Terbenam in english - Turing Bletchley: A Universal Image Language Representation model by Microsoft
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T-Bletchley is unique in that the system can do image retrieval from just the encoded image vectors and does not use any text metadata.
There are obviously specific signs for many words available in sign language that are more appropriate for daily usage.
We vectorized the input queries for text-to-image with the text encoder and for image-to-image with the image encoder.
Even before fine-tuning, T-Bletchley significantly outperforms previous models.
To achieve universality, we trained the model on a parallel corpus of 500 million translation pairs.
In the first example, T-Bletchley understands that the text in the image is about the differences between microeconomics and macroeconomics and retrieves similar slides.
Mitigating negative effects from these biases is a difficult, industry-wide issue and Microsoft is committed to the advancement and use of AI grounded in principles that put people first and benefit society.
Turing Bletchley: A Universal Image Language Representation model by Microsoft
Images and captions were independently encoded, and the model was then trained by applying a contrastive loss on the generated image and text vectors.
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