Why Google is the big data company that matters most
Google Image Search just got a whole lot better, and the company’s purpose-built machine learning system infrastructure is a big reason why. No surprise, Jeff Dean helped build it. Read more »
Google Image Search just got a whole lot better, and the company’s purpose-built machine learning system infrastructure is a big reason why. No surprise, Jeff Dean helped build it. Read more »
Facebook has been calling on users, external data sources and machine-learning models to improve its Graph Search function. But Facebook must do more to make the tool a widely used utility. Read more »
Sure, a lot of data scientists spend their days trying to optimize ads or movie recommendations, but a growing number are spending their free time tackling bigger causes. Read more »
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Machine learning service BigML and open data service Quandl are collaborating to make it easy to build predictive models around economic data. More importantly, though, is how easy Quandl makes it to find and use data. Read more »
Machine-learning startup Wise.io is leaving one accelerator and joining another as it seeks to help enterprises make predictions on several kinds of incoming data. Read more »

The big data skeptics have been getting louder over the past few months, but the message doesn’t resonate too loudly. No one said big data was perfect data. Read more »
Startup WibiData has raised another $15 million and wants to turn the lessons it has learned in the field into generic software that can let anyone build predictive applications on Hadoop. Read more »

Cascading creator Concurrent has developed a new open source tool called Pattern for running machine learning models on Hadoop clusters. When combined with its SQL tool called Lingual, users can move data from one stage to another easily. Read more »
Few companies today have the time or the analytics expertise to apply statistics and complex data modeling to regular or even daily business decisions and operations. Now, however, an ecosystem of companies is emerging to fill this need. Read more at GigaOM Pro »
Google said Thursday it is establishing a Quantum Artificial Intelligence Lab to trigger the next phase of machine learning with the power of quantum computers. The efforts could trickle down to ordinary people. Read more »
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When it comes to using big data technology effectively, there’s a lot to like about SaaS. When companies like BloomReach create and analyze massive web-wide data sets, they automate insights that almost no individual company could discover on its own. Read more »
Graph databases and graph-processing applications have been popping up all over the place lately, and now they’re starting to go commercial. On Tuesday, popular open source project GraphLab joined the ranks of graph startups. Read more »
MailChimp wasn’t always a big data company, but 12 years into its existence the company is using its mountains of email data to do everything from modeling spam to connecting subscribers. Read more »

Machine learning startup Skytree has raised $18 million for its software that makes short work of pattern recognition across massive datasets. Read more »
Artificial intelligence expert and Google Director of Research was elected to the American Academy of Arts and Sciences last week. He’s well known for a 2009 paper titled “The Unreasonable Effectiveness of Data.” Read more »
A startup called Infer has taken on $10 million in venture funding to help more companies get a better idea of which leads to focus on in their sales and marketing lead lists. Read more »

Data scientist might be the sexiest job of the 21st century, but it’s hardly an easy gig to land. Here is some advice from practitioners at Netflix, Orbitz and Hortonworks on how get hired and even do the hiring. Read more »

Call it whatever you want — big data, data science, data intelligence — but be prepared to have your mind blown. Imagination and technology are on a collision course that will change the world in profound ways. Read more »

Even though a perception persists that machines can increasingly solve complex problems and process large amounts of data on their own, machine learning experts say humans still play a key role. Read more »
Microsoft had a handful of journalists at its new Envisioning Center last week to show off its latest and greatest technology. Here’s what it demonstrated. Read more »
Microsoft is no joke when it comes to building web infrastructure and developing techniques such as machine learning. The company thinks its heavy investment in these areas will pay off big-time in the years to come. Read more »

A group of European researchers has created a cloud platform designed to serve as a central processing and data-access brains for robots located throughout the world. Read more »
We talk a lot about big data, but only analyze 1 percent of what’s available. In order to take advantage of the other 99 percent, we need to reconsider how we do big data. Read more »
Companies are rushing to embrace the promise of big data to understand both their businesses and the ways in which customers interact with them. But effective data-based decisions are not made in response to simplistic data reporting; they are made in response to considered and ongoing data analysis. Read more at GigaOM Pro »
Just when you thought spam was under control, a new breed of spammers is taking up new methods to infiltrate our inboxes, search results and social media feeds. Data science could make them very effective. Read more »
IBM is turning Watson loose on lung cancer, offering up a cloud-based service designed to let doctors from around the country find the best-possible treatments for their patients. Read more »
Causata is really good at helping companies identify consumers and, thanks to new machine learning features, helping them predict behavior many steps down the line. Does all this personal data create a privacy concern? Depends who you ask. Read more »
Gravity, a startup that personalizes reader content for web publishers, is opening up its recommendation engine to anyone that wants to use it. Considering the increasing importance of personalization online, this could be a good deal. Read more »
IBM is giving Rensselaer Polytechnic Institute in New York its own Watson system similar to the one that crushed its human competitors on Jeopardy!. The goal is to give Watson new skills and push it into new industries. Read more »
Numenta, the latest startup from Palm creator Jeff Hawkins, aims to help us make sense of fast-flowing machine-to-machine data by recognizing patterns and building models. Its latest customer is smart-grid efficiency expert EnerNOC. Read more »
Is there there really a model for predicting the success of Kickstarter campaigns? A new interactive model from machine learning service BigML offers a fun way to try, although the dearth of public data from Kickstarter might affect its accuracy. Read more »
Russia’s answer to Google hopes to validate its core MatrixNet machine learning technology – until now best-known for improving Yandex’s search ranking – by handing it over to nuclear physicists at CERN. Read more »
While some are hoping for better software to reduce the need for data scientists, WibiData’s Omer Trajman thinks we need more of them. Better software, he argues, is actually just a tool to make it easier for data scientists to do world-changing work. Read more »

Big data technologies are like manufacturing robots: they let people do what they’re already trying to do, only faster than before and at a much greater scale. But as with any other product, that analyzed data is nothing without humans to do something with it. Read more »

IBM has just hired a former Assistant Secretary of Defense as a VP for research strategy. With an expertise in cybersecurity and big data, Zachary Lemnios has some predictions and thoughts about big data and machine learning worth hearing. Read more »
A group of British researchers recently analyzed 2.5 million newspaper articles in order to prove that new data analysis techniques, such as machine learning and natural-language processing, can accurately classify media content. They hope their approach can save academicians untold hours of manual labor. Read more »

According to the New York Times, National Football League teams are often years behind their peers in other professional sports when it comes to data analysis. Machine learning could help teams make more sense of the myriad variables that currently keep them relying on human intuition. Read more »

Even if you don’t agree with ZestFinance’s business, it’s hard to argue with its grasp of big data and applied mathematics. Now, the company has added a human touch to machine learning in order to make its models for assessing repayment risk even more accurate. Read more »
In just a few years, big data has turned from a buzzword and concept best left for large web companies into a force that drives much of our digital lives. Here are five technological trends that will change how data is processed and consumed going forward. Read more »

An MIT researcher says he has created an algorithm that can identify Twitter trends hours before the service can itself. If the algorithm works as he says, it could help Twitter — and many more companies — make a lot of money. Read more »
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