Jul 01, 2021 | Rejoice tutorials-guides

The Everyday Applications of Artificial Intelligence in some Aspect of today’s world.

We are at the cusp of the next major leap in artificial intelligence. Artificial intelligence (AI) is already here but is not yet widely applied. Industries are already starting to use AI solutions to solve real-world problems, but the more widespread application of AI is still a decade away. Artificial intelligence is about more than just robots and self-driving cars. It's also becoming a new way to measure our own intelligence.  This blog post introduces you to the recent most common applications of AI that you will encounter in your day-to-day life.

Achieving a reduction in commute time is not an easy problem to solve.  The expected and the unexpected can contribute to traffic congestion on a single trip: accidents, maintenance of roads and railroads, and weather conditions can stop traffic flow at a moment's notice. Furthermore, long-term trends may not correspond exactly to historical data due to key factors such as changes in population count and demographics, local economies, and zoning policies. How AI already helps to tackle transportation's complexities.

1. Predictions from Google powered by AI
Google Maps (Maps) can analyze the speed of traffic using anonymized location data from smartphones. With access to vast amounts of data, Maps can reduce time spent on the road by suggesting the fastest routes to and from work.
2. Ridesharing Apps Like Uber and Bolt
How are fares determined? How is time spent waiting for a car minimized? How are passengers matched only with other riders who are on the same route to minimize detours? All these questions are best answered with
3. Commercial flights utilize AI autopilots
 In aviation, artificial intelligence autopilots date back to 1914, which is an amazingly early application of AI technology. This reduces the time that pilots spend guiding their own 


1. Diagnosing Diseases
Algorithms trained with Machine Learning can detect patterns as well as doctors do. There is one important difference between algorithms and human learners - they require many, many examples to teach themselves. Furthermore, textbooks need to be neatly digitized - since machines can't read between the lines. Hence, Machine Learning can be useful in areas where a doctor already uses digital diagnostic information.
For example;
  • Analyzing electrocardiograms as well as cardiac MRI images to assess the risk of sudden cardiac death or other heart conditions.
  • Using CT Scans to diagnose cancerous lesions or strokes.
  • Analyzing skin images for classifying lesions 
  • Diabetic retinopathy: finding indicators in eye images
 As the application of Machine Learning in diagnostics advances, more ambitious systems will combine multiple data sources (CT, MRI, genomics, proteomics, patient data, and even handwritten medical records) in assessing a disease's progression.
2. Individualize treatment
Medications and treatment schedules are adapted to the needs of each patient. Thus, personalized treatment has the enormous potential to improve patients' quality of life. Unfortunately, determining which factors are important in determining a patient's treatment is difficult. By using Machine Learning in this way, it is possible to automate these complicated statistical analyses and discover which characteristics indicate that a patient will respond to a particular treatment. The algorithm can thus predict a patient's likely response to a certain type of treatment.


Movie production
A movie production involves various steps such as script-writing, location scouting, storyboarding, creating shot lists, budgeting, arranging for recording, and editing. A team of professionals from the film industry collaborates on these procedures. 

Automated subtitle 
The process of creating subtitles and synchronizing them with lip movements in movies and videos is complex. Audio and subtitles can become out of sync as a result of a slight delay in the display of the subtitles. A big-budget film also must have subtitles in multiple languages to appeal to a global audience. With AI, subtitles in more than one language can be accurately produced. Aside from that, AI tools can be useful for film industry professionals in determining when and how long subtitles should be displayed. Therefore, the use of AI in media and entertainment can streamline the creation and synchronization of subtitles. 

The next blog would contain more practical applications of Artificial Intelligence. To know what this artificial intelligence is all about, click here for more information. Contact us at www.enquiry@zkyte.com.ng for more inquiries.
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