Smart Shipping Port to be Built on Innovative Applications of IoT & Artificial Intelligence

IBM & Port of Rotterdam will work together to develop model for a smart shipping port. Port will use Internet of Things (IoT) sensors, artificial intelligence (AI), and big data to increase its efficiency. Information regarding weather, water, and communications etc. will be measured by IoT. Combined with this data, the real time information on ship cargos and officials will be provided to all concerned parties. As per the estimates, shipping companies may realize savings upto $80000/hour post-implementation. Additional technologies will be implemented into the project on an on-going basis.

AI Powered Wearables to Detect Signs of Diabetes

A study made by health startup Cardiogram and the University of California, San Francisco revealed that combining neural networks with common fitness-centric wearable can help detect early signs of diabetes. It works on an algorithm that connects heart rate variability to the likelihood of diabetes. Cardiogram and UCSF resorted to semi-supervised machine learning techniques to train the DeepHeart deep neural network using 33,628 person-weeks worth of health sensor data. The accuracy touched a mark of 85%. Anyone with a compatible smartwatch or fitness tracker can simply download the app and get themselves checked instantaneously.



Machine Learning to Benefit the Steel Making Industry

AI may not be known for its role in manufacturing and operations, but there is an opportunity to use these tools to dramatically improve the efficiency and effectiveness of these important industries. Big River Steel, based in Arkansas, makes extensive use of sensors, control systems, and machine learning-based optimization. There are six major areas in which Big River uses machine learning, namely demand prediction, sourcing and inventory management, scheduling optimization, production optimization, predictive maintenance, and outbound transportation optimization.

Artificial Intelligence to Help User Stay Motivated to Workout

Rock My World, San Diego-based company has designed the app “” keeps user motivated to work out on a daily basis. User interact with artificial intelligence through Facebook Messenger. User logs in their workout and AI responds back with encouragement and appreciation. One of the main objective of the app is to keep user laughing by engaging them with interactive conversations. The challenge Jolt faces is how does it naturally process language to make it capable of fluid conversations. AI does not have the ability to infer things from a conversation that are not explicitly said, unlike humans. Currently it asks user for extra confirmation, but it detracts the conversation from being natural.



Artificial Intelligence to Manage Crowd Gathering in Public Places

Four Japanese companies TBWA\Hakuhodo, Yukai Engineering, Crimson Technology and Kotobukisun have partnered to launch a new smart megaphone, “Animegaphone” to provide better crowd control in Japan. In Japan, use of megaphones have become so common that now announcements and instructions are often ignored by the public at large. The new megaphone is equipped with voice changing artificial intelligence technology that analyses vocal data input while reflecting the user’s speech pattern, accent, intonations and other individual vocal characteristics. It then synthesises and merges the voice into a pre-registered voice of another person, with almost no lag or delay. Authorities believe that changing a security personal’s voice to that of the leader of the crowd can get their attention and further make them obey instructions as well.

AI to Combat Online Hate Speeches

With never ending online rage and low tolerance for else’s opinions, hate speeches seemed insurmountable until now. But now, Agency Possible and software company Spredfast aims to curb the menace of hate speech. “WeCounterHate” counter hate speeches online on Twitter and makes donation to a non-profit organization “Life After Hate” for every tweet it cleans. Life After Hate is a nonprofit founded in 2011 that offers community education, helps individuals exit hate groups and provides support for family and friends. Creative technologist Shawn Herron inspired the idea with a text to executive creative director Ray Page. One challenge for Possible was to develop programming ability to identify hate speech. The team used Spredfast to find different kinds of hate speech, program that into an AI engine to teach it what hate speech is and classify tweets based on how hateful they were.



Now Google Is Teaching AI How to Multitask

Google’s Deepmind team revealed a new approach to train deep learning networks that combines advanced algorithms and old school video games. The team developed a training system called Importance Weighted Actor-Learner Architectures (IMPALA) with which an AI system plays a whole bunch of video games really fast and sends the training information from a series of “actors” to a series of “learners.” Google used its own DMLab-30 training set which is built on ID Software’s Quake III game.

AI Developed Test to Help Early Detection of Leukemia

Sophia Genetics, a Swiss company, has developed a molecular diagnostics tool in which the technology reads the genome more precisely to improve the diagnosis of leukemia and boost the personalization of cancer care. The company has received a CE-IVD mark which means it can now trade its invention within the European single market. The test allows the detection of mutations that cause blood cancers like leukemia. The technology behind the test can even read key biomarkers of blood cancers like mutations to the CEBPA, FLT3, and CALR genes, thus helping in early detection. Company’s AI data analysis technology is combined with liquid biopsies which makes the test more accurate.



An Algorithm to Summarize Lengthy Texts

Researchers at Salesforce have developed an algorithm showing how computers can be deployed to summarize lengthy documents, thus saving a lot of human time and effort. It uses several machine-learning approaches to produce accurate snippets of text from its longer pieces. System learns from examples of good summaries and also uses artificial attention to the text it is receiving and sending. This helps to ensure that there aren’t too many repetitive strands of text while summarizing. Caiming Xiong, a research scientist at Salesforce believes that the software could provide synopsis of customer e-mails. summarize daily news articles and many other similar repetitive tasks.


A Machine Learning Way to Detect and Treat People with Depression

A new study published by Clinical Psychological Science has unveiled “class of words” that can help predict whether someone is suffering from depression or not. Researchers Mohammed Al-Mosaiwi and Tom Johnstone of Department of Psychology, School of Psychology and Clinical Languages, University of Reading claimed that people showing signs of depression tends to use more of ‘absolutist words’ than their counterparty control group. Computerised text analysis methods are used to process texts to generate a score. Scoring methodology includes calculating the percentage prevalence of words and classes of words, lexical diversity, average sentence length, grammatical patterns and many other metrics. Research included recovery forums too and found out that negative emotion words were used at comparable levels to control the control groups while positive emotion words were elevated by approximately 70%.


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