Big Data Analytics Solutions | Financial Services in India |Decimal Point Analysis
Image 19 June 2019
Image
 
Image

Technology

AI To Help Detect Objects and Classify Images

Nomura Research Institute (NRI) is helping Japanese convenience stores use data from in-store cameras to monitor inventory. NRI is also helping Japanese airports to optimise people flow based on traffic patterns observed inside the airport. For this, NRI turned to Acer and AWS to meet their goals. Acer aiSage, is an edge computing device that uses computer vision and AI to provide real-time insights. Acer aiSage makes use of Amazon SageMaker Neo, a service that lets a person train models that detect objects and classify images once and run them anywhere, and AWS IoT Greengrass, a service that brings local compute, messaging, data caching, sync and machine learning inference capabilities to edge devices. Amazon SageMaker Neo makes it possible to train machine learning models once and run them anywhere in the cloud and at the edge. It starts with a machine learning model and is then trained using Amazon SageMaker. With a single click, it compiles the trained model into an executable. Read More

Image
Image

Nanoengineering

AI Graph Networks to Accurately Predict Properties of Molecules & Crystals

Nanoengineers at the University of California have developed new deep learning models that can accurately predict the properties of molecules and crystals. These models provide researchers the means to rapidly scan the nearly-infinite universe of compounds to discover potentially transformative materials for various technological applications, such as high-energy-density Li-ion batteries, warm-white LEDs, and better photovoltaics. To construct the model, the team used a new deep learning framework called graph networks, developed by Google DeepMind. The graph network-based models, dubbed MatErials Graph Network (MEGNet) models, outperformed the state of the art in predicting 11 out of 13 properties for the 133,000 molecules in the QM9 data set. The team also trained the MEGNet models on about 60,000 crystals in the Materials Project. The models outperformed prior machine learning models in predicting the formation energies, band gaps and elastic moduli of crystals. Read More

Image
Image

Telecommunication

Thanks to AI! Background Noise on Calls Could Now Be a Thing of the Past

Krisp is an app that uses machine learning to silence the bustle of a home, shared office or coffee shop so that the speaker’s voice and the voices of others come through clearly. Like so many apps and services these days, Krisp uses machine learning. But unlike many of them, it uses the technology in a fairly straightforward, easily understandable way. The machine learning model is trained to recognise the voice of a person talking into a microphone. By definition, pretty much everything else is just noise — so the model just sort of subtracts it from the waveform, leaving the audio clean. It can also mute sound coming from the other direction — that is, the noise on the receiver’s end. The app is now available on Windows and Mac after a long beta. Read More

Image
Image

Security & Surveillance

AI to Reduce Racial Bias When Charging People with Crimes

Stanford University is helping San Francisco prosecutors reduce racial bias in court. The "bias mitigation tool," which was developed by the Stanford Computational Policy Lab, scans police incident reports and automatically eliminates race information and other details that could identify someone's racial background as a way to prevent prosecutors from being influenced by implicit biases. The tool, which was built at no cost to the city, works in two phases. First, the technology redacts information including the names of officers, witnesses and suspects, as well as specific locations, districts, hair and eye colour — basically anything that could be used to suggest a person's race. After finishing the bias mitigation review, prosecutors will make a preliminary charging decision. Then, during the second phase, they'll have access to the full unredacted report and any other non-race blind information such as police body camera footage. The tool will be fully implemented starting July 1, 2019. Read More

Image
Image

Healthcare

AI to Assist in Disease Diagnosis

UK-based technology startup, Feebris is using AI algorithms for the precision detection of complex respiratory conditions. It connects to existing medical sensors and can be used by non-doctor users to identify respiratory issues early, avoiding complications and hospitalisations. Based on a mobile application, Feebris is powered by off-the-shelf sensors such as digital stethoscopes and pulse oximeters. A non-medical user can capture measurements, which are then analysed by Feebris’ algorithms to identify different disease markers and detect a health issue. A recommendation is issued to the user and a summary of the examination could be shared with a doctor. Feebris has already achieved a plethora of impressive milestones. Following successful clinical tests that proved the efficacy of the AI in detecting childhood pneumonia, the platform is now being used in India by community health workers to deliver 10,000 examinations to children under the age of 5. Read More

Image
Image

Logistics

AI Solution to Optimize Logistics Network

Thyssenkrupp Materials Services (tkMX), one of Germany-based thyssenkrupp AG’s strategic business areas has built an AI solution. The “Alfred” AI solution, powered by Microsoft Azure, helps the company analyse and process more than two million orders per year and better serve its 250,000 global customers. Though Alfred has been in place for just under a year, the solution is already helping tkMX optimise its logistics network – allocating materials to the right location much faster, minimizing transport volume and enhancing usage of the company’s transport capacity. Alfred dynamically indicates from which site one should ship which material to which customer. Alfred also optimizes stock levels. Alfred states what the perfect price for a specific customer for a specific product is. Alfred also visualizes and states which customers are profitable and which customers are not. Alfred can help build a predictive maintenance model for machinery and tells which machine is about to break. Alfred also helps to optimize supply network in terms of physical sites, like where should one open the next site or close it down. Read More

Image
Image

Miscellaneous

Say Adios to Typos! AI is Here!

WhiteSmoke is a top-rated app that uses intelligent algorithms to spot small and big mistakes. It works across all major platforms, providing assistance with spelling, grammar, and more. At present, people probably rely on Microsoft Word or Google Docs to flag up problems in prose. But these apps aren’t smart enough to understand the true meaning of each sentence. As a result, they regularly miss errors and make unhelpful suggestions. In contrast, WhiteSmoke utilises AI technology to spot the errors that other apps miss. The app finds spelling mistakes, grammar problems, and punctuation slip-ups in 50 languages. It can also make smart style suggestions and check one’s work for plagiarism—perfect for students. WhiteSmoke is available as a standalone desktop app on Windows and Mac and as a browser extension. A Premium subscription of the app includes free updates for life. Read More

Image
Image

Decimal Point Analytics Pvt Ltd does not make any recommendation, solicitation, or offer for any securities and is not responsible for suitability of any securities for any purpose, investment or otherwise. It is the sole responsibility of the client, as a professional organization, to exercise professional due diligence in ensuring suitability of investment and ensuring that when the client publishes a part or full report under its own brand, the legal requirements for distribution of such material are complied with in all the jurisdiction in which it is published. Decimal Point Analytics Pvt. Ltd. shall not be responsible for any loss suffered by the user. The returns indicated, including future projections, in any investment report prepared by Decimal Point Analytics Pvt Ltd are not guaranteed in any manner and may not be achieved.

India :

5A, B-Wing, Trade Star Building, J. B. Nagar, Andheri-Kurla Road, Andheri (East), Mumbai - 400 059, Maharashtra, India
+91 22 30015200
info@decimalpointanalytics.com

United Kingdom:

1st Floor, 99, Bishopsgate, London, EC2M 3XD, United Kingdom

+ 44 20 3286 1998
info@decimalpointanalytics.com

USA:

17 State Street, Suite 4000, New York, NY 10004 U.S.A

+1 (917) 341 3218
info@decimalpointanalytics.com

www.decimalpointanalytics.com

×

Decimal Point Analytics (DPA) will process the information in this form to share information as requested. By checking the above box you confirm your acceptance to receive the communication. You can unsubscribe any time by clicking the ‘Unsubscribe’ link in the footer of any email you receive from us, or by contacting us at

We use cookies to measure website performance, provide social media features and personalize content.
Close this dialog to confirm you are happy with that, or find out more in the privacy statement.