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Why Is AI booming Now

Why Is AI booming Now

Why Is AI booming Now

Why Is AI booming Now?

In this AI (Artificial Intelligence) testing tutorial, let’s learn why AI is booming.
A neural network has been out since the nineties with the seminal paper of Yann LeCun. However, AI began to become famous around the year 2012.

Explained by three critical factors for its popularity are as follows:
1. Hardware
2. Data
3. Algorithm

Machine learning is an experimental field that must have data to check new ideas or approaches thoroughly. With the internet boom, data has become more easily accessible. Besides, huge companies like NVIDIA and AMD have developed high-performance graphics chips for the gaming market.

Hardware

In the last twenty years, the power of the CPU’s powered, allowing the user to be small in the deep-learning model on any laptop. However, it would be best if you had a more powerful machine to process a deep-learning model for computer vision or deep learning. Thanks to the investment of NVIDIA and AMD, a brand new generation of GPU (graphical processing unit) are available. These chips allow parallel computations. It implies that the machine can separate the analyses over several GPUs to speed up the calculations further.

For example, with an NVIDIA TITAN X, it takes two days to train a model called ImageNet against weeks for a traditional CPU. Besides, big companies use clusters of GPU to further train deep learning models with the NVIDIA Tesla K80 because it helps reduce the data center cost and provides better performance.

NVIDIA TITAN X vs NVIDIA Tesla K80 for Artificial Intelligence (AI), Data and Algorithm

Deep learning is the model’s structure, and the data is fluid to make it alive. Data powers artificial intelligence. Without data, there is nothing can be done. Furthermore, the latest Technologies have pushed the boundaries of data storage. Nowadays, it is easier to store a large amount of data in a data center than in earlier times.


Moreover, the Internet revolution makes data collection and distribution available to feed machine learning algorithms. If you’re familiar with Flickr, Instagram, or any other sort of app with images, you’ll be able to guess their AI potential. There are numerous pictures with tags available on these websites. Those pictures are often used to train a neural network model to recognize an object on the image without needing to collect and label the data manually.

Data

Artificial intelligence (AI) combined with data is the new gold. Data is nothing but a unique competitive advantage that no firm should neglect. AI provides the best answers from your data. When all the firms can have similar technologies, the one with data will have a competitive advantage. To give an idea, the globe creates about 2.2 exabytes, or 2.2 billion gigabytes, daily. A company requires exceptionally diverse data sources to find the patterns and thus learn that too in a substantial volume.

Algorithm

Hardware is more potent than ever, and data is quite easily accessible, but the development of more accurate algorithms makes the neural network more reliable. Additionally, Primary neural networks are nothing but a simple multiplication matrix without in-depth statistical properties. Since 2010, remarkable discoveries have been made to improve the neural network.

AI or Artificial intelligence uses a progressive learning algorithm to let the data do the programming entirely. It implies the computer can teach itself how to perform different tasks, like finding anomalies, to become a chatbot.

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