AI-related buzz and movie robots have very little to do with the AI capability being discussed in this course.
General AI, or strong AI, refers to AI solutions that are capable of solving problems on a large scale, understanding what they are doing, and being self-aware. The Terminator and the android Data from Star Trek fall into this category. Strong AI should be seen as something that currently exists only in the entertainment industry, and the situation is unlikely to change for a long time to come.
Strong AI was previously seen as something that existed only in the entertainment industry, and that the situation would unlikely change for a long time to come. However, recent advancements in Generative AI from companies like OpenAI may result in fiction becoming reality much earlier than previously anticipated. OpenAI hopes to achieve General AI before the end of this decade.
Narrow AI refers to AI solutions that are capable of solving one task at a time, without awareness or understanding of the context of the task. In practice, therefore, an AI solution for playing chess wouldn’t be able to drive a car or distinguish animals in pictures.
From a programming perspective, we can sometimes combine different AI solutions, creating the illusion that the AI can do many things. Narrow AI doesn't actually understand or think, but seeks to predict the “right answer” based on training data. The following article is an example of a situation that can arise when AI doesn't understand the context but predicts the “right answer”.
Advancements in Generative AI and more capable models have been published since 2022 i.e. after this article was published. Such advancements have enabled techniques like prompt engineering to inject contextual information. Also guardrails have been implemented by the technology vendors like OpenAI to address and limit the potential for harm. Additional guardrails e.g. company policies could also be integrated to further align the output generated.
All current AI solutions are therefore narrow AI, and their use and development can still achieve many far-reaching benefits.