You are free to share this article under the Attribution 4.0 International license. A new artificial intelligence system can look at a photo of an outfit and suggest helpful tips to make it more fashionable. Suggestions may include tweaks such as selecting a sleeveless top or a longer jacket. "We thought of it like a friend giving you feedback," says Kristen Grauman, a professor of computer science at the University of Texas at Austin whose previous research has largely focused on visual recognition for artificial intelligence. "It's also motivated by a practical idea: that we can work with a given outfit to make small changes so it's just a bit better."

GFAIH will take place in Paris, France, at the 3 Mazarine conference centre of the Institut de France from October the 28th to the 30th, 2019. The Global Forum on AI for Humanity (GFAIH) takes place in the context of the forthcoming organisation of a Global Partnership on AI (GPAI), as decided at the last G7 summit. It will serve as the formal launch pad for GPAI and will inform GPAI Working Groups' future agenda. The GFAIH will gather experts from AI, social sciences, humanities, and engineering, as well as innovators, economic actors, policy makers and civil society representatives in order to: • reach a common understanding of the perspectives brought by AI, of the challenges to be addressed, and the methods and tools for addressing them • deliberate about projects, studies and social experiments that can lead to a corpus of shared knowledge and shape R&D agendas • consider Global Partnership initiatives to put the progress of AI for the benefit of humankind. The art exhibition of the forum is "Au-delà du Terroir, Beyond AI Art", curated by Emily L. Spratt The GFAIH is organised under the auspices of the French governement.

With the emergence of AI, there is much promise for its application in the healthcare industry. There is evidence of AI tools in medical applications that can improve efficiency of treatments and reduce costs by minimizing the risks of false diagnosis. Although it's yet to be seen how quickly the industry at large will adopt AI, we thought we'd share some interesting use cases and examples. Healthcare apps can be used to deliver medication alerts, patient education material and human-like interactions to gauge a patient's current mental state. The application of AI in the form of a personal assistant can impact monitoring and assisting patients with some of their needs when clinical personnel are not available.

Retailers the world over are relying on technology to predict consumers' purchase behaviour. For example, in its flagship store in London, Marks & Spencer analyses data from videos and IoT (Internet of Things) sensors to equip its employees to serve customers in a personalised way. UK-based supermarket chain Sainsbury's is also developing a data insights platform, which will analyse real-time consumer data and identify current trends. McDonald's in the US is reportedly working on a technology that would predict a customer's order, based on his or her past purchases. With the pressure to reinvent marketing strategies mounting, retailers in India, too, are rising to the occasion. Of late, a few offline retailers have been tapping social media analytics, machine learning and artificial intelligence (AI) data to gather information about consumers' buying history and online activities.

The Telangana government will declare 2020 as the year of Artificial Intelligence (AI) to promote its use in various sectors such as agriculture, urban transportation and healthcare. This was announced by Information Technology Minister K.T. Rama Rao during a meeting with NASSCOM President Debjani Ghosh here on Friday. The minister announced that the government would organise a series of events throughout the year centred around the AI theme. KTR, as the minister is popularly known, highlighted the various initiatives taken by the state government in the areas of emerging technologies. "Telangana government is continuing to attract investors from marquee companies which are setting up their R&D and technology development centres in emerging technologies such as IoT, AI, machine learning, cyber security and blockchain," KTR said.

Samantha Hoffman is an analyst of Chinese security issues at the Australian Strategic Policy Institute (Aspi). She recently published a paper entitled Engineering Global Consent: The Chinese Communist Party's Data-Driven Power Expansion. Internet pioneers heralded a time when information would be set free, giving people everywhere unfiltered access to the world's knowledge and bringing about the decline of authoritarian regimes… that's not really happened has it? Bill Clinton said that, for China, controlling free speech online would be like "nailing Jell-O to the wall". I wish he had been right.

The world of data can be chaos! New technologies, tools, products and the ever-changing industry dynamics--there sure is a lot to keep up with. So, what do you do to cut through the noise? Well… one way is to follow the greatest in the world of data science and simply hang on to their every word. We created a list of people who are followed by the humans of data around the world, share their experiences and insights regularly on social media and are well connected to the community.

Recent surveys, studies, forecasts and other quantitative assessments of the progress of AI highlighted the growth in consumers' acceptance of chatbots, especially for help with routine tasks; questions about medical AI algorithms missing the worst patient outcomes; and new predictions for 2020 and beyond about the future of AI and work. Manpower France collects 1.3 million invoices from 80,000 companies annually. After nine months of testing Sidetrade's Aimie, a traditional machine learning-based tool, Manpower found that its collections increased 12% [Fortune] The first eight IT teams at Fannie Mae to receive Moogsoft's AIOps tool have seen a 35% reduction in IT incidents over the past 12 months; the teams using the AIOps tool have cut the time needed to resolve problems by between 25% and 75%, depending on the issue; Fannie expects that when it deploys the AI system to all business units and the system gets better at pinpointing root causes, monthly incidents will decline by 50% to 60% over the next year [WSJ] Familial hypercholesterolaemia or FH is a common genetic disorder that carries a 20-times higher risk for life-threatening cardiovascular disease, but today less than 10% percent of the 1.3 million Americans born with FH are diagnosed. The FIND FH screening algorithm was trained on data from 939 clinically diagnosed individuals and 83,136 individuals presumed free of FH. The model was then applied to a national health-care encounter database (170 million individuals) and an integrated health-care delivery system dataset (174,000 individuals).

Google on Friday announced its "biggest leap forward" in years in its search algorithm, offering an unusually detailed public explanation of its secret formula. The world's most popular internet search engine said its latest refinement uses machine learning to improve how it handles conversationally phrased English-language requests. "We're making a significant improvement to how we understand queries, representing the biggest leap forward in the past five years, and one of the biggest leaps forward in the history of search," Google search vice president Pandu Nayak said in an online post. The California-based internet company last year debuted a neural network-based technique for processing "natural language." The company said the new effort is based on what it calls Bidirectional Encoder Representations from Transformers (BERT), which seeks to understand query words in the context of sentences for insights, according to Nayak.

Finding new medicines is like finding a needle in a haystack. By linking a powerful computational ... [ ] approach to advances in chemical manufacturing, this company is making piles of needles. Finding new drugs is hard. Sometimes we don't even know how a disease works, and drug tests in animals don't always go the same as in humans. Drugs can even behave very differently from person to person.