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.
Active and passive voice checker
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"There has to be a better way in line with our history," Isaacman said. "We did not just jump right to Apollo 11. We did it through Mercury, Gemini, and lots of Apollo missions, with a launch cadence every three months. We shouldn't be comfortable with the current cadence. We should be getting back to basics and doing what we know works."
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