Google temporarily bans addiction center ads globally following exposure of seedy referral deals

 Google is temporarily halting advertisements worldwide for addiction and rehabilitation centers, following a report last week showing it was acting as a platform for shady referral services earning huge undisclosed commissions. Read More
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The Most Exciting Pet Gadgets Of CES 2018

In addition to being the year of the smart home, 2018 is the year of connected gadgets for your pet. After all, who says wearables and other connected devices are reserved for humans? A dog or cat is just like a member of the family. It only makes sense that tech companies would target our love for them with connected pet toys. If there’s something you regularly use for your dog or cat, there’s probably a smart version at CES. Actijoy Pet Tracking System Just like people, dogs can be overweight. If you leave food out all day, your dog will...

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As David Letterman’s first Netflix guest, Barack Obama warns against the ‘bubble’ of social media

 David Letterman seems to be taking the title of his new Netflix show very seriously: On the very first episode of My Next Guest Needs No Introduction With David Letterman, he’s joined by former U.S. President Barack Obama. The episode has plenty of funny moments, like Obama ribbing Letterman about his nearly Biblical beard. But they cover substantive political topics, too — not… Read More
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Google Duo Lets You Call People Without the App

Google has quietly updated Duo to allow users to call people who don’t even have the Duo app installed. This means that Google Duo users can make voice calls or video calls to their contacts using Duo even if the other person has never even heard of this particular messaging app. The number of messaging apps Google offers has been well documented. There’s Allo and Duo (which can now make voice calls) and Hangouts (which has been split into Chat and Meet). And all of them do pretty much the same thing. However, Duo does have a cool new trick...

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Analytics Driven Managed Services

In today’s world, the amount and volume of data is rising abruptly and rapidly. We see tremendous and continuous disruptions in data analytics, knowledge management, business intelligence and intelligent automation. As such, new trends like Big Data and Analytics have become very pertinent with the CXOs IT landscape modernization and rationalization agenda. As the insights-driven road-maps and strategies take shape, these will become very important source of competitive differentiation in the market. The current challenge for many enterprises is how to utilize and capitalize big data analytics and derive maximum benefits considering the technological disruptions and very light budget.

Breaking down Analytics Driven Decision Making

Analytics refers to the discovery and communication of relevant insights from data. We understand that data-driven decision making emphasize upon quantitative aspects of data: number crunching and proper data processing to come up with results based upon numbers as the underlying facts.

Now, analytics driven decisions takes data-driven decision making to the next step, into the domain of qualitative analysis. This allows for the integration of quantitative and qualitative data and hence another layer of insights gets added which allows for one more layer of consideration and results in showing various data-points which influence the decision making process.

Consider an example, using analytics driven decision making, CXOs can not only focus on which IT lever is causing the main problem, but they can also get insights on what can be done to prevent and predict it before occurring, so that proactive measures can be taken and the business sees no down-time. By concentrating on analytics driven decision-making, enterprises can focus upon important questions of What and Why. It implies that decision-makers can see an overall view of what is happening and why is it happening along with how it can be prevented. It can have an immediate business impact in terms of accurate measurement of key metrics and costs efficiencies.

How to become Analytics Driven?

The key to launching analytics at a corporate level starts with utilizing the right tools and proper training on these tools. For enterprises, which want to leverage the power of analytics into their business domains, experts and tools, customized to their needs is the starting point. For many enterprises, it is logical to assume that this is not their core competency and hence they need external consulting to find ways to integrate business intelligence, revamp performance management, risk mitigation, compliance and governance mechanisms.

Therefore, the important decisions with the CXOs is that before pondering over capitalizing on Analytics, they must have a strategic road-map regarding governance models at information, technological and project levels. This shall ensure alignment of analytics with the core business objectives. This is also necessary to integrate new technologies into existing IT landscape resulting in maximum value derivation to the enterprises.

Yesojo’s Nintendo Switch projector dock is a dream accessory

 The Yesojo Nintendo Switch projector dock got a lot of attention when we covered the launch of its crowdfunding campaign last year, but at CES, it was on display and working, with the company ready to ship to its early backers. We got to spend some time with the portable projector, which gives your Switch a high-resolution screen you can take with you anywhere – and we came away very… Read More

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Cherry’s new low-profile switches may help bring mechanical keyboards to more laptops

 You may not think much about the switches that sit underneath the keycaps of your keyboard, but there are many enthusiasts who really, really care. The trend is clearly going toward slim keyboards — and that’s not lost on Cherry. At CES this week, the company introduced a new line of keyboard switches that may just be small enough to bring mechanical keyboards to more laptops. Read More

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Yesojo’s Nintendo Switch projector dock is a dream accessory

