Rightmove topped the leaderboard in early trade, after its results enthused investors. It saw a 9% uplift in revenues as estate agents upped spend on the portal’s extra services to keep homebuyers engaged. Rightmove is trying to move with the times, by dramatically increasing spend on AI innovations. The scale of the spend, with a bulk of a £60 million investment due to be spent on the technology over the next three years, had caused jitters among shareholders. However, now that revenues are showing some signs of keeping up with the company’s ambitions, it’s helped quell some concerns.
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存量积压与市场饱和已成为不可忽视的结构性因素。2025年，中国酒店市场供给端虽延续扩张，但已逐步进入以存量为主导的运行阶段。，推荐阅读Line官方版本下载获取更多信息
As a data scientist, I’ve been frustrated that there haven’t been any impactful new Python data science tools released in the past few years other than polars. Unsurprisingly, research into AI and LLMs has subsumed traditional DS research, where developments such as text embeddings have had extremely valuable gains for typical data science natural language processing tasks. The traditional machine learning algorithms are still valuable, but no one has invented Gradient Boosted Decision Trees 2: Electric Boogaloo. Additionally, as a data scientist in San Francisco I am legally required to use a MacBook, but there haven’t been data science utilities that actually use the GPU in an Apple Silicon MacBook as they don’t support its Metal API; data science tooling is exclusively in CUDA for NVIDIA GPUs. What if agents could now port these algorithms to a) run on Rust with Python bindings for its speed benefits and b) run on GPUs without complex dependencies?