If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Every week we bring to you best research papers, articles and videos that we have found interesting that week. Rubik's Code is a boutique data science and software service company with more than 10 years of experience in Machine Learning, Artificial Intelligence & Software development. Check out the services we provide. Eager to learn how to build Deep Learning systems using Tensorflow 2 and Python? Get our'Deep Learning for Programmers' ebook here!
We've picked our favorite AI-related stories from 2019. While we celebrate the positive impacts of artificial intelligence let's not forget there's also a lot to be concerned about. Apple Card users have alleged that its credit decision algorithm discriminates against women. Moving AI from the cloud to the edge was a big trend in 2019. Chris Cheng, distinguished technologist on the hardware machine learning team at Hewlett Packard, takes a look at some of the latest research being done on AI inference at the edge.
Over the years, artificial intelligence has amazed everyone with numerous breakthroughs, and this year it was no different. The whole year, we witnessed awe-inspiring innovations in reinforcement learning, neural networks, among others. Tech companies from across the world benchmarked various leaps in artificial intelligence to further eliminated the doubts people had about achieving true AI. As a chronicler of the technological progress in the space of analytics, artificial intelligence, data science and big data, among others, Analytics India Magazine was on top of every jaw-dropping development. We bring to you the top 7 amazing AI advancements that changed the world forever.
As you may already know, the amount of data that we create, and store, as human beings has been growing immensely in the last few years. We start having more and more devices that can create, send, store and save data – we can just look at our mobile phones, and how powerful they have become in the last few years. One study is showing that the amount of data, on a global level, will reach 175 zettabytes (ZB) by year 2025 (just as a fun-fact, and for comparison: 1000 Terabytes 1 Petabyte; 1000 Petabytes 1 Exabyte; 1000 Exabytes 1 Zettabyte). Obviously, this is a lot of data. Data can be considered everything that one business creates, or even an individual (from basic stuff like pictures, documents to a more complex calculation, and similar).
Last year we were amazed by the level of dexterity achieved by OpenAI's Dactyl system which was able to learn how to manipulate a cube block to display any commanded side/face.If you missed that article, read about it here. OpenAI then set themselves a harder task of teaching the robotic hand to solve a Rubik's cube. Quite a daunting task made no easier by the fact that it would use one hand which most humans would find it hard to do. OpenAI harnessed the power of neural networks which are trained entirely in simulation. However, one of the main challenges faced was to make the simulations as realistic as possible because physical factors like friction, elasticity etc. are very hard to model.
Find all our Student Opinion questions here. Last week, a robotic hand successfully solved a Rubik's Cube. While that feat might seem like a fun parlor trick, it's a sign that robots are being programmed to learn and not just memorize. Robots are already playing important roles inside retail giants like Amazon and manufacturing companies like Foxconn by completing very specific, repetitive tasks. But many believe that machine learning will ultimately allow robots to master a much wider array of more complex functions.
U.S.-based artificial intelligence research organization OpenAI have rolled out a robot hand that can take and solve a Rubik's Cube. Joshua Gans is a professor of Strategic Management at the Rotman School of Management and the chief economist at the Creative Destruction Lab. Tiff Macklem is dean of Rotman School of Management at the University of Toronto. Last week, the U.S.-based artificial intelligence research organization, OpenAI, rolled out a robot hand that can take and solve a Rubik's Cube. Creating a robot with visual sense and complex touch and dexterity is an impressive achievement in AI.
Plastic Dinosaur's normal living space is a big warehouse with a lot of interesting features for it to clamber over and peer behind. But it's noticed that the bipeds he shares the space with come and go through parts of the barriers that contain him. He's noticed that they can swing part of the barrier open, pass through the opening and then the barrier closes behind them. He's seen space behind the barriers that he hasn't explored. Plastic Dinosaur wanders over to the door, peering at things as he goes to see if anything more interesting shows up.
Yesterday, artificial intelligence(AI) powerhouse OpenAI astonished the world by unveiling a prototype of a robotic arm that could solve a Rubik's cube with one hand. The prototype didn't only represent a milestone for the robotics ecosystem in solving high complexity tasks that actively require sensorial information but it also resulted on a major achievement for the AI community. The reason is that the OpenAI robot was completely trained using simulations based on the reinforcement learning models that the OpenAI Five system used to beat human players in Dota2. The research was discussed in a paper that accompanied the news. The importance of OpenAI's achievement was not about designing a robot that could solve a Rubik's cube.
Meta-Learning describes the abstraction to designing higher level components associated with training Deep Neural Networks. The term "Meta-Learning" is thrown around in Deep Learning literature frequently referencing "AutoML", "Few-Shot Learning", or "Neural Architecture Search" when in reference to the automated design of neural network architectures. Emerging from comically titled papers such as "Learning to learn by gradient descent by gradient descent", the success of OpenAI's rubik's cube robotic hand demonstrates the maturity of the idea. Meta-Learning is the most promising paradigm to advance the state-of-the-art of Deep Learning and Artificial Intelligence. OpenAI set the AI world on fire by demonstrating ground-breaking capabilities of a robotic hand trained with Reinforcement Learning.