It’s time for people operations to join the data revolution

GUEST: The world is awash with data. From optimizing supply chains to understanding customer sentiment, from tracking the spread of contagious disease to predicting churn — data and algorithms have given us incredible leverage in business and in life. Although the field of business analytics was born in the 1950s, it was only in the…

http://venturebeat.com/2015/04/04/its-time-for-people-operations-to-join-the-data-revolution/

B2C becomes B2B every time someone walks into an office with their smartphone in their pocket

Hunter Walk

B2C becomes B2B every time someone walks into an office with their smartphone in their pocket. It’s been amazing over the last 18 months to see Shyp make organic inroads into small businesses, retailers, marketing departments, etc not because they’ve targeted these customers or because the product has evolved specifically in their direction (more work to be done!) but because individuals in San Francisco, NYC, Miami have used the app in the personal lives. It then occurs to them that this magical service isn’t just for sending a gift or returning an ecommerce purchase but can be used for jobs big and small, one-offs or reoccurring. There’s a car dealership using Shyp to send 75+ parts per week to mail order customers. There’s a SF-based unicorn startup which did $20,000 of shipping with Shyp one week. There’s a major league pro sports team which sent expensive memorabilia to select season…

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Five lessons you can learn from Twitter’s top 1,000 users: Be a pop star, don’t live in SF

Gaming execs: Join 180 select leaders from King, Glu, Rovio, Unity, Facebook, and more to plan your path to global domination in 2015. GamesBeat Summit is invite-only — apply here. Ticket prices increase on April 3rd! So, you’ve been on Twitter for a while, or you’ve just joined (insert GIF of Twitter CEO Dick Costolo doing a happy dance). And you’re…

http://venturebeat.com/2015/04/02/five-lessons-you-can-learn-from-twitters-top-1000-users-be-a-pop-star-dont-live-in-sf/

Researchers show a machine learning network for connected devices

Gigaom

Researchers at Ohio State University have developed a method for building a machine learning algorithm from data gathered from a variety of connected devices. There are two cool things about their model worth noting. The first is that the model is distributed and second, it can keep data private.

The researchers call their model Crowd-ML and the idea is pretty basic. Each device runs a version of a necessary app, much like one might run a version of SETI@home or other distributed computing application, and grabs samples of data to send to a central server. The server can tell when enough of the right data has been gathered to “teach” the computer and only grabs the data it needs, ensuring a relative amount of privacy.

The model uses a variant of stochastic (sub)gradient descent instead of batch processing, to grab data for machine learning, which is what makes the Crowd-ML…

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