Organizations are using deep learning (DL), a growing branch of artificial intelligence (AI), to streamline their operations and increase productivity.
See below how several organizations in various industries are applying deep learning to deliver business outcomes:
5 Deep Learning Case Studies
Zendesk is a software as a service (SaaS) provider that helps companies create strong customer relationships that facilitate productivity and growth.
As their user base grew, Zendesk needed to find a way to keep up with customers wanting to find answers to their questions as fast as possible. However, routing them to talk to a support agent isn’t scalable and would still mandate wait time. Zendesk addressed this challenge by creating Answer Bot using deep learning.
Using neural networks, Zendesk developed a virtual customer assistant that’s able to answer customer questions using content straight from the Zendesk Guide knowledge base.
“For Answer Bot, we liked the idea that a deep learning model could help the application continually fine-tune itself to give customers the best possible answers,” said Soon-Ee Cheah, a data scientist at Zendesk. “We can scale our deep learning models very efficiently using GPU-processing power on AWS, and that will benefit us while we grow our applications to accommodate more customers.”
Deep learning solutions: Amazon Simple Storage Service (S3), Amazon EC2, Amazon Aurora, and Amazon SageMaker.
Instantaneous answers to customer questions
Scalable software infrastructure to meet customer demand
Quick to train and deploy.
2. 90 Seconds
90 Seconds is a video creation platform that regularly manages 12,000 video professionals in over 160 countries. While they started as a low-profile business in New Zealand, their growth forced their hand into using more tech in their operation to keep up with the rise in demand.
By working alongside the Google Cloud Platform, they’re able to train deep learning algorithms to analyze videos and provide relevant analysis for brands. The algorithms are also able to identify and extract specific content from videos, like footage of sunsets or people, and analyze how they contribute to the performance of the video in terms of viewer count and social media engagement.
“Google Cloud Platform has played a key role in helping our business grow to this point,” said Dat Le, director of data science and engineering at 90 Seconds. “We see technologies like Cloud Vision API, Cloud Video Intelligence, and Cloud AutoML helping us become a more intelligent, valuable provider to brands in future.”
Industry: Media production
Deep learning solutions: Cloud Vision API, Cloud Video Intelligence, Kubernetes Engine, Compute Engine, Cloud SQL, BigQuery, and Cloud AutoML.
Scalable solution that supports the growing demand for cloud video production
Accelerates software development
Facilitates decision-making by capturing and analyzing data from multiple services
Supports an online marketplace of 12,000 videos creative professionals and 3,000 brands […]
Read more: www.datamation.com