Final answer:
Artificial Neural Networks are an example of machine learning that allows computers to recognize patterns and solve problems. They are part of the broader field of AI which includes various types and raises questions about ethics and governance. AI is rapidly advancing, with applications such as self-driving cars and virtual assistants, pushing the boundaries of automation and cognitive technologies.
Step-by-step explanation:
An example of machine learning that allows computers to recognize patterns and solve problems is Artificial Neural Networks (ANNs). These networks effectively define artificial intelligence as "the simulation of human intelligence by machines programmed to mimic human thought and actions." ANNs are a type of artificial intelligence that can handle various cognitive tasks by mimicking the neural connections of a human brain. This enables them to learn from data inputs and improve over time without being explicitly programmed for each task.
The field of artificial intelligence includes various types such as reactive machines, limited memory, theory of mind, and self-aware AI. Despite discussions surrounding the true cognitive abilities of AI, significant strides have been made. AI implementations excel in domains like self-driving cars and personal assistants like Apple's Siri—examples of weak AI—which perform primarily one task. Conversely, strong AI aims to perform multiple tasks and process information akin to human cognition. The development of AI raises questions about ethics, governance, and transparency, especially given biases that can exist in algorithms.
Computer engineers are at the forefront of designing instructional sets in computer programs, allowing for sophisticated controls in various industries. With the rapid expansion of AI applications in our daily lives and its potential to surpass human decision-making speed, the governance, and transparency of AI systems have become significant topics of concern and research.