The vast scope of AI/ML and its potential

Artificial Intelligence and Machine Learning are creating a lot of buzz in the industry. With fast growing users and abundant amount of data available on the internet, it helps to derive trends of data application via AI and ML techniques for the users/consumers.

Every person using a mobile and internet is utilising AI and ML technologies. When they are browsing the internet, the relevant ads that pop-up on the Google search engine are aided by AI and ML.

What is Artificial Intelligence and Machine Learning?

Machine Learning (ML) - it can be defined as the acquisition of knowledge or skill. Any analysis done for ML is done on acquired data, to train a system

Artificial Intelligence (AI) – it emphasizes the creation of intelligent systems that work via cognition like humans. Algorithms are used to deduce from the data and define automated action to be performed by machine/system, which further reduces workload for the humans. AI and ML are already big with online sales and e-commerce business domains.

Examples of how AI and ML are helping:

Traffic Predictions: It is helping to predict traffics by using GPS navigation services. All our current locations and velocities are being saved at a central server for managing traffic and this data is then used to build a map of current traffic. While this is helping to prevent traffic and does congestion analysis, the underlying problem is that there are less number of cars that are equipped with GPS. In this scenario, Machine Learning helps to estimate the regions where congestion can be found based on daily experiences.

Videos Surveillance: Powered by AI, video surveillance system is making it possible detect crime by tracking unusual behaviour of people, like standing motionless for a long time, stumbling, or napping on benches etc. The system can help to avoid mishaps by alerting human attendants. When such activities are reported and counted to be true, they help to improve the surveillance services, it proves that Machine Learning is doing its job.

Other ways in which AI and ML is helping:

Evolutionary Computation: It is an Artificial Intelligence subfield that is closely linked to computational intelligence, involving lots of combinatorial optimization problems and continuous optimization. This subfield is employed in problem-solving systems that use computational models with evolutionary processes as the key design elements.

Expert Systems: these are the computer applications which are developed to solve complex problems in a particular domain, at the level of extra-ordinary human intelligence and expertise.

Robotics: Robotics is a branch of AI, composed of different branches and application of robots. AI Robots are artificial agents who act in the real-world environment, aimed to manipulate objects by perceiving, picking, moving and destroying it.

Natural Language Processing (NLP): NLP refers to AI method of communicating with an intelligent system using a natural language such as English. Processing of NLP is required when you want an intelligent system like robot to perform as per human instructions, when you want to hear decision from a dialogue based clinical expert system etc.

Neutral Networks: These are a popular target representation for learning and these networks are inspired by the neurons in the brain but do not actually stimulate neurons. Artificial Neural Networks (ANNs0 are statistical models directly inspired by and partially modelled on biological neutral networks. They are capable of modelling and processing non-linear relationships between inputs and outputs in parallel. This is mainly used to do the analysis of the data in the Machine Learning.

Based on the thought process and intelligent actions taken by human brain the elements of Artificial Intelligence are derived. The below picture depicts the elements of Artificial Intelligence.

Potential of AI and ML: According to a report by Price Water Cooper Global – ‘By 2030, AI will be contributing USD $15.7 trillion to the businesses worldwide’. The potential usage of AI into the businesses for products, lifestyle and services is tapped very little. There are already a lot of online trainings available and some even guarantee placements for aspiring professionals across the globe. AI will not reduce jobs but will be helpful for data analysts and scientists.

Flow diagram of the Machine Learning and Artificial Intelligence systems

Examples of AI and ML affecting daily lives:

Automated tech support and online chatbots are already supported for many e-commerce sites

Voice assistants supporting the search engines, like Siri, Alexa and Cortana

Facial Recognition – pattern matching AI techniques, like iPhone X unlocking, driver fatigue check in a car

Shopping malls sending alerts based on lifestyle and interest criteria – taking searching engine data

Possibilities of AI / ML:

Improved product recommendations – user’s browsing habits across the IT domain can improve recommendation engine and give bigger surface area for Sales team. It can improve online product recommendation for customers

Customer Segmentations – Classification in ML can help the segmentation/personas of the users. Customize the UI layout based on the segmentation

Order code sequencing – Show most frequently searched order code/bought order code at the top of the buying list

Portal Access – Based on customer IP address/geo location history, user’s login behaviour can be predicted, and if that changes abruptly, extra layers of authentication and security can be activated

Smart inventory and Supply Chain predictability – AI built based on customer growth and customers’ purchase history can be leveraged in building Smart Inventory System and optimizing the Supply chain

Document Retrieval – applying filters for product selection based on user phrases

Predict system failures – deep learning algorithm to predict system failures and how it impacts customers

Voice recognition commands and smart searches – find product and tech support, using any keyword

Sita T,
Director Software Engineering, Dell Technologies