What is AI (Artificial Intelligence) ?
Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. Examples of AI applications include expert systems, natural language processing (NLP), speech recognition and machine vision.
As the hype around AI has accelerated, vendors have scrambled to promote how their products and services incorporate it. Often, what they refer to as "AI" is a well-established technology such as machine learning.
AI requires specialized hardware and software for writing and training machine learning algorithms. No single programming language is used exclusively in AI, but Python, R, Java, C++ and Julia are all popular languages among AI developers.
How does AI work?
In general, AI systems work by ingesting large amounts of labelled training data, analysing that data for correlations and patterns, and using these patterns to make predictions about future states.
For example, an AI chatbot that is fed examples of text can learn to generate lifelike exchanges with people, and an image recognition tool can learn to identify and describe objects in images by reviewing millions of examples. Generative AI techniques, which have advanced rapidly over the past few years, can create realistic text, images, music and other media.
Programming AI systems focuses on cognitive skills such as the following:
- This aspect of AI programming involves acquiring data and creating rules, known as algorithms, to transform it into actionable information. These algorithms provide computing devices with step-by-step instructions for completing specific tasks.
- This aspect involves choosing the right algorithm to reach a desired outcome.
- Self-correction.This aspect involves algorithms continuously learning and tuning themselves to provide the most accurate results possible.
- This aspect uses neural networks, rule-based systems, statistical methods and other AI techniques to generate new images, text, music, ideas and so on.
Differences among AI, machine learning and deep learning
The terms AI, machine learning and deep learning are often used interchangeably, especially in companies' marketing materials, but they have distinct meanings. In short, AI describes the broad concept of machines simulating human intelligence, while machine learning and deep learning are specific techniques within this field.
The term AI, coined in the 1950s, encompasses an evolving and wide range of technologies that aim to simulate human intelligence, including machine learning and deep learning. Machine learning enables software to autonomously learn patterns and predict outcomes by using historical data as input. This approach became more effective with the availability of large training data sets. Deep learning, a subset of machine learning, aims to mimic the brain's structure using layered neural networks. It underpins many major breakthroughs and recent advances in AI, including autonomous vehicles and ChatGPT.
Why is AI important today?
AI is important for its potential to change how we live, work and play. It has been effectively used in business to automate tasks traditionally done by humans, including customer service, lead generation, fraud detection and quality control.
In a number of areas, AI can perform tasks more efficiently and accurately than humans. It is especially useful for repetitive, detail-oriented tasks such as analysing large numbers of legal documents to ensure relevant fields are properly filled in. AI's ability to process massive data sets gives enterprises insights into their operations they might not otherwise have noticed. The rapidly expanding array of generative AI tools is also becoming important in fields ranging from education to marketing to product design.
Advances in AI techniques have not only helped fuel an explosion in efficiency, but also opened the door to entirely new business opportunities for some larger enterprises. Prior to the current wave of AI, for example, it would have been hard to imagine using computer software to connect riders to taxis on demand, yet Uber has become a Fortune 500 company by doing just that.
AI has become central to many of today's largest and most successful companies, including Alphabet, Apple, Microsoft and Meta, which use AI to improve their operations and outpace competitors. At Alphabet subsidiary Google, for example, AI is central to its eponymous search engine, and self-driving car company Waymo began as an Alphabet division. The Google Brain research lab also invented the transformer architecture that underpins recent NLP breakthroughs such as OpenAI's ChatGPT.
AI is the Future
AI in Manufacturing
Manufacturing has been benefiting from AI for years. With AI-enabled robotic arms and other manufacturing bots dating back to the 1960s and 1970s, the industry has adapted well to the powers of AI. These industrial robots typically work alongside humans to perform a limited range of tasks like assembly and stacking, and predictive analysis sensors keep equipment running smoothly.
AI in Healthcare
It may seem unlikely, but AI healthcare is already changing the way humans interact with medical providers. Thanks to its big data analysis capabilities, AI helps identify diseases more quickly and accurately, speed up and streamline drug discovery and even monitor patients through virtual nursing assistants.
AI in Finance
Banks, insurers and financial institutions leverage AI for a range of applications like detecting fraud, conducting audits and evaluating customers for loans. Traders have also used machine learning’s ability to assess millions of data points at once, so they can quickly gauge risk and make smart investing decisions.
AI in Education
AI in education will change the way humans of all ages learn. AI’s use of machine learning, natural language processing and facial recognition help digitize textbooks, detect plagiarism and gauge the emotions of students to help determine who’s struggling or bored. Both presently and in the future, AI tailors the experience of learning to student’s individual needs.
AI in Media
Journalism is harnessing AI too, and will continue to benefit from it. One example can be seen in The Associated Press’ use of Automated Insights, which produces thousands of earning reports stories per year. But as generative AI writing tools, such as ChatGPT, enter the market, questions about their use in journalism abound.
AI in Customer Service
Most people dread getting a robocall, but AI in customer service can provide the industry with data-driven tools that bring meaningful insights to both the customer and the provider. AI tools powering the customer service industry come in the form of chatbots and virtual assistants.
AI in Transportation
Transportation is one industry that is certainly teed up to be drastically changed by AI. Self-driving cars and AI travel planners are just a couple of facets of how we get from point A to point B that will be influenced by AI. Even though autonomous vehicles are far from perfect, they will one day ferry us from place to place.