 The Yesojo Nintendo Switch projector dock got a lot of attention when we covered the launch of its crowdfunding campaign last year, but at CES, it was on display and working, with the company ready to ship to its early backers. We got to spend some time with the portable projector, which gives your Switch a high-resolution screen you can take with you anywhere – and we came away very… Read More

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How to Emulate Android Apps on Linux

If you’re a hardcore Android fan, you’re probably aware that your favorite mobile operating system descends from Linux. We’ve covered in the past how Android is based on open source components, and that the Linux kernel is one of those. It stands to reason then that if they’re so close, it should be relatively easy to run Android apps on Linux. As it turns out, that’s correct. Normally running apps for one operating system on another is tricky. But there are a couple of methods available for Linux users to run Android apps that make things comparatively easy. Let’s take...

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Facebook stock dips after the platform deprioritizes publishers

 Facebook shares fell around 5% on Friday following the news that the company would retool its News Feed to boost social interactions over stories from publishers. Mark Zuckerberg announced the news on Thursday evening in a post on his own Facebook page to expected investor skittishness. “I want to be clear: by making these changes, I expect the time people spend on Facebook and some… Read More
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7 Tips to Get the Best Performance From Your Raspberry Pi 3

Finding your Raspberry Pi 3 isn’t quite reaching its limits? You’re not alone. Despite it being the most advanced version of the little computer to date, it can be tricky to get your set up right. It doesn’t matter whether you’re using your Raspberry Pi to run retro games, as a media center, or any of the other wonderful projects that might pique your interest. If the Pi isn’t configured to run at its most optimum, you’re going to have a bad experience. No one wants that. So, take a look at our seven tips to find out just what...

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The Google Brain Team — Looking Back on 2017 (Part 2 of 2)

Posted by Jeff Dean, Google Senior Fellow, on behalf of the entire Google Brain Team

The Google Brain team works to advance the state of the art in artificial intelligence by research and systems engineering, as one part of the overall Google AI effort. In Part 1 of this blog post, we shared some of our work in 2017 related to our broader research, from designing new machine learning algorithms and techniques to understanding them, as well as sharing data, software, and hardware with the community. In this post, we’ll dive into the research we do in some specific domains such as healthcare, robotics, creativity, fairness and inclusion, as well as share a little more about us.

Healthcare
We feel there is enormous potential for the application of machine learning techniques to healthcare. We are doing work across many different kinds of problems, including assisting pathologists in detecting cancer, understanding medical conversations to assist doctors and patients, and using machine learning to tackle a wide variety of problems in genomics, including an open-source release of a highly accurate variant calling system based on deep learning.

A lymph node biopsy, where our algorithm correctly identifies the tumor and not the benign macrophage.

We have continued our work on early detection of diabetic retinopathy (DR) and macular edema, building on the research paper we published December 2016 in the Journal of the American Medical Association (JAMA). In 2017, we moved this project from research project to actual clinical impact. We partnered with Verily (a life sciences company within Alphabet) to guide this work through the regulatory process, and together we are incorporating this technology into Nikon's line of Optos ophthalmology cameras. In addition, we are working to deploy this system in India, where there is a shortage of 127,000 eye doctors and as a result, almost half of patients are diagnosed too late — after the disease has already caused vision loss. As a part of a pilot, we’ve launched this system to help graders at Aravind Eye Hospitals to better diagnose diabetic eye disease. We are also working with our partners to understand the human factors affecting diabetic eye care, from ethnographic studies of patients and healthcare providers, to investigations on how eye care clinicians interact with the AI-enabled system.

First patient screened (top) and Iniya Paramasivam, a trained grader, viewing the output of the system (bottom).

We have also teamed up with researchers at leading healthcare organizations and medical centers including Stanford, UCSF, and University of Chicago to demonstrate the effectiveness of using machine learning to predict medical outcomes from de-identified medical records (i.e. given the current state of a patient, we believe we can predict the future for a patient by learning from millions of other patients’ journeys, as a way of helping healthcare professionals make better decisions). We’re very excited about this avenue of work and we look to forward to telling you more about it in 2018.

Robotics
Our long-term goal in robotics is to design learning algorithms to allow robots to operate in messy, real-world environments and to quickly acquire new skills and capabilities via learning, rather than the carefully-controlled conditions and the small set of hand-programmed tasks that characterize today’s robots. One thrust of our research is on developing techniques for physical robots to use their own experience and those of other robots to build new skills and capabilities, pooling the shared experiences in order to learn collectively. We are also exploring ways in which we can combine computer-based simulations of robotic tasks with physical robotic experience to learn new tasks more rapidly. While the physics of the simulator don’t entirely match up with the real world, we have observed that for robotics, simulated experience plus a small amount of real-world experience gives significantly better results than even large amounts of real-world experience on its own.

