
The AI imagery competition is getting personal.
Google this week unveiled a new challenger to OpenAI’s vaunted DALLE-2 text-to-image generator — and took shots at its rival’s efforts.
Both models convert text prompts into pictures. But Google’s researchers claim their system provides “unprecedented photorealism and deep language understanding.”
![: Example qualitative comparisons between Imagen and DALL-E 2 [54] on DrawBench prompts from Conflicting category. We observe that both DALL-E 2 and Imagen struggle generating well aligned images for this category. However, Imagen often generates some well aligned samples, e.g. “A panda making latte art.”](https://cdn0.tnwcdn.com/wp-content/blogs.dir/1/files/2022/05/Screenshot-2022-05-25-at-10.58.07.png)
In tests, the Google team said Imagen “significantly outperformed” DALL-E 2.

Imagen’s developers have even invented a new method of measuring the supremacy of their creation.
Dubbed DrawBench, the benchmark compares human judgments on the outputs of different text-to-image generators.
Unsurprisingly, Google’s metric gave strong scores to Google’s system.
“With DrawBench, extensive human evaluation shows that Imagen outperforms other recent methods by a significant margin,” the researchers said in their study paper.
![Example qualitative comparisons between Imagen and DALL-E 2 [54] on DrawBench prompts from Colors category. We observe that DALL-E 2 generally struggles with correctly assigning the colors to the objects especially for prompts with more than one object.](https://cdn0.tnwcdn.com/wp-content/blogs.dir/1/files/2022/05/Screenshot-2022-05-25-at-10.56.15.png)
You can try some interactive demos at the Imagen website, but these only let you use a small selection of phrases to form a constrained sentence.
Until the model and code get a public release, cynics will suspect that Google’s cherry-picking the results.
![Example qualitative comparisons between Imagen and DALL-E 2 [54] on DrawBench prompts from Text category. Imagen is significantly better than DALL-E 2 in prompts with quoted text.](https://cdn0.tnwcdn.com/wp-content/blogs.dir/1/files/2022/05/Screenshot-2022-05-25-at-10.59.38.png)
The researchers warn that generative methods can spread misinformation, stir harassment, and exacerbate marginalization.
“Our preliminary assessment also suggests Imagen encodes several social biases and stereotypes, including an overall bias towards generating images of people with lighter skin tones and a tendency for images portraying different professions to align with Western gender stereotypes,” said the researchers.
![Example qualitative comparisons between Imagen and DALL-E 2 [54] on DrawBench prompts from Reddit category.](https://cdn0.tnwcdn.com/wp-content/blogs.dir/1/files/2022/05/Screenshot-2022-05-25-at-10.54.57.png)
I await their update with caution. As someone who creates images for articles every day, the prospect of AI labs competing to offer better results is attractive.
On the other hand, I don’t want our robot overlords to replace artists with algorithms.
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