In perhaps the ultimate cool endorsement, last week at WWDC Apple announced optical character recognition will be embedded in iOS 15. Named LiveText OCR, Apple describes it as “secure on-device intelligence to help you discover more in your photos, quickly find what you’re looking for, and relive special moments.”
Move over, machine learning, here come the deep learning algorithms. We predict that deep learning models will disrupt the status quo of document classification over the next 12 – 24 months, as customers discover that they can train an AI classifier with as few as five samples and deploy it in a matter of hours. Without the need for Amazon, Google, Microsoft, or IBM, and without the traditional massive compute costs and data sets associated with Deep Learning to date. Time will tell if we are right or not, but change is on the horizon.
We’ve been talking about multimedia data capture in ECM and BPM for at least 20 years. Recent advancements in computing power and deep learning, leveraged by innovative companies like AnyClip and Veritone, are finally moving into the information management mainstream. We expect to see this take off over the next 2-3 years.
Today there was important news in the Cognitive Capture market. ABBYY, a privately-held company, announced an investment from Marlin Equity Partners, which will make Marlin the largest shareholder. Terms of the investment were not revealed. Marlin is a global private equity firm that acquires businesses across diverse industries and has built a significant portfolio of software companies.
We attended OpenText World Europe this April to learn where the ship is headed. OpenText made it very clear that it is staking its content management future on the cloud. The company announced Cloud Editions 21.2, an all-encompassing, all-in effort to achieve that long turn away from on-premise legacy software. Mark Barranchea, CEO, pledged an R&D investment of over $1 billion in R&D in their diverse stable of products. For a company with $3 billion in sales last year, that is a very impressive number.
Under the hood, Vantage utilizes Convolutional Neural Networks (CNN) that are pre-trained on hundreds of thousands of documents to extract visual features from a document. A Recurrent Neural Network (RNN) is used to extract semantic features of the text. While undoubtedly welcome to the large community of ABBYY users and the market at large, neither method is ground-breaking or particularly innovative.
