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14 January 2018
The secret to avoiding CES cynicism is never really going
I’ve been going to CES for almost ten years now, and it amazes me that really, nothing has changed. The same people are saying the same things on the same stages, selling the same people the same junk with… well, slightly different numbers attached. But this year I had a great time and found some amazing companies — because I avoided at all costs actually stepping foot on… Read More
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13 January 2018
CTRL+T podcast: Diversity and its discontents
No one is down with how diversity is unfolding in Silicon Valley. Depending on how one looks at it, they’re going to have an issue with it. White men are crying foul, saying they’re being left out of these conversations and initiatives. However, actual marginalized people are, rightfully so, saying not enough is being done to diversify the industry and foster inclusion. If you… Read More
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How to Secure Your Social Network Privacy for the New Year
People are starting to wake up to the threat an unsecure social media account poses to their online privacy and security. It's time you secured your accounts.
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Google Assistant had a good CES
Celine Dion at Caesar’s, David Copperfield at the MGM Grand, Google at the Las Vegas Convention Center. The company wallpapered the Vegas monorail and plastered the words “Hey Google” on every rentable screen in town. Take that, Donny and Marie. That crazy booth in the Convention Center parking lot seemed like a terrible idea on Tuesday when the rains opened up and… Read More
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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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12 January 2018
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)
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.
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| A lymph node biopsy, where our algorithm correctly identifies the tumor and not the benign macrophage. |
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| First patient screened (top) and Iniya Paramasivam, a trained grader, viewing the output of the system (bottom). |
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.
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| A Message Passing Neural Network predicts quantum properties of an organic molecule |
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| Finding a new exoplanet: observing brightness of stars when planets block their light. |
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.
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| A garden drawn by the SketchRNN model; an interactive demo is available. |
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.
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| Facets provides insights into your training datasets. |
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.
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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. |
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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