Image 28 January 2019
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Finance

AI Technology Eliminates Manual Data Entry

Canoe Intelligence is a new AI-driven solution that uses cutting-edge ocular character recognition (OCR) techniques, natural language processing technology, machine learning, and a thorough validation process to eliminate the error-prone, slow, and un-secure manual data entry process for institutional investors, pensions funds and family offices worldwide. Firms have historically relied on teams of individuals or offshore groups to manually manage data extraction and document storage, leading to industry-wide frustrations due to errors, latency, spiraling costs, and lack of control. Canoe solves these problems using a proprietary, patent-pending AI engine. Using the merits of traditional conditional random fields modeling and cutting-edge deep learning algorithms, as well as OCR, Canoe’s technology recognizes, validates and extracts unstructured investment data across asset classes, ownership structures, and document types. The data is organized digitally for easy and immediate access, and can be seamlessly fed into any portfolio reporting, accounting, and analytics platform. Read More

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Retail

AI-Powered Tool Brings Visual Search to Mobiles

Marks and Spencer (M&S) has teamed up with visual AI startup Syte, to introduce a new AI-powered ‘Style Finder’ tool to its website which allows shoppers to search for items in menswear and womenswear ranges using an image. Shoppers can now upload an existing photo or take a new one of any outfit to explore a range of similar-looking products on the M&S website. The tool uses AI technology to find results with the closest match, which customers can then narrow down with additional filters such as size, price and color. Style Finder helps customers instantly find what they're looking for, without the need to manually search and filter through the products. Read More

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Infrastructure

AI Could Change the Way Cities Maintain Roads

RoadBotics uses state-of-the-art computer-vision techniques to help local governments better manage roads. The company’s machine-learning algorithms process images of the road collected via smartphone. Then, it uses these images to produce an in-depth online map of road conditions that officials can use to make maintenance and repair decisions. The company sends out a vehicle—or the city could use its own service vehicles—with a dashboard-mounted smartphone to drive every mile of a city’s network. Videos along with their GPS location are uploaded to a cloud server. The company’s AI algorithm then uses deep-learning techniques to analyse each frame in the video, pixel by pixel. The company trains the neural networks by feeding them marked-up images of road surfaces where different colours correspond to different types of damage. The software creates a map of the road network with an overlay that shows each 3-meter stretch of road on a color-coded scale, with 1 (or green) being excellent to 5 (or red) meaning terrible and in need of repair. Read More

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Pharma

AI Finds Non-Infringing Ways to Copy Drugs

Researchers have demonstrated an AI which can find new methods for producing existing drugs in a way that doesn’t infringe on existing patents. Called Chematica, the software platform does something called “retrosynthesis,” like the kind of reverse engineering that takes place when an engineer dissects an existing product to see how it works. In the case of Chematica, this process is based on a deep knowledge of how chemical interactions take place. It has around 70,000 synthetic chemistry “rules” coded into its system, along with thousands of additional auxiliary rules prescribing when particular reactions occur and with which molecules they’re compatible. An algorithm then inspects the massive number of possible reaction sequences in order to find another way to the same finish line. Read More

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Gems and Jewellery

AI Spots Imperfection in Gems

Swiss diamond advisory firm, Diamond Pro has developed Ringo, which it is calling the world’s first AI tool to help prospective diamond buyers determine the best options while purchasing jewellery online, based on specifications such as certification, shape, setting style, and precious metal type. Diamond experts at the firm trained Ringo by having the tool review photographs of tens of thousands of diamonds. Ringo tasks buyers with narrowing down parameters in several categories, which the tool’s search algorithms use to recommend diamonds within a certain price range, in certain colors, and with a baseline level of clarity and symmetry. Its computer vision models can detect when inclusions will be visible once the diamond is placed in a particular ring setting. Ringo allows users to choose a lower clarity diamond that is clean without trusting an undereducated salesperson or blindly trusting an online store. Read More

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Healthcare

AI-Based System Can Speed Up Chest X-Ray Process

Scientists have developed a novel AI system that can reduce the time needed to process abnormal chest X-rays from 11 days to less than three days. The system developed by researchers at the University of Warwick in the UK may dramatically reduce the time needed to ensure that abnormal chest X-rays with critical findings will receive an expert radiologist opinion sooner. The researchers extracted a dataset of half million anonymized adult chest radiographs (X-rays) and developed an AI system for computer vision that can recognize radiological abnormalities in the X-rays in real-time and suggest how quickly these exams should be reported by a radiologist. The team developed and validated a Natural Language Processing algorithm that can read a radiological report, understand the findings mentioned by the reporting radiologist and automatically infer the priority level of the exam. Read More

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Agriculture

AI Can Pick Out the Bad Apples

Israeli startup Clarifruit uses computer vision and machine learning technology to quickly evaluate the quality, ripeness, and freshness of fruits and vegetables. The company has developed a produce monitoring mobile app that scans fruits and vegetables and analyses their condition to determine whether or not they are ready to go to market. The app can analyse data on such elements as the colour, size, firmness, and sugar content of a fruit or vegetable. The app can also detect imperfections such as stains. The app allows growers to instantly asses produce and transmit the data throughout the supply chain. The goal is to cut down on food waste and provide an alternative to expensive and time-consuming manual testing. Read More

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Miscellaneous

AI Predicts Parking Availability by Using Weather, Traffic Speed and Meter Data

Scientists at Carnegie Mellon University have developed an AI system that predicts parking occupancy in real time. Rather than collect data from parking sensors, which are susceptible to failure and error, the AI system depends on parking meter transactions to first estimate parking availability before using additional data for prediction. An estimated 95% of on-street paid parking is managed by meters, making their model more generalizable than sensor-dependent systems. The team used a graph convolutional neural network to model the statistical relationship among parking locations, traffic flow, parking demand, road links, and parking blocks. Together with a recurrent neural network with long-short term memory, a type of AI algorithm capable of learning long-term dependencies and a multi-layer decoder, the system extracted parking information from traffic-related data sources and output occupancy forecasts. In the future, the researchers plan to work on a model that incorporates additional traffic-related data, including traffic counts, road closure, incidents and events. 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

New Cryptography Techniques Needed for Quantum Computing

IBM, one of the leading researchers and implementors of both quantum computing and quantum-resistant security protocols states that cryptographic technology based on elliptic curves will not withstand the onslaught of quantum computers in the future. Data that is being stored today using existing cryptography methods will eventually be cracked by quantum computers capable of exponentially faster computational performance. According to IBM, a leading candidate for quantum-safe cryptography standard lies in lattice cryptography, a field which has already been studied for decades. Lattice cryptography has a unique characteristic that will make it reasonably impenetrable by quantum computing. Lattice cryptography hides data inside complex algebraic structures. It requires solving for two unknowns – a multiplier array and an offset. Read More

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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.

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