In this video, I show you a real-time simulation of space-time distortions that produce gravity because of its mass. The simulator is made in Unreal Engine 4 and C++.
In 1905, Albert Einstein determined that the laws of physics are the same for all non-accelerating observers and that the speed of light in a vacuum was independent of the motion of all observers. This was the theory of special relativity. It introduced a new framework for all of physics and proposed new concepts of space and time.
Einstein then spent 10 years trying to include acceleration in the theory and published his theory of general relativity in 1915. In it, he determined that massive objects cause a distortion in space-time, which is felt as gravity.
Our neural network implementation in Unreal Engine 4 can have different purposes, educational or as a tool for data scientist developers.
This tool is really easy to be used: you can change the number of layers and the neurons per layer. In the example showed I have used the MNIST dataset for number recognition, furthermore, I can use different datasets.
If you want to use this tool for educational purposes, you can debug and see how the neural networks work. It is really practical and I recommend whoever wants to start AI. This application is progress, although you would be able to see the advances.
Computer vision has recently experienced a boom in the AI field. It has many applications and it could be very useful to provide a machine the sense. It is used in words and number recognition, to classify objects in clusters and it also gives us the possibility to make autonomous cars. We have seen posts about autonomous cars and computer vision is the next step to achieve this.
We have used a simple backpropagation neural network to recognize the numbers that implement mini-batch learning, momentum, Xavier initialization, and normalization. It is really an advanced ANN that classifies numbers in 10 cluster that represents each one a number between 0 and 9.
Evolutionary algorithm learning process of cars in UE4 C++
AI is a new field that appeared a few decades ago and has seen an unprecedented growth. The AI approach has been used in numerous fields, such as finance, medicine, music, customer service, and transportation. Some of the big challenges we have to cope with are the computing power and lack of documentation. Big companies such as Google and Apple do not share advances in this field, the secretism characterizes this scientific field and thus the information we can get is very restrictive.
In this work, we introduce a model of an autonomous car and then examine different algorithms capable of driving the car in a simulated. We also discuss the difficulties we need to deal with such as local minimums, losing diversity, fitness functions, localization, performance, and future applications.
Gravity simulator that imitates Solar System planets movement in 3d
This project enables us to simulate gravitational forces and apply them to objects with a certain mass. It calculates the forces of n-body objects and their interactions, it can be used to see simulate the Solar System conditions. The gravity simulator could have educational porpuses.