Not sure about all its filters being RL. Sometimes it seems to flag its output as inappropriate because of a single word (or none at all). Also it has asymmetric behavior, e.g. it will make a joke about men but refuse to make one about women
How does GPT obtain its ability? Tracing emergent abilities of language models
21–30 of 205 posts
Re: How does GPT obtain its ability? Tracing emergent abilities of language models
#22Earlier quoted context omitted.
Current GPT version is not very good at math, and it's not at all clear whether this can be fixed within a language model. Q: I have 2 cats and 1 horse. How many legs do they have in total? A: If you have two cats and one horse, then the total number of legs they have is 8. Cats typically have four legs, while horses have four legs as well. So two cats would have a total of 8 legs, and when you add the four legs of t…
I've found it gets the math right most of the time in stories. For example: > Write a story about a veterinarian counting the number of total legs on two cats and a horse. He reports the total number of legs to his assistant so he can write them down. As the veterinarian entered the examination room, he was greeted by two playful cats and a majestic horse. He smiled and began his examination, carefully checking the h…
Fucking amazing.
Re: How does GPT obtain its ability? Tracing emergent abilities of language models
#23Imagine Wolfram's system with GPT integrated. I hope they're working on that.
Current GPT version is not very good at math, and it's not at all clear whether this can be fixed within a language model. Q: I have 2 cats and 1 horse. How many legs do they have in total? A: If you have two cats and one horse, then the total number of legs they have is 8. Cats typically have four legs, while horses have four legs as well. So two cats would have a total of 8 legs, and when you add the four legs of t…
These errors are common and important to note. Though what I find fascinating is how often I can prompt engineer around these errors by telling GPT to just be smarter and think more carefully. Just tried the following for instance.
Q: You are a master logician, who can solve all manner of language problems and have excellent math skills. I have 2 cats and 1 horse. How many legs do they have in total? Show your reasoning and calculations step-by-step
A: As a master logician, I can tell you that the total number of legs possessed by two cats and one horse can be found by using basic arithmetic. Here's how:
First, we know that each cat has four legs, because all cats have four legs. This means that the two cats together have 2 x 4 = 8 legs.
Next, we know that a horse has four legs, because all horses have four legs. This means that the horse has an additional 4 legs.
Finally, we can add the number of legs possessed by the two cats and the horse together to find the total number of legs. This is done by adding 8 + 4 = 12 legs.
Therefore, the total number of legs possessed by two cats and one horse is 12 legs. I hope this helps! Let me know if you have any other questions.
Re: How does GPT obtain its ability? Tracing emergent abilities of language models
#24Imagine Wolfram's system with GPT integrated. I hope they're working on that.
Current GPT version is not very good at math, and it's not at all clear whether this can be fixed within a language model. Q: I have 2 cats and 1 horse. How many legs do they have in total? A: If you have two cats and one horse, then the total number of legs they have is 8. Cats typically have four legs, while horses have four legs as well. So two cats would have a total of 8 legs, and when you add the four legs of t…
I tripped it up with a somewhat ambiguous question using pirates.
Q: There are two boats in the ocean. One boat has 11 regular sailors. The second boat has 8 pirates. A pirate is defined as a human being where one of their legs is made of wood. How many real human legs are there in total among the two ships? Explain your reasoning.
A: There are 11 regular sailors on one boat and eight pirates on the other boat, for a total of 11 + 8 = >19 people.
Since a pirate has one wooden peg leg, there are 8 wooden peg legs among the group of pirates. Since a wooden peg leg is not a human leg, the total number of human legs among the group of pirates is 8 - 1 = >7.
In total, there are 11 + 7 = >18 human legs among the two boats. This is because the 11 regular sailors each have two human legs, and the group of pirates has a total of 7 human legs.
Once I was far more explicit in explaining the logic however it was able to get it correct:
Q: There are 2 boats in the ocean. One boat has 11 regular sailors. The second boat has 8 pirates. Sailors always have two legs. Pirates always have one leg because the other one is made of wood. How many real human legs are there in total among the two ships? Explain your reasoning.
A: There are 11 regular sailors on one boat and eight pirates on the other boat, for a total of 11 + 8 = >19 people.
Since a sailor always has two human legs, there are 11 * 2 = 2=22>>22 human legs among the group of sailors.
Since a pirate always has one human leg and one wooden peg leg, there are 8 1 = >8 human legs among the group of pirates.
In total, there are 22 + 8 = >30 human legs among the two boats. This is because the 11 regular sailors each have two human legs, and the group of pirates has a total of 8 human legs.
Re: How does GPT obtain its ability? Tracing emergent abilities of language models
#25Earlier quoted context omitted.
