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.

Multiple examples have recently gone viral, each demonstrating the shortcomings of Google's search methods and the ability of the AI utilised to generate factual information. Ask Google if Obama is planning a coup, and you'll get the answer that he might be. Ask Google if women are evil and Google delivers the answer that all women have a "degree of prostitute in them". Ask Google if all republicans are fascists, and Google produces an answer that includes the suggestion they're all Nazis. Most of these answers are derisory and inherently damage Google's brand. More dangerous, however, is the potential to warp users' perception of the world by providing incorrect and unfortunately inflammatory information. By giving patently false narratives top billing on Google lends these stories unwarranted credibility. Google's utilisation of AI is helping to usher in what has been called the "post-truth" era.

We consider machine learning in a comparison-based setting where we are given a set of points in a metric space, but we have no access to the actual distances between the points. Instead, we can only ask an oracle whether the distance between two points $i$ and $j$ is smaller than the distance between the points $i$ and $k$. We are concerned with data structures and algorithms to find nearest neighbors based on such comparisons. We focus on a simple yet effective algorithm that recursively splits the space by first selecting two random pivot points and then assigning all other points to the closer of the two (comparison tree). We prove that if the metric space satisfies certain expansion conditions, then with high probability the height of the comparison tree is logarithmic in the number of points, leading to efficient search performance. We also provide an upper bound for the failure probability to return the true nearest neighbor. Experiments show that the comparison tree is competitive with algorithms that have access to the actual distance values, and needs less triplet comparisons than other competitors.

Databases are widespread, yet extracting relevant data can be difficult. Without substantial domain knowledge, multivariate search queries often return sparse or uninformative results. This paper introduces an approach for searching structured data based on probabilistic programming and nonparametric Bayes. Users specify queries in a probabilistic language that combines standard SQL database search operators with an information theoretic ranking function called predictive relevance. Predictive relevance can be calculated by a fast sparse matrix algorithm based on posterior samples from CrossCat, a nonparametric Bayesian model for high-dimensional, heterogeneously-typed data tables. The result is a flexible search technique that applies to a broad class of information retrieval problems, which we integrate into BayesDB, a probabilistic programming platform for probabilistic data analysis. This paper demonstrates applications to databases of US colleges, global macroeconomic indicators of public health, and classic cars. We found that human evaluators often prefer the results from probabilistic search to results from a standard baseline.

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.