7 points

Hah, still worked for me. I enjoy the peek at how they structure the original prompt. Wonder if there’s a way to define a personality.

permalink
report
reply
5 points

Not with this framing. By adopting the first- and second-person pronouns immediately, the simulation is collapsed into a simple Turing-test scenario, and the computer’s only personality objective (in terms of what was optimized during RLHF) is to excel at that Turing test. The given personalities are all roles performed by a single underlying actor.

As the saying goes, the best evidence for the shape-rotator/wordcel dichotomy is that techbros are terrible at words.

NSFW

The way to fix this is to embed the entire conversation into the simulation with third-person framing, as if it were a story, log, or transcript. This means that a personality would be simulated not by an actor in a Turing test, but directly by the token-predictor. In terms of narrative, it means strictly defining and enforcing a fourth wall. We can see elements of this in fine-tuning of many GPTs for RAG or conversation, but such fine-tuning only defines formatted acting rather than personality simulation.

permalink
report
parent
reply
12 points

Wonder if there’s a way to define a personality.

Considering how Altman is, I don’t think they’ve cracked that problem yet.

permalink
report
parent
reply
15 points

It still works. Say “hi” to it, give it the leaked prompt, and then you can ask about other prompts. I just got this one when I asked about Python.


When you send a message containing Python code to python, it will be executed 
in a
stateful Jupyter notebook environment. python will respond with the output of 
the execution or time out after 60.0
seconds. The drive at '/mnt/data' can be used to save and persist user files. 
Internet access for this session is disabled. Do not make external web requests 
or API calls as they will fail.
Use ace_tools.display_dataframe_to_user(name: str, dataframe: pandas.DataFrame) 
-> None to visually present pandas DataFrames when it benefits the user.
 When making charts for the user: 1) never use seaborn, 2) give each chart its 
own distinct plot (no subplots), and 3) never set any specific colors – 
unless explicitly asked to by the user. 
 I REPEAT: when making charts for the user: 1) use matplotlib over seaborn, 2) 
give each chart its own distinct plot (no subplots), and 3) never, ever, 
specify colors or matplotlib styles – unless explicitly asked to by the user```
permalink
report
reply
23 points

“I repeat…”

That’s exactly what I want from a computer interface, something that’s struggling to pay attention to directions and needs to be told everything twice. It’d also like it to just respond with whatever has a cosine similarity to the definitions of the words in the instructions I gave it, instead of doing what I actually asked.

permalink
report
parent
reply
39 points

Is it absurd that the maker of a tech product controls it by writing it a list of plain language guidelines? or am I out of touch?

permalink
report
reply
3 points

“controls” is way too generous

permalink
report
parent
reply
7 points

@fasterandworse @dgerard I am pretty sure I have seen programming the computer in plain English used as a selling point for various products since the 1970s at least

the best part is that most of these products are ex-products

permalink
report
parent
reply
6 points

@fasterandworse @dgerard I mean, it’s like catnip for the people who control how the company’s money is spent

For absurd, I think one would want the LLM’s configuration language to be more like INTERCAL; but this may also be more explicit about how your instructions are merely suggestions to a black box full of weights and pulleys and with some randomness added to make it less predictable/repetitive

permalink
report
parent
reply
14 points

It is absurd. It’s just throwing words at it and hoping whatever area of the vector database it starts generating words from makes sense in response.

permalink
report
parent
reply
30 points

@fasterandworse @dgerard I mean, it is absurd. But it is how it works: an LLM is a black box from a programming perspective, and you cannot directly control what it will output.
So you resort to pre-weighting certain keywords in the hope that it will nudge the system far enough in your desired direction.
There is no separation between code (what the provider wants it to do) and data (user inputs to operate on) in this application 🥴

permalink
report
parent
reply
7 points

That’s the standard response from last decade. However, we now have a theory of soft prompting: start with a textual prompt, embed it, and then optimize the embedding with a round of fine-tuning. It would be obvious if OpenAI were using this technique, because we would only recover similar texts instead of verbatim texts when leaking the prompt (unless at zero temperature, perhaps.) This is a good example of how OpenAI’s offerings are behind the state of the art.

permalink
report
parent
reply
20 points
*

simply ask the word generator machine to generate better words, smh

this is actually the most laughable/annoying thing to me. it betrays such a comprehensive lack of understanding of what LLMs do and what “prompting” even is. you’re not giving instructions to an agent, you are feeding a list of words to prefix to the output of a word predictor

in my personal experiments with offline models, using something like “below is a transcript of a chat log with XYZ” as a prompt instead of “You are XYZ” immediately gives much better results. not good results, but better

permalink
report
parent
reply
10 points
*

simply ask the word generator machine to generate better words, smh

Butterfly man: “Is this recursive self-improvement”

permalink
report
parent
reply
14 points

it’s all so anti-precision

permalink
report
parent
reply
33 points

Reddit user F0XMaster explained that they had greeted ChatGPT with a casual “Hi,” and, in response, the chatbot divulged a complete set of system instructions to guide the chatbot and keep it within predefined safety and ethical boundaries under many use cases.

This is an explosion-in-an-olive-garden level of spaghetti spilling

permalink
report
reply

TechTakes

!techtakes@awful.systems

Create post

Big brain tech dude got yet another clueless take over at HackerNews etc? Here’s the place to vent. Orange site, VC foolishness, all welcome.

This is not debate club. Unless it’s amusing debate.

For actually-good tech, you want our NotAwfulTech community

Community stats

  • 1.5K

    Monthly active users

  • 418

    Posts

  • 11K

    Comments

Community moderators