GPT-3 Generated Haikus

Ive been facinated by this art form since reading The Heart of Haiku by Jane Hirshfield a number of years ago.

Given i’ve been learning the basics of GPT-3 the past couple of days, I thought that generating short poems would be firmly within its wheelhouse, and also a good learning experience on how to ‘prompt’ the system.

Method:

GPT-3 was prompted using the following haikus (in English):

1. The Old Pond by Matsuo Bashō,

2. A World of Dew by Kobayashi Issa,

3. Lighting One Candle by Yosa Buson,

4. A Poppy Blooms by Katsushika Hokusai,

5. Over the Wintry by Natsume Sōseki

I ‘asked’ GPT-3 to produce both the haiku title as well as the body of text. The engine used was davinchi, a Temp of 0.7 and a Top P of 1.

Limitations:

1. We are training this on Japanese poems translated into English, and therefore the limitations on poem structure not conforming to the standard 5–7–5 syllables.
2. Limited ‘prompt’ material.
3. Only a small batch of poems generated: the below is pretty much an unfiltered first set of results.

Results:

Below are the results of the first batch of GPT-3 AI generated Haikus (in order of my subjective preference!):

By Cleaving Wood

By cleaving wood
I learn more of Truth
Than by reading books

A Child’s Dream

A child’s dream
Runs into a wall
Of reality.

Starlight

On a clear October night
The fireflies glitter
Over the mountains.

Years Are Just Hours

Years are just hours
Though dream-dimmed hours
of sleep.

Riding on the Clouds

Riding on the clouds
The soul is lifted up
Above the woes of the world.

A Winter Moon

A winter moon
In the silent sky —
All is frozen.

Flowers of the season

Flowers of the season
All scatter their petals,
One by one, in the wind

At the Foot of Autumn

The foot of autumn:
Infinite sadness and silence —
Yet bursts of inspiring energy!

The Wild Birds

Dropping down to the ground
The wild birds choose a branch
To stay

Winter Daydreaming

Winter daydreaming;
The heron under the deep snow;
High tide smacks as it retreats.

Initial Observations

1. From what I can tell from a cursory review there is little to no plagiarism here, it has not simple repeated Haikus in its training material, or the prompt I have provided it.
2. Most of the titles are simply the first line of the Haiku, this is likely given that a similar trend occurs within the training material. However, this is not universal. It is very interesting that “Starlight’ has no mention of stars but there is a reference to fireflies glittering over mountains.
3. The structure of the Haikus are not very consistent, but this is likely due to training material of Japanese poems translated to English, therefore a next step is to train on native English versions.
4. I do not see much evidence yet of juxtaposition or kireji ‘cutting word’, but again this may improve using native english haikus.

Overall i’m impressed with the outputs, which I believe could be improved by refining the prompts using a native english set — more to follow.

Thanks to Hamilton Keats @ Azoras.co.uk for GPT-3 access