In addition to real-world robotic experience and simulated robotic environments, we have developed robotic learning algorithms that can learn by observing human demonstrations of desired behaviors, and believe that this imitation learning approach is a highly promising way of imparting new abilities to robots very quickly, without explicit programming or even explicit specification of the goal of an activity. For example, below is a video of a robot learning to pour from a cup in just 15 minutes of real world experience by observing humans performing this task from different viewpoints and then trying to imitate the behavior. As we might be with our own three-year-old child, we’re encouraged that it only spills a little!

We also co-organized and hosted the first occurrence of the new Conference on Robot Learning (CoRL) in November to bring together researchers working at the intersection of machine learning and robotics. The summary of the event contains more information, and we look forward to next year’s occurrence of the conference in Zürich.

Basic Science
We are also excited about the long term potential of using machine learning to help solve important problems in science. Last year, we utilized neural networks for predicting molecular properties in quantum chemistry, finding new exoplanets in astronomical datasets, earthquake aftershock prediction, and used deep learning to guide automated proof systems.

A Message Passing Neural Network predicts quantum properties of an organic molecule

Finding a new exoplanet: observing brightness of stars when planets block their light. 

Creativity
We’re very interested in how to leverage machine learning as a tool to assist people in creative endeavors. This year, we created an AI piano duet tool, helped YouTube musician Andrew Huang create new music (see also the behind the scenes video with Nat & Friends), and showed how to teach machines to draw.

A garden drawn by the SketchRNN model; an interactive demo is available.

We also demonstrated how to control deep generative models running in the browser to create new music. This work won the NIPS 2017 Best Demo Award, making this the second year in a row that members of the Brain team’s Magenta project have won this award, following on our receipt of the NIPS 2016 Best Demo Award for Interactive musical improvisation with Magenta. In the YouTube video below, you can listen to one part of the demo, the MusicVAE variational autoencoder model morphing smoothly from one melody to another.

People + AI Research (PAIR) Initiative
Advances in machine learning offer entirely new possibilities for how people might interact with computers. At the same time, it’s critical to make sure that society can broadly benefit from the technology we’re building. We see these opportunities and challenges as an urgent matter, and teamed up with a number of people throughout Google to create the People + AI Research (PAIR) initiative.

PAIR’s goal is to study and design the most effective ways for people to interact with AI systems. We kicked off the initiative with a public symposium bringing together academics and practitioners across disciplines ranging from computer science, design, and even art. PAIR works on a wide range of topics, some of which we’ve already mentioned: helping researchers understand ML systems through work on interpretability and expanding the community of developers with deeplearn.js. Another example of our human-centered approach to ML engineering is the launch of Facets, a tool for visualizing and understanding training datasets.

Facets provides insights into your training datasets.

Fairness and Inclusion in Machine Learning
As ML plays an increasing role in technology, considerations of inclusivity and fairness grow in importance. The Brain team and PAIR have been working hard to make progress in these areas. We’ve published on how to avoid discrimination in ML systems via causal reasoning, the importance of geodiversity in open datasets, and posted an analysis of an open dataset to understand diversity and cultural differences. We’ve also been working closely with the Partnership on AI, a cross-industry initiative, to help make sure that fairness and inclusion are promoted as goals for all ML practitioners.

Cultural differences can surface in training data even in objects as “universal” as chairs, as observed in these doodle patterns on the left. The chart on the right shows how we uncovered geo-location biases in standard open source data sets such as ImageNet. Undetected or uncorrected, such biases may strongly influence model behavior.

We made this video in collaboration with our colleagues at Google Creative Lab as a non-technical introduction to some of the issues in this area.

Our Culture
One aspect of our group’s research culture is to empower researchers and engineers to tackle the basic research problems that they view as most important. In September, we posted about our general approach to conducting research. Educating and mentoring young researchers is something we do through our research efforts. Our group hosted over 100 interns last year, and roughly 25% of our research publications in 2017 have intern co-authors. In 2016, we started the Google Brain Residency, a program for mentoring people who wanted to learn to do machine learning research. In the inaugural year (June 2016 to May 2017), 27 residents joined our group, and we posted updates about the first year of the program in halfway through and just after the end highlighting the research accomplishments of the residents. Many of the residents in the first year of the program have stayed on in our group as full-time researchers and research engineers, and most of those that did not have gone on to Ph.D. programs at top machine learning graduate programs like Berkeley, CMU, Stanford, NYU and Toronto. In July, 2017, we also welcomed our second cohort of 35 residents, who will be with us until July, 2018, and they’ve already done some exciting research and published at numerous research venues. We’ve now broadened the program to include many other research groups across Google and renamed it the Google AI Residency program (the application deadline for this year's program has just passed; look for information about next year's program at http://ift.tt/2hHjufa).

