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) …
And if this was not enough, the new Rubik's Official App, available initially on IOS, also includes games with a virtual Cube, so you can learn and have fun simply by swiping a finger, even if you don't own the twisty Cube. You can select your choice of game from Rubik's Mini (2 2) or the original Rubik's Cube (3 3), to the more challenging Rubik's Master (4 4) or the Rubik's Professor (5 5). The app will also allow you to keep track of your solving times and allow you to share the information digitally. Christoph Bettin, the CEO for Rubik's Brand, said, "The Cube has fascinated fans for four decades and I'm the first to admit that the puzzle can be challenging. Research supports the view that solving a Cube links brilliantly with the teaching of science, technology, engineering and maths (STEM), and this high-tech app captures this, while creating fun and excitement."
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!
Every week we bring to you best AI research papers, articles and videos that we have found interesting, cool or simply weird 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!
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!
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).
This article is a part of Artificial Neural Networks Serial, which you can check out here. In the previous blog posts, we covered some very interesting topics regarding Artificial Neural Networks (ANN). The basic structure of Artificial Neural Networks was presented, as well as some of the most commonly used activation functions. Nevertheless, we still haven't mentioned the most important aspect of the Artificial Neural Networks – learning. The biggest power of these systems is that they can be familiarized with some kind of problem in the process of training and are later able to solve problems of the same class – just like humans do!
Now, if there is something that data scientists like to do, is merge concepts and create new beautiful and unexpected models. That is why in this article, we will find out what happens when we give the learning agent ability to "see", i.e. what happens when we involve convolutional neural networks into Deep Q-Learning framework.
In the previous article, we talked about the way that powerful type of Recurrent Neural Networks – Long Short-Term Memory (LSTM) Networks function. They are not keeping just propagating output information to the next time step, but they are also storing and propagating the state of the so-called LSTM cell. This cell is holding four neural networks inside – gates, which are used to decide which information will be stored in cell state and pushed to output. So, the output of the network at one time step is not depending only on the previous time step but depends on n previous time steps. Ok, that is enough to get us up to speed with theory, and prepare us for the practical part – implementation of this kind of networks.
Artificial intelligence might arguably be the newest frontier of human experience, but there's no denying that man has been fascinated with the concept for millennia. From the mythical stories of Hephaestus creating mechanical servants and brazen-footed bulls that puffed fire from their mouths, to the talking heads of the 13th century, to IBM Watson and modern forms of AI, the subject has been bubbling on the surface of human consciousness. The time is now here for AI to come of age; and, in many ways, it already has. But now there's a new problem, and it's not one of how AI can be implemented, as has been the major challenge in the past. AI has now sprouted into a plethora of forms, each rivaling the other in an attempt to showcase its superior capabilities.
Before any build log, here's a video: That was a Rubik's cube being solved in 0.38 seconds. The time is from the moment the keypress is registered on the computer, to when the last face is flipped. It includes image capture and computation time, as well as actually moving the cube. The motion time is 335 ms, and the remaining time image acquisition and computation. For reference, the current world record is/was 0.637 seconds.