decodering

decodering:

It’s incredibly exciting to see how the Web is evolving, and 2013 has a lot more in store. Over the next year, there are a number of technologies coming down the pipeline that have the potential to radically transform how we use and develop for the Web.

Alex MacCaw highlights:

  1. CSS Custom Filters
  2. Autocomplete API
  3. Google Chrome Apps
  4. ECMAScript 6
  5. Web Components

Aha!

productivegossip
productivegossip:

blog.nielsen:

State of the Media: The Social Media Report 2012
Social media and social networking are no longer in their infancy. Social media continues to grow rapidly, offering global consumers new and meaningful ways to engage with the people, events and brands that matter to them.  According to Nielsen and NM Incite’s latest Social Media Report, consumers continue to spend more time on social networks than on any other category of sites—roughly 20 percent of their total time online via personal computer (PC), and 30 percent of total time online via mobile.  Additionally, total time spent on social media in the U.S. across PCs and mobile devices increased 37 percent to 121 billion minutes in July 2012, compared to 88 billion in July 2011.

Read more
Read the report

productivegossip:

blog.nielsen:

State of the Media: The Social Media Report 2012

Social media and social networking are no longer in their infancy. Social media continues to grow rapidly, offering global consumers new and meaningful ways to engage with the people, events and brands that matter to them.  According to Nielsen and NM Incite’s latest Social Media Report, consumers continue to spend more time on social networks than on any other category of sites—roughly 20 percent of their total time online via personal computer (PC), and 30 percent of total time online via mobile.  Additionally, total time spent on social media in the U.S. across PCs and mobile devices increased 37 percent to 121 billion minutes in July 2012, compared to 88 billion in July 2011.

Read more

Read the report

wired
wired:

There are millions of apps out there, and some of them are actually useful.
2012 was an especially busy year for developers, who churned out roughly eleventy-billion apps, including a few for Windows phones. We saw the rise and rise of Instagram, the short-lived Draw Something fad and the inauguration of presidential campaign apps.
We’ve already run down the essential apps — 413 essential apps, to be exact — and now, as the year has wound down, we run down the most memorable.
Check them out here, and tell us how much you disagree with us!

wired:

There are millions of apps out there, and some of them are actually useful.

2012 was an especially busy year for developers, who churned out roughly eleventy-billion apps, including a few for Windows phones. We saw the rise and rise of Instagram, the short-lived Draw Something fad and the inauguration of presidential campaign apps.

We’ve already run down the essential apps — 413 essential apps, to be exact — and now, as the year has wound down, we run down the most memorable.

Check them out here, and tell us how much you disagree with us!

blakemasters

blakemasters:

Here is an essay version of my class notes from Class 6 of CS183: Startup. Errors and omissions are my own. Credit for good stuff is Peter’s entirely. This class was kind of a crash course in VC financing. I didn’t include all the examples since you can learn more about VC math elsewhere, e.g. here

poptech
poptech:

Everything You Wanted to Know About Data Mining but Were Afraid to Ask

Big data is everywhere we look these days. Businesses are falling all over themselves to hire ‘data scientists,’ privacy advocates are concerned about personal data and control, and technologists and entrepreneurs scramble to find new ways to collect, control and monetize data. We know that data is powerful and valuable. But how? 
This article is an attempt to explain how data mining works and why you should care about it. Because when we think about how our data is being used, it is crucial to understand the power of this practice. Without data mining, when you give someone access to information about you, all they know is what you have told them. With data mining, they know what you have told them and can guess a great deal more. Put another way, data mining allows companies and governments to use the information you provide to reveal more than you think. 
To most of us data mining goes something like this: tons of data is collected, then quant wizards work their arcane magic, and then they know all of this amazing stuff. But, how? And what types of things can they know? Here is the truth: despite the fact that the specific technical functioning of data mining algorithms is quite complex — they are a black box unless you are a professional statistician or computer scientist — the uses and capabilities of these approaches are, in fact, quite comprehensible and intuitive.
Read more.[Image: Reuters]

(via theatlantic)

poptech:

Everything You Wanted to Know About Data Mining but Were Afraid to Ask

Big data is everywhere we look these days. Businesses are falling all over themselves to hire ‘data scientists,’ privacy advocates are concerned about personal data and control, and technologists and entrepreneurs scramble to find new ways to collect, control and monetize data. We know that data is powerful and valuable. But how? 

This article is an attempt to explain how data mining works and why you should care about it. Because when we think about how our data is being used, it is crucial to understand the power of this practice. Without data mining, when you give someone access to information about you, all they know is what you have told them. With data mining, they know what you have told them and can guess a great deal more. Put another way, data mining allows companies and governments to use the information you provide to reveal more than you think. 

To most of us data mining goes something like this: tons of data is collected, then quant wizards work their arcane magic, and then they know all of this amazing stuff. But, how? And what types of things can they know? Here is the truth: despite the fact that the specific technical functioning of data mining algorithms is quite complex — they are a black box unless you are a professional statistician or computer scientist — the uses and capabilities of these approaches are, in fact, quite comprehensible and intuitive.

Read more.[Image: Reuters]

(via theatlantic)