A) How AI and imagery build a self-updating map
B) How AI and imagery build a self-updating map
Building a map is complex, and keeping it up-to-date is even more challenging.
Think about how often your city. Town or neighborhood changes on a day-to-day basis. Businesses and shops open and close. Stretches of highway are added. And roadways change. In today’s Maps 101 installment. We’ll dive into two ways Google Maps uses advancements in AI and imagery to help you see the latest information about the world around you every single day.
C) How AI and imagery build a self-updating map
Automatically updating business hours
Over the past few years. Businesses have experienced a lot of change including constantly updating operating hours based on changing pandemic-related restrictions. To keep up with this pace of change. We developed a machine learning model that automatically identifies if business hours are likely wrong, then instantly updates them with AI generated predictions.
D) How AI and imagery build a self-updating map
Let’s look at Liam’s Lemonade Shop as an example. To start. Our systems consider multiple factors such as when. Liam last updated their business profile, what we know about other shops’ hours. And the Popular Times information for the shop. Which uses location trends to show when it tends to be busiest.
To see if business hours need updating, we check a store’s Popular Times information and when its business profile was last updated.
So what’s next?. Our algorithms analyze the business hours of other nearby lemonade shops. Information from Liam’s website. And Street View images of Liam’s storefront that look specifically for business hour signs to determine the most accurate business hour prediction. At the same time. We enlist the help of the Google Maps community including Local Guides and even the business owners themselves through their Google Business Profile to verify the information we predicted. In Argentina, Australia, Chile, France, Japan, Mexico, New Zealand, Peru, and the United States. We also use Duplex conversational technology to call businesses just like Liam’s and ask for their hours directly. With this new AI-first approach. We’re on track to update the hours for over 20 million businesses around the globe in the next six months – helping you know exactly when your favorite store. Restaurant or cafe is open for business .
How AI and imagery build a self-updating map
Road information that reflects the real world
We’re also experimenting with ways we can use imagery to make updates to other helpful information.
For instance. Starting in the U.S., we’re launching a third-party imagery pilot to let you see the most up-to-date speed limit information in your town, which can help keep you safe while driving. Here’s how it works:
Say our systems think that the speed limit information on a particular highway needs to be updated.
With the help of third-party imagery partners that already gather roadway imagery to improve delivery routes. We can request a photo of the specific stretch of road that also includes a speed limit sign. If the partner has this photo available, we then use a combination of AI and help from our operations team to identify the sign in the image. Extract the new speed limit information. And update Google Maps.
Representative imagery featuring a speed limit sign, with license plates blurred
Over time. This technology will bring more details to the map that can help make your drives safer and more efficient like where potholes and school zones are or where new construction is happening. And as with all Google Maps features. We designed this pilot with privacy top of mind. For an extra layer of privacy. We blur the photo again when we receive it and delete the photo after we use it to update the map.
AI, imagery and Duplex technology will continue to play a critical role in helping make Google Maps the most comprehensive and useful map possible. For more behind-the-scenes looks at the technology that powers Google Maps. Check out the rest of our Maps 101 blog series.
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Source: The Keyword
Building a map is complex, and keeping it up-to-date is even more challenging.
We developed a machine learning model that automatically identifies if business hours are likely wrong, then instantly updates them with AI generated predictions.
Our systems consider multiple factors such as when. Liam last updated their business profile, what we know about other shops’ hours.
Building a map is complex, and keeping it up-to-date is even more challenging.
We developed a machine learning model that automatically identifies if business hours are likely wrong, then instantly updates them with AI generated predictions.
Our systems consider multiple factors such as when. Liam last updated their business profile, what we know about other shops’ hours.
Building a map is complex, and keeping it up-to-date is even more challenging.
We developed a machine learning model that automatically identifies if business hours are likely wrong, then instantly updates them with AI generated predictions.
Our systems consider multiple factors such as when. Liam last updated their business profile, what we know about other shops’ hours.
Building a map is complex, and keeping it up-to-date is even more challenging.
We developed a machine learning model that automatically identifies if business hours are likely wrong, then instantly updates them with AI generated predictions.
Our systems consider multiple factors such as when. Liam last updated their business profile, what we know about other shops’ hours.
Building a map is complex, and keeping it up-to-date is even more challenging.
We developed a machine learning model that automatically identifies if business hours are likely wrong, then instantly updates them with AI generated predictions.
Our systems consider multiple factors such as when. Liam last updated their business profile, what we know about other shops’ hours.
Building a map is complex, and keeping it up-to-date is even more challenging.
We developed a machine learning model that automatically identifies if business hours are likely wrong, then instantly updates them with AI generated predictions.
Our systems consider multiple factors such as when. Liam last updated their business profile, what we know about other shops’ hours.