What can deep learning do for your business?

Deep learning is the application of deep neural networks to machine learning. It has made possible the massive recent advances in speech recognition, computer vision, language translation, and self-driving car technologies. But how can deep learning help more traditional businesses and institutions?

One way to think of deep learning is as an automatic form of machine learning. In machine learning, mathematical and statistical techniques are applied to data to discern patterns of information that could be used to gain insights or make predictions. Machine learning requires skilled data scientists to shift through many data dimensions to find useful features that exhibit correlations to useful hypotheses or business intelligence. In supervised deep learning, the neural network will automatically find relevant features in the data, if they are present, that correlates to the hypotheses or business intelligence that are being tested. This is particularly important if the quantity of data is massive and difficult for humans to process. A key benefit of deep learning is its superior performance with larger data sets, as shown in the image below by Andrew Ng, formerly the leader of Google Brain and Baidu AI Research and currently adjunct professor of artificial intelligence at Stanford University.

A few examples of use cases for deep learning in business include finding patterns in responses to online advertising, identifying customer behaviors, identifying causes of clinical treatment results (good or ill) from factors in patient records and free text notes by clinicians, and automatically extracting correct course of actions from past employee behaviors for training or to minimize future mistakes. Where there’s data, there is a potential application of deep learning to make use of that data for better work automation, improving sales performance, or gain predictive intelligence.

Here is how Simplify.ai can help

We have extensive experience with deep learning across several domains, from supervised learning to computer vision to natural language processing.  To demonstrate the potential for applying natural language processing to business, we have developed a conversational interface for taking restaurant order via voice that includes being able to handle non-linear interactions with memory and goals.  Below is a video demonstration of this capability.

Aside from supporting voice interfaces, natural language processing can extract useful information from free text data, such as doctor’s notes or operation journals, that can then be processed by a deep neural network to find useful insights or predictive intelligence from correlation with other data.

Key to Simplify.ai’s cost effective deep learning solution is our Deep Learning No Coding software platform.  Every deep learning solution is a living process that needs to be refined and augmented over time with new training data.  By implementing our deep learning solution with our software platform, the maintenance of the solution can be managed over time by our customers with little or no further consulting requirements, resulting in large economic savings of our solution over time.  Standard maintenance processes, such as retraining models with new data, testing model performance as the business evolve, and even modifying the neural network to handle new processes and data structures, can all be done within our software platform with no coding.  For applicable services, sufficient licensing of our Deep Learning No Coding software platform for the future care and maintenance of deep learning models is included with our consulting agreement.  Working with our Deep Learning No Coding software platform is simple, as shown in the following video.

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