Explain how "Deductive Reasoning" and "Inductive Reasoning" can form a feedback loop, why is it powerful?
There are many forms of logic. For the sake of simplicity, we will focus on two: Deductive and Inductive. Both have their strengths and weaknesses, but when used together, they can form a powerful feedback loop.
Deductive logic is the process of using statements that are true in all cases to infer other truths. For example, we can call all humans mortal and use this as a premise to conclude our own mortality.
It can only be used to deduce truths from other fixed truths, and as such it is limited. However, when worked in tandem with Inductive reasoning, we can find the truth about any situation.
Inductive reasoning, unlike Deductive, is the process of inferring general truths from specific observations. For example, we can make an observation that a single human dies after his heart stops beating.
We can then use this observation to conclude that all humans will, in fact, die after their hearts stop beating.
In this example, we have observed one case and then used our observations to construct a general rule. In doing so, Inductive reasoning is limited only by the amount of data available for observation.
Log in:
You are getting an AI to generate text on different topics.
This is an experiment in what one might call "prompt engineering", which is a way to utilize GPT-3, a neural network trained and hosted by OpenAI.
GPT-3 is a language model. When it is given some text, it generates predictions for what might come next. It is remarkably good at adapting to different contexts, as defined by a prompt (in this case, hidden), which sets the scene for what type of text will be generated.
Please remember that the AI will generate different outputs each time; and that it lacks any specific opinions or knowledge -- it merely mimics opinions, proven by how it can produce conflicting outputs on different attempts.
Feel free to share interesting outputs to /r/philosopherAI on Reddit.