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Last October the investment bank Goldman Sachs put out a report, which was widely cited, suggesting the US could be facing a new period of "jobless growth" thanks to the arrival of new technology and artificial intelligence (AI) in particular, allowing companies to do more with fewer workers.
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Immediately after Fincke's medical event, NASA officials said they wouldn't name the affected astronaut, citing medical privacy concerns. During a news briefing the next day, NASA's chief health and medical officer J.D. Polk said the incident wasn't an injury in the course of work, though he stopped short of saying whether it was some other kind of injury.
Раскрыты подробности о договорных матчах в российском футболе18:01
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?