秘鲁今天的现实同样提醒我们，制度信任不是通过口号能够建立的，它需要稳定、清晰的权力边界和长期一致的规则。秘鲁的困境正在于此，它不是没有产权，而在没有稳定保护产权的制度。1990年代向前一步，2016年后却步步后退。市场还在，但法治不稳；产权有形，但安全无感。企业家既看不清明天的政府，也看不清明年的政府，更无法判断政策与资产是否安全。在这样的环境下，再完美的产权制度，也可能沦为一纸空文。
“It is certainly not good for investment,” Smeaton tells me, with the wry understatement common to Scots. “Or for the U.S. consumer. They are paying higher prices.” MorphCostume’s outfits now cost 9% more, after Smeaton’s business was hit by a $3 million duty bill.
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A decade after a new constitution promised a fresh start, many young people say those hopes remain unmet. By some estimates, about one in five young Nepalis is out of work.
Many people reading this will call bullshit on the performance improvement metrics, and honestly, fair. I too thought the agents would stumble in hilarious ways trying, but they did not. To demonstrate that I am not bullshitting, I also decided to release a more simple Rust-with-Python-bindings project today: nndex, an in-memory vector “store” that is designed to retrieve the exact nearest neighbors as fast as possible (and has fast approximate NN too), and is now available open-sourced on GitHub. This leverages the dot product which is one of the simplest matrix ops and is therefore heavily optimized by existing libraries such as Python’s numpy…and yet after a few optimization passes, it tied numpy even though numpy leverages BLAS libraries for maximum mathematical performance. Naturally, I instructed Opus to also add support for BLAS with more optimization passes and it now is 1-5x numpy’s speed in the single-query case and much faster with batch prediction. 3 It’s so fast that even though I also added GPU support for testing, it’s mostly ineffective below 100k rows due to the GPU dispatch overhead being greater than the actual retrieval speed.