The global business economy is slowly moving to a full-fledged AI and Machine Learning driven setup. It’s no longer a matter of how the world will see AI ML applications in their lives, but it’s a matter of when. Some experts in the data science industry feel we have already crossed the initial stages in AI, even as we move to the new era of the Industrial Revolution perched from the upper threshold in ‘Applied AI” tools.
We have numerous examples in the Applied AI field. But, I chose to showcase the best indigenously built Applied AI Machine Learning products that you can draw inspiration from.
One of the first voice-based AI assistant to ever make it to the commercial market was Apple’s Siri. An outcome of extensive research and development in the Applied AI machine learning technologies yielded this unique virtual assistant for Apple’s iOS, iPad, macOS, watchOS, and tvOS.
Today, AI Machine learning engineers keep Apple Siri in their core prototyping to understand the nuances of Natural language processing, NLP user interface, voice recognition, and customization of smartphone features meeting conversational AI benchmarks set by other AI ML assistants in the market, including Google Assistant, Amazon Alexa, and Microsoft Cortana.
But, Apple Siri remains the hot favorite in Applied AI Machine Learning research projects carried out by the young developers.
Uber, the world’s most popular cab hailing service provider, has been leading the effort in Applied AI systems with its ingenious AI development centers. The company uses a self-styled Applied AI platform to advance its data science efforts in automated mobility and passenger / driver experience management.
Uber AI extensively focuses on the hard problems facing mobility services, road safety, passenger experience, driver fatigue, and pricing models for various traffic conditions. The same applied AI has helped the company augment its services and diversify into newer avenues, including in food delivery, product recommendations, advertising, and merchandising. It has also acquired companies to expand beyond cabs and minis. Today, it assists numerous Open AI projects such as Pyro, Plato, and Ludwig — enhancing the overall adoption rate of AI ML platforms created using Uber AI’s wide ranging expertise in training, testing, and prototyping Universal NLP and Conversational AI applications.
Earlier this year, MIT announced its AI-enriched GPS navigation tool for digital mapping platforms. It’s called RoadTagger, a powerful cartographic tool that extracts data from satellite imagery to tag road entities in digital maps using advanced GPS navigation support. Since I know how Google Maps work and how they acquire data for GPS navigation, it wasn’t that hard to evaluate MIT’s RoadTagger’s performance and accuracy. It is the safest and most importantly the “cheapest” Mapping tool that uses Applied AI Machine Learning techniques such as Convolutional Neural Networking (CNN) along with Graph Neural Network (GNN) to improve the overall quality of digital mapping services.
If you are into Applied AI big time, try exceeding these benchmark projects.