Implementation of Self Organizing Map Neural Network clustering to derive Empathy and Adoption Criterion of Compost Sample

The artificial intelligence self-organizing neural network is a supervised or unsupervised kind of attempt to find features and similarities in high dimension data that characterizes the data. SOM is a learning algorithm both supervised and competitive unsupervised, specifying the behavior of a node impact only those nodes and arcs near to it to uncover the hidden patterns in data. Since, compost sample consists of several mineral nutrients consisting of both light and heavy weighted metals. Out of these metals some are beneficial and some may cause terrible harm to the development of crops. Finding prediction range for such critical high dimension sample data like compost is an entail. This paper introduces the implementation process of a self-organizing neural network on the compost sample data to characterize each mineral nutrient according to a desirable value.

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Machine Learning to infer voting share in Spanish president elections

The avalanche of personal and social data circulating in Online Social Networks over the past 10 years has attracted a great deal of interest from Scholars and Practitioners who seek to analyse not only their value, but also their limits.

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“Extremely efficient AI and Machine Learning algorithms, using CPU, without any GPU, for image recognition applications”

We have used our Cognitive-Based Explainable-AI for image recognition applications.  In one case, we used only an average laptop, with CPU (not using any GPU) for both the training and recognition of the objects.  We only need 3 samples for the training purposes, in some cases.  It also needs much smaller computing power or footprint to run, as well as much lower wattage/energy/battery usage, which are huge advantages.  These are huge scientific, algorithmic, and engineering breakthroughs.

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The future of AI

As a futurist, In this speech, I will talk about the future scenarios of AI and robotics development as well as their impact on the job market as well as the education. I will also talk about the opportunities and challenges of AI in the future. Artificial General Intelligence (AGI) and Artificial Super Intelligence (ASI) will be discussed as well.

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Identifying Motion-State Hemodynamic Changes in the Motor Cortex Using fNIRS to Control A Prosthetic Arm

Neural-machine interfaces (NMIs) allow direct translation of electric, magnetic or metabolic brain signals into control commands of external devices such as robots, prostheses or exoskele-tons. Advanced myoelectric prosthetic devices for upper-limb amputees are limited due to the lack of appropriate signal sources on residual amputee muscles and insufficient real-time con-trol. NMIs are representing a recent approach to develop practical applications.

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Content Summarization at scale using State-of-Art NLP techniques in cloud environment

While natural language processing isn’t a new science it is rapidly advancing thanks to an increased interest in human-to-machine communications, plus an availability of big data, powerful computing and enhanced algorithms. NLP, also known as computational linguistics, is the combination of AI and linguistics that allows us to talk to machines as if they were human. Natural language processing helps computers communicate with humans in their own language and scales other language-related tasks.

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Future of banking with the First Arab AI and Blockchain-based eKYC-as-a-service "Meen.World" and “AnaMeen” verified digital identity app launched in Jordan

Today, Jordan Ahli Bank announced launching the instant "Bank Account–Opening" service for the first time in the Jordanian market, allowing new and existing clients to open bank accounts immediately and electronically. Through this service, Ahli provides its clients with all banking services without any exception and without the need to ever visit any of the bank’s branches unless they want to.

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State of the art and challenges on economic time series forecasting

Several techniques from the area of knowledge of artificial intelligence have been widely applied for the prediction of economic time series. The main reason for that application is to use the resulting forecasts to support the decision making process of the economic agents (e.g.: individuals, companies, governments, central banks,...).

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Automatically Resolve Trouble Tickets with Hybrid NLP

Application service providers manage huge and complicated infrastructures. Like any complicated systems, things could go wrong due to various reasons (e.g. network connection response problems, infrastructure resource limitations, software malfunctioning issues, etc.) from time to time. How to quickly resolve issues when they happen becomes critical to help improve customer satisfaction and retention. Recently, fast advancement of natural language processing (NLP) algorithms have helped solving many practical problems by analyzing text information. Powerful algorithms have been developed to interpret human language and derive predictions.

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My Story, the Story AI Tells; Bias & Privacy

With the new world of AI, there are ethical considerations with implementation. We have been thrust quickly and deeply in this new world in 2020. There are ethical implications with bias that need to be considered. Toyota Corporation does not have a quality department. Quality is every employee’s role. Business leaders will benefit greatly with a strategy to build infrastructure correctly. Humans have bias, and we are being tasked to feed AI information.

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"How to deliver a machine learning project from data collection to production"

Machine learning hype is fading out, but the technology is here to stay. Thousands of people are transitioning from data analysis, economics, finance, etc., to the data science field and honing their skills in programming and math. Tons of ML and MLOps frameworks have been built to support this fast growing field.

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