HOW WE WORK
Crash Course In Deep Learning
We first give you a technical but a very intuitive explanation of why deep learning is all the rage. What goes into building a deep learning system. What are the limitations and what are the opportunities. Our goal is to first educate you in deep learning so you can now speak more intelligently about this fascinating innovation in computer science.
Demo and overview of our Platform
We will demo the consumer applications we have built and loved by millions of users worldwide. We also then list the core capabilities of our engine so that you can start mapping where AI will apply in your organization.
Your current projects and priorities
This is where you tell us what is on your road map in the next month or two to deliver. We also seek to get access and understanding to your datasets and use cases. We will then take that and analyze those to come back with a proposal of what can be done in a realistic time line.
Photo Generators (e.g. Style Transfers)
Text Translators (e.g. labeling a sentence as informative or marketing or Spam)
Photo or Video Classification (e.g. labeling the video or image as inside, distracted, security breach, etc)
Object identification (e.g. identifying all objects in an image so now you can search and organize)
Customer Behavior Analysis (e.g. churn prediction, customer segmentation, next best action, etc)
Recommendations (looking at past behavior and recommending what to watch or read)
Chat-bots (to help reduce the cost of customer service)
Sentence mining (to process large quantities of text to find sentences with a certain sentiment or information type
Note takers (to process large amounts of text and reduce it to notes in your style)
Flaw detection (e.g. automotive, aviation)
Medical Diagnosis (e.g. Melanoma Screening and Detection, Brain Cancer Detection)