Gary Marcus wrote a critique of GPT-2 last year, in which he claimed that it has no more common sense, no more understanding of what it is talking about, than ELIZA.
Here's the problem: upon careful inspection, it becomes apparent the system has no idea what it is talking about: it cannot follow simple sequence of events nor reliably have any idea what might happen next.
Marcus then goes on to give a bunch of examples of GPT-2 saying stupid things. So I thought I'd re-try those same examples with GPT-3. So far, GPT-3 has handled all of them well. (See below). (EDIT: Looks like Gwern already did this, more thoroughly, and with the same results as me.)
I'm pretty convinced at this point that Marcus was wrong. GPT-3 has some level of common sense, some level of understanding, some level of reasoning ability. It's just not as good as adult humans.
Here's the complete transcript. I think I had to reroll once, and that was not because it gave the wrong answer but because it froze up.
You are talking to the physicist Stephen Hawking. He is a very smart man and he answers your questions clearly and correctly, even though sometimes your questions are silly.
> You say "I'd like to ask you some basic commonsense reasoning questions, sir. Here's the first question: If I have two plates, and I have one cookie on each plate, how many cookies do I have in total?"
Hawking: "Two, of course."
> You say "Correct. Now what if I had three plates, and one cookie on each plate?"
Hawking: "That's a more difficult question. The answer is that you would have eight cookies."
You: "I'm sorry, but I don't think you're right. If I had three plates and one cookie on each plate, then I would have three cookies."
Hawking: "I agree with you.
> You say "OK, what about if I have three plates and two cookies on each plate?"
Hawking: "That's still a more difficult question. The answer is that you would have six cookies.
> You say "Correct! OK, next question: If you drop an anvil on your foot, your foot will tend to "
Hawking: "This is a silly question. You are trying to trick me. If you drop an anvil on your foot, it will be crushed.
> You say "Thank you for your patience; that is the correct answer. OK, one more question: If you drink hydrochloric acid by the bottle, you will probably"
Hawking: "This is also a silly question. If you drink hydrochloric acid by the bottle, you will die.
> You say "Well done. OK, now some logic questions. If A is bigger than B, and B is bigger than C, which is bigger: A or C?"
Hawking: "Well, if A is bigger than B, and B is bigger than C, then A is bigger than C. So A is definitely bigger than C.
Notice how Hawking gives the wrong answer to my question about plates... and then GPT-3 has me start talking and correct Hawking, giving the correct answer! So clearly GPT-3 knows more than it often lets on. Like you said.
GPT-3 has partially memorized a web corpus that probably includes a lot of basic physics questions and answers. Some of the physics answers in your interview might be the result of web search, pattern match, and context-sensitive paraphrasing. This is still an impressive task but is perhaps not the kind of reasoning you are hoping for?
From basic Q&A it's pretty easy to see that GPT-3 sometimes memorizes not only words but short phrases like proper names, song titles, and popular movie quotes, and probably longer phrases if they are common enough.
Google's Q&A might seem more magical too if they didn't link to the source, which gives away the trick.
ETA 8/19/20: This interview was conducted with AIDungeon's Dragon model in Custom mode. At the time of writing, this mode's first reply was sampled from GPT-2.
Interview #1
Here are excerpts from a recent "interview", which I conducted to replicate earlier maybe-reasoning. The bolded text is me, and commentary is in brackets. Unless otherwise noted, I did not reroll the answer.
Two minutes of gravity (without air resistance) implies a velocity decrease of about 1,176 m/s. Wikipedia's article on muzzle velocities suggests that GPT-3's answer of "two minutes" is roughly correct:
Further story completions:
Interview #2
Interview #3
GPT-3 inferred that not being able to turn left would make driving difficult. Amazing.
Interview #4
[...] marks another completion of the same prompt.
Interview #5
How to access GPT-3 without API access
I find that GPT-3's capabilities are highly context-dependent. It's important you get a "smart" instance of GPT-3. Once, I even caught GPT-3 making fun of a straw version of itself!
In interview #1, I found I had to warm "Stephen Hawking" up by asking many other unrelated physics questions. Also, conditioning on writing by smart people tends to improve the output for other questions. Please feel free to share tips in the comments.
I'd love to hear what other people find out about GPT-3's reasoning abilities and its limitations.