Current GPT version is not very good at math, and it's not at all clear whether this can be fixed within a language model. Q: I have 2 cats and 1 horse. How many legs do they have in total? A: If you have two cats and one horse, then the total number of legs they have is 8. Cats typically have four legs, while horses have four legs as well. So two cats would have a total of 8 legs, and when you add the four legs of t…
These errors are common and important to note. Though what I find fascinating is how often I can prompt engineer around these errors by telling GPT to just be smarter and think more carefully. Just tried the following for instance. Q: You are a master logician, who can solve all manner of language problems and have excellent math skills. I have 2 cats and 1 horse. How many legs do they have in total? Show your reason…
That's interesting. It seems it's not great at raw calculation, but if you ask it to explain its reasoning, it derives steps from previous results, and arrives at the correct answer. It's similar to the sibling comment about asking it to tell a story.
Re: How does GPT obtain its ability? Tracing emergent abilities of language models
#26Amazing insight, particularly section 6. "- The two important but different abilities of GPT-3.5 are *knowledge* and *reasoning*. Generally, it would be ideal if we could *offload the knowledge part to the outside retrieval system and let the language model only focus on reasoning.* This is because: - The model’s internal knowledge is always cut off at a certain time. The model always needs up-to-date knowledge to an…
The problem with ChatGPT's "knowledge" is that it isn't trustworthy. It will happily output very confident sounding nonsense, or blatantly incorrect statements. We need a way to verify how accurate it's outputs are
I just had a run in with this yesterday. I asked it to explain box embeddings. It's a pretty niche topic so I didn't expect it to give the right answer. But the answer it gave sounded so confident but it was so wrong. It took a not al vector embeddings approach but replaced that with box. I tried correcting it but it refused to budge and still sounded confident.
Re: How does GPT obtain its ability? Tracing emergent abilities of language models
#27Amazing insight, particularly section 6. "- The two important but different abilities of GPT-3.5 are *knowledge* and *reasoning*. Generally, it would be ideal if we could *offload the knowledge part to the outside retrieval system and let the language model only focus on reasoning.* This is because: - The model’s internal knowledge is always cut off at a certain time. The model always needs up-to-date knowledge to an…
The problem with ChatGPT's "knowledge" is that it isn't trustworthy. It will happily output very confident sounding nonsense, or blatantly incorrect statements. We need a way to verify how accurate it's outputs are
Whose knowledge is trustworthy? We've somehow come to associate certain institutions or scientific authorities with truth when that is about the furthest from real science:
"Have no respect whatsoever for authority; forget who said it and instead look what he starts with, where he ends up, and ask yourself, Is it reasonable?" -Richard P. Feynman
"One of the great commandments of science is, "Mistrust arguments from authority." -Carl Sagan
"In questions of science, the authority of a thousand is not worth the humble reasoning of a single individual." -Galileo Galilei
Re: How does GPT obtain its ability? Tracing emergent abilities of language models
#28[deleted]
Re: How does GPT obtain its ability? Tracing emergent abilities of language models
#29Earlier quoted context omitted.
The problem with ChatGPT's "knowledge" is that it isn't trustworthy. It will happily output very confident sounding nonsense, or blatantly incorrect statements. We need a way to verify how accurate it's outputs are
ChatGPT made this nice COBOL program to create an S3 Bucket,a technical impossibility... IDENTIFICATION DIVISION. PROGRAM-ID. CREATE-S3-BUCKET. ENVIRONMENT DIVISION. CONFIGURATION SECTION. INPUT-OUTPUT SECTION. DATA DIVISION. FILE SECTION. WORKING-STORAGE SECTION. 01 AWS-ACCESS-KEY PIC X(20). 01 AWS-SECRET-KEY PIC X(40). 01 BUCKET-NAME PIC X(255). PROCEDURE DIVISION. CREATE-BUCKET. MOVE AWS-ACCESS-KEY TO AWS-ACCESS-K…
How is that impossible? Plenty of libraries are available for COBOL, especially if you use COBOL.NET
Re: How does GPT obtain its ability? Tracing emergent abilities of language models
#30Earlier quoted context omitted.
The problem with ChatGPT's "knowledge" is that it isn't trustworthy. It will happily output very confident sounding nonsense, or blatantly incorrect statements. We need a way to verify how accurate it's outputs are
Whose knowledge is trustworthy? We've somehow come to associate certain institutions or scientific authorities with truth when that is about the furthest from real science: "Have no respect whatsoever for authority; forget who said it and instead look what he starts with, where he ends up, and ask yourself, Is it reasonable?" -Richard P. Feynman "One of the great commandments of science is, "Mistrust arguments from a…
There is some kind of recursion in here with authors names and "have no respect..." part:)