When Intel® AI Builders partner Mphasis set out to build Mphasis DeepInsights™, a Cognitive Intelligence platform for enterprise customers, they chose Intel® to help them reach their goals.
We interviewed Dr. Jai Ganesh, Senior Vice President & Head of Mphasis NEXTlabs, to get a more in-depth understanding of how Mphasis chose to utilize both Intel® technology and their participation in the Intel® AI Builders program.
Intel: What Intel® AI tech are you using & what have you done with it?
Dr. Ganesh: We are using deep learning models such as Generative Adversarial Networks (GANs) to automatically generate images from text as well as web pages from images. The web pages are generated using a combination of Convolutional Neural Networks (CNN) and Long Short-Term Memory Networks (LSTM). The graphical user interface creation process in software development involves converting the wireframes and screenshots created by designers into computer code. This applies for user interface creation for custom software, websites, and mobile applications.
Currently, every step of this development process is manual, costly, and time consuming. Executing these tasks involve bringing various stakeholders together to explore alternate options, including creating new images, mock screens and prototypes, which are eventually placed into interactive screens. Many of the tasks are repetitive and hence primed for automation and disruption.
We at Mphasis NEXTlabs are leveraging deep learning approaches to streamline this process and help teams design new images, interfaces, screens, experiences, and products in an intuitive manner thereby improving efficiency, innovation, and productivity. The project aims to leverage deep learning algorithms on training data to automate the front-end development process thereby reducing the time, cost, and effort to go from requirements to code.
We are using the following technologies:
- Intel® Xeon® Gold processors and Intel® Xeon® Platinum processors
- Intel® optimized Tensorflow*, Python* and other relevant libraries
- Intel® Math Kernel Library (Intel® MKL) for lower level optimizations
Further, our developers use training resources provided by the Intel® AI Academy which is a great resource for learning about Machine Learning & Deep Learning modeling. We use it often to explore new concepts. Additionally, we have found the blogs from Intel® AI DevCon (AIDC) to be very informative.
Intel: What do you see as the primary benefits of Intel® AI and/or working with our teams?
Intel provides optimized hardware and software for building and deploying state of the art deep learning models. In addition:
- Intel has optimized several of the commonly used deep learning frameworks which helps us in making our products stand out and get significant, performance gain
- The Intel team has been very helpful and proactive in answering our technical queries related to the deployment of deep learning frameworks on Intel architecture
- We see Intel as a strategic partner who can help connect us with customers who are interested in our AI and cognitive solutions
Intel: Any last words on the future of the partnership between Intel and Mphasis?
Dr. Ganesh: Intel® AI Builders is a tremendous opportunity for us to leverage the vast array of hardware and software assets as well as training material made available by Intel to optimize various aspects of the AI model development and testing life cycle.
Mphasis has been an early partner in the Intel® AI Builders program and we look forward to our continued association with Intel towards building world class solutions for our customers.
Artificial Intelligence Conference, London
Don’t miss your chance to see the solutions Mphasis has developed and chat with Archisman Majumdar and Jai Ganesh in real-time. Join Archisman and Jai at the London O’Reilly Mphasis session on October 11, where they will outline the process of automated user interface creation using deep learning and share techniques for text-to-image creation and template-to-code generation, along with cloud technologies in automated deployment, management, and scaling of such applications.
Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis’ Front2Back™ Transformation approach. Front2Back™ uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis’ Service Transformation approach helps ‘shrink the core’ through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis’ core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients.