Deep learning seeing widespread adoption in APAC region
Deep learning is expected to be a major factor in the momentum for the adoption and growth of wider artificial intelligence (AI) in the APAC region, according to new research from GlobalData.
As a sub-category of machine learning, deep learning is fast becoming part of mainstream AI deployments – new software to join the today's extensive roster of digital assistants is currently being developed and will likely be introduced in the next few years, says GlobalData.
The research and data company estimates the APAC region to account for approximately 30% of the global AI platforms’ revenue (around USD$97.5 billion) by 2024.
However, the share is expected to significantly go up, given the incumbent technology companies and the increasing number of start-ups that specialise in this field.
Digital assistants, such as Siri, Alexa and Cortana, are some of the most common examples of leverage deep learning to some extent for natural language processing (NLP) as well as speech recognition.
Some of the other key usage areas of deep learning include multi-lingual chatbots, voice and image recognition, data processing, surveillance, fraud detection and diagnostics.
“The APAC market is proactively deploying deep learning-based AI solutions to bring increased offline automation, safety and security to businesses and their assets,” says GlobalData Lead ICT analyst Sunil Kumar Verma.
“In addition, AI hardware optimisation with increased computing speed on small devices will result in the cost reduction and drive deep learning adoption across the region.”
Especially in the APAC region, deep learning is increasingly driven by product launches and technical enhancements by regional technology vendors.
For instance, China-based SenseTime leverages its deep learning platform to power image recognition, intelligent video analytic and medical image recognition to its customers, through its facial recognition technology called DeepID.
An India-based start-up called DeepSight AI Labs similarly uses deep learning to develop SuperSecure - Platform, a smart retrofit video surveillance solution that works on any CCTV to provide a contextualized AI solution to detect objects and behaviours.
Australia-based Daisee too offers an algorithm called Lisa, which leverages a speech-to-text engine to identify key conversational elements, determine its meaning and derive its context.
Similarly, Cognitive Software Group is using deep learning for the tagging of unstructured data to enhance natural language understanding.
“Although still in its infancy, deep learning is proving to be a stepping stone for technology landscape evolution in APAC,” says Verma.
“However, with the lack of skilled professionals and the fact that only a handful of technology companies are focussing on investing, hiring and training their workforce specifically for Deep Learning, there would be some initial roadblocks before witnessing success in adoption rates.”