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While there aren’t many sure bets in life, one thing you can reliably count on is the business community latching on to a fresh set of buzzwords each year that suddenly become so popular they are here, there, and everywhere. When that happens, you will quickly see rampant misuse of the term, whether intentional or not. One such term that is gaining traction is deep learning. While it may sound somewhat intuitive at first glance, deep learning actually describes something extremely complex.
I’m not a data scientist and don’t want to offend anyone by oversimplifying this, but as most folks reading this don’t work with neural networks and language models on a daily basis, I’m going to boil it down a bit. Deep learning is a subset of machine learning, and is a way to process data, images, and text faster and with less human interaction than traditional techniques because it has the ability to learn on its own.
And while this term has become incredibly popular lately, deep learning has actually been part of many people’s lives for quite some time. For instance, your bank likely uses predictive analytics to identify fraud and assess risks in your accounts, while your personal electronics may feature virtual assistants such as Siri or Alexa that can take actions on your behalf. Self-driving cars, SpaceX rockets, and Amazon warehouse robots are some other examples (I recommend watching the documentary AlphaGo) of deep learning being leveraged to do things humans were never able to do before.
Another thing that was previously impossible is ubiquitous document automation, regardless of formatting, layout or language. Document automation has been around in various forms for quite some time, but legacy tools can only understand 20% of the most simplistic document types. Additionally, these tools often require templates, hard coding, and laborious maintenance to work with that limited subset of documents. For example, every year tax documents change, businesses update the layouts on their forms, new companies join the market, and new document classes are added.
At Applica, we knew there had to be a better way to solve this problem, and since we couldn’t find it, we decided to build it ourselves. Applica’s data science team had the realization back in 2018 that deep learning is the key to ubiquitous document automation–allowing for extraction, comprehension, and decision making on all types of business documents. After years of research and development, we released our product as the first, and only, deep learning-based automation solution on the market. While other companies may claim to use deep learning, at the root of their tools are outdated methodologies that simply can’t do what Applica can.
With a science-first approach, Applica’s R&D team is unique in that we don’t just leverage the latest projects from the open source community, we actually build our own deep learning algorithms and language models (which are trained on more than two million business documents, a corpus that is nearly impossible to match in this space). In 2021 we released TILT, the only commercially available generative language model, which is simultaneously blowing minds and winning prestigious industry awards. And with numerous patents and six innovation grants from the European Union, Applica’s team is continually called upon by industry analysts to discuss our product functionality and the architecture of our models. Even our lab has $1.5M of graphics cards used to train models (sorry crypto miners). We also spoke at Nvidia’s GTC conference on Deep Learning.
So what does all this mean for your organization? First off, if you are not using an automation solution that is deep learning-based, your current investments will unfortunately have limited utility. And while they may work fine for now on basic use cases, the next few years will not be kind to template- and rule-based solutions, as they are unable to scale to meet the growing demands of a rapidly changing business world. Second, if you are still on the fence about the unique value of a deep learning based approach to automation, that’s ok. It can be difficult to understand why such a radically different solution is the way to go when all other automation products have been pushing a deterministic approach for many years.
If you are interested in learning how true deep learning can compound the value of your tech investments, connect with an Applica expert today.
Interested in digging deeper into our tech? Check out our library of published papers.
