How PayPal uses deep learning and detective work to fight fraud
New crime needs new algorithms
Hui Wang has seen the nature of online fraud change a lot in the 11 years she’s been at PayPal. In fact, a continuous…
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Hui Wang has seen the nature of online fraud change a lot in the 11 years she’s been at PayPal. In fact, a continuous…
So much for AlchemyAPI CEO Elliot Turner’s statement that his company is not for sale. IBM has bought the Denver-based deep learning…
A team of researchers from Stanford University and Google have released a paper highlighting a deep learning approach they say shows promise in the…
More AWS perks for business users Amazon Web Services has beefed up its identity management and access control capabilities so that businesses…
As deep learning continues gathering steam among researchers, entrepreneurs and the press, there’s a loud-and-getting-louder debate about whether its algorithms actually operate…
Microsoft researchers claim in a recently published paper that they have developed the first computer system capable of outperforming humans on a…
There are a couple of seemingly contradictory memes rolling around the deep learning field. One is that you need a truly epic amount of…
We are thrilled to announce the launch of Gigaom’s newest conference, Structure Intelligence. In the past year we’ve seen massive growth in…
A Sunnyvale, California, startup called Orbeus has developed what could be the best application yet for letting everyday consumers benefit from advances…
Open the closet of any gadget geek or computer nerd, and you’re likely to find a lot of skeletons. Stacked deep in…
Google employs some of the world’s smartest researchers in deep learning and artificial intelligence, so it’s not a bad idea to listen to…
If you’re interested in assessing how and when a given data technology — deep learning, machine intelligence, natural language generation — can…
The second-annual Structure Data Awards are here, where Gigaom picks the most-interesting and most-promising data startups that launched in the previous year.…
Facebook on Friday open sourced a handful of software libraries that it claims will help users build bigger, faster deep learning models…
Chinese search engine company Baidu says it has built the world’s most-accurate computer vision system, dubbed Deep Image, which runs on a supercomputer…
Artificial intelligence is already very real. Not conscious machines, omnipotent machines or even reasoning machines (yet), but statistical machines that automate and increasingly…
I take a lot of photos on my smartphone. So many, in fact, that my wife calls me Cellphone Ansel Adams. I can’t…
There is no other way to put it: 2014 was a huge year for the big data market. It seems years of talk…
As 2014 draws to a close, the tech world seems a little weary. It was a draining year if you were plugged…
Two studies published this week provide even more evidence that deep learning models are very good at computer vision and might be able…
Hampton Creek, a San Francisco startup that uses advanced data analysis to develop eco-conscious, egg-free food products, has raised a $90 million series…
Chinese search engine giant Baidu says it has developed a speech recognition system, called Deep Speech, the likes of which has never…
IBM says it has developed a machine learning system that identified images of skin cancer with better than 95 percent accuracy in…
Microsoft started rolling out a new feature for Skype on Monday called Skype Translator which will translate communications from users using different languages in near real-time — that is, as you’re chatting on Skype.
A new startup called Butterfly Network, from genomic-technology pioneer Jonathan Rothberg, hopes to improve the world of medical imaging using advanced chip technologies, tablet devices and deep learning. Rothberg explains how and why deep learning is key to the company’s plans.
University of Toronto researcher and part-time Google distinguished researcher Geoff Hinton is responsible for many recent advances in deep learning, and many advances in neural network research over the past few decades. Here are some highlight of a recent Reddit AMA with Hinton.
New funding for deep learning startups focused on medical imaging suggests investors see more promise in the applications of deep learning than for the models themselves.
Recent comments by machine learning experts have caused a stir, but debate over the novelty or architecture of deep learning might be best left in academia . As AI techniques make their way into developers’ hands, whether they catch on depends on whether they’re useful.
The Google-owned artificial intelligence outfit DeepMind has revealed a partnership with Oxford University that involves a “substantial donation” to set up a…
The science of identifying the positions of arms, legs and joints within images is becoming a popular pastime among deep learning researchers. The techniques they develop could be particularly important in fields such as human-computer interaction and computer animation.
Machine learning startup GraphLab is boosting the capabilities of its platform, which aims to help users build and then serve their predictive models, has released a new version of its software that includes support for deep learning models.
AlchemyAPI’s deep-learning-based system can now be used to tag famous people in photos, or to recognize non-celebrities via labeled images in corporate or social networks. It’s the latest — but not the last — service the company has released since getting started analyzing text in 2012.
Gigaom recently hosted a meetup featuring thought leaders and entrepreneurs in the world of artificial intelligence and deep learning. Watch the videos of their presentations here.
Microsoft Azure now provides a speech-recognition service for audio-visual content that indexes the files based on what’s actually said in them. This could automate the searchability, categorization and description of content that used to be a mystery if it wasn’t properly labeled.
North Carolina State researchers built a deep learning system that was able to predict players’ goals in an open-ended video game nearly 63 percent of time. It’s not perfect and it’s not proof of a gaming revolution, but it’s a big improvement and a good start.
Nvidia is fully embracing the effectiveness of GPUs for running deep learning algorithms, releasing over the weekend a new set of libraries designed to let researchers experience the performance boost of GPUs without having to optimize their models for the hardware.
The annual ImageNet computer vision competition took place in August, and once again the winning techniques blew away past winners. John Markoff…
Baidu says its 100-billion-neuron deep learning system will be complete within six months, powering a fast transition away from text as the dominant search input. Thanks to smartphones and its new Baidu Eye technology, the company expects voice and image search to dominate within five years.
