Artificial Intelligence Software
Artificial Intelligence Software Machine Learning Tools and Artificial Intelligence Tools have been the fastest growing areas of the market. AI was developed in the 1980s. However, the exponential growth in AI and its applications has only occurred in the recent past. Artificial Intelligence, which is the artificial intelligence created by machines, is more likely than human intelligence to attempt to replicate the human intelligence process.
Artificial Intelligence Applications and Areas
You will see many areas where AI is being extensively used in the following image.
Machine Learning
Machine Learning requires that a goal be defined, and that the machine learn the steps necessary to reach it. Let’s use an example to show you how a machine can learn from a set of pictures that shows a cat and one of a lion. The model must respond positively to any picture of a cat that appears on its screen. To help it learn, it will be exposed to many pictures of cats in advance so it can become familiar enough to recognize the cat when it appears on the screen.
Robotics in Artificial Intelligence tools
This area of machine intelligence focuses on building and manufacturing robots. We see that robots are available in every form today. One example of a robot is the ATM that we use to withdraw cash. There are also many intelligent working robots. Amazon warehouse houses more than 100 000 robots who do the shipping within the warehouse.
Natural Language Processing
Natural language processing refers to the manipulation of speech, voices and text. NLP allows us to draw many important conclusions. For example, Automating the task of categorizing feedback can be automated. If users are unhappy with the service or happy, we can implement NLP to come up with a conclusion. We can analyze their comments via NLP.
Artificial Intelligence tools for vision
This field allows the machine to see. This can be used to give a robot the ability to see, or a car with digital signal processing to see through a camera.
Autonomous Driving and Vehicles
Artificial Intelligence deals with making vehicles and driving autonomous. Uber has made autonomous vehicles, which are operated in very few places, without the assistance of a driver.
Top Artificial Intelligence Tool/Frameworks
AI is the talk because AI is changing the world every day. Google, Facebook, Amazon and others are creating frameworks and tools that they can then share in open-source AI software. We will be looking at some of the most important frameworks and tools in AI.
Berkeley Vision and Learning Center created Caffe. This deep learning framework is extremely popular and widely used by AI engineers and enterprise customers due to its speed. Caffe can process over 50 million images in a single day. Caffe’s main applications are in research, speech, multimedia, visions, and other areas.
Tensor Flow
Tensor flow, an open-source framework created by Google for numerical computation intelligence, is called Tensor flow. It computes using data flow graphs. If we visit the website, https://www.tensorflow.org/, we can see lots of tutorials and learning that anyone can get and start with using tensor flow.
Theano in Artificial Intelligence Tools
Theano is a new open-source library which was created at the University of Montreal in Quebec, Canada, by the LISA Group. Theano is very similar in many ways to tensorflow, but there are some differences. Theano is more flexible than Tensorflow in terms of data visualization options and GPU support.
Keras and Artificial Intelligence Tools
Keras is an open source neural network library written in Python language. It can be used with other libraries, such as TensorFlow, Theano and others. Francois Chollet from Google was the one who developed it.
Keras doesn’t handle low-level computations, but instead uses other libraries like Tensorflow or Theano. Keras is responsible for high-level API. It compiles models with loss or optimizer functions. We can visit https://keras.io/ to see many tutorials, and learn how anyone can start using Keras.
Scikit-Learn Artificial Intelligence Tools
Scikit learn, an open-source machine learning program written in python, is once again available. It was developed in python by David Cournapeau, as part of the Google Summer of Code 2007 project. Scikit learn allows you to use a variety of unsupervised and supervised machine-learning algorithms within your Python program.
This library is based upon Scientific Python. We must install it before we can use sci-kit-learn. Some features offered by sci-kit Learn are:
NumPy It supports large, multi-dimensional arrays and many mathematical functions.
SciPy The library contains modules that can be used for scientific and technical computing. These include modules for optimization, linear algebra, signal and picture processing, integration, and so on.
Matplotlib It’s primarily used as a visualization/plotting library. You can use it to create many graphs that allow you to visualize machine learning models.
IPython This console is used for interactive computing and can be used in conjunction with multiple programming languages. Pandas The library is used to perform data manipulation and analysis.
Pytorch, Artificial Intelligence Tools
PyTorch (a scientific package that uses Python) is based upon Python. It makes use of the power of GPUs (Graphics processing unit). It has an intuitive API, and offers dynamic graphs that can change during run time.
Additional Resource:
https://www.brookings.edu/research/what-is-artificial-intelligence/
https://www.sciencedirect.com/topics/computer-science/artificial-intelligence
https://plato.stanford.edu/entries/artificial-intelligence/
