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Human Resource

AI Can Predict Which Workers Are About to Quit Their Jobs

IBM has developed an AI that is 95.0% accurate in predicting workers who are planning to leave their jobs. IBM HR has a patent for its "predictive attrition program" which was developed with Watson to predict employee flight risk and prescribe actions for managers to engage employees. By better understanding data patterns and adjacent skills, IBM AI can zero in on an individual's strengths. In turn, this can enable a manager to direct an employee to future opportunities they may not have seen using traditional methods. The IBM technology can view the tasks employees are completing, the educational courses they have taken and any rankings they have earned. Through these data points, the AI skills inference and HR managers can gain a greater understanding of an employee's skill set than they would by assessing the feedback from manager surveys. The AI retention tool is part of a suite of IBM products that are designed to upend the traditional approach to human resources management. Read More

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Healthcare

AI Can Detect Liver Cancer Earlier Than Other Traditional Methods

Genetron Health and the Chinese Academy of Medical Sciences Cancer Hospital announced that they have found a way to detect liver cancer linked to hepatitis B, months before it can be picked up by other methods. The method called HCCscreen, applies AI to look for tumour-related mutations in DNA in blood. Researchers found that the new method could pick up early signs of the cancer in people who had tested negative based on traditional alpha-fetoprotein (AFP) and ultrasound examinations. The researchers first used the AI technology to identify biomarkers common in known cases of a type of liver cancer called hepatocellular carcinoma, or HCC. The team then developed the HCCscreen technique to look for those markers and used it on 331 people with hepatitis B who had tested negative for liver cancer in AFP and ultrasound exams. Twenty-four people tested positive with HCCscreen and were tracked over eight months, with four eventually being diagnosed with early-stage liver cancer. Read More

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Security

AI Prison Guard Makes Prison Break Impossible

Yancheng prison, a high-security Chinese facility, is using AI to govern convicts. The network of cameras will be able to monitor inmates’ every movement and flag up anything that is deemed abnormal or worrying to the human guards. The new “smart jail” system involves a network of surveillance cameras and hidden sensors that reach out like neuron fibers through the compound with a blanket coverage extending into every cell. The network collects and streams data to the “brain”, a fast, AI-powered computer that can recognize, track and monitor every inmate around the clock, without blinking. At the end of each day, the system generates a comprehensive report, including behavioural analysis, on each prisoner using different AI functions such as facial identification and movement analysis. Most of the time the reports are archived, but if anything, abnormal is detected, the machine will flag an alert. The system would know where each inmate is and what he or she is doing, no matter how large the inmate population, thus causing some experts to believe that the system will make escape impossible. Read More

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Agriculture

What Makes This Basil Taste So Good? It’s AI!

A study conducted by MIT Researchers in collaboration with Cognizant revealed that machine learning can been used to create basil plants that are extra delicious. The researchers behind the AI-optimised basil used machine learning to determine the growing conditions that would maximise the concentration of the volatile compounds responsible for basil’s flavour. The basil was grown in hydroponic units within modified shipping containers in Middleton, Massachusetts. Temperature, light, humidity, and other environmental factors inside the containers could be controlled automatically. The researchers tested the taste of the plants by looking for certain compounds using gas chromatography and mass spectrometry. They then fed the resulting data into machine learning algorithms. The research showed, counterintuitively, that exposing plants to light 24 hours a day generated the best taste. Going ahead, the research group plans to study how the technology might improve the disease-fighting capabilities of plants as well as how different flora may respond to the effects of climate change. Read More

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Healthcare

AI Can Now Diagnose Complex Eye Diseases in Real Time

DeepMind, the British AI group, has built a working prototype of a device that can diagnose complex eye diseases in real time. In a live demonstration this month of its AI system, where a patient agreed to be examined publicly, DeepMind performed a retinal scan and real-time diagnosis of her eye. The scan was analysed by a set of algorithms in Google Cloud, which provided an urgency score and a detailed diagnosis, all in roughly 30 seconds. The system can detect a range of eye diseases — including glaucoma, diabetic retinopathy and age-related macular degeneration — with the same level of accuracy as the world’s leading specialists. In recent months, the company has collaborated with the team at Moorfields to build a working product, although it has not yet received any regulatory approval. Read More

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Music

AI To Help Recognise, Assess Violinist's Gestures

Scientists from the Pompeu Fabra University in Spain have developed a novel AI system that provides real-time accurate information about a violinist's movements when playing the instrument. These gestures are extremely important, in part because they are directly related to the sound and the expressiveness of the musicians. The researchers applied AI to the automatic classification of violin bow gestures according to the performer's movement. After extracting the characteristics of the information concerning movement and audio, the researchers trained a system to automatically identify the different bow techniques used in playing the violin. The model can determine the different techniques studied with over 94.0% accuracy. The results enable applying this work to a practical learning scenario, in which students of violin can benefit from the feedback provided by the system in real time. Read More

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Healthcare

AI Can Help Treat Brain Tumours

Researchers have developed an AI method for the analysis of brain tumours, paving the way for individualized treatment of tumours. According to the study, published in The Lancet Oncology, AI machine learning methods, carefully trained on standard magnetic resonance imaging (MRI), are more reliable and precise than established radiological methods in the treatment of gliomas, a type of tumour that occurs in the brain and spinal cord. For the study, the team included 500 brain tumour patients. Using a reference database with MRI scans of patients, the algorithms automatically recognized and localized brain tumours using artificial neural networks. The algorithms were also enabled to volumetrically measure the individual areas. Read More

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Miscellaneous

AI Model Learns Relationships Among Objects with Minimal Training Data

rResearchers at MIT, MIT-IBM Watson AI Lab and DeepMind demonstrateds the potential of symbolic AI applied to an image comprehension task. The hybrid model managed to learn object-related concepts like colour and shape and then used that knowledge to understand object relationships in a scene with minimal training data and “no explicit programming.” The team’s model comprises a perception component that translates the images into an object-based representation, and a language layer that extracts meanings from words and sentences and creates “symbolic programs” (i.e., instructions) that tell the AI how to answer the question. A third module runs the symbolic programs on the scene and spits out an answer, updating the model when it makes mistakes. The researchers trained it on images paired with related questions and answers from Stanford University’s CLEVR image comprehension test set. was able to interpret new scenes and concepts “almost perfectly” and handily outperformed other AI systems with just 5,000 images and 100,000 questions used. 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

Scientists Build a Machine to Quantum Superposition of Possible Futures

Researchers from Nanyang Technological University, Singaporec and Griffith University in Australia have constructed a prototype quantum device that can generate all possible futures in a simultaneous quantum superposition. For instance, even if we have only two possibilities to choose from each minute, in less than half an hour there are 14 million possible futures. In less than a day, the number exceeds the number of atoms in the universe. The researchers realised that a quantum computer can examine all possible futures by placing them in a quantum superposition. The team implemented a specially devised photonic quantum information processor in which the potential future outcomes of a decision process are represented by the locations of photons – quantum particles of light. They then demonstrated that the state of the quantum device was a superposition of multiple potential futures, weighted by their probability of occurrence. prototype simulates at most 16 futures simultaneously, the underlying quantum algorithm can Read More

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