We’ve now reviewed the top 5 data trends projected by Datanami for 2019 – we’re already halfway through the fun! Let’s see how stack up for trend #6.
“Deep learning” is one of the biggest tech buzzwords of the past several years, and for good reason.
Neural networks, a machine learning model that is a rough approximation of the human brain, form the underpinning of deep learning. Computer scientists have found that neural networks can be used for a wide range of applications to great effect: everything from image recognition and natural language processing to artificial speech synthesis.
As just a quick primer, deep learning is responsible for all of the technological developments below and more:
- The Google Translate machine translation service.
- The computer vision software powering self-driving cars.
- The FaceApp mobile app, which went viral this year for its ability to drastically change a person’s appearance in a photograph.
- Fake audio and video recordings known as “deepfakes,” which are convincing yet false imitations of reality.
Within the enterprise, deep learning has many applications: developing better recommender systems (useful for customer-facing businesses like Netflix and Amazon); restoring damaged and noisy images; discovering promising new drug candidates; building chatbots that can hold realistic conversations with human users; and much more.
Despite its great promise, deep learning is still a highly active area of research, and still in its infancy when it comes to business applications. According to a 2018 survey of AI “early adopters,” just half said their company was already using deep learning, so there’s still plenty of time to get in at the ground level.
Want to know what’s coming down the pipe for deep learning in 2020 and beyond as it pertains to your organization? Check out our blog post “The Future of Deep Learning for Your Business.”
To get more detail on this and the other 9 data trends of 2019, Download “Analysis of the Top 10 Big Data Trends of 2019.”
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This blog post discusses the release of Oracle Analytics Cloud, a service that includes Essbase Cloud, Business Intelligence Cloud and Data Visualization Cloud.