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Democratization of Artificial Intelligence: Is it a Boon or Bane?

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Internet is everywhere, anyone from anywhere could access it and learn many things indeed. The same applies to Artificial Intelligence (AI) as well. Anyone with access to the internet could learn and explore the realms of AI without depending on an external factor like a course or maybe a degree. Anyone who has a spark to learn AI in and out could do it just with the readily available sources. This is the exact concept of the Democratization of Artificial Intelligence.


An AI-Controlled Drone Racer Has Beaten Human Pilots For The First Time

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Drone racing is an increasingly popular sport with big money prizes for skilled professionals. New control algorithms developed at the University of Zurich (UZH) have beaten experienced human pilots for the first time – but they still have significant limitations. In the past, attempts to develop automated algorithms to beat humans have run into problems with accurately simulating the limitations of the quadcopter and the flight path it takes. Traditional flight paths around a complex drone racing course are calculated using polynomial methods which produce a series of smooth curves, and these are not necessarily as fast as the sharper and more jagged paths flown by human pilots. A team from the Robotics and Perception Group at UZH has developed a trajectory planning algorithm to calculates the optimal route at every point in the flight, rather than doing it section by section.


Using Machine Learning to Increase the Accuracy of your Questionnaire or Calculator

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In this article, I will help you use machine learning alongside your calculator or questionnaire to learn more about your users. After reading, you will know everything you need to fill in the blanks of optional questions with educated guesses as to what users might have responded. I used Python Pandas to do so, but all concepts should carry over to any language you're using. Thus, continue reading if you check the following boxes. You want to improve the accuracy of your calculator or quiz's results Great -- lets dive in!


AI's human protein database a 'great leap' for research

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Scientists on Thursday unveiled the most exhaustive database yet of the proteins that form the building blocks of life, in a breakthrough observers said would "fundamentally change biological research". Every cell in every living organism is triggered to perform its function by proteins that deliver constant instructions to maintain health and ward off infection. Unlike the genome -- the complete sequence of human genes that encode cellular life -- the human proteome is constantly changing in response to genetic instructions and environmental stimuli. Understanding how proteins operate -- the shape in which they end up, or "fold" into -- within cells has fascinated scientists for decades. But determining each protein's precise function through direct experimentation is painstaking.


Getting Started in Medical AI

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The course takes a top-down approach starting with a few lines of computer code, rather than establishing detailed mathematical notation. The first lesson will guide you through the construction and testing of your own deep learning model.


Neural Style Transfer

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Leon Gatys et al. introduced the Neural Style Transfer technique in 2015 in "A Neural Algorithm of Artistic Style". As stated earlier, Neural Style Transfer is a technique of composing images in the style of another image. Neural Style Transfer (NST) refers to a class of software algorithms that manipulate digital images or videos to adapt the appearance or visual style of another image. NST algorithms are characterized by their use of deep neural networks for the sake of image transformation. If you want to go deep into the original technique, you can refer to the paper from this link.


Demystifying Artificial Intelligence

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Artificial intelligence (AI) leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. Artificial intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. Tesla CEO Elon Musk, the second richest in the world, even stated: "We're headed toward a situation where AI is vastly smarter than humans. I think that time frame is less than five years from now."


Algorithm May Help Autonomous Vehicles Navigate Narrow, Crowded Streets

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The researchers developed a method to model different levels of driver cooperativeness how likely a driver was to pull over to let the other driver pass and used those models to train an algorithm that could assist an autonomous vehicle to safely and efficiently navigate this situation. An algorithm developed by researchers at Carnegie Mellon University (CMU) could enable autonomous vehicles to navigate crowded, narrow streets where vehicles traveling in opposite directions do not have enough space to pass each other and there is no knowledge about what the other driver may do. Such a scenario requires collaboration among drivers, who must balance aggression with cooperation. The researchers modeled different levels of cooperation between drivers and used them to train the algorithm. In simulations, the algorithm was found to outperform current models; it has not yet been tested on real-world vehicles.


Five Reasoning Methods To Rule Them All.

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The five reasoning methods are also called the five tribes. They help to solve the Master Algorithm. Each of the five tribes has a different technique and strategy for solving problems that result in unique algorithms. If we are successful to combine these algorithms, then it will lead us to (theoretically) the master algorithm. These are defined by the Portugues author, Pedro Domingos in his book The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World.


12 Bytes by Jeanette Winterson review – how we got here and where we might go next

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In Mary Shelley's 1818 novel Frankenstein, a scientist creates life and is horrified by what he has done. Two centuries on, synthetic life, albeit in a far simpler form, has been created in a dish. What Shelley imagined has only now become possible. But as Jeanette Winterson points out in this essay collection, the achievements of science and technology always start out as fiction. Not everything that can be imagined can be realised, but nothing can be realised if it hasn't been imagined first.