SPRING 2024

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THE DISTRIBUTOR’S LINK
ERIC DUDAS PROMPT ENGINEERING 101 FOR DISTRIBUTORS from page 86
ChatGPT: “The information I’ve provided about the
“Fully Threaded Radio” podcast is based on my training
data up until April 2023. I don’t search the web or access
live data for information. My responses are generated
from the knowledge I was trained on, which includes a
wide range of sources and data. For the most current and
detailed information, especially for updates or specifics
not covered in my training, consulting direct sources such
as … would be recommended.“
ME: “I’m just wondering if I give you extra information
about the subject, do you then consider it training data
and add it to what you consider your general knowledge?”
ChatGPT: “When you provide extra information
during our conversation, I use that information to tailor
my responses to your questions within the context of our
current interaction. However, I don’t retain or learn from
user inputs in a way that would modify my training data
or update my general knowledge for future interactions.
Each session with me is stateful within the conversation
but doesn’t contribute to a learning process across
conversations.”
ME: “If you don’t have the capability to update
yourself by retaining knowledge, then what do you
consider “machine learning”?”
ChatGPT: ““Machine learning” refers to a subset
of artificial intelligence (AI) where computer algorithms
improve automatically through experience and by using
data. These algorithms build models based on sample or
historical data to make predictions or decisions without
being explicitly programmed to perform the task. Machine
learning involves…”
Chat went on for three lengthy paragraphs with details
about its definition of machine learning. It seems to know
a ton about machine learning. I didn’t teach it any of that.
I pressed the point.
ME: “Part of what you’re saying is contradictory. You
need to be able to assimilate new data, or understanding,
as well as make new connections among data elements
and concepts involving those data. Do you agree?”
Chat’s answer is a little long, but the whole thing is
worth sifting through because it gets to the point:
ChatGPT: “You’re touching on a nuanced aspect of
how AI and machine learning models operate, and I see
where the confusion might come from. Let me clarify:
[1] Learning Phase: During the training phase,
machine learning models, including large language models
like me, assimilate new data, understand patterns, and
make connections among data elements and concepts.
This is when the model “learns” from vast datasets. It
adjusts its internal parameters to minimize errors in its
predictions or outputs based on the input it receives.
This process is iterative and involves going over the
training data multiple times to improve accuracy and
understanding.
[2] Deployment Phase: Once the model is deployed,
as in the case with me in this interactive setting, it
operates based on the state it was in at the end of its
last training phase. In this phase, the model does not
continue to learn from new data or interactions. Instead,
it applies the patterns, relationships, and knowledge it
acquired during training to answer questions and engage
in conversations. The model can make connections based
on its training but does not assimilate new information
or adjust its understanding based on interactions postdeployment.
So, while I’m capable of “making new connections
among data elements and concepts” based on my
training, I do not assimilate new data or update my
understanding in real-time during user interactions. Any
learning or assimilation of new information would occur
during a subsequent training phase conducted by the
developers, not dynamically during deployment.
The distinction is between the model’s capability to
apply learned knowledge (which I can do) and the ability
to update its knowledge base in real-time based on new
data (which I cannot do post-deployment). This ensures
consistency and reliability in responses but also means
the model’s knowledge is fixed as of its last update and
does not include new information or changes that occur
after that point.”
It refers to itself in the first person, and then to
the model, which it considers itself to be a part of. But
it refers to the model in the third person. Is it trying to
confuse me on purpose? I don’t recall HAL ever doing this.
CONTINUED ON PAGE 129