Deep Learning Developers Eye Fintech Apps
With artificial intelligence all the rage these days, market trackers are attempting to gauge just where the technology is headed and which industry sectors will lead development for specific big data and other enterprise use cases.
The latest attempt comes from Evans Data Corp. in the form of an AI and big data survey released on Wednesday (Jan. 11). The survey of 440 AI developers found that more than one-third of respondents are focusing on deep learning techniques, with most targeting the financial and insurance sectors.
Other sectors where deep learning implementations are expected to have an impact include the Internet of Things (14.9 percent) and “non-computer” manufacturing (12.5 percent), reported the market researcher based in Santa Cruz, Calif.
Nearly one-third of AI developers focused on deep learning implementations are relying on numerical inputs as the most common data type, Evans Data added. Still images and video (27.2 percent) along with text (26.9 percent) also were widely used, followed by audio files and sensor data, the survey found.
“Much of that interest [in deep learning application development] is centered on new applications for video and audio analytics—deducing meaningful data from multimedia inputs,” the report states.
AI developers also were asked whether they use tools such as text classification algorithms as a way of applying machine learning to the study of text data for applications like virtual assistants. More than three-quarters, 79.6 percent, said they did. “That’s an indicator that teaching is an element of most developers’ use cases,” the survey noted.
As AI and deep learning development gains momentum, the survey also found that a growing percentage of developers expect to deploy resulting big data and analytics platforms in the cloud. While not specifying a timeframe for deployment, more than 40 percent of programmers said they expect to deploy as many as half of those solutions in the cloud while more than one-third said most applications would eventually be cloud-based.
Still, the survey found that “the public cloud is no longer a migration destination for the entirety of most organizations’ assets. While some organizations will take advantage of public cloud’s convenience, most organizations already possess the on-premises infrastructure they need to support at least some part of their big data platforms,” the market researcher said.
Signs that the cloud migration has begun appeared last year when deep-learning startups such as application builder Algorithmia announced cloud-based platforms for creating deep learning environments used to train models.
While deep learning is expected to transform a range of industries, Evans Data CEO Janel Garvin noted that the financial technology sector “is particularly ripe for this” development. Along with helping financial advisers tailor recommendations for specific requirements, Garvin argued, “Getting AI into the financial services sector can mean a revolutionary breakthrough for banking institutions of all types.”