE and Firefox, can be attributed to mobile browsing, primarily that conducted on smartphones. “Today, mobile [operating systems are] more important, giving Google and Apple a leg up with default status on Android and iOS,” said ADI analyst Tyler White in a statement.