Mark Zuckerberg and Priscilla Chan's $45 billion philanthropy organization is making its first acquisition in order to make it easier for scientists to search, read and tie together more than 26 million science research papers. The Chan Zuckerberg Initiative is acquiring Meta, an AI-powered research search engine startup, and will make its tool free to all in a few months after enhancing the product. Meta could help scientists find the latest papers related to their own projects, while assisting funding organizations to collaborate with researchers and identify high-potential areas for investment or impact. What's special about Meta is that its AI recognizes authors and citations between papers so it can surface the most important research instead of just what has the best SEO. It also provides free full-text access to 18,000 journals and literature sources. Meta co-founder and CEO Sam Molyneux writes that "Going forward, our intent is not to profit from Meta's data and capabilities; instead we aim to ensure they get to those who need them most, across sectors and as quickly as possible, for the benefit of the world."

Science search engine Meta has signed an agreement to be acquired by the Chan Zuckerberg Initiative, pending shareholder and court approvals, it announced late Monday. The Facebook-founder-owned philanthropic organization revealed (on Facebook) that it would offer Meta's tools free to all researchers. Meta's secret sauce is artificial intelligence, rather than the more programmatic algorithms used by search engines like Google, and that it's optimized for scientific research. By opening up the tool to all, CZI's goal is to break down some of the barriers that preclude the sharing of information, thereby encouraging scientific progress. "In the field of biomedicine alone, researchers publish more than 4,000 scientific papers every day. But many of these papers will not be read by the scientists who could learn the most from them," said CZI's Cori Bargmann and Brian Pinkerton, in a statement.

In September, Facebook CEO and his wife Dr. Priscilla Chan promised to spend a whopping $3 billion of the Chan Zuckerberg Initiative's extensive capital over the next 10 years, as it works towards its lofty goal of curing, preventing or managing all diseases by the end of the century. To get a little bit closer to that goal, the Initiative announced Monday that it will acquire the AI-powered research paper search engine Meta and make the service free for anyone to use. Meta's search platform uses machine intelligence to analyze the number and quality of citations in medical journals and research papers, and then sorts them into the largest knowledge graph of its kind. Search results are then ranked in order of importance, similar to how Google News search gives a higher rank to highly linked sources, thus making it easier to find the most relevant or authoritative research among the thousands of scientific papers that are published every day. While that will undoubtedly help students and scientists save tons of time sifting through articles on PubMed, Meta can also help organizations decide where to direct their research budgets by identifying trends in certain areas of study or finding authors who have shown promising work in the past.

Travel brands should ensure they consider the search "intent" of prospective customers when optimising their pages, as Google turns more to advanced tech to serve results. With the search giant's increased use of machine learning and sophisticated artificial intelligences techniques to display results, smaller travel brands in particular must understand how a subtle shift is taking place in how SERPS (Search Engine Results Pages) are served. Larger travel companies, Searchmetrics argues, have an advantage as Google appears to rank them higher for content than similar items from lower-profile brands. Google is looking to understand the "real intention" behind words used by consumers, in a bid to make results more relevant, says Marcus Tober, Searchmetrics CTO and founder. "With the help of user signals, such as how often certain results are clicked and how long people spend there, the search engine gets a sense of how well searchers' questions are answered; allowing it to continually refine and improve relevance. "A searcher who types'things to remember for my beach holiday' into the search box is most likely looking for a short list for example; someone who types'height Mont Blanc' wants a single piece of information, while a query like'nice beach mallorca' is most likely wanting a series of images and a'how to pack a suitcase' query might be best served with video content." Interestingly, word count on content is beginning to become a determininh factor of the placement of sites in search results. This, according to Searchmetrics, is due to top performing results generally more detailed, cover more aspects of a topic (destination, for example). The number of keywords, however, is no longer as important as previously thought of, Tober argues. "Google is no longer just trying to reward pages that use more matching keywords with higher rankings; it is trying to interpret the search intention and boosting the content that is most relevant to the query." Finally, backlinks are also becoming less important to achieve a high ranking in SERPS. It remains a "strong correlation", Tober says, but things have changed, not least because mobile searches are now so popular and, generally, pages are more often than not "shared" or "liked", rather than linked to. "Google's application of machine learning to evaluate search queries and web content means that the factors it uses to determine search rankings are changing all the time.

Google is using the space above its search results to promote products owned by its parent company, Alphabet, Inc., it was reported on Thursday. The Internet search giant was found to utilize the precious space in order to push various products like its own Pixel phones as well as Nest smart thermostats and smokes detectors, and Android smart watches, The Wall Street Journal reported. Nest Labs is a Palo Alto, California-based company that manufactures thermostats, smoke detectors, and other home security products. It was acquired by Alphabet, Inc. in 2014 for $3.2billion. Google is using the space above its search results to promote products owned by its parent company, Alphabet.

Powerset, Inc., based in San Francisco, is on the verge of offering an innovative natural-language search engine, based on linguistic research at the Palo Alto Research Center (PARC). The engine does more than merely accept queries asked in the form of a question. The company claims that the engine finds the best answer by considering the meaning and context of the question and related Web pages. "Powerset extracts deep concepts and relationships from the texts, and the users query and match them efficiently to deliver a better search," Powerset CEO Barney Pell says. Even though attempts have been made at natural-language search for decades, Powerset says that its system is different because it has solved some of the fundamental technological problems that have existed with this kind of search.

The 3-D research was seminal in the fields of computer vision and artificial intelligence. Known as "constraint propagation," the technique is now used in industry for solving problems like route scheduling, package routing and construction scheduling. At M.I.T., Dr. Waltz was taught by Marvin Minsky, a pioneer in artificial intelligence. Dr. Waltz graduated in 1972, then taught computer science at the University of Illinois at Urbana-Champaign and, later, at Brandeis University in Massachusetts. But it was as a member of a group of researchers at the Thinking Machines Corporation, in Cambridge, Mass., that Dr. Waltz made his breakthrough in information retrieval.

With the advent of the World-Wide Web and the huge increase in the use of the Internet, there has been a corresponding increase in demand for text retrieval systems that can work in distributed, wide-area network environments. This demand also comes from groupware applications such as Lotus Notes, which facilitate the rapid creation of databases distributed throughout an organization. One problem of this type is addressed by Web search engines, such as Infoseek and Lycos, which index Web pages and provide access to them. The more general problems are locating the best databases to search in a distributed environment that may contain hundreds or even thousands of databases, and merging the results that come back from the distributed search. The results must be merged in order to produce the overall ranking of retrieved items, instead of a collection of individual rankings.

Tony Rose, vice-chair of the BCS Information Retrieval Specialist Group, looks at the management problems associated with the huge volumes of data that society produces. It has often been said that we are currently living through an information revolution. The internet age has undoubtedly brought with it a massive increase in the volume of data being produced and stored worldwide, driven by an ever-increasing demand for communication networks and online information access. For example Computing magazine reports that global information storage grew by about 30 per cent between 1999 and 2003, and that during 2002 about five exabytes of new, unique data was stored on print, film magnetic and optical storage (a volume roughly equivalent to 37,000 times the size of the book collection in the Library of Congress). Moreover when we examine the implications of this for individuals across the globe, the consequence is that almost 800Mb of recorded information is produced for each person on earth in a single year.