This article is part of the discovery activities of the Digital Innovation Lab in IT Services. We are seeking to experiment with synthetic content generated by AI. By showing how generative AI tools can be used with specific prompts, we hope to encourage open discussion and collaborative innovation – see how you can get involved below.
For this item, we asked a generative AI tool - Microsoft Bing Chat - to define ‘what is AI?’.
Synthetic content generated by Microsoft Bing Chat. This text has not been edited for style or content for the purposes of this experiment.
What is AI?
AI stands for artificial intelligence, which is the ability of machines or software to perform tasks that normally require human intelligence, such as recognizing images, understanding natural language, playing games, or making decisions. AI is a broad field that encompasses many subfields and applications, such as machine learning, computer vision, natural language processing, robotics, speech recognition, and more.
AI works by using algorithms, which are sets of rules or instructions that tell a machine or software how to solve a problem or achieve a goal. Algorithms can be simple, such as adding two numbers, or complex, such as finding patterns in large amounts of data. Algorithms can also be adaptive, meaning that they can learn from data and improve their performance over time.
There are different types of AI, depending on how they are designed and what they can do. Some common types are:
- Narrow AI: This is the most common and widely used type of AI today. It refers to AI systems that are designed to perform specific tasks or functions, such as filtering spam emails, recommending products, or driving cars. Narrow AI systems are usually based on machine learning techniques, such as supervised learning, unsupervised learning, or reinforcement learning. Narrow AI systems can be very effective and efficient at their tasks, but they cannot generalize to other domains or situations that they were not trained for.
- General AI: This is the hypothetical type of AI that can perform any intellectual task that a human can do, such as reasoning, planning, creativity, or common sense. General AI systems would be able to understand and interact with any type of data, context, or environment, and learn from their own experiences. General AI systems would also be able to explain their actions and decisions, and have goals and values. General AI is the ultimate goal of many AI researchers and enthusiasts, but it is still far from being achieved.
- Super AI: This is the hypothetical type of AI that can surpass human intelligence and capabilities in every aspect. Super AI systems would be able to outsmart, outperform, and outthink humans in any domain or task. Super AI systems would also have self-awareness and consciousness, and be able to create and modify their own algorithms. Super AI is the most speculative and controversial type of AI, as it raises many ethical and existential questions about the future of humanity and its relationship with machines.
End of synthetic content.
Tool and prompts used
This text was produced by Microsoft Bing Chat. The keywords and prompts used were: ‘Bing values: write about: what is ai? Professional, blog post, long’. Read more information on Microsoft’s approach to AI.
The content has been produced by a generative AI tool using information available on the internet; no University data has been used as part of this experiment. The content has been left purposefully unedited by humans so that the output can be analysed and discussed.
What do you think? Join the discussion
This is part of a series of experimental articles exploring the possibilities, challenges and benefits of generative AI tools. We’re keen to encourage discussion about the use of AI tools – please join the Generative AI SIG Teams channel and help us to expand the experiment and inspire others to learn more about this new technology.
Can you suggest other tools to use or other prompts? What would you like to ask AI?
For further information about Digital Innovation, please contact innovation@it.ox.ac.uk.
