Google has been forced to open up Android to rival search engines and applications in Russia, after settling a two-year battle with competition authorities for 439m roubles (£6.2m). The deal sets a new precedent for Google, which until now has resisted permitting the pre-installation of rival search engines and certain applications on to the world's most popular operating system. In 2015, Russia's Federal Antimonopoly Service (FAS) ruled that the Android-maker was breaking the law and abusing its dominant position through restrictions on third-party manufacturers, fining Google 438m rubles (£6.2m) in August 2016. The FAS said that Google will no longer demand exclusivity of its applications on Android devices sold in Russia and will not restrict the pre-installation of rival search engines and other applications. Google will also develop a tool allowing users to choose the default search engine on new and existing Android devices, a similar measure put in place by Microsoft for browser choice on Windows following antitrust action by the European Commission.

A little over two years ago, Russia's largest search provider, Yandex, filed a complaint against Google for what it believed were anti-competitive practices. Now, Russia's Federal Antimonopoly Service has given credence to Yandex's claims and "issued a prescription to Google in order to require the company to remove anti-competitive restrictions from its agreements with manufacturers," according to a press release. That means Google won't be able to pre-install apps on phones, control the default search engine or place its own apps on device home screens in the region. Furthermore: "Google will be committed to securing the rights of the third parties to include their search engines in the choice window." In a "few months," Google will have a home-screen search widget that will offer up any manner of search providers (yep, including Yandex) assuming they sign a commercial agreement for their inclusion in the query box. For its part, the FAS says that this is a good move to ensure everyone is on the same footing in terms of competition for app placement and web searches.

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Statistical query (SQ) algorithms are algorithms that have access to an {\em SQ oracle} for the input distribution $D$ instead of i.i.d.~ samples from $D$. Given a query function $\phi:X \rightarrow [-1,1]$, the oracle returns an estimate of ${\bf E}_{ x\sim D}[\phi(x)]$ within some tolerance $\tau_\phi$ that roughly corresponds to the number of samples. In this work we demonstrate that the complexity of solving general problems over distributions using SQ algorithms can be captured by a relatively simple notion of statistical dimension that we introduce. SQ algorithms capture a broad spectrum of algorithmic approaches used in theory and practice, most notably, convex optimization techniques. Hence our statistical dimension allows to investigate the power of a variety of algorithmic approaches by analyzing a single linear-algebraic parameter. Such characterizations were investigated over the past 20 years in learning theory but prior characterizations are restricted to the much simpler setting of classification problems relative to a fixed distribution on the domain (Blum et al., 1994; Bshouty and Feldman, 2002; Yang, 2001; Simon, 2007; Feldman, 2012; Szorenyi, 2009). Our characterization is also the first to precisely characterize the necessary tolerance of queries. We give applications of our techniques to two open problems in learning theory and to algorithms that are subject to memory and communication constraints.

It's the thing no one wants to talk about but everyone is Googling. No, really: "Vaginal discharge" is searched more than 50,000 times per month worldwide according to Buzz Sumo, a keyword search engine. Everyone is wondering about this, so don't worry. I had a friend just the other day ask me if having regular discharge was normal. "I actually just cannot stay dry," she informed me.

Google and Facebook are both in the spotlight for disseminating so-called "fake news", despite the artificial intelligence (AI) systems that these companies developed and deploy on their platforms. In a much simpler time, Google was a search engine that indexed websites. Today, the search giant is evolving towards giving users summarised answers to their billions of questions. Type in a word and you'll get the definition. Type in a name and you'll get a short biography. Type in a question and roughly one in five times, Google will generate a specific answer.

About the author: Committed in developing integrated online marketing strategic solutions, Thincr LLC is specialized in providing consultancy in the realms of image reinforcement, branding, persuasion, and attitude change through Paid Search, Search Engine Optimization, Social Media, and Email Marketing. Thincr, LLC is dedicated in publishing while supporting growth and innovation and providing online businesses efficient and valuable references to help them excel in their marketing campaigns.

Artificial intelligence (AI) has come a long way since Alan Turing first posed the question, "Can machines think?" in 1950. Computers have since defeated a Russian chess grandmaster at his own game, won at Jeopardy, written a sci-fi screenplay from scratch, and can successfully prompt suggestions every time you make a search engine query. Machine learning algorithms are enabling marketers to make sense of overwhelming amounts of data and deliver better customer experiences. And to generate content in record time. The power of artificial intelligence is changing the content marketing landscape for the better. And this is exactly what we're going to discuss today.

For at least part of Friday, search engine Ask.com was plagued by a technical issue that resulted in the search queries of its users being publicly viewable online for anyone to see. The log of user actions was available on the Ask.com server status page, which displayed a rolling log of every request sent to the site--including individual search queries. The problem was first spotted by Catalyst director of strategy and innovation Paul Shapiro, who brought attention to the issue Friday morning on Twitter. It's unclear how long the problem persisted before being discovered by Shapiro. According to the server status page, the server had last been restarted three days prior, meaning the information could have been available for three days before being spotted. Each action on the log was accompanied with an IP address.

Things change pretty much on a daily basis in the world of SEO. Since the announcement of Google's AI machine learning algorithm – RankBrain – in 2015, one of the most discussed topics in SEO galleries is: With Google admitting RankBrain being one of the top three ranking factors, these discussions have become even more worthwhile. In past 3-4 months, we also saw a spike in the number of SERPed members asking the same question. And, multiple posts claiming 2017 as the year of AI and Voice Search, we think it is the right time to dive deeper to understand more about it. To get more clarity on this topic, we decided to go straight to the big guns and find out what they think about it. The responses from each expert are compiled below. Fasten your seat belts and get ready for an awesome ride. Albert Mora is the CEO and co-founder of Seolution, an SEO agency for Shopify e-commerce sites. He has been doing SEO from 1997 and has around 20 years of experience. Follow Albert on Twitter here. Since the beginning of the Internet, artificial intelligence has played a relevant role in the operation of search engines. Logically, the algorithms have been evolving, but the fundamental underlying principle remains the same: search engines want to deliver quality search results to the users. For this reason, if you want a long term sustainable SEO results, you must think about the users first, not about the search engines. Alex has more than 15 years of experience in Digital Marketing, and he is working online since 2002.