Can Computers be Creative? How? How can [a creative idea] arise, then, if not by magic? And how can one impossible idea be more surprising, more creative, than another? How can creativity happen?
– from Margaret Boden. Creativity and Unpredictability. Stanford Electronic Humanities Review 4(2), 1995.
Definitions of the term'Artificial Intelligence' tend to fit one of the following categories: While all of these options are similar in that they deal with'intelligent behavior' in computers, they are also quite different. The first refers to a research discipline, while the second and third describe what that research discipline seeks to create. The ways in which the term'AI' can be used depend on which of these definitions you consider valid. For instance, news articles often have titles to the effect of "Google's new AI learned X" or "A new AI can do Y," such as: But, such usage ("An AI Developed", "AI can now", etc.) is only valid with that third'intelligent entity' definition. If the first'field of research' definition is chosen instead, these titles would have to be rewritten as "Google's new AI algorithm learned X" or "A new AI system can do Y."
There was a time when we heard terms like Artificial Intelligence and Machine Learning only in sci-fi movies. But today, technological advances have brought us to a point where businesses across verticals are not only talking about, but also implementing artificial intelligence and machine learning in everyday scenarios. AI is everywhere, from gaming stations to maintaining complex information at work. Computer Engineers and Scientists are working hard to impart intelligent behavior in the machines making them think and respond to real-time situations. AI has evolved from being a research topic to being at the early stages of enterprise adoption.
An important feature of human intelligence is the ability to learn. The amazing learning abilities of the human brain enable babbling babies to grow into learned and easy-to-talk adults. For human beings, learning is an innate ability. The universal existence of this ability makes us ignore its strangeness and preciousness. As far as artificial intelligence research is concerned, how to make machines possess the most universal capabilities in the human world is a very challenging research direction. In different research paths, the subjects, contents and methods of learning are quite different.
The company OpenAI has developed an extremely powerful machine-learning system that can rapidly generate text with minimal human input. The system is known as GPT-3 and it does everything from crafting an email to writing advanced fiction. However, the FT's innovation editor, John Thornhill, explains, there are barriers and even a dark side to this tool. A transcript for this podcast is currently unavailable, view our accessibility guide.
To understand if machines can create art, to analyse the kind of art that can be generated by man-machine collaboration, to ask ourselves whether, as human beings, we're able to appreciate the art produced by Artificial Intelligence or collaborate with it. Arthur I. Miller ground-breaking theory of creativity applies to both humans and machines. He goes on to focus on AI-created art, literature and music. He explores how machines will be able to acquire the characteristics of human creativity - inspiration, suffering, being'out there' in the world, focus, perseverance, discovering new problems and being unpredictable. In the course of this research Miller interviewed over a hundred leaders in the field.
The future won't be made by either humans or machines alone, but by both, working together. Technologies modeled on how human brains work are already augmenting people's abilities, and will only get more influential as society gets used to these increasingly capable machines. Technology optimists have envisioned a world with rising human productivity and quality of life as Artificial Intelligence systems take over life's drudgery and administrivia, benefiting everyone. Pessimists, on the other hand, have warned that these advances could come at great cost in lost jobs and disrupted lives. And fearmongers worry that AI might eventually make human beings obsolete.
It can churn out emails, computer code, internet ads, plotlines for video games, guitar riffs and suggestions for Halloween costumes. It can write disarmingly plausible poems in the spirit of Emily Dickinson, prose in the style of Ernest Hemingway and even, if so instructed, an imaginary conversation between Dickinson and Hemingway. The possibilities seem almost endless. So when I had the opportunity to interact with GPT-3, a new language-generation model that has caused a sensation in the artificial intelligence world over the past few months, I enlisted its help in drafting myself a new biography, infused with the spirit of hero Luke Skywalker. Trained on pretty much all the text accessible on the internet, GPT-3 is remarkable for its speed, scale and versatility.
An interesting concept from literary theory states that if a reader wants to make sense of a text, then he will find an interpretation of that text that is consistent with his own world view, or perhaps more precisely, with his view of the world he supposes the text to concern. Oftentimes, to fulfill such a desire requires the reader to fill gaps in his own knowledge, as well as gaps in the logic or rhetoric of the writer by reading between the lines. In this way, all texts are essentially a dialogue initiated by the writer and continued by the reader, with the reader forming, perhaps erroneously, the intentions of the writer. Upon learning of this concept, I fell enamored with writing poetical nonsense with snippets of text found in books and magazines.ᵃ I was excited by the idea of reader attempting to interpret meaning from my curated words and phrases and by doing so finding his own meaning in the resulting lines; perhaps this excitement is a form of sadism -- I don't know -- but during my cut-and-paste creative process, each poem began to take on a personal meaning to me, so perhaps not.
The New York Times reported that an AI system known as Aristo had become the first to successfully pass a standardized eighth-grade science test. The achievement arrived four years after a competition in which 700-plus scientists all failed to build a system capable of accomplishing the same task despite the incentive of the contest's $80,000 prize. Aristo has been viewed as a significant breakthrough in the evolution of AI technology, with far-reaching implications for natural language processing, business intelligence and more. The system provides a vivid illustration of the differences between human and artificial intelligence. It shows why the most effective AI systems still incorporate help from human experts -- a fact that has big implications for AI in business and other applications. The Aristo system represents a major step toward imbuing AI with what one Wired article refers to as "common sense," the expansive and unconscious background knowledge that we apply when navigating new situations or engaging in conversation.