Jason Corkill

jasoncorkill

AI & ML interests

Human data annotation

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replied to their post about 21 hours ago
reacted to their post with ❀️πŸ”₯πŸš€ 13 days ago
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3227
πŸš€ We tried something new!

We just published a dataset using a new (for us) preference modality: direct ranking based on aesthetic preference. We ranked a couple of thousand images from most to least preferred, all sampled from the Open Image Preferences v1 dataset by the amazing @data-is-better-together team.

πŸ“Š Check it out here:
Rapidata/2k-ranked-images-open-image-preferences-v1

We're really curious to hear your thoughts!
Is this kind of ranking interesting or useful to you? Let us know! πŸ’¬

If it is, please consider leaving a ❀️ and if we hit 30 ❀️s, we’ll go ahead and rank the full 17k image dataset!
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replied to their post 13 days ago
posted an update 13 days ago
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3227
πŸš€ We tried something new!

We just published a dataset using a new (for us) preference modality: direct ranking based on aesthetic preference. We ranked a couple of thousand images from most to least preferred, all sampled from the Open Image Preferences v1 dataset by the amazing @data-is-better-together team.

πŸ“Š Check it out here:
Rapidata/2k-ranked-images-open-image-preferences-v1

We're really curious to hear your thoughts!
Is this kind of ranking interesting or useful to you? Let us know! πŸ’¬

If it is, please consider leaving a ❀️ and if we hit 30 ❀️s, we’ll go ahead and rank the full 17k image dataset!
Β·
reacted to their post with πŸ”₯πŸ‘€πŸš€ 15 days ago
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3039
πŸ”₯ Yesterday was a fire day!
We dropped two brand-new datasets capturing Human Preferences for text-to-video and text-to-image generations powered by our own crowdsourcing tool!

Whether you're working on model evaluation, alignment, or fine-tuning, this is for you.

1. Text-to-Video Dataset (Pika 2.2 model):
Rapidata/text-2-video-human-preferences-pika2.2

2. Text-to-Image Dataset (Reve-AI Halfmoon):
Rapidata/Reve-AI-Halfmoon_t2i_human_preference

Let’s train AI on AI-generated content with humans in the loop.
Let’s make generative models that actually get us.
posted an update 15 days ago
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3039
πŸ”₯ Yesterday was a fire day!
We dropped two brand-new datasets capturing Human Preferences for text-to-video and text-to-image generations powered by our own crowdsourcing tool!

Whether you're working on model evaluation, alignment, or fine-tuning, this is for you.

1. Text-to-Video Dataset (Pika 2.2 model):
Rapidata/text-2-video-human-preferences-pika2.2

2. Text-to-Image Dataset (Reve-AI Halfmoon):
Rapidata/Reve-AI-Halfmoon_t2i_human_preference

Let’s train AI on AI-generated content with humans in the loop.
Let’s make generative models that actually get us.
reacted to their post with πŸ‘πŸš€ 21 days ago
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2730
We benchmarked @xai-org 's Aurora model, as far as we know the first public evaluation of the model at scale.

We collected 401k human annotations in over the past ~2 days for this, we have uploaded all of the annotation data here on huggingface with a fully permissive license
Rapidata/xAI_Aurora_t2i_human_preferences
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reacted to their post with πŸš€πŸ§ πŸ‘€β€οΈ 21 days ago
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4663
Runway Gen-3 Alpha: The Style and Coherence Champion

Runway's latest video generation model, Gen-3 Alpha, is something special. It ranks #3 overall on our text-to-video human preference benchmark, but in terms of style and coherence, it outperforms even OpenAI Sora.

However, it struggles with alignment, making it less predictable for controlled outputs.

We've released a new dataset with human evaluations of Runway Gen-3 Alpha: Rapidata's text-2-video human preferences dataset. If you're working on video generation and want to see how your model compares to the biggest players, we can benchmark it for you.

πŸš€ DM us if you’re interested!

Dataset: Rapidata/text-2-video-human-preferences-runway-alpha
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