Image 26 November 2018
Image
 
Image

Logistics

UPS Uses AI to Deliver Holiday Gifts in The Worst Storms

UPS recently built an online platform that combines machine learning and advanced analytics. The app—called Network Planning Tools, or NPT for short—lets the company’s engineers view activity at UPS facilities around the world and route shipments to the ones with the most capacity. The app gets some of its smarts from AI, which it uses to create forecasts about package volume and weight based on analysis of historical data. The launch of the NPT app has given employees a single, cloud-based platform where they could view data and run simulations to help create their plans and schedules. The algorithms understand the distribution of all the packages in every UPS trailer or plane and can figure out the best way to bypass a problematic location while still meeting deadlines and not overwhelming other UPS facilities. Read More

Image
Image

Natural Language Processing

The AI System Can Complete Your Sentence

Google alongside researchers from the Allen Institute for Artificial Intelligence, a lab based in Seattle, unveiled an English test for computers. It examined whether machines could complete sentences. The AI system, Bert can complete the missing parts of sentences almost as well as some humans. With its fundamental understanding of language, Bert or Bidirectional Encoder Representations from Transformer, can take a sentence like “the man walked into a store and bought a ____ of milk”, and fill it with the appropriate words. Though it may seem like a simple task, it can open the doors to a wide range of possibilities for AI. Natural Language Processing (NLP) brings computers closer to a human-level understanding of language. A computer system like this can learn, understand and process the small idiosyncrasies of language and use them to tackle specific tasks. Read More

Image
Image

Retail

Deep Learning Can Solve Retail Forecasting Challenges

AI is the key to unleashing value from retail datasets, particularly those used to forecast future demand. Accurate forecasts are critical for retailers (and the industries that rely on them for distribution, like consumer-packaged goods) as they depend on these predictions for revenue and operational management. Deep learning-powered solutions can find complicated patterns in data sets. For larger retailers, deep learning supports millions of SKUs at the same time, which is beneficial as it allows the models to learn from the similarities and differences to discover correlations for competition or promotion. For example, winter gloves usually sell well when puffer jackets are selling well. Read More

Image
Image

Publishing

AI Tools to Assist with Peer Review

UNSILO, Denmark, uses NLP and ML to analyse manuscripts. It automatically pulls out key concepts to summarize what the paper is about. UNSILO uses semantic analysis of the manuscript text to extract what it identifies as the main statements. This gives a better overview of a paper than the keywords typically submitted by authors. UNSILO then identifies which of these key phrases are most likely to be claims or findings, giving editors an at-a-glance summary of a study’s results. It also highlights whether the claims are similar to those from previously published papers, which could be used to detect plagiarism or simply to place the manuscript in context with related work in the wider literature. UNSILO’s prototype gets information from the PubMed Central scholarly database, which lets it compare new manuscripts with the full text of 1.7 million published biomedical research papers — a large, but limited, data set. The company says it will soon add more than 20 million further PubMed papers. Read More

Image
Image

Miscellaneous

Machine Learning to Help Manage Disasters Via Social Media Message Sorting

A research team from the Indian Institute of Technology, Kharagpur developed an algorithm for effective management of disaster time social-media posts in a bid to effectively manage the disaster. Social media platforms as they have become essential sources of real-time information regarding disasters. The victims, on-site volunteers and empathisers all of whom act as ‘social sensors’ are the ones that provide information. However, the vast volume of flow and arbitrary nature of the content makes it challenging to locate relevant information. The social media posts often contain informal language without any grammar, arbitrary shortening of words and images. The algorithm, therefore, attempts to sort the variegated, overwhelming number of social media posts during disasters. This can help real-time disaster-related news to reach the right places. The research team has employed ‘Neural Network and Deep Learning’ models to understand social media text. It can also filter rumours and hate posts. Read More

Image
Image

Miscellaneous

Suggesting Cooking Recipes Through Simulation and Bayesian Optimization

A research paper presented by University of Madrid, has presented a methodology for generating cooking recipes from an input space of variables such as ingredients, tools and other variables. Cooking can be modelled in an optimization framework, as it involves a search space of ingredients, kitchen tools, cooking times or temperatures No analytical expression can model all the recipes, so no gradients are available. The objective function is subjective, in other words, it contains noise. Moreover, evaluations are expensive both in time and human resources. Bayesian Optimization (BO) emerges as an ideal methodology to tackle problems with these characteristics. In this paper, the researchers propose a methodology to suggest recipe recommendations based on a Machine Learning ML- model that fits real and simulated data and BO Read More

Image
Image

Renewable Resources

Solving Global Water Crisis with Artificial Intelligence

Hydrological issues like flooding, precipitation, contaminant transport, and groundwater management require the availability of detailed and accurate data about the water systems, which are usually not available in the developing countries due to economic and infrastructure limitations. In such challenging scenarios, AI comes as a friendly alternative for water management. ANN algorithms are supporting to build water plants that give updated statistics about the present resources and aid to build models for the upcoming situations. It is also helping in developing the present water resources. The decision-making abilities of AI can optimize and automate of the available resources. The governing bodies and water concerned departments can understand real-time water loss and misusage, with an AI-driven planning. Recently in Greece, researchers have used a feedforward neural network trained algorithm for the stimulation of decreasing groundwater trends. They used the precipitation, temperature and groundwater level data as the vector for neural networks for prediction. Read More

Image
Image

“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.”

 
Image

Quantum Computing

Quantum Sound Waves to Open Doors for More Powerful Sensors

Scientists with the Institute for Molecular Engineering at the University of Chicago and Argonne National Laboratory have built a mechanical system—a tiny "echo chamber" for sound waves—that can be controlled at the quantum level, by connecting it to quantum circuits. The breakthrough could extend the reach of quantum technology to new quantum sensors, communication and memory. The research focuses in part on quantum electrical circuits to hook up one of these circuits to a device that generates surface acoustic waves—tiny sound waves that run along the surface of a block of solid material, like ripples moving across the surface of a pond. This phenomenon plays a key role in everyday devices like cell phones, garage door openers and radio receivers. A key breakthrough was building the two systems separately, on different kinds of material, and then connecting them together. This allowed the team to optimize each component and yet still communicate with one another. Read More

Image
Image

Quantum Computing

Quantum Computing ‘Breakthrough’ Could Lead to Commercialization

To make quantum computers usable, scientists need to expand the number of qubits and the size of the machines. This increases the probability that external factors will negatively influence the operation and effectively enforces a limit on the possible number of qubits. To solve the issue of “environmental noise”, theoretical scientist Dr Florian Mintert and colleagues from Imperial College London have used quantum physics and microwave technology – similar to that used in mobile phones – to help insulate the new computers. “They may be able to help us create new pharmaceuticals, find new cures for diseases such as dementia, create powerful tools for the financial sector, be of benefit to agriculture through more efficient fertiliser production, among many other applications". His team is now using the new technique as it puts the final touches to a powerful quantum computer prototype that is currently in its laboratory at the University of Sussex. 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