Such a public battle could have left everyone involved bruised. But investors seem to have decided that no one lost, rewarding all three companies. Least surprising was the 12% leap in Netflix’s stock price on news of the deal. Wall Street had thought all along that WBD was an overpriced acquisition. (Netflix would have paid $83 billion to WBD.) Investors were glad to see the streamer put aside its ambition of owning the traditional Hollywood studio. As for WBD itself, investors clearly felt Paramount was paying a decent price for the entire company. On news of the deal, WBD stock barely budged; it was almost exactly where it had been in December when the whole fray began.
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?
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In a filing to the supreme court of Nepal, Khapung later denied responsibility, and Nepal Police told the BBC that the decision to give the order to fire was made by the committee that Rijal headed up. In a letter, the force said that Khapung "did not issue the order to use force ahead of the committee's decision".，更多细节参见Line官方版本下载
“中国一強”「レアアース」 日本の戦略に密着取材