Google's annual developer conference is normally a relentlessly positive cheerleading session to excite developers to create products for the company and its Android operating system. But this year, there was a hint of a more serious tone as the company discussed creating technology that is not simply innovative, but responsible. The theme of the company's annual conference was "Make Good Things Together." Google chief executive Sundar Pichai said in a keynote address to about 7,000 developers and journalists that Google wants to push ahead to innovate, but he acknowledged that the tech giant can't be "wide-eyed" about it. "There are important questions being raised about the impact of these advances and the role they'll play in our lives," he said. "We know the path ahead needs to be navigated carefully and deliberately."

As Mnih paper explained (while the parameters θ of the policy and v of the value function are show to be separate, for generality we always share some of the parameters in practice with all non-output layers shared) it means that for the CNN part we share the parameters (weights). I understand that what you say is that the loss function is the sum of two variables calculated from two functions, the one calculated from policy loss and the other calculated from the value loss. And as consequence "Even though you add policy loss and the value loss at the end to create ONE loss function, they are effectively still two separate loss functions. "So when the backward pass flows through them, it is equally given to both functions without any interaction. " So as I understand you explain that there is still 2 gradients, one for the policy and one for the value because there is still 2 loss function.

You've probably been to a supermarket that printed coupons for you at checkout. Or listened to a playlist that your streaming service generated for you. Or gone shopping online and seen a list of products labeled "you might be interested in…." that did indeed contain some stuff that you were interested in. Recommendation engines take data about you, similar consumers, and available products, and use that to figure out what you might be interested in and therefore deliver those coupons, playlists, and suggestions. Recommendation engines can be extremely complex.

Pichai's optimism about the news business continues, says that there's "more great journalism being produced today than ever before". He admits that it's also true that people turn to Google in times of need and there is a responsibility to provide that information. "We want to make sure we're giving them deeper insight and the fuller perspective," Pichai says before passing on the baton to Trystan Upstill who will talk about the Google News redesign.

Google's Assistant, its answer to Amazon's Alexa and Apple's Siri, is getting smarter, more visual, and potentially, more helpful. At the I/O conference in Mountain View, Calif., Google put the spotlight on the assistant, bringing new voices, including one from singer John Legend, and more visuals. Additionally, Google has beefed up voice commands for its popular Maps app, bringing the Assistant to the feature in the summer. Google execs offered demos on new iPad-like Smart Displays coming from Lenovo and Google later in the year, which will allow voice navigation via the Google Assistant to say, watch Jimmy Kimmel Live via YouTube TV or order lattes from Starbucks. Google emphasized that visuals will be coming to the Google Assistant app, to marry voice navigation with tools like food recipes, where you'll get spoken step-by-step instructions, along with video.

Google is working on technology it's calling Google Duplex that will use artificial intelligence to call businesses to make appointments and other tedious calls. In two demonstrations, one setting up a hair appointment and another a restaurant reservation, a realistic-sounding automated voice used pauses and "ums" and "mmm-hmms" to sound more human during interactions with people. "Hi, I'm calling to book hair appointment for a client," the AI voice said in the demo and then negotiated a time and date for the appointment. At its annual developers conference Tuesday, Google emphasized the technology is still in development and rolling out as "an experiment" in coming weeks. "We really want to work hard to get this right," CEO Sundar Pichai said.

Imagine you have the chance to bring back someone you love. Someone you never thought you'd see again. But the only way you can do this is by implanting memories into a bot designed to look and speak like that person, designed to help you cope as your own memories fade away. And which memories would you opt to keep … and or forget? These are just a few of the questions raised by Jordan Harrison's Pulitzer Prize-nominated play, Marjorie Prime, a fascinating and deeply human meditation on life, loss, memory, and how technology interweaves itself between all three.

Google confirmed earlier rumors surrounding its News app at the I/O developers conference on Tuesday, showing off a completely reimagined product designed to handle the rigors of our modern news cycle. The company is heavily leveraging its existing AI and Machine Learning technologies to analyze news articles in real time and organize them into storylines. The AI reportedly "understands the people, places and things involved in a story as it evolves, and connects how they relate to one another," according to a release. How the system will weed out disreputable or falsified sources, remains to be seen. Using this automated vetting system, the new Google News app will offer users a personalized stream of content that is most personally important to them.

I somewhat disagree with your comment, and overall isn't very helpful to be honest. Image Recognition is nowhere near solved and has only shown promise for high accuracy recently due to innovation in model architectures and the availability of highly parallelisable processing. Typically large dimensional data can be understood by ML much better than humans ( and in shorter times). The whole point is that it find these optimisations and discrimination hyperplanes within your data. There is of course an amount of preprocessing which can be done to reduce the dimensionality making the problem easier to solve.

Google has announced sweeping changes to its news offering, as it looks to prioritise trust. The company has long offered a specialist news service that aggregates stories from around the rest of the web. But the internet has become a much more difficult place for the news, after a run of stories that have undermined trust in platforms and publishers. Now the site claims that its newly redesigned Google News offering will make it far easier to keep up with the news, and avoid false or misleading reports. It does that using a combination of artificial intelligence and other tools.