AI and its uses
1 March 2023
Nowadays, AI is in everything. Every company, every startup, every program says that its powered by 'AI.' Actually it has now crept into many applications that we use daily. The smartphones increasingly use AI for various application. Your photos, your videos, the routing through maps all have some element of AI in it. Many new companies be it in tech area or not now put 'powered by AI' in their marketing material to part you from your hard earned cash. AI now seems to be a halo that people put around their products to give it a divine meaning. To make it extra-ordinary. To make it seem like Magic!
WHAT IS AI??
Artificial Intelligence has always been a topic that seems to be too cutting edge. Its an unknown sort of black magic that makes things happen without you knowing how it happens. From a definition point of view, AI can be defined as 'The theory and development of computer systems able to perform tasks normally requiring human intelligence'.
In computer science, tasks were done algorithmically. Inputs and all scenarios were painstakingly created as requirements and a code was written for every possible scenario and outcome. AI is an evolution of computer science where the computer is able to work out scenarios by itself without having preiously coded knowledge of it. So it learns by itslef and can give out an answer. This makes it very powerful as a human who has written the code does not have to predict all scenarios and code it.
WHAT IS AI used for?
There are several applications of AI, however simplistically put, AI does three things.
Prediction
Optimisation
Automation
Every use of AI can be categorised in these three areas. And it does so based on data that is fed into it for it to learn. I will expand on each area and logically explain what these three generalisations of AI mean. Now each of these are intertwined in such a way that depending on the context, automation can be considered prediction or Optimisation and sometimes construed interchangably.
“By far, the greatest danger of Artificial Intelligence is that people conclude too early that they understand it.”
—Eliezer Yudkowsky
PREDICTION
Based on data that is fed into the system, the AI is able to predict what will happen in the future. This is more than just extrapolation. Algorithms are able to predict future scenarios based on different trajectories, and even weight the trajectories by probability. Then it's able to give a predictive score of what might happen, and suitable actions can be taken against those.
AI s used extensively for prediction in a variety of fields, including finance, healthcare, and weather forecasting. One of the most common applications of AI for prediction is in financial modeling. AI-based algorithms can analyze vast amounts of financial data to predict stock prices, market trends, and other critical indicators. For example, the hedge funds use AI algorithms to predict stock prices and generate significant profits for its clients. By analyzing patterns in historical data and using machine learning techniques, these algorithms can identify investment opportunities and make accurate predictions about future market conditions.
Another area where AI is widely used for prediction is healthcare. Medical professionals can use AI algorithms to predict patient outcomes and develop personalized treatment plans. For example, AI can be used to analyze patient data such as medical history, test results, and genetic information to predict the risk of developing certain diseases or conditions. This can help doctors identify patients who may need more aggressive treatment and develop treatment plans that are tailored to individual patient needs. AI can also be used to predict the efficacy of different treatments and identify potential side effects before they occur.
Finally, AI is commonly used for weather forecasting. By analyzing vast amounts of weather data, AI algorithms can predict weather patterns and severe weather events with a high degree of accuracy. This information is critical for industries such as agriculture, transportation, and energy production, which rely heavily on weather forecasts to make decisions. For example, energy companies use weather prediction models to predict demand for electricity and adjust production accordingly. Similarly, airlines use weather data to plan flights and avoid dangerous weather conditions. Overall, AI-based weather forecasting provides essential information to help businesses and individuals make informed decisions and mitigate the risks associated with severe weather events.
OPTIMISATION
This is used when different types of parameters have competing requirements and we need. Consider an electric car, it needs to be charged to a certain percentage to ensure that you reach your destination tomorrow, but you also want to charge it when its cheapest or the greenest? These are three different requirements that need to be balanced. Optimisation is actually where most AI applications are mainly based on. Consider a picture that you take on your iPhone or android phone. Based on the picture, different parameters such as brightness, colour etc are balanced to give you a perfect looking picture.
