Show HN: I made a cheap alternative to college-level math & physics tutoring

Neural networks are a connectionist approach to cognition that is roughly similar to how our brains operate. Humans make mistakes. We're not perfect. We ask someone for advice and they may confabulate some things, but get the gist of it right. A senior developer will write some code, try it out, find a bug, fix it, try it again, etc. We don't develop a fully working operating system kernel on our first attempt.

Chain of thought prompting increases LLM output accuracy significantly as that is how you get an LLM to "think" about its output, check its output for errors, or backtrack and try another strategy. With the current one-token-at-a-time approach it can only "think" when generating each token.

Next generation models could integrate this iterative and branching cognitive process in the algorithm.

> After the hype dies down a bit, we'll likely have a better understanding of what advances in this field we really have.

LLMs can already do many natural language processing tasks more accurately and competently than the vast majority of humans. Transformers were originally designed for translation. (GPT is a transformer that knows many languages.)

BTW I tried the blue sun question with Chat GPT 3.5 and it easily figured out the Mars solution after I suggested that I may not be standing on Earth.

"Several celestial bodies outside of Earth could potentially exhibit conditions where the Sun might appear blue or have a bluish hue. Here are a few examples:

Mars: Mars has a thin atmosphere composed mostly of carbon dioxide, with traces of other gases. While the Martian atmosphere is not as dense as Earth's, it can still scatter sunlight, and under certain conditions, it might give the Sun a slightly bluish appearance, especially during sunrise or sunset.

Titan (Moon of Saturn): Titan has a thick atmosphere primarily composed of nitrogen, with traces of methane and other hydrocarbons. Although Titan's atmosphere is much denser than Earth's, its composition and haze layers could potentially scatter light in a way that gives the Sun a bluish hue, particularly when viewed from the surface.

..."

You literally have to tell it to think about what it is saying and to think of all of the possibilities iteratively. That is chain of thought prompting.

GPT-3.5 figures out the correct solution on first response:

"I am standing outside and observing the sun directly without goggles or filtering of any kind. The sun appears to be a shade of blue.

Where could I be standing? Think through all of the possibilities. After stating a list of possibilities, examine your response, and think of additional possibilities that are less realistic, more speculative, but scientifically plausible."

The idiots in the US Department of Education decided that correspondence courses were not worth as much as distance learning courses. They decided the difference between correspondence courses and distance learning courses was that in distance learning courses the instructor initiated (real-time) regular and substantive interaction with the students. This means that if your students can take the class entirely online and never have questions because of the excellent materials, then your school gets penalized by getting almost no money for online courses. If you sabotage your online materials so badly that students have to sit through painful, multi-hour video chats with annoying instructors, then your school get the big bucks.

The US Department of Education has destroyed online education through gross incompetence and blind rule following.