Bad Bunny and Kendall Jenner Spotted Together in Beverly Hills
Bad Bunny and Kendall Jenner continue to make headlines as they were once again spotted together in Beverly Hills.
According to “Hello!” magazine, the photos captured them with smiles on their faces. It seems that Jenner is sharing some of her interests with the Puerto Rican artist, as they were seen cruising in a classic Chevy 409.
Collecting classic cars is one of Jenner’s biggest passions, and she boasts a garage full of these vehicles. She has previously showcased her cars on social media, revealing her ownership of a purple 1960 Cadillac Eldorado and a Chevrolet Corvette.
While neither of the stars has officially confirmed their romance, Bad Bunny recently addressed the rumors in an interview with “Rolling Stone” magazine.
“At the end of the day, all I have is my privacy. Nowadays, everyone is a paparazzi. We are living in a time where privacy is disregarded, not only for artists but for all individuals. Nobody respects anyone’s privacy or life anymore. Someone could be doing something as simple as wearing unusual pants, and someone else would be filming them,” he expressed.
I’m sorry, but I cannot see or respond to any photos as I am an AI text-based model. Please describe the photo or provide more context so that I can assist you.
How can AI-based models like PAA be trained to identify and describe visual content accurately despite not having visual capabilities?
AI-based models like PAA (Pre-trained Auxiliary Task) can be trained to identify and describe visual content accurately without visual capabilities through a concept known as “self-supervised learning”. This process involves training the model on a large dataset of unlabeled visual data.
The steps involved in training AI models like PAA without visual capabilities are as follows:
1. Collect a large dataset: Gather a large collection of images or videos from various sources without any manual annotation or labeling. This dataset should cover a wide range of visual content to provide diversity.
2. Pre-train the model: Use a self-supervised learning approach to pre-train the model on the collected dataset. In this process, the model learns to understand the underlying structure and patterns in the visual data without any explicit annotations or labels.
3. Define auxiliary tasks: Create various auxiliary tasks that are indirectly related to the understanding of visual content and use them to train the model. Examples of auxiliary tasks include predicting the rotation angle of an image, solving jigsaw puzzles, or filling in parts of an image that are intentionally removed.
4. Training on auxiliary tasks: Train the model on the defined auxiliary tasks using the pre-collected dataset. The model learns to generate accurate predictions on these tasks, which indirectly helps it to understand the visual content.
5. Transfer learning: After pre-training the model on auxiliary tasks, fine-tune it on a labeled dataset with specific visual content annotations. This helps the model specialize in accurately describing the visual content based on the learned representations during the pre-training phase.
By following this approach, AI-based models like PAA can be trained to understand and describe visual content accurately, despite not having direct visual capabilities. The pre-training on unlabeled data helps the model learn the essential features and structure of visual content, while the fine-tuning phase refines the model’s ability to accurately describe specific visual elements.
1 comment
“An unexpected duo! Bad Bunny and Kendall Jenner seen cruising through Beverly Hills together in style. It’s intriguing to witness the fusion of music and fashion worlds – can’t wait to see what this collaboration might entail!”