Artificial Intelligence to Assess Business Health and Sales Projections Based on Social Media Score

After Chipotle Mexican Grill Inc.’s queso was trolled on Twitter on its debut last year, Royal Bank of Canada Capital Markets research department used artificial intelligence to robustly understand how social media actions, like tweets and Google searches can affect their business. The result was a research note subtitled “Worst queso scenario?” that used analysis of tweets and Google searches to help analyst David Palmer make estimates on Chipotle’s earnings and sales. Data showed that negative tweets outnumbered positive ones in the week after the queso launch, and that sentiment remained negative, though improving, for some time. Two years ago, finding correlations between social media data and stocks didn’t work, but advances in natural language processing with AI makes this data more valuable in finding impact.

Artificial Intelligence to Automate Material Designing

Materials scientists have always tried to incorporate natural traits like toughness of bones or conch shells into man-made materials. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have developed a system where designers numerically specify the properties they want their materials to have, and the system generates a microstructure that matches the specification. The optimal microstructure of the material is produced by tradeoff between three different mechanical properties. Researchers generated computer models of microstructures and used simulations to score them according to measurements of three or four mechanical properties. Each score defines a point in a three- or four-dimensional space. Then they constructed a cloud of points, each of which corresponded to a specific microstructure. Once the cloud was dense enough, the researchers computed a bounding surface that contained it. Points near the surface represented optimal trade-offs between the mechanical properties.



Deepmind Develops AI to Diagnose Eye Diseases

Google’s DeepMind has developed artificial intelligence to diagnose diseases by analyzing medical images. The company developed an algorithm and trained it by feeding it data from thousands of retinal scans. The algorithm can analyze for diseases like diseases glaucoma, diabetic retinopathy and age-related macular degeneration. Google did it in partnership with National Health Service and London’s Moorfields Eye Hospital. Algorithm has been trained using 3D retinal scans provided by Moorfields. In the next stage, company is looking for conducting clinical trials and training the algorithm to analyze radiotherapy scans. DeepMind now employs 100 people in its health team, compared with just 10 three years ago. The company has set up a research unit focused on the ethical and social implications of the AI it is creating.

Google To Use ML to Predict Flight Delays

“Google Flight app” is now going to predict whether your next flight is getting delayed or not. The app uses previous flight histories combined with machine learning algorithms to predict delays. The predictions are made before the official airlines announcements. User needs to just put in their flight number or the route they are travelling to receive details instantaneously on their phone screens. The company claims to be at least 80 per cent confident in the predictions. Other optional features like overhead bin space size, seat selection, baggage fee etc. are in pipeline. Currently, the features are currently limited to American, Delta, and United Airlines.



Machine Learning Start-Up to Explore Fish Farming

Aquabyte, a ML startup has raised $3.5 million in seed funding to develop ML software which can reduce costs for fish farming. The company is working with pilot customers in Norway and San Francisco. The company will develop two algorithms one to determine the size of salmon over time, and the other to determine the presence of sea lice, a parasite sometimes found on salmon. "Fish are exothermic - and respond to their environment - which means that a lot of data, from both camera data using computer vision, multi-sensory environmental data like temperature and oxygen, and human input data such as how much to feed - make this a very rich data problem for machine learning," said Aquabyte CEO Bryton Shang. The data is gathered using underwater 3D cameras.

Google Is Using Machine Learning to Clean Its Play Store

Over the past 12 months Google took down 700,000 apps from the Play Store. Google used its AI-powered engine to detect abusive app content and behaviors like impersonation, inappropriate content, or malware which then helped the human reviewers detect problematic apps. Earlier, Adult Swine bug had infected Play Store by sending malicious ads to kids. The company boasts that 99 percent of apps “with abusive contents” were tossed from the Play Store before anyone could install them. There is still a lot of work to be done on the algorithm along with making detection engine more powerful. “Despite the new and enhanced detection capabilities that led to a record-high takedown of bad apps and malicious developers, we know a few still manage to evade and trick our layers of defense.”, says the company.



Artificial Intelligence Helps to Decipher Ancient Manuscripts

Greg Kondrak, a computer science professor and graduate student called Bradley Hauer used natural language processing to decipher the texts written in “Vonyich” manuscript from 15th century. The first step was to figure out the language of origin which were written on delicate vellum pages with illustrations. Using samples of 400 different languages from the “Universal Declaration of Human Rights” the researchers tried to decode the language. They first turned to Hebrew scholars to decode the text followed by Google Translator to come up with a meaningful sentence. Kondrak says that he is looking forward to using the algorithms he and the student developed on other ancient manuscripts.

Artificial Intelligence to Detect Sexual Orientation

Stanford researcher Michal Kosinski published a preprint of a paper claiming that the profile pictures one uploads to social media and dating websites can be used to predict our sexual orientation. Kosinski, a Polish psychologist, co-authored a paper that found that people’s Facebook “likes” could be used to predict personal characteristics like personality traits. Kosinski built a program with his co-author Yilun Wang using a common artificial intelligence program to scan more than 30,000 photos uploaded to an unnamed dating site to figure out a pattern about what could distinguish a gay person’s face from a straight person’s. The resulting program accurately identified a gay man 81 percent of the time and a gay woman 71 percent of the time. The program based its decision on differences in facial structure.



MIT To Probe Deeper into Human and Artificial Intelligence

Massachusetts Institute of Technology is launching a programme to understand human intelligence and apply that knowledge to develop intelligent machines. “MIT Intelligence Quest” is seen as an academic effort to stop flow of most talented scientists and engineers away from the world of academia towards tech and finance industry, majorly. The tech industry has acknowledged the fact that it has been poaching too many AI experts from various universities which can adversely affect the research and development in the field. The industry is responding to this by increasing academic funding to universities and by having more collaborations with them. University’s president Rafael Reif said that MIT IQ programme aims to answer two big questions, “How does human intelligence work, in engineering terms? And how can we use that deep grasp of human intelligence to build wiser and more useful machines?”


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