Webcam bots

A real-time system to identify objects and speaks what it sees was the plan; it could be really useful tool for the visually impaired, as it could make navigation easier. It doesn’t take any effort for humans to tell apart a cat and a dog or recognize a human’s face.But these are actually hard problems to solve with a computer.So instead, he had the bot play itself over and over again, learning which techniques worked the best, called reinforcement learning.“I just sort of forgot about it for a week,” said Firoiu, who coauthored the paper with William F. “A week later I looked at it and I was just like, ‘Oh my gosh.’ I tried playing it and I couldn’t beat it.” Watch Phillip take on the pros below: The bot almost learns to make its own flow chart.

Fake profiles and fake chats are created by miscreants to adversely affect your business and to divert traffic on to their platform.In the last few years, Deep Neural Networks lead to breakthrough results on pattern recognition problems, and one of the essential components to understanding these breakthrough results has been the CNN (Convolutional Neural Networks).Training a Deep Neural Network capable of classifying a large number of different classes in just two days was totally impractical, so we used the pre-trained Inception v3: Inception-v3 is trained for the Image Net Large Visual Recognition Challenge using the data from 2012.Students from MIT and New York University developed an AI bot that ended up teaching itself in two weeks to beat professional gamers during the Genesis 4 Super Smash Bros tournament last month.The AI, nicknamed Phillip, was originally trained with CUDA, Tesla K20/TITAN X GPUs and the Tensor Flow deep learning framework – but the creator Vlad Firoiu couldn’t train it to be as strong as the in-game bot.