Every summer there is a mass exodus from New York City towards the white beach at Jones Beach State Park. Here, looking out over the Atlantic Ocean, you can sunbathe, catch a concert or play a game of mini-golf. And get away from the bustle of the city. But you have to get there first. And there's something odd about the route you take. The flyovers over the Southern State Parkway that leads to Jones Beach are low.
Then we apply softmax function on the final scores to convert them into probabilities. And the data is classified into a class that has the highest probability value(refer to the following image). But in sudoku, the scenario is different. We have to get 81 numbers for each position in the sudoku game, not just one. And we have a total of 9 classes for each number because a number can fall in a range of 1 to 9. To comply with this design, our network should output (81*9) numbers.
The new-age technologies are changing the overall scenario of the business world and defining the true essence of'Innovation'. These technologies are changing the workspace functionalities and client engagements alongside rolling out a vast array of opportunities for the youngsters of today and tomorrow. From banking to healthcare, these technology advancements are taking the center stage and helping every sector to withstand the changing times. The way of doing business is changing and so is the career space. It is an era where tech-trends are redefining entrepreneurship to its best.
One reason, researchers say: there are billions of potential moves available to a Rubik's Cube player, with the puzzle's six sides and nine sections, but only one goal: each of the cube's six sides displaying a solid color. Finding a solution to a puzzle with that degree of complexity, and among billions of potentialities, involves a degree of abstract thinking that, researchers say, begins to approximate human reasoning and decision-making.
Over the past few years, the term "deep learning" has firmly worked its way into business language when the conversation is about Artificial Intelligence (AI), Big Data and analytics. And with good reason – it is an approach to AI which is showing great promise when it comes to developing the autonomous, self-teaching systems which are revolutionizing many industries. Deep Learning is used by Google in its voice and image recognition algorithms, by Netflix and Amazon to decide what you want to watch or buy next, and by researchers at MIT to predict the future. The ever-growing industry which has established itself to sell these tools is always keen to talk about how revolutionary this all is. But what exactly is it?
In recent years AI models have learned to play games ranging from Go to Poker to StarCraft. One-by-one, the machines have demonstrated their superiority over even the strongest human players. With the challenge seemingly solved for existing games, what about testing AI in an entirely different way -- by having it design new games for humans to play? A team of researchers has proposed a Generative Adversarial Network based model tasked with creating playable and aesthetically appealing game levels for popular action-adventure video game series The Legend of Zelda. In their paper Bootstrapping Conditional GANs for Video Game Level Generation, researchers from New York University, IT University of Copenhagen, OriGen.ai, and modl.ai
AI automation is coming, and it's going to impact knowledge workers -- writers, artists, designers, scientists, managers, and entrepreneurs. However, even when AI automation completely replaces the need for a human -- such as in its conquest of strategy games like Chess and Poker -- the world doesn't end and the human element doesn't disappear. Largely better, in some ways worse, but life in fact goes on. Humans keep doing our thing. And the machines keep getting better, and better, and better.
Microsoft is turning to AI and machine learning to let Xbox gamers filter the language they see in text messages. It is introducing customisable filters that let gamers choose the vocabulary they see in messages from friends and rival players. Initially the filters cover just text but will eventually apply to voice chat as well. In a blog, Microsoft said the filters would be trialled with Xbox testers in October and then rolled out to all users of its console later in the year. Players will be able to decide what level of filtering they want to apply to their interactions with friends or people they take on in games, it said.
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.