Artificial Intelligence and Deep Learning
You have undoubtedly heard the buzzwords: Artificial Intelligence and Deep Learning. These technologies are absolutely essential when processing vast quantities of data. According to Nvidia, AI and Deep learning "pours vast quantities of data through neural networks, training them to perform tasks too complicated for any human coder to describe."
To harness the full potential and power of AI & Deep Learning, GPUs are necessary to process vast quantities of data (check out a recent article in the OrboNation Blog).
The potential usages of these technologies are limitless and there is virtually (pun intended!) no industry in the world which does not utilize these technologies to help achieve their goals.
OrboZone AI & Deep Learning Experience
Experience two versions of the AI & Deep Learning video, each with its own genre soundtrack. What gets you the most "hyped" about the AI and Deep Learning innovations?
AI & Deep Learning Experience - Version 1
Soundtrack Genre: Dubstep
AI & Deep Learning Experience - Version 2
Soundtrack Genre: Instrumental
AI and Deep Learning -- Powered by GPU
There in a huge difference between the capabilities of CPU and GPU - particularly when processing inputs for training in neural networks. In an article on towardsdatascience.com, author Jason Dzouza explains that "if your neural network has around 10, 100 or even 100,000 parameters. A computer would still be able to handle this in a matter of minutes, or even hours at the most." However, typical neural networks are not that simple:
“A neural network that takes search input and predicts from 100 million outputs, or products, will typically end up with about 2,000 parameters per product. So you multiply those, and the final layer of the neural network is now 200 billion parameters. And I have not done anything sophisticated. I’m talking about a very, very dead simple neural network model.”
— Ph.D. student at Rice University
If you are looking for more information, we recommend checking out "the ai podcast" from NVIDIA (see below) as they cover myriad topics around AI & Deep Learning and GPUs.
AI & Deep Learning is Everywhere
The fact that you most likely interact with AI & Deep Learning on a daily basis without realizing it may -- or not -- come as a shock to you. Let's take a look at some examples of AI with which you interact on a daily basis.
Mobile Phone
Autonomous Vehicles
Navigation
Ever use the assistant on your Apple or Android phone? You guessed it! These assistants incorporate artificial intelligence and natural language processing (NLP) to analyze what you dictate and provide relevant results.
Autonomous vehicles are not the wave of the future...they are here today! Take for instance Telsa. A full build of Autopilot neural networks involves 48 networks that take 70,000 GPU hours to train with output 1,000 distinct tensors (predictions) at each timestep.
Ever use a navigation app on your phone like Google Maps, Apple Maps, or Waze? Ever wonder why it takes you down random streets or off the beaten path? These apps are using AI to analyze hundred of data points to find the fastest way to your destination, helping you avoid traffic jams!
Photo Gallery: AI & Deep Learning
Artificial Intelligence and Deep Learning are represented graphically in many fascinating ways -- check some of them out in our visual gallery! (Hover over the image for description)
AI & Deep Learning around the world
Electronifying documents is driving automation.
Deep Learning Neural Networks consists on many different parts
Neural networks layers include input, hidden, and output layers
Visual representation of AI and Deep Learning processing large quantities of data
Various buzzwords describing AI & Deep Learning.
Visual concept of Artificial Intelligence
Artificial Intelligence is the umbrella term which robotics processing automation, machine learning, deep learning, and neural networks fall under
