Google is leading the way toward accessible machine learning through APIs that empower businesses to build machine learning into a wide range of solutions.
Key AI/Machine Learning Use Cases
From self-driving cars to autonomous forklifts or drones, AI and machine learning underpin these types of robotics technologies. AI and machine learning are naturally suited to analyze images because the software is programmed for basic recognition and then can analyze data from images to identify clear and underlying patterns. For example, drones in warehouses can learn to recognize traffic patterns in the facility and identify items on shelves, allowing for a higher degree of autonomy than if they were purely programmed to recognize signs and scan barcodes.
Like autonomous vehicles, the visual analysis offered by AI and machine learning are vital for any robotics applications. However, robust machine learning is particularly beneficial here as robots can automatically learn better ways to complete the work they are tasked with. Furthermore, using AI and machine learning in this setting allows for closer interactions between humans and robots with reduced risk as robots are aware of nearby human workers and can respond accordingly.
AI and machine learning capabilities pay off in two ways for analytics use cases. The technology performs backend data analysis to identify patterns in large data sets while delivering visualizations and actionable data points to end users in a way that is relevant to their job role and responsibilities.
In practice, AI and machine learning extend the value of data analytics solutions by deepening analysis and making insights as actionable as possible for end users.
Whether you’re using physical robots or software-based automation tools, AI and machine learning can provide a heightened layer of intelligence to allow automation solutions and improve decision-making. Instead of relying almost exclusively on strict data parameters and pre-written algorithms, AI and machine learning systems can more flexibly interpret data to improve automation.
Conversational AI Chatbot Boosts Local Government’s Digital Engagement
Learn how Placer County worked with Dito & Google Cloud to develop a “conversational AI” tool to better service its constituents. Their deployed solution works across multiple voice platforms, such as Google Assistant with Dialogflow, Amazon Alexa, and mobile/web interfaces, to more efficiently support its constituents across a variety of departments and use cases.