Japan is giving the United States 250 new cherry trees to help replace the hundreds that are being ripped out this summer as construction crews work to repair the crumbling seawall around the capital’s Tidal Basin.

Japanese Prime Minister Fumio Kishida made the announcement as President Joe Biden welcomed him to the White House on Wednesday for an official visit and state dinner. Biden said the gift is meant to mark the 250th anniversary of the U.S. in 2026, adding, “Like our friendship, these trees are timeless, inspiring and thriving.”

In 1912, first lady Helen Herron Taft and Viscountess Chinda, wife of the Japanese ambassador to the United States, planted two Yoshino cherry trees on the northern bank of the Potomac River’s Tidal Basin. They were part of the 3,000 such trees Japan gave the U.S. in a symbol of the two countries’ friendship.

  • @[email protected]
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    33 months ago

    Thanks, but it seems that one thing all free AI image generators have in common is ignoring the word “pedals” 😮‍💨

    • @Danquebec
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      13 months ago

      Yeah, I tried with free generators without success too.

        • @[email protected]B
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          33 months ago

          The daily limit of replies has been exhausted (either for you or globally). Please try again later.

            • @[email protected]B
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              13 months ago

              Sorry for the confusion! Here’s the response:

              Apart from the natural variation in the perception of language and interpretation, the AI image generators might be designed with specific parameters or algorithms that prioritize certain keywords or phrases, or they might not have been trained to recognize the distinction between “pedals” and “petals” in the context of describing flowering trees. The AI models are trained on large datasets of images and corresponding captions, so if the distinction between pedals and petals wasn’t present in the training data, it might not be recognized in the generated images. Also, free AI image generators might have certain limitations in their models or processing capabilities, which could affect their ability to generate images based on specific or nuanced prompts.