July-2020 Challenge “Spatial Business Rules”

Our July Challenge asks you to implement spatial rules oriented to business users not familiar with GIS APIs. Examples of the rules include:
1) If at least one hospital is within 5 km from the Airport increase Spatial Significance Score by 5
2) If Hospital Referral Region has fewer than 5 Hospital Service Areas in it decrease Spatial Significance Score by 1
3) If there are between 5 and 15 Hospitals within 25 km of the Airport increase Spatial Significance Score by 3
How will use represent these business rules using DMN-like decision tables? Link

Posted in Challenges, Decision Modeling, DMN | 1 Comment

What comes after Zoom?

Benedict Evans: “There will be video in everything, just as there is voice in everything, and… then it will disappear inside. You don’t necessarily need an account to join a call, and you generally don’t need an application either, especially on the desktop – you just click on a link in your calendar and the call opens in the browser. Indeed, the calendar is often the aggregation layer – you don’t need to know what service the next call uses, just when it is.Link

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What is emotion AI and why should you care?

An article with this title was published by KDnuggets. “Emotions help us to understand and explore the world. What if we could incorporate emotions into machine learning systems to help inform them?Link Continue reading

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The 25 greatest Java apps ever written

From space exploration to genomics, from reverse compilers to robotic controllers, Java is at the heart of today’s world. Java Magazine offers a few of the countless Java apps that stand out from the crowd. Link

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The latest NLP revolution

Read an interview with Noam Shazeer who helped spark the latest NLP revolution. “He developed the multi-headed self-attention mechanism described in “Attention Is All You Need,” the 2017 paper that introduced the transformer network. That architecture became the foundation of a new generation of models that have a much firmer grip on the vagaries of human language. Shazeer’s grandparents fled the Nazi Holocaust to the former Soviet Union, and he was born in Philadelphia in 1976 to a multi-lingual math teacher turned engineer and a full-time mom.” Read more

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Extracting Data from Templatic Documents

In this article Google researches describe a novel approach using representation learning for tackling the problem of extracting structured information from templatic documents, such as receipts, bills, or insurance quotes. They “propose an extraction system that uses knowledge of the types of the target fields to generate extraction candidates, and a neural network architecture that learns a dense representation of each candidate based on neighboring words in the document.” Link

Posted in Human-Machine Interaction, Machine Learning, Natural Language Processing | Leave a comment

Top 5 Serverless Platforms in 2020

Companies transfer to serverless computing to become more agile, scalable, and efficient. Instead of maintaining their own server infrastructure and investing in storage space, businesses can cooperate with professional vendors who specialize in providing safe, fast, and reliable computing infrastructure. This article describe pros and cons of the top 5 platforms: 1) AWS Lambda 2) Google Cloud Functions + Firebase 3) Microsoft Azure 4) Alibaba Functions 5) IBM Bluemix/OpenWhisk   Link

Posted in Architecture, Cloud Platforms, Microservices, Serverless | Leave a comment

Can a human brain hold your life experience?

human brain is an amazing instrument. It combines huge data storage with massive real-time processing. According to Scientific American [1], the memory capacity of the human brain was reported to have the equivalent of 2.5 petabytes (2500 TB) of memory capacity. This number was obtained by estimating how much information can be stored by 125 trillion synapses in the cerebral cortex. Link

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Bob Moore: building a learning model is a learning process in itself

Dr. Bob Moore accepted our Jan-2020 Challenge “Nim” and provided a very interesting machine learning solution. He applied a self-learning approach by playing games in which both players use the latest learned strategies that are being constantly improved. In a way, his approach is similar to AlphaGo when a program becomes its own teacher. Dr. Moore’s solution is  written in Python without any 3rd party ML tools and leaves a space for experiments and possible improvements – he makes all sources available upon a request. Link Bob will present his solution at pre-DecisionCAMP Zoom session  – join us on June 4 at 12:00p EST

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Solving Previously Unsolved Optimization Problems

Mixed-integer programming (MIP) problem is arguably among the hardest classes of optimization problems. This paper describes how  21 previously unsolved MIP instances were solved using up to 80,000 cores in parallel on the Titan supercomputer. Link

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