AI-embedded applications has widespread in various fields including manufacturing, automotive, utilities, transportation, and the public sector.
Below are the field in which AI-embedded has been in our daily rituals for ease and comfort.
Reducing commute times is not a simple task to solve.It involves :
- Multiple modes of transportation
- Unexpected events such as road or track maintenance
- Weather conditions
Long-historical data fluctuates due to changes in population count and demographics, local economics, and zone policies.
The companies which are solving the commuting issues :
Google’s AI-Powered Predictions:
Hundreds of millions of people around the world give Google real-time data that it uses to analyze traffic and road conditions. This allows the company to analyze the total number of cars, and how fast they're going, on a road at any given time.
Google Maps also incorporates traffic and incident data, like accident reports, from Waze, the popular navigation app that Google bought for more than $1 billion in 2013. Waze gets its information from users who report things like accidents on the road or traffic jams. Google also gets information from local departments of transportation.
Ridesharing Apps Like Uber
The application uses GPS for riders and drivers to find one another which improves estimated times of arrival (ETAs), reduces rider and driver cancellations.
Uber AI uses computer vision, natural language processing, deep learning, advanced optimization methods, intelligent location and sensor processing across the company
Uber leverages neural networks to forecast rider demand, pick-up and drop-off ETAs, and hardware capacity planning requirements, among other variables that drive our operations.
Checking reports,assignments daily without technology was monotonous ; however, grammar corrector, checking plagiarism or assigning to-do lists has made teachers burden lighter and speedy.
Plagiarism detection needs a huge database of reference materials to compare student text.
"The algorithmic key to plagiarism is the similarity function, which outputs a numeric estimate of how similar two documents are."
A brute force search comparing every string of text to every other string of text in a document database will have a high accuracy.
Mediocre standing in line for depositing checks or money or making transactions from bank-to-bank , these all activities made easier with online payments applications.
Virtual Check Deposits:
Most large banks offer the ability to deposit checks through a smartphone application, eliminating a need for customers to physically deliver a check to the bank.
FICO, the company that creates the well-known credit ratings used to determine value, uses neural networks to predict fraudulent transactions
Credit Decisions for loan :
FICO uses ML both in developing your FICO score, to make credit decisions, and in determining the specific risk assessment for individual customers.
Social medias are competing with each other for the latest features,latest trends or using latest technologies.
Identify faces feature :
When you upload photos to Facebook, the system automatically highlights faces and suggests friends tag.
How can it instantly identify which of your friends is in the photo?
Facebook uses AI to recognize faces: ML algorithms that mimic the structure of the human brain—to power facial recognition software.
Snapchat introduced facial filters, called Lenses, in 2015. These filters track facial movements, allowing users to add animated effects adjusted when their faces moved.
AI embedded technology had innovated in distinct fields from navigation,banking sectors to social media filtration.With the help of deep learning, neural network to MI algorithms ; integration of technologies has build ease-comforting applications for humans.