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Apple Shares Massive Dataset to Help Researchers Build Nano Banana Like AI Models

Apple Shares Massive Dataset to Help Researchers Build Nano Banana-Like AI Models

Apple wants to help researchers and developers build better AI models with its dataset, even when it struggles to do so itself.

Written by Akash Dutta, Edited by Ketan Pratap | Updated: 29 October 2025 15:20 IST

Apple Shares Massive Dataset to Help Researchers Build Nano Banana-Like AI Models

Photo Credit: Reuters

Apple said the dataset was created due to the absence of large-scale and openly accessible images

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Highlights

Apple’s Pico-Banana-400K is a dataset for text-guided image editing
The company used Nano Banana’s output to create the dataset
Apple’s dataset comes with a non-commercial research license

Apple researchers have released a large-scale dataset to help others develop image editing artificial intelligence (AI) models. Dubbed Pico-Banana-400K, the dataset contains 4,00,000 real images and their AI-edited counterparts that can be used to train large language models how to handle text-based image editing requests. It is an open-source dataset available with a research-only license, meaning it cannot be used for commercial purposes. Interestingly, the Cupertino-based tech giant's new dataset release comes at a time when it is struggling with native AI models itself.

Apple's Pico-Banana-400K Will Help Others Build Image Editing Models

A research paper titled “Pico-Banana-400K: A Large-Scale Dataset for Text-Guided Image Editing” was published on arXiv, an online journal. The dataset contains roughly 4,00,00 real photo edit pairs, built from OpenImages, organised into a 35-type edit taxonomy and split into single-turn edits, multi-turn sequences and preference pairs.

These design choices matter because they shift the training signal from synthetic, narrowly curated examples to instruction-rich, real-world scenarios that resemble what users actually ask for.

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Pico-Banana-400K was produced by chaining a powerful generative model (Nano Banana) to create edits and another large multimodal model to act as an automated judge, filtering and retrying failed attempts. The result is a dataset emphasising photographic diversity, human-centric scenes and text-heavy shots. The photos also focus on nuance, with long and short instruction pairs to support research work.

Additionally, it also includes negative examples and preference pairs, which are crucial for alignment research and for teaching models not just what to do but what “better” looks like. The paper explicitly documents which edit types are robust (style transfers, global photometric changes) and which remain brittle (precise spatial relocations, text replacement on signs), making it unusually candid about limitations.

The dataset is currently available on GitHub, and can be used for any non-commercial use cases.

Interestingly, Apple has seemingly stalled with the company's in-house AI progress. While it has integrated the Apple Intelligence in more apps and features with the iPhone 17 series launch, the company continues to delay the Siri overhaul which was first announced in 2024.

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Further reading: Apple, AI, Artificial Intelligence

Akash Dutta Email Akash Dutta

Akash Dutta is a Chief Sub Editor at Gadgets 360. He is particularly interested in the social impact of technological developments and loves reading about emerging fields such as AI, metaverse, and fediverse. In his free time, he can be seen supporting his favourite football club - Chelsea, watching movies and anime, and sharing passionate opinions on food. More