We’re fascinated by the possibilities of Artificial Intelligence and the truly transformative opportunities it offers our customers. We’ve been digging deep into machine learning, computer vision and other AI capabilities for quite some time now, and believe they will grow into a significant part of our business. We’re not alone: IDC predicts 75 percent of developer teams will include cognitive and AI functionality in one or more applications this year.
“A lot of the sales process for AI and ML is centered around education…people are not calling asking for either specifically.”
– Vishwas Lele AIS
To assist companies looking to build an AI-focused practice, Microsoft recently released the AI Practice Development Playbook
with guidance and resources around developing an AI strategy, gaining the required skills, plus how to market and sell these cutting-edge offerings. AIS is proud to be a contributing expert and co-author of the Playbook, along with our fellow Microsoft partners and other leading AI data scientists.
Get your copy of the AI Playbook right here. We’d love to hear what you think of it!
What is MTConnect?
MTConnect is the communication standard of choice for manufacturing. It allows organized retrieval of data from shop floor equipment in a structured XML.
The adjacent diagram depicts the key components of MTConnect. Let us start with the shop floor equipment shown at the bottom of the diagram – a CNC lathe. Above that, we have an optional adapter component that converts machine-specific data into a MTConnect defined format. The adapter component is optional as most manufacturers are building this capability directly into their machines. On the top is the agent component responsible for converting MTConnect data into XML. Additionally the agent also exposes a RESTful service that can be used to retrieve data. Read More…
At a recent holiday dinner, a conversation with a friend eventually progressed to the topics of self-driving cars and facial-recognition software – and the overall roles and capabilities of artificial intelligence (AI). My friend’s assertion was that “AI is ultimately about pattern matching.” In essence, you equip the AI with a library of “patterns” and their corresponding associated actions. Based on the input it receives from the real world, the AI software program will then make an attempt to match the input to a stored pattern and execute the corresponding associated action.
Of course any program, regardless of whether it is designed to steer a car or detect a face in an image, relies on pattern-matching at the lowest level. That said, as we will see shortly, a deep learning-based approach is a fundamentally different way to solve the problem. And it’s an approach that is poised to reinvent computing. Read More…
Business leaders are constantly looking at how they can use the underwriting process to improve profits.
What if insurance underwriters or the underwriting processes could look into the past at a more detailed level and predict exactly how a risk would perform in the future? What If underwriters were provided with a solution that would provide meaningful insight into customers’ risk characteristics? Data analytics, data mining and predictive modeling can provide this ability to enhance business processes and improve profits for Insurance companies.
Our experienced technical team recently pulled together a white paper on this topic. These guys have worked with one of the largest personal property insurers in the country for several years, and have loads of experience in implementing cost-saving solutions for this industry. In this paper, they discuss auto and property/casualty insurance underwriting, how big data analytics can influence an increase in sales and revenues for companies and introduce a high level Microsoft based solution implementation that can solve this business problem.
Download your copy today and share with you team!
AIS developed a prototype web application that leverages open standards for real-time data sharing and geospatial processing. It’s highly suggested you read our first two blog posts on this application, part one and part two.
In this post, we are going to discuss three areas of improvement for the application. We wanted to improve collaboration, improve management of events by adding a search capability, and improve the edit capabilities. Read More…
AIS developed a prototype that highlights the features and capabilities of open standards for geospatial processing and real-time data sharing through web applications. If you haven’t already, please click here to read part one.
After getting the VIIRS data into our application using GeoServer, our next objective was to enhance the prototype to demonstrate some of the exciting things AIS is able to do through the use of various web technologies. Our goal was to provide a highly collaborative environment where clients on a variety of devices could all interact in real time with map data.
Figure 1: 3D Map Displaying WMS Layers
Although AIS is proud to center their technology on Microsoft’s frameworks and technology stack, AIS is also adept at working with a broad range of other technologies to give clients solutions that are custom-tailored to their needs.
One such project is the recently released Web Report Editing Tool, or WebRET. WebRET was custom-built in the Ohio Development Center for the specific needs of our government client. In this instance, the client needed a back end that was compatible with the Java Runtime Environment, so we used JRuby on Rails to provide a modern yet JRE-compatible back end.
To learn more about the technologies used in WebRET, take a look at the whitepaper below.
Web Report Editing Tool Case Study (PDF)
Click here to read more about AIS’ custom application development service offerings and how they’ve helped our clients.
Because of our broad knowledge in building web applications, AIS decided to develop a prototype that highlights the features and capabilities of open standards for geospatial processing and data sharing through web applications.
We chose the Visible Infrared Imaging Radiometer Suite (VIIRS) as our data source for the demonstration. VIIRS collects visible and infrared imagery and radiometric data for civil and military Earth monitoring. (The Day/Night Band (DNB) datasets available from NOAA’s Comprehensive Large Array-Data Stewardship System are not quite in the format we need for our application, since they are sensor data records stored within an HDF5 container.)