Artificial intelligence (AI) is a division of computer science focused on building intelligent machines capable of performing smart tasks that require human intervention. Artificial intelligence is the combination of machine learning, deep learning, neural networks and data mining - all seen championing the business world.
Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks associated with intelligent beings. Encyclopaedia Britannica
AI performs depending on the assigned task. This includes unique implementations and strategies but isolated as two main approaches:
This approach uses algorithms — a series of direct instructions used by computers to solve problems. The chosen algorithm will determine and direct the AI on how to approach the difficulty it faces. Each defined algorithm will have different goals, strengths, weaknesses and approaches, depending on the desired result and problem at stake.
An examples-based approach creates models out of data by finding patterns. Models, in this case, can be examples of visualisations or predictions. Some examples of the data used in these scenarios include user profiles, data logs, transactions, weather reports, etc. The AI is "fed" data, and using machine learning; it gains a general understanding of the project by identifying patterns in the data set.
AI programming focuses on cognitive skills - characterised as four types of AI: reactive, limited memory, theory of mind and self-aware. The processes to achieve these include:
Learning processes: Acquiring data and creating rules which turn the data into actionable information. These provide the machine with actionable instructions to complete specific tasks.
Reasoning processes: Determining the correct algorithm (path) to achieve the desired outcome.
Self-correction processes: A process of continuous adjustment, fine-tuning and developing the algorithm to ensure the desired results.
In a 2016 article Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, explained that AI could categorise into the following four types:
Reactive machines: These AI systems are task-specific and have no memory. These systems cannot use past experiences to inform future ones. A notable example includes IBM's Deep Blue - A chess program that beat Garry Kasparov in 1996 and 1997.
Limited memory: Systems that have partial memory to inform future decisions. They are used in self-driving cars, which learn through various data inputs such as LiDAR and cameras.
Theory of mind: AI systems that can identify human emotions and predict human behaviour. The social intelligence these systems achieve is pivotal for effective interaction with human teams.
Self-awareness: Yet to exist, these systems have a sense of consciousness which allows the machine to understand its current state.
The following is some of the most critical events in AI.
"A Logical Calculus of Ideas Immanent in Nervous Activity." A paper by Warren McCullough and Walter Pitts proposed the first mathematic model for building a neural network.
The theory that neural pathways generate from experiences and that connections between neurons become stronger the more frequently used, proposed by Donald Hebb.
Self-learning program to play checkers, developed by Arthur Samuel.
IBM machine automatically translates 60 Russian sentences into English.
Artificial Intelligence (AI) is first introduced in the Dartmouth Summit Research Project on Artificial intelligence, where AI goals are outlined.
The inception of the programming language PROLOG.
More than a billion dollars a year is being spent on expert systems, which forms the industry known as the Lisp machine market.
Cheaper alternatives emerged, and the Lisp machine market collapsed in 1987. The end of the DARPA led Strategic Computing Initiative in 1993 after almost $1 billion of spending and falling far short of expectations.
Deployment of DART by U.S forces, an automated logistics planning and scheduling tool, during the Gulf War.
World chess champion Gary Kasparov, beaten by IBM's Deep Blue.
Breakthroughs in speech recognition applications such as google speech.
Google's self-driving car passes a human driving test.
Google DeepMind's AlphaGo defeats world champion Go player Lee Sedol.
Weak AI, also known as narrow AI, excels at performing one task exceptionally well, such as answering questions or playing chess. Strong AI can perform a range of functions and eventually teach itself to solve new problems.
Weak AI requires human input and relies on it to define its working parameter. Strong AI does not require human intervention; thus, over time, strong AI develops consciousness to improve its learning.
Automation: Automation tools can expand the yield and types of tasks performed. Robotic process automation automates rules-based data processing tasks that are often repetitive.
Machine learning: The methodology of computers to perform without programming. Implied as the automation of predictive analytics. There are three types of machine learning algorithms which include:
The advent of artificial intelligence for manufacturing will revolutionise the entire sector. Increasing value to intelligent supply chains through mass customisation, efficiency, predictive maintenance and raw material stock analysis, to name a few.
The pandemic has allowed a hard reset and a chance for manufacturers to implement advanced artificial intelligence into their supply chain. What are the use cases of AI in manufacturing?
Applying AI to manufacturing can reduce running costs significantly.
Predictive maintenance allows manufacturers to predict when machines need maintenance with a high degree of accuracy. Advanced sensors and analytics embedded into the machinery will enable manufacturers to prevent unplanned downtime using machine learning and, for example, predicting the optimal time to replace or resharpen tools in the manufacturing chain.Supply chain management will be able to benefit from using big data. Manufacturers collect a whole host of data but often struggle with making sense of it all. With intelligent AI, manufacturers will be able to unlock the previously unreachable insights. From traditional preprogrammed robots to AI-powered robots, improvements in robotics can interpret data efficiently and make decisions on their own. This alone will not only save time but manufacture to a better standard. This is because AI-powered robots can interpret data from CAD models and schematics to identify the most efficient and appropriate way to complete the task without any preprogramming.
Mass customisation is a manufacturing technique that enables the personalisation of custom-made products at scale. AI provides the possibility of creating customised solutions for development and production through greater efficiency of modular output. AI algorithms can formulate and implement changes by looking at patterns in consumer behaviour, socio-economic and macroeconomic factors, location and more. This means a more personalised solution for the customer and optimisations and adaptations made independently by the AI.
The manufacturing sector is the perfect candidate for artificial intelligence. As the technology matures and costs drop, expect to see more manufacturers utilising AI as it becomes more accessible. The future of AI is inevitable in an industry known for embracing new and emerging technologies. Manufacturers are consistently looking to minimise cost, make data-driven decisions, optimise operations and deliver a better product to their consumers.
How far away are we from a future surrounded by artificial intelligence? Most of the methodologies and applications of AI mentioned are possible today; the algorithms have to be applied. What we are yet to see is the successful execution of artificial general intelligence.
The mammoth task of replicating the processing power of a human brain to achieve artificial general intelligence is pending, and quantum computing is likely to be our portal. We will likely begin to see the first AGI systems in 2030, and it could take up to 2060 to see AI with the consciousness of a human.