Smart Apps
There are tremendous opportunities to use AI, ML, and other data-driven methods to generate intelligent apps. We offer the opportunity to discover how to make apps smarter to achieve better businesses and improve customer experience.
Barriers to Success
Many barriers exist to building intelligent apps and the fields of AI and app development exist in separate silos. We aim to remove these barriers and help leverage AI and ML for real-time improvements to software applications.
Approach
We must be intentional in our approach to build smart apps. The Smart Apps Project uses an application-centric system combined with a data-driven mindset to help build intelligent apps.
Training vs Inference
You might think ML requires huge amounts of data and computing, but once ML models have been trained, we can often apply them in milliseconds to help make apps more intelligent.
Two Dominant Drivers of Technology
How do we connect them in real time to get smarter apps?
In our world of technology today, the main two drivers – software applications and artificial intelligence – have remained siloed. This approach results in a disconnect, leading to difficulty in leveraging AI models to make apps that are smart and drive more value.
We can and should harness the power of machine learning in the applications customers use. The Smart Apps Project seeks ways to incorporate AI, machine learning, and related technologies into applications in real time to achieve better customer experience and business outcomes.