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Banking

National Australia Bank Trials AI Based Cardless ATM Transaction

National Australia Bank (NAB) and Microsoft have designed a proof of concept automatic teller machine (ATM) using Artificial Intelligence (AI) and cloud computing technologies. The cloud-based app removes the need for physical cards or devices to access cash from ATMs. Instead, a customer who opted into the service would be able to withdraw cash from an ATM using facial recognition technology and a PIN. Designed as a prototype solely to gage customer experience, the machine is able to recognize a person's face with a single scan allowing them access to their bank account. While customers may not have to remember to bring their key card, they will still have to remember their pin number to access their funds. Read More

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Healthcare

AI Tools to Improve Pathologist Accuracy and Efficiency

Two recent studies have shown that computer-assisted analysis using Google’s LYNA algorithm shows significant gains in speed required to analyze stained lymph node slides and sensitivity of micrometastases detection. The AI analyzes gigapixels worth of slide data to highlight regions of concern in slides and samples for deeper manual inspection. Google researchers analyzed whole slide images from hematoxylin-eosin-stained lymph nodes for 399 patients. They then compared the LYNA findings to those of an independent lab using a different scanner. “LYNA achieved a slide-level area under the receiver operating characteristic (AUC) of 99% and a tumor-level sensitivity of 91%. AI algorithms can exhaustively evaluate every tissue patch on a slide, achieving higher tumor-level sensitivity than, and comparable slide-level performance to, pathologists. Read More

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Media

AI Anchor to Read the News

Xinhua, China’s state-run press agency, has unveiled new “AI anchors” — digital composites created from footage of human hosts that read the news using synthesized voices. Xinhua has used footage of human anchors as a base layer, and then animated parts of the mouth and face to turn the speaker into a virtual puppet. By combining this with a synthesized voice, Xinhua can program the digital anchors to read the news, far quicker than using traditional CGI. Two anchors (one for English broadcasts and one for Chinese) were created in collaboration with local search engine company Sogou. Each anchor can “work 24 hours a day on its official website and various social media platforms, reducing news production costs and improving efficiency,” says Xinhua. Read More

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Healthcare

AI Can Diagnose Alzheimer’s 6-years Earlier Than Conventional Methods

A new study published in the medical journal Radiology showed that deep learning AI to find metabolic changes in the brain can predict Alzheimer’s disease. The research team trained the deep learning algorithm using imaging technology known as 18-F-fluorodeoxyglucose positron emission tomography (FDG-PET). FDG is a radioactive glucose compound that can be injected into the blood, and the scan can then measure the uptake of FDG in the brain cells; that uptake is an indicator of metabolic activity in the brain. The researchers had access to over 2,100 FDG-PET brain images from 1,002 patients. The algorithm was able to score 100% at detecting the disease on an average of 6 years earlier than the final diagnosis was made. The significant benefit with this new AI is that diagnosing Alzheimer’s early can allow treatments and interventions before the loss of brain volume is so massive that intervention is too late. Read More

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Human Resource

AI to Spot and Stop the Quitters in Organizations

Technology can help retain valued staff by spotting potential problems which could cause them to quit. Machine-learning embedded in employee interactions with work systems takes it a step further offering opportunities to monitor and shape behaviour. Aside from the arguably immoral possibilities of tighter employee control, positive applications include strengthening trust and preventing quitters. Gamification, personalised to an employee’s working style, promises to be an HR tool that could deter quitting. AI-powered algorithms improve retention rates and the return on human capital. Read More

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Healthcare

Machine-learning to Aid Critical Decisions in Sepsis Care

Researchers from MIT and Massachusetts General Hospital (MGH) have developed a predictive model that could guide clinicians in deciding when to give potentially life-saving drugs to patients being treated for sepsis in the emergency room. In a paper being presented this week at the American Medical Informatics Association’s Annual Symposium, the researchers describe a model that “learns” from health data on emergency-care sepsis patients and predicts whether a patient will need vasopressors within the next few hours. Early prediction could, among other things, prevent an unnecessary ICU stay for a patient that doesn’t need vasopressors, or start early preparation for the ICU for a patient that does. In predicting whether patients needed vasopressors in the next two or more hours, the model was correct 80% to 90% of the time, which could prevent an excessive half a litre or more of administered fluids, on average. Read More

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Roads & Infrastructure

Machine Learning Models to Identify Faults in Bridges

The 86 years old Sydney Harbour Bridge is in constant need of care and attention. But finding faults along the 1149-metre-long deck and 134 metre high steel arch bridge (the world’s tallest) is hard. Applying machine learning algorithms to the 2,400-sensor data means the bridge crew is alerted to issues before they appear as cracks on the surface. Work is now underway to identify faults even sooner; potentially months before they occur. Factors like the weather and temperature have a significant effect on steel. These variables are included in the training of the machine learning model, so it can account for them. The machine learning models are being constantly refined, which is now exploring clustering techniques to further improve accuracy and predict faults. Read More

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Entertainment

AI to Predict Which Movies Will Be Hits

The movie studio 20th Century Fox has developed a machine learning algorithm to predict who will like new movies. This analysis explores the temporal sequencing of objects in a movie trailer. Temporal sequencing of objects in a movie trailer (e.g., a long shot of an object vs intermittent short shots) can convey information about the type of movie, plot of the movie, role of the main characters, and the filmmakers cinematographic choices. When combined with historical customer data, sequencing analysis can be used to improve predictions of customer behavior. To explore object sequencing in movie trailers, the researchers proposed a video convolutional network to capture actions and scenes that are predictive of customers’ preferences. The model learns the specific nature of sequences for different types of objects (e.g., cars vs faces), and the role of sequences in predicting customer future behavior. The model showed how such a temporal-aware model outperforms simple feature pooling methods proposed in previous works and, importantly, demonstrate the additional model explain-ability allowed by such a model. Read More

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Pharma

AI to Resolve Bottlenecks in Drug Research

Researchers at the University of Waterloo have developed a new system that could significantly speed up the discovery of new drugs and reduce the need for costly and time-consuming laboratory tests. The new technology called Pattern to Knowledge (P2K) can predict the binding of biosequences in seconds and potentially reduce bottlenecks in drug research. Although a large amount of biological sequence data has been collected, extracting meaningful and useful knowledge is difficult. P2K algorithms tackle this challenge by disentangling multiple associations to identify and predict amino acid bindings that govern protein interactions. Since P2K is much faster than existing biosequence analysis software with almost 30% better prediction accuracy, it could significantly speed up the discovery of new drugs. Although still in the early prototype stage, the research team have made the online P2K system available publicly to researchers to start identifying new bio-sequence interactions. Read More

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Healthcare

AI Can Estimate Acute Kidney Injury Risk from Clinical Notes

Acute kidney injury (AKI) — a condition in which the kidneys suddenly fail to filter waste from the blood — can devastate the renal system of critically ill patients. A paper published by researchers at Northwestern University and the University of Texas Health Science describe an AI system that can collect and extract risk factors from electronic health records (EHRs) and predict the likelihood of AKI within the first 24 hours following intensive care unit (ICU). To train the AI system, the team sourced records of over 40,000 patients who stayed in ICUs. Five algorithms were used to classify the ICU stays and estimate AKI risk from scikit-learn, an open-source machine learning library for the Python programming language. In testing, the researchers’ supervised learning classifier was able to identify patients at risk of developing AKI more than 50% of the time and with precision. Read More

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“Quantum Computing, a revolution in technology, has shown great promise towards solving complex computing problems currently outside the capabilities of current computers. Though in its infancy, we at Decimal Point Analytics strongly believe that it is going to grow exponentially in the near future. It holds the potential not only to boost the AI revolution but also transform the way data is synthesized. The articles on Quantum computing will give an insight into the recent developments in this space.”

 
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Quantum Computing

Volkswagen to Improve Traffic with Quantum Computing

The German manufacturer's team of IT experts have recently developed a traffic management algorithm powered by quantum computers to precisely predict urban traffic movement. With this information, public transportation organizations, taxi companies, and transport service providers will be able to deploy their fleets considerably more efficiently while minimizing wait time for passengers. The benefit of using quantum computing for such a complex task is its speed and enormous capacity to crunch extensive datasets. Supercomputers are often not advanced enough to use such immense volumes of information to develop an optimized solution. Volkswagen's process consists of two main steps: the analysis of anonymous user movement data with conventional computers, and the optimization of traffic flow thanks to predictive analytics with quantum computers. The group intends to test the algorithm in Barcelona where the traffic database is abundant. Read More

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Quantum Computing

Australian Experiment Shines Light on A New Pathway for Quantum Technology

Scientists in Australia have for the first time demonstrated the protection of correlated states between paired photons — packets of light energy — that could one day prove valuable in building the supercomputers of the future. The experimental breakthrough showed a way to protect correlated photons from losing information encoded in them and researchers believe it could open the door to building a new type of quantum bit, known as qubits, which are the building blocks of quantum computers. “There is still a lot of the fundamental and applied research that needs to happen before it becomes completely commercial. There’s lots of different areas in the quantum space — there’s quantum sensing, quantum communications, quantum computing and fundamental quantum technology,” the researcher said. Read More

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