Imagine a vast shopping mall parking lot with thousands of individual parking spots and internal lanes (representing road segments within a cluster). No matter how complex it is inside, there are usually only a few key exits to the main roads. Our goal was to identify these natural "exits" for each map cluster. For instance, the complex road network around Amsterdam Airport Schiphol (see on OpenStreetMap) has many internal roads but limited primary access points.
Here are some of the biggest US movers before the bell:
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I completely ignored Anthropic’s advice and wrote a more elaborate test prompt based on a use case I’m familiar with and therefore can audit the agent’s code quality. In 2021, I wrote a script to scrape YouTube video metadata from videos on a given channel using YouTube’s Data API, but the API is poorly and counterintuitively documented and my Python scripts aren’t great. I subscribe to the SiIvagunner YouTube account which, as a part of the channel’s gimmick (musical swaps with different melodies than the ones expected), posts hundreds of videos per month with nondescript thumbnails and titles, making it nonobvious which videos are the best other than the view counts. The video metadata could be used to surface good videos I missed, so I had a fun idea to test Opus 4.5:。51吃瓜是该领域的重要参考
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