Large language models (LLMs) are the first neural network machines capable of carrying on conversations with humans. They are trained on billions of words of text scraped from the internet. They generate text responses to text inputs. They have transformed the public awareness of artificial intelligence, bringing on reactions ranging from astonishment and awe to trepidation and horror. They have spurred massive investments in new tools for drafting texts, summarizing conversations, summarizing literature, generating images, coding simple programs, supporting education, and amusing humans. Experience with them has shown them likely to respond with fabrications (called "hallucinations") that severely undermine their trustworthiness and make them unsafe for critical applications. Here, we will examine the limitations of LLMs imposed by their design and function. These are not bugs but are inherent limitations of the technology. The same limitations make it unlikely that LLM machines will ever be capable of performing all human tasks at the skill levels of humans.

Artificial intelligence is changing our world. The arrival of ChatGPT in 2022 brought AI into the public spotlight with a dramatic new capability. A user can how engage in a fluent conversation in ordinary language with a computer. Suddenly many people want to know what AI is, whether it is safe, and what benefits it might bring. Artificial intelligence is defined to be a collection of machines and algorithms that perform tasks normally considered to require human cognition. Opinions and claims about the possible benefits and risks of AI are all over the map. In response to the confusion, the Ubiquity editors are launching a symposium on AI. It will be a series of about two dozen articles on the many aspects of AI and its applications. The series will be synthesized into the "Ubiquity Report on Artificial Intelligence," which is intended to be an authoritative and trustworthy summary of present and future AI.

More than the 70 years since its emergence in the early 1950s, artificial intelligence (AI) is performing cognitive tasks traditionally considered the unique province of humans. This progress did not occur in a vacuum. AI emerged against a rich background of technologies from computer science and ideas about intelligence and learning from philosophy, psychology, logic, game theory, and cognitive science. We sketch out the enabling technologies for AI. They include search, reasoning, neural networks, natural language processing, signal processing and computer graphics, programming and conventional software engineering, human-computer interaction, communications, and specialized hardware that provides supercomputing power. Beyond these technologies is the notion of Artificial General Intelligence that has or exceeds the capabilities of the human brain. Currently this is completely aspirational and is not expected to be possible before 2025, if ever. Artificial Intelligence is based on a variety of technologies, none of which seek to emulate human intelligence.