The cost of groceries soared following Russia's invasion of Ukraine, which pushed up energy prices. Own-brand products, which make up most of the goods on Aldi and Lidl shelves, now make up more than half of everything shoppers buy, by value.
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In recent years, LLMs have shown significant improvements in their overall performance. When they first became mainstream a couple of years before, they were already impressive with their seemingly human-like conversation abilities, but their reasoning always lacked. They were able to describe any sorting algorithm in the style of your favorite author; on the other hand, they weren't able to consistently perform addition. However, they improved significantly, and it's more and more difficult to find examples where they fail to reason. This created the belief that with enough scaling, LLMs will be able to learn general reasoning.
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This works, but it has a vulnerability: it hardcodes the native code string manually. If fermaw’s integrity check was especially paranoid and compared the spoofed string against the actual native code string retrieved from a trusted reference (say, by calling Function.prototype.toString.call(originalFunction) on a cached copy of the original), the manually crafted string might not match precisely, particularly across different browser versions or platforms where the exact whitespace or formatting of [native code] strings varies slightly.
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