A San Diego-based startup called Nervana Systems has raised a series A round for its specialized deep learning computing system. It’s a smart move given the hype and legitimate promise of the space, but the best path for commercializing the tech is an open question.
The NSF has funded projects that will investigate how deep learning algorithms run on FPGAs and across systems using the high-performance RDMA interconnect. Another project, led by Andrew Ng and two supercomputing experts, wants to put the models on supercomputers and give them a Python interface.
Join Gigaom for a free meetup on artificial intelligence and machine learning. Speakers from Google, Microsoft Research, Baidu and more will discuss the state of the art in fields such as deep learning, and how things will change when they go mainstream.
A Spotify intern and Ph.D. student published a blog post laying out his work to improve Spotify’s recommendation algorithms using deep learning to analyze the acoustic properties of songs. He hopes his models can help listeners discover new and relatively unheard music.
A Cambridge, Massachusetts, startup called Nara has released a service the company claims use “deep learning artificial intelligence” to improve online personalization. Essentially, the…
Scientists have researched the effectiveness of deep learning techniques for discovering exotic particles and found some significant improvements over previous methods. They believe deep learning could help analyze data from the Large Hadron Collider.
Microsoft, which recently showed off its machine learning research with Skype Translate, is opening up those capabilities with a new cloud service called Azure Machine Learning.
A startup called Ersatz Labs is promising deep learning, delivered via appliance or the cloud, usable by pretty much anybody already familiar with machine learning. It’s the latest attempt to take the data-processing approach out of the lab and into the mainstream.
Skymind is providing commercial support and services for an open source project called deeplearning4j. It’s a collection of of approaches to deep learning that mimic those developed by leading researchers, but tuned for enterprise adoption.
It’s been many years in the making and it may take a couple more before it’s widely available, but Microsoft’s research into real-time voice translation looks set to pay off.
Deep learning startup AlchemyAPI is expanding its scope from text analysis to computer vision with a new API-based service called AlchemyVision. The company’s neural network system is continuously scanning images on the web and getting smarter by the day.
Big data has been a buzzword for years, but it’s a lot more than just buzz. There are now so many tools and technologies for creating, collecting and analyzing data that almost anything is possible if you know where to look.
Computer vision startup Jetpac, which specialized in categorizing Instagram images from vacation destinations, has released an iOS software development kit and app based on a popular deep learning architecture.
Microsoft keeps rolling out new features in Bing that it claims make it superior to, or at least more interesting, than Google’s dominant search engine. They’re not the sexiest applications of artificial intelligence, but they are easy, practical and tied to big money.
GPU maker Nvidia is hoping to ride the wave of artificial intelligence. The company is already powering machine learning workloads within data centers of large companies, but now it’s targeting individuals with a cheap-but-powerful development kit targeted at robotics and the internet of things.
New research highlights a computer vision system that’s much better at telling when people are faking expressions of pain than are other humans. It’s the latest in a series of computer vision advances that foretell a brave, new and possibly creepy world.
The company wants to build a system that sees and learns like the human brain. That could be decades out, but Silicon Valley is very interested.
A Facebook research paper details a new method for recognizing the people in images by combining deep learning techniques with a method for recomposing angled images as straight-on ones. It’s the latest in a series of advances web companies have made in this field.
Structure Data has a great lineup of speakers, including a handful that will be talking about how to take advantage of new types of data. Here is a list of sessions anyone interested in sensors, location or artificial intelligence won’t want to miss.
A robotics startup called Neurala has received a patent (No. 8,648,867) for a GPU-based system designed to run artificial neural network models. The…
One of the big themes at our Structure Data conference in March is the advent of new techniques to make sense of new data sources. One of the most-promising is video, which had value well beyond capturing crimes and making us laugh on YouTube.
IBM has launched a whole new division around Watson, but a slow start in terms of uptake might be a sign of concern. Watson’s best chances for success might lie in the cloud, where its capabilities can really be pushed to the limit.
http://www.technologyreview.com/view/523326/how-google-cracked-house-number-identification-in-street-view/ This post from the MIT Technology Review discusses how Google used deep learning to recognize houses numbers and make Street View…
A new algorithm out of the University of California, San Diego, is getting better at predicting what subculture, or “urban tribe,” people belong to by learning what visual features usually accompany goths, bikers, surfers and others in online photos.
Facebook has hired deep learning expert Yann Lecun from New York University to head up its new artificial intelligence lab. It’s part of a bigger push along with — and against — companies like Google and Microsoft to advance research while improving their platforms.
Google has released another paper showing off the power of its deep learning techniques for text analysis. It shows how models can detect similar usage of words across different languages, meaning it can accurately translate words and concepts from one language to another.
A Denver-based startup called AlchemyAPI is close to rolling out deep-learning-based image recognition via its API service. The company has made something of a name for itself in the text-analysis world, and it says it can do image recognition as well as Google.
The glut of research in teaching computers to analyze and understand images could prove very helpful in letting us take full advantage of the countless hours of video we’ll produce as wearable cameras go mainstream.
On this week’s show we give you the scoop on Samsung’s watch, ponder if the Nook is cooked and learn all about deep learning.
Google researchers have developed new methods for analyzing language using deep learning techniques. They’ve also open sourced an implementation of their work so any researchers can experiment with it. It could be the first of many deep learning tools designed for mass consumption.
New research shows that it’s possible to train Google-style neural networks with GPUs and Infiniband at low cost. The work could help drive further GPU adoption.