4. Image recognition
Posted: Mon Feb 17, 2025 6:21 am
Are you also surprised when the Google Photos app recognises all your family members in the photos on your phone? Yes, Artificial Intelligence is behind this.
However, computers do not read images, as if you see a picture of a dog, for example, Google only sees codes. Therefore, they need to learn what the characteristics of a dog's photograph are in order to understand when they are there.
That's where computer vision comes in. This technology allows you to train your computer to recognize patterns of colors and shapes in images. This way, machines are closer to human vision and can make decisions based on what they see.
So the app doesn't just recognize photos of dogs, it also recognizes photos of your dog. It doesn't just recognize photos of people in general, it also recognizes photos of your family or friends. And the more users tell the bots who or what is in the pictures, the more they learn.
This way, Google Photos can organize and group the photos you save, so you can find them with a simple search.
And to give you a clearer idea, in this article Google explains how this technology works.
Source: Android Police
5. Product prices
Who hasn't been scared by the price of an Uber on a busy afternoon? Yes, Artificial Intelligence is also behind!
Dynamic pricing, based on demand and supply of a product, is another possibility for the practical application of machine learning.
For example, when a lot of people leave a football match, Uber fares go up.
At the same time, more drivers tend to come to the venue because the prices are better. But once the event is over, the rates return to normal, often cheaper than a taxi.
The same is true for Airbnb, which offers sweden phone number list the Smart Pricing feature for hosts who want to adopt it. In this way, prices vary according to the demand for accommodations with similar characteristics to those of the host, as well as data such as location, season, accommodation rating, proximity to check-in, among other factors.
Okay, so dynamic pricing is nothing new – hotels and airlines have been using this strategy for years: as demand increases, the price goes up.
However, before AI, this dynamic depended on user-defined rules.
Machine learning, on the other hand, enables algorithms to recognize patterns that humans miss, predict future situations, and update prices in real time. In other words, pricing becomes dynamic, accurate, and fast.
AI-powered dynamic pricing takes into account current demand for a product and user behavior, as well as external data such as news, weather, local events, time, traffic, etc.
So if a show is advertised in a particular city, algorithms can capture this information and adjust prices instantly, which would be very difficult for a human to do.
However, computers do not read images, as if you see a picture of a dog, for example, Google only sees codes. Therefore, they need to learn what the characteristics of a dog's photograph are in order to understand when they are there.
That's where computer vision comes in. This technology allows you to train your computer to recognize patterns of colors and shapes in images. This way, machines are closer to human vision and can make decisions based on what they see.
So the app doesn't just recognize photos of dogs, it also recognizes photos of your dog. It doesn't just recognize photos of people in general, it also recognizes photos of your family or friends. And the more users tell the bots who or what is in the pictures, the more they learn.
This way, Google Photos can organize and group the photos you save, so you can find them with a simple search.
And to give you a clearer idea, in this article Google explains how this technology works.
Source: Android Police
5. Product prices
Who hasn't been scared by the price of an Uber on a busy afternoon? Yes, Artificial Intelligence is also behind!
Dynamic pricing, based on demand and supply of a product, is another possibility for the practical application of machine learning.
For example, when a lot of people leave a football match, Uber fares go up.
At the same time, more drivers tend to come to the venue because the prices are better. But once the event is over, the rates return to normal, often cheaper than a taxi.
The same is true for Airbnb, which offers sweden phone number list the Smart Pricing feature for hosts who want to adopt it. In this way, prices vary according to the demand for accommodations with similar characteristics to those of the host, as well as data such as location, season, accommodation rating, proximity to check-in, among other factors.
Okay, so dynamic pricing is nothing new – hotels and airlines have been using this strategy for years: as demand increases, the price goes up.
However, before AI, this dynamic depended on user-defined rules.
Machine learning, on the other hand, enables algorithms to recognize patterns that humans miss, predict future situations, and update prices in real time. In other words, pricing becomes dynamic, accurate, and fast.
AI-powered dynamic pricing takes into account current demand for a product and user behavior, as well as external data such as news, weather, local events, time, traffic, etc.
So if a show is advertised in a particular city, algorithms can capture this information and adjust prices instantly, which would be very difficult for a human to do.