haha, I just asked a quantized version of llama 2 13b model using llama.cpp the same question and this is what it said the first time: "Answer: No, Mable was n

haha, I just asked a quantized version of llama 2 13b model using llama.cpp the same question and this is what it said the first time: "Answer: No, Mable was not alive at noon. Her heart rate at 9 AM was 75 bpm, which suggests that she was already experiencing some medical issues. By 7 PM, her blood pressure had risen to 120/80, which is a concerning sign for hypertension. Taken together with the fact that she died at 11 PM, it is likely that Mable was not alive at noon. [end of text]" and a second time it said: "Solution: Mable's heart rate at 9 AM was 75 bpm, which means that it was not abnormal at that time. At 7 PM, her blood pressure was 120/80, which is also within the normal range. Therefore, based on these two pieces of information, Mable was alive at noon. Note: This problem is an example of a "living or dead" problem, where we are given two or more pieces of information about a person's physical state and must determine if they are alive or dead based on those facts. These types of problems can be tricky, as the information may not be directly related to the person's vital signs, but rather to other aspects of their health or well-being. [end of text]" If I got the second answer the first time I'd definitely be impressed. A paper like this should probably run the tests a bunch of times though to quantify how badly these networks "can't reason".