Problem Solving In Artificial Intelligence

One of the biggest of these is - how do we keep the systems safe?

Algorithms are based on data, so any change to that data will change the behaviour and outcomes.

After initial teething problems, the robot started answering the students’ questions with 97% certainty.

The university designed the robot after their research showed that one of the main factors behind students dropping out is a lack of support.

For example, a recent ground-breaking discovery on the disease Amyotrophic Lateral Sclerosis (ALS), was made through a partnership between Barrow Neurological Institute and the artificial intelligence company IBM Watson Health.

IBM Watson, the artificial intelligence computer, reviewed thousands of pieces of research and was able to identify new genes linked to ALS.Thanks to ‘neural networks’ in its spam filters, Google now boasts of 0.1 percent of spam rate.Brain-like “neural networks” in its spam filters can learn to recognize junk mail and phishing messages by analyzing rules across an enormous collection of computers.In addition to spam detection, social media websites are using ML as a way to identify and filter abuse.Unsupervised learning enables a product based recommendation system.Given a purchase history for a customer and a large inventory of products, ML models can identify those products in which that customer will be interested and likely to purchase.The algorithm identifies hidden pattern among items and focuses on grouping similar products into clusters.ML programs use the discovered data to improve the process as more calculations are made.Thus machines can learn to perform time-intensive documentation and data entry tasks.A model of this decision process would allow a program to make recommendations to a customer and motivate product purchases.E-Commerce businesses such as Amazon has this capability.


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