Skip to main content

Move over, Shakespeare: This sonnet-writing A.I. is the poet we need

“With joyous gambols gay and still array,
no longer when he ‘twas, while in his day
at first to pass in all delightful ways
around him, charming, and of all his days.”

Don’t worry: You haven’t accidentally clicked on pre-Digital Trends, by mistake. This is part of a Shakespearean sonnet created by deep learning artificial intelligence — and, shockingly, it’s actually pretty good. The bot was created by researchers at IBM Research Australia, the University of Toronto, and University of Melbourne. Trained on around 2,600 real sonnets, it mimics the iambic pentameter and rhyming pattern of the poems most famously written by ol’ Bill Shakespeare himself.

Recommended Videos

“While the application itself may not seem directly relevant to real-world applications, the underlying machinery of our model shares the same core algorithm that drives other problems that require generation,” Jey Han, one of the researchers on the project, told Digital Trends. “[These might include] translation, summarization, and chatbots. When we started the project, a research question that we wanted to address was, ‘how do we build machines that can produce a coherent narrative that spans multiple sentences?’ And we thought poetry is a good place to start.”

We previously covered some pretty interesting attempts to mimic creativity using A.I. These have included everything from Google’s DeepDream image generation project to a bot-written script for TV comedy Scrubs, which was then read by actor Zach Braff. While A.I. is currently in the process of munching up jobs in the real world, however, the researchers on this particular project think there’s still a way to go before top-tier poets are put out of business by machines. If, indeed, it ever happens.

“The conclusion in the paper is that we should focus more effort on ‘content’ in future work: Spend less time on rhyme and meter, and more time on emotion and readability,” Adam Hammond, a University of Toronto English professor, who lent his expertise to the project, told us. “I’m excited to see what’s possible, but I’m very skeptical. I think it’s quite easy to have a deep learning model spit out lines of verse in rhyming iambic pentameter. It’s much, much, much, much harder to train it to have an opinion, or a feeling, or a desire, or a story to tell.”

A paper describing the work is available to read online.

Luke Dormehl
I'm a UK-based tech writer covering Cool Tech at Digital Trends. I've also written for Fast Company, Wired, the Guardian…
The future of A.I.: 4 big things to watch for in the next few years
brain with computer text scrolling artificial intelligence

A.I. isn’t going to put humanity on the scrap heap any time soon. Nor are we one Google DeepMind publication away from superintelligence. But make no mistake about it: Artificial intelligence is making enormous strides.

As noted in the Artificial Intelligence Index Report 2021, last year the number of journal publications in the field grew by 34.5%. That’s a much higher percentage than the 19.6% seen one year earlier. A.I. is going to transform everything from medicine to transportation, and there are few who would argue otherwise.

Read more
Google’s LaMDA is a smart language A.I. for better understanding conversation
LaMDA model

Artificial intelligence has made extraordinary advances when it comes to understanding words and even being able to translate them into other languages. Google has helped pave the way here with amazing tools like Google Translate and, recently, with its development of Transformer machine learning models. But language is tricky -- and there’s still plenty more work to be done to build A.I. that truly understands us.
Language Model for Dialogue Applications
At Tuesday’s Google I/O, the search giant announced a significant advance in this area with a new language model it calls LaMDA. Short for Language Model for Dialogue Applications, it’s a sophisticated A.I. language tool that Google claims is superior when it comes to understanding context in conversation. As Google CEO Sundar Pichai noted, this might be intelligently parsing an exchange like “What’s the weather today?” “It’s starting to feel like summer. I might eat lunch outside.” That makes perfect sense as a human dialogue, but would befuddle many A.I. systems looking for more literal answers.

LaMDA has superior knowledge of learned concepts which it’s able to synthesize from its training data. Pichai noted that responses never follow the same path twice, so conversations feel less scripted and more responsively natural.

Read more
How the USPS uses Nvidia GPUs and A.I. to track missing mail
A United States Postal Service USPS truck driving on a tree-lined street.

The United States Postal Service, or USPS, is relying on artificial intelligence-powered by Nvidia's EGX systems to track more than 100 million pieces of mail a day that goes through its network. The world's busiest postal service system is relying on GPU-accelerated A.I. systems to help solve the challenges of locating lost or missing packages and mail. Essentially, the USPS turned to A.I. to help it locate a "needle in a haystack."

To solve that challenge, USPS engineers created an edge A.I. system of servers that can scan and locate mail. They created algorithms for the system that were trained on 13 Nvidia DGX systems located at USPS data centers. Nvidia's DGX A100 systems, for reference, pack in five petaflops of compute power and cost just under $200,000. It is based on the same Ampere architecture found on Nvidia's consumer GeForce RTX 3000 series GPUs.

Read more