Our work in 2017 spanned more than we’ve highlighted on in this two-part blog post. We believe in publishing our work in top research venues, and last year our group published 140 papers, including more than 60 at ICLR, ICML, and NIPS. To learn more about our work, you can peruse our research papers.

You can also meet some of our team members in this video, or read our responses to our second Ask Me Anything (AMA) post on r/MachineLearning (and check out the 2016’s AMA, too).

The Google Brain team is becoming more spread out, with team members across North America and Europe. If the work we’re doing sounds interesting and you’d like to join us, you can see our open positions and apply for internships, the AI Residency program, visiting faculty, or full-time research or engineering roles using the links at the bottom of g.co/brain. You can also follow our work throughout 2018 here on the Google Research blog, or on Twitter at @GoogleResearch. You can also follow my personal account at @JeffDean.

Thanks for reading!

39 million Americans now own a smart speaker, report claims

 One in six Americans now own a smart speaker, according to new research out this week from NPR and Edison Research – a figure that’s up up 128 percent from January, 2017. Amazon’s Echo speakers are still in the lead, the report says, as 11 percent now own an Amazon Alexa device compared with 4 percent who own a Google Home product. Today, 16 percent of Americans own a… Read More

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Waymo’s self-driving Chrysler Pacifica begins testing in San Francisco

 Waymo is bringing its self-driving cars back to San Francisco streets for testing. TechCrunch has obtained pictures of the Waymo Chrysler Pacifica autonomous test vehicle on SF city roads, and Waymo confirmed that it is indeed bringing test vehicles back to one of the first spots where it ever tested AVs in the first place. A Waymo spokesperson provided the following statement about its… Read More
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3 Best Cheap Linux Laptops to Save Money

Linux often gets associated with being cheap. It’s a bit unfair, but it’s true that you can save some big bucks if you buy a computer with a free operating system. So how inexpensive can you go? Check out these best cheap Linux laptops to save money. Yes, you can install Linux on just about any computer out there, so the need for a dedicated machine is difficult to understand. It’s all about drivers though, as there is plenty of hardware that doesn’t play nicely with Linux drivers, and so you have a dysfunctional component. A dedicated Linux machine will...

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How Websites Secretly Record Your Activity With Session Replay Scripts

The internet is the world’s greatest surveillance tool. Or at least that’s how it often feels. We’ve always known that we’re being watched online, but many of us thought it was just to sell us more. Post-Snowden it became clear that governments and companies around the world use every last drop of data they can find in order to surveil and profile us. The NSA wants to know every digital move we make. Amazon and Google are installing surveillance devices in our homes. Facebook wants to profile and commodify our lives. Now there is another thing to add to the...

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Facebook Focuses Your Feed on Family and Friends

Facebook is changing the News Feed, focusing on posts from family and friends rather than those from pages and brands. The social network is also trying to initiate more meaningful social interactions, which will be promoted above more passive activities such as watching videos. Facebook had mixed fortunes in 2017. One the one hand its userbase continued to grow, but on the other hand it faced criticism over the way it’s changing society. This led to founder and CEO Mark Zuckerberg promising to fix Facebook in 2018, and those efforts are starting to bear fruit. Mark Zuckerberg Makes Changes In...

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10 of the Best Dark Comedies to Watch on Netflix

There are days when you’re happy with your life and the world around you, and then there are days when everything you do makes you feel like you’re beating your head against a wall. That’s because the world can be a dark place, and things are looking particularly bleak at the moment. Of course, when you’re enjoying one of your happy days, you might want to watch something cheerful like uplifting romantic comedies or brilliant stand-up shows. But if you are looking to wallow in your own misery, it’s time to turn to the dark side of Netflix. The following...

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Flock vs. Slack: Which Team Communication Tool Is Best for You?

Slack took the world by storm when it released in 2013, enabling companies to communicate internally using real-time chat instead of email. With its advanced features and slick design, Slack became the go-to solution for big teams, especially those with remote workers. But not everyone likes Slack. All kinds of Slack alternatives have popped up over the years, trying to dethrone the king by being unique in this way or that. Flock, on the other hand, is a direct competitor to Slack that aims to be the same but more productive without gimmicks. If you need a real-time communication tool...

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The Best Kanban Chrome Extensions to Manage Your Projects

People perpetually look for ways to streamline their processes, maximize their productivity and manage their workflows. Kanban is one popular process that does all of those things. Developed by a Toyota engineer, it originated in the manufacturing sector. However, many tech firms now use Kanban to meet development goals. How Does Kanban Work? Task prioritizing is one of Kanban’s main concepts. Think about the constant influx of user requests after a software release. In that scenario, people who use Kanban visualize the workflow on Kanban boards. They also take a team approach to assigning priorities for each user request or...

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