How AI is helping us in various fields

Hello my dear friends welcome to our blog verryonel today's yopto is AI part -2 its advantages so lets explore it-:

 1. Music & Movies

Composers have experimented with a variety of computational techniques for music composition. Some works use mathematically inspired techniques, including the use of stochastic processes or sequences, to create melodic, harmonic, and rhythmic structures. Other examples use learnin ag-based approaches. Learning can be knowledge-based, drawing from music theory, composer and period style to create new musical compositions. Learning can also be example-based, where algorithms learn to imitate style from examples of music performed by others. The task of the algorithm is then to learn the underlying structures and patterns that are found in musical excerpts. Such compositions can take place in real time, allowing the algorithms to respond in real time to the improvisations of the human performer.

2. Self driving cars

For an automobile to be autonomous, it needs to be continuously aware of its surroundings—first, by perceiving (identifying and classifying information) and then acting on the information through the autonomous/computer control of the vehicle. Autonomous vehicles require safe, secure, and highly responsive solutions which need to be able to make split-second decisions based on a detailed understanding of the driving environment.

For the vehicle to be truly capable of driving without user control, an extensive amount of training must be initially undertaken for the Artificial Intelligence (AI) network to understand how to see, understand what it’s seeing, and make the right decisions in any imaginable traffic situation. The compute performance of the autonomous car is on par with some of the highest performance platforms that were only possible just a few years ago. 

 

1. Suicide prevention and Ads

AI models predict individual risk

Current evaluation and management of suicide risk is still highly subjective. To improve outcomes, more objective AI strategies are needed. Promising applications include suicide risk prediction and clinical management.

 

Suicide is influenced by a variety of psychosocial, biological, environmental, economic and cultural factors. AI can be used to explore the association between these factors and suicide outcomes.

 

 

AI can also model the combined effect of multiple factors on suicide, and use these models to predict individual risk.

 

As an example, researchers from Vanderbilt University recently designed an AI model that predicted suicide risk, using electronic health records, with 84 to 92 per cent accuracy within one week of a suicide event and 80 to 86 per cent within two years.

 

    Moving forward with caution

As the field of suicide prevention using artificial intelligence advances, there are several potential barriers to be addressed:

 

1.  Privacy: Protective legislation will need to expand to include risks associated with AI, specifically the collection, storage, transfer and use of confidential health information.

 

2.  Accuracy: AI accuracy in correctly determining suicide intent will need to be confirmed, specifically in regards to system biases or errors, before labeling a person as high (versus low) risk.

 

3.  Safety: It is essential to ensure AI programs can appropriately respond to suicidal users, so as to not worsen their emotional state or accidentally facilitate suicide planning.

 

4.  Responsibility: Response protocols are needed on how to properly handle high risk cases that are flagged by AI technology, and what to do if AI risk assessments differ from clinical opinion.

 

5.  Lack of understanding: There is a knowledge gap among key users on how AI technology fits into suicide prevention. More education on the topic is needed to address this.

4. Amazon product recommendations and pricing

    1. Amazon recognizes the patterns in user purchases and product research, recommends them other products that they might be interested in. These recommendations are predicted to increase sales by up to 30% and are in par with the effect 2 stars increase create on a five star scale rating.

    2. Airlines use these kinds of patterns on their websites to alter prices per individual to achieve maximum profits.

5. Medicine

    1. Our eye is a window into our health. Using millions of retinal scans, AI learnt the pattern to identify diseases like diabetes, high blood pressure, cardiovascular risk etc. These models are loaded into handheld devices, which can be used even by nurses, and can be shipped to remote parts of the world, improving healthcare for everyone.

    2. Models can be used to predict serious illnesses a day prior to occurring, which can save several lives.

    3. Tissue, X-ray and MRI scans can identify cancers, tumors and fractures better than a human doctor can. There is one radiologist for every 12,500 people in the world. AI can help us here.

6. Sales and service

    1. Behavioral patterns analyze and alert companies if a customer is about to discontinue a service or product.

    2. Chat bots that can process natural language can reduce the number of human operators needed in Customer Service department.

7. Voice Generation

    1. Google Duplex and Wave net are examples where AI can generate speech that sounds like us. Once released, you can imagine it doing almost every conversation. For example making a reservation and updating Google maps with store holiday timings. Can you think of some examples? Please leave a comment below!

8. Fraud and Credit

    1. Supervised learning models are very good at detecting fraud; it only takes 40ms for raising the red flag.

    2. Many banks can determine credit worthiness based on the transactions, instead of relying on credit agencies.

9. Spam Filters

    1. Everyone is bombarded with spam emails. Email services like Gmail used to have highly skilled computer programmers, code the patterns to mark as spam. Now AI models can identify spam and scams even if the content and the sender are changed.

10. Education

    1. We can predict if a student is likely to dropout. This will help schools to allocate additional resources to the student so that they can be successful.

    2. Courses can be customized to individual student’s needs and learning abilities.

    3. Plagiarism can be identified using AI with more accuracy and efficiency. Regular brute force methods take a lot of resources and often miss subtle variations.

12. Data Center and Grid Management

    1. When Google employed its Deep Mind AI to reduce power consumption in its data centers, it nearly reduced that by 40%.

    2. Google is working on developing such models for power plant efficiency, electric grid management, water usage, and efficiency of manufacturing facilities.

12. Weather Predictions

    1. Weather is one of the most complex pattern recognition for humans to do. AI can be easily trained to do this bidding for us with utmost accuracy.

So that for all today .