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An AI Was Taught to Play the World's Hardest Video Game and Still Couldn't Set a New Record

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What's the hardest video game you've ever played? If it wasn't QWOP then let me tell you right know that you don't know how truly difficult a game can be. The deceptively simple running game is so challenging to master that even an AI trained using machine learning still only mustered a top 10 score instead of shattering the record. If you've never played QWOP before, you owe it to yourself to give it a try and see if you can even get your sprinter off the starting line. Developed by Bennett Foddy back in 2008, QWOP was inspired by an '80s arcade game called Track & Field that requires players to mindlessly mashing buttons to win a race.


New Machine Learning Theory Raises Questions About the Very Nature of Science

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A novel computer algorithm, or set of rules, that accurately predicts the orbits of planets in the solar system could be adapted to better predict and control the behavior of the plasma that fuels fusion facilities designed to harvest on Earth the fusion energy that powers the sun and stars. The algorithm, devised by a scientist at the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL), applies machine learning, the form of artificial intelligence (AI) that learns from experience, to develop the predictions. "Usually in physics, you make observations, create a theory based on those observations, and then use that theory to predict new observations," said PPPL physicist Hong Qin, author of a paper detailing the concept in Scientific Reports. "What I'm doing is replacing this process with a type of black box that can produce accurate predictions without using a traditional theory or law." Qin (pronounced Chin) created a computer program into which he fed data from past observations of the orbits of Mercury, Venus, Earth, Mars, Jupiter, and the dwarf planet Ceres.


Interview with Intelenz Co-Founder & Head of Product Development: Renzo Zagni

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Renzo Zagni is the Co-Founder and Head of Product Development at Intelenz, a Silicon Valley Founder Institute portfolio company. Intelenz leverages the power of AI and machine learning to automate workflows and day to day processes for large enterprise organizations. Process automation enables enterprises to design workflows that reduce manual work, minimize risk, and accelerate process execution times while increasing overall business productivity. In short, process automation allows business to do more, with less, while also eliminating the risk of employee burnout, human error and extended product delivery outcomes. Intelenz's platform includes a patented No-Code'Virtual Process Manager' software, which uses AI and machine learning models through an intuitive user interface.


Pandas - Tricks Part 1 (Data Analysis with python) - Machine learning concepts

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Pandas is an extremely useful tool for Data Analysis. So, lets dive straight into some tricks that will make your life simpler using Pandas apply function. In this blog post, we will learn about how to unleash the power of pandas apply function. Create a Data frame(Table) using random data. Pass multiple arguments to a function using apply.


SARDO Is a Smartphone-Sniffing Search and Rescue Drone

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For anyone who has ever misplaced their iPhone, Apple's "Find My" app is a game-changer that borders on pure magic. Sign into the app, tap a button to sound an alarm on your MIA device, and, within seconds, it'll emit a loud noise -- even if your phone is set on silent mode -- that allows you to go find the missing handset. Yeah, it's usually stuck behind your sofa cushions or left facedown on a shelf somewhere. You can think of SArdo, a new drone project created by researchers at Germany's NEC Laboratories Europe GmbH, as Apple's "Find My" app on steroids. The difference is that, while finding your iPhone is usually just a matter of convenience, the technology developed by NEC investigators could be a literal lifesaver.


Facebook's new AI teaches itself to see with less human help

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Most artificial intelligence is still built on a foundation of human toil. Peer inside an AI algorithm and you'll find something constructed using data that was curated and labeled by an army of human workers. Now, Facebook has shown how some AI algorithms can learn to do useful work with far less human help. The company built an algorithm that learned to recognize objects in images with little help from labels. The Facebook algorithm, called Seer (for SElf-supERvised), fed on more than a billion images scraped from Instagram, deciding for itself which objects look alike. Images with whiskers, fur, and pointy ears, for example, were collected into one pile.


How To Improve Programming Skills, For Data Scientists And Machine Learning Practitioners

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Algorithms tend to scare a lot of ML practitioners away, including me. The field of machine learning arose as a method to eliminate the need to implement heuristic algorithms to detect patterns, we left feature detection to neural networks. Still, algorithms have their place in the software and computing domain, and certainly within the machine learning field. Practising the implementation of algorithms is one of the recommended ways to sharpen your programming skills. Apart from the apparent benefit of building intuition on implementing memory-efficient code, there's another benefit to tackling algorithms which is the development of a problem-solving mindset.


Affordable legal advice for all – from a robot

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An academic and a lawyer have teamed up to develop a robot lawyer, which, if successful, will make legal advice affordable to people from all backgrounds, while revolutionising the legal sector. Robots could take on significant parts of a lawyer's work, reducing the costs and barriers to access to legal services for everyone, rather than just those who can afford the high costs. The project, at the University of Bradford, is initially working on a machine learning-based application to provide immigration-related legal advice, but if successful, it could be replicated across the legal sector. The idea has received government backing in the form of a £170,000 grant from Innovate UK Knowledge Transfer Partnerships. Legal firm AY&J Solicitors is providing a further £70,000 as well as the vital knowledge of lawyers.


Top Data Science Entry Level Job

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While I will not be discussing specific companies to apply to, I will be discussing certain characteristics of an entry-level job that you should look for when becoming a Data Scientist. These qualities can also be applied to current and future jobs as a Data Scientist. The name of a company can be an important factor because it can exude reputation and stability, but you will not want to limit your search to only those companies and that is why looking for specific characteristics are also just as important. Below, I will be going more in detail about things like the business, your team, and skills to look for when you are going to land your first job as a Data Scientist. When you are first starting off as a Data Scientist, you will want to make sure you are not necessarily just doing busy work, and have a project that you can focus on right away -- after learning the data and business first.


MeInGame: A deep learning method to create videogame characters that look like real people

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In recent years, videogame developers and computer scientists have been trying to devise techniques that can make gaming experiences increasingly immersive, engaging and realistic. These include methods to automatically create videogame characters inspired by real people. Most existing methods to create and customize videogame characters require players to adjust the features of their character's face manually, in order to recreate their own face or the faces of other people. More recently, some developers have tried to develop methods that can automatically customize a character's face by analyzing images of real people's faces. However, these methods are not always effective and do not always reproduce the faces they analyze in realistic ways.