Democratization-of-Deep-Learning_Updated Brand.pdf - The...

The Democratization of
Artificial Intelligence and
Deep Learning

Abstract
Deep learning is driving rapid innovations in artificial intelligence and influencing massive disruptions across all
markets. This paper provides an understanding of the promise of deep learning, the challenges with leveraging
this technology, how it is currently solving real-world problems, and more importantly, how deep learning can be
made more accessible for data professionals as a whole.
What is Deep Learning?
Deep learning, which is a specialized and advanced form of machine learning, performs what is considered
“end-to-end learning”. A deep learning algorithm is given massive volumes of data, typically unstructured and
disparate, and a task to perform such as classification. The resulting model is then capable of solving complex
tasks such as recognizing objects within an image and translating speech in real time.
Deep learning models can be trained to perform complicated tasks such as image or speech recognition and
determine meaning from these inputs. A key advantage is that these models scale well with data and their
performance will improve as the size of your data increases.
FEATURE EXTRACTION + CLASSIFICATION OUTPUT
CAR
NOT CAR
INPUT
DEEP LEARNING
INPUT FEATURE EXTRACTION CLASSIFICATION OUTPUT
CAR
NOT CAR
MACHINE LEARNING
2

Deep learning not only performs best with larger volumes of data, but also requires powerful hardware such as
graphical processing units (GPUs) in order to perform. The deep learning market is expected to be worth $1.75
billion by the year 2022
1
. Investment in this area is driven by the fact that 61% of enterprises with an innovation
strategy are applying AI to their data to find previously missed opportunities such as process improvements or
new revenue streams
2
.
Innovative Deep Learning Uses
Deep learning has enabled innovation and transformation across a broad range of industries. From anomaly
detection to video analysis, businesses have been able to leverage artificial intelligence to gain competitive
advantage and even change the way their markets approach the customer experience.
IMAGE CLASSIFICATION
This is the process of an AI application identifying and detecting an object or a feature in a
digital image or video. Image classification has taken off in the retail vertical which is using
deep learning models to quickly scan and analyze in-store imagery to intuitively determine
inventory movement. This has lead to streamlined operations, reduced costs, and new sales
opportunities
3
.
VOICE RECOGNITION
This is the ability of a deep learning model to receive and interpret dictation or to understand
and carry out spoken commands. Models are able to convert captured voice commands to
text and then use natural language processing to understand what is being said and in what
context. This has delivered massive benefits to industries like automotive which uses voice
commands to enable drivers to make phone calls and adjust internal controls – all without