AI is a powerful tool for optimisation that can be used to improve efficiency and reduce costs in a variety of industries. One of the most common applications of AI for optimisation is in supply chain management. By analysing data on inventory levels, production capacity, and shipping times, AI algorithms can optimise supply chain operations to minimise costs and reduce waste. For example, Walmart uses AI-based algorithms to optimise its supply chain operations and reduce the amount of waste generated in its stores.
Another area where AI is widely used for optimisation is in manufacturing. AI algorithms can be used to optimize production schedules, reduce downtime, and improve product quality. For example, General Electric uses AI-based algorithms to optimize production at its jet engine manufacturing plant in North Carolina. By analysing data on production rates, maintenance schedules, and quality control, these algorithms can optimise the production process to minimize downtime and reduce defects, resulting in faster production and higher-quality products.
Finally, AI is commonly used for optimisation in transportation and logistics. By analysing data on shipping routes, vehicle maintenance schedules, and fuel consumption, AI algorithms can optimise transportation operations to reduce costs and improve efficiency. For example, UPS uses AI-based algorithms to optimise its delivery routes and reduce the number of miles driven by its trucks. By analysing data on traffic patterns, delivery times, and customer preferences, these algorithms can optimise delivery schedules to reduce the amount of time spent on the road and minimise fuel consumption, resulting in lower costs and improved efficiency. Overall, AI-based optimisation provides a powerful tool for businesses to improve efficiency, reduce costs, and maximise profitability.
“Before we work on artificial intelligence why don’t we do something about natural stupidity?”
—Steve Polyak
AUTOMATION
Automation is when different tasks are combined in such a way that it removes intermediate inputs from a user. Automation is applied in several ways where a system can 'learn' most probabilistic user inputs and do those without actually requiring a manual input. For example, Google maps/ apple maps on your phone does this. If every Monday you go to work, then it will automate the steps required to open the map, input the address and press go. It will give you a notification of a suggested address and you only have to press Go.
AI is a critical component of automation, enabling machines and systems to operate with minimal human intervention. One of the most common applications of AI for automation is in manufacturing. AI-based robots can be programmed to perform a wide range of tasks, from assembly line operations to quality control inspections. For example, car companies use AI-based robots to assemble vehicles in its factories. These robots can perform tasks such as welding, painting, and assembly with a high degree of accuracy and efficiency, reducing the need for human labor and improving production speed.
Another area where AI is widely used for automation is in customer service. AI-based chatbots can be programmed to answer common customer questions and provide support around the clock, reducing the need for human customer service representatives. For example, Bank of America uses an AI-based chatbot called Erica to provide support to its customers. Erica can answer questions about account balances, transaction history, and other common banking tasks, enabling customers to access information and complete transactions without the need for human intervention.
Finally, AI is commonly used for automation in logistics and transportation. AI-based systems can be used to manage shipping and delivery operations, from route planning to tracking and delivery confirmation. For example, Amazon uses an AI-based system called Amazon Robotics to automate its shipping and logistics operations. Amazon Robotics uses robots to move products through its warehouses, reducing the need for human labor and improving efficiency. Additionally, Amazon uses AI-based algorithms to optimize delivery routes and predict shipping times, enabling customers to receive their orders faster and more reliably. Overall, AI-based automation provides a powerful tool for businesses to improve efficiency, reduce labor costs, and improve customer service.
SO WHAT DOES IT MEAN FOR US?
As AI continues to advance and become more integrated into various industries, it's important we stay up-to-date with the latest developments in the field. To avoid being left behind, we should prioritise learning about AI and its applications in our fields, whether through attending conferences, participating in training programs, or engaging with online resources. Additionally, we should be proactive in seeking out opportunities to integrate AI into our work, whether through automating routine tasks or using AI-based algorithms for optimisation and prediction. By embracing AI and incorporating it into our workflows, we can stay competitive in a rapidly evolving job market and drive innovation in our industries.