This document provides an overview of using ChatGPT for intelligent automation through UiPath. It discusses how ChatGPT can be implemented in UiPath using web API activities. It also covers the benefits and limitations of using ChatGPT, as well as best practices for developing ChatGPT models and considerations for privacy, ethics, security and governance. The document concludes with information on UiPath's community resources for learning RPA skills and connecting with other automation professionals.
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5. Introducing ChatGPT
• ChatGPT is a Large language model based on GPT
(Generative Pre-trained Transformer) 3.5 architecture,
which is designed to generate human-like responses to text-
based inputs.
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7. Applications of using GPT models & ChatGPT
Values of using ChatGPT
• Enhanced customer experience.
• Increased efficiency.
• Cost-effective.
• Improved accuracy.
• Personalization.
8. ChatGPT in Digital Transformation
Customer Service
ChatGPT can be used to
provide 24/7 customer
support through a chatbot.
It can assist customers with
their queries, provide
solutions to their problems,
and even help them with
their purchases.
Personalized
Recommendations
ChatGPT can be used to
analyze customer data and
provide personalized
recommendations based on
their preferences, purchase
history, and behavior
patterns
Content Creation
ChatGPT can be used to
generate high-quality
content, such as product
descriptions, blog posts,
and social media posts. It
can save businesses time
and money by
automating the content
creation process
Sales Support
ChatGPT can be used to
assist sales teams by
providing them with
relevant information
about customers and
prospects. It can help
sales reps to close deals
faster and more
efficiently.
Language
Translation
ChatGPT can be used to
translate text from one
language to another in
real-time. This can be
useful for businesses
that operate in multiple
countries or have a
diverse customer base.
9. Limitations of ChatGPT
Bias
Like any other language
model, ChatGPT can be
biased based on the data it
has been trained on. This can
lead to biased responses or
perpetuate stereotypes and
discrimination.
Contextual Understanding
ChatGPT can struggle with
understanding the context of
a conversation, especially
when it comes to sarcasm,
irony, or humor. This can
result in inappropriate or
irrelevant responses.
Lack of Common Sense
ChatGPT lacks common sense
reasoning abilities, which can
limit its ability to understand
certain concepts and make
logical inferences.
Inability to Learn
ChatGPT can't learn on its
own and is only as good as
the data it has been trained
on. It requires continuous
updates and maintenance to
stay relevant.
Limited domain
Knowledge
ChatGPT may not have deep
knowledge in specific
domains, such as medicine or
law, which can affect its
ability to provide accurate
and relevant responses.
Inability to understand
Visuals
ChatGPT is a language model
and cannot understand or
interpret visual cues, which
can limit its ability to
comprehend certain contexts
or situations.
10. ChatGPT for Intelligent Automation
Competitive Advantage of using ChatGPT over other Chatbot models
ChatGPT's natural language processing (NLP)
capabilities are among the most advanced in the
industry, allowing it to understand and generate
human-like responses to a wide variety of questions
and prompts
NLP/NLG capabilities
Large-Scale Training data
Customizable responses
Continuous learning & Fine tuning
Multi-Lingual Support
East Integration
High accuracy
11. ChatGPT for Intelligent Automation
Extracting business value from ChatGPT
More than 13 million users use ChatGPT to support their attended
automations everyday.
Humans are in the driver’s seat even when using ChatGPT to do their
work. Asking the right questions and phrasing the best prompts are
now invaluable skills in a workforce.
Overall, tools like ChatGPT have the potential to improve efficiency
and productivity in a variety of business contexts by automating tasks
that would normally be performed by humans.
However, ChatGPT is still a relatively new technology, and its
capabilities are likely to continue to evolve and improve over time.
12. ChatGPT for Intelligent Automation
Why should you use ChatGPT for your automation?
Data Privacy
ChatGPT is designed to
ensure the privacy of user
data. It follows strict data
privacy regulations and
guidelines and has measures
in place to prevent
unauthorized access or use of
user data.
Ethical AI
ChatGPT is designed to follow
ethical AI principles, including
fairness, transparency, and
accountability. It is trained on
diverse data sets to ensure
that it is not biased towards
specific groups or individuals.
Human Oversight
ChatGPT is to be used in
conjunction with human
oversight and evaluation. This
can help ensure the quality
and accuracy of its output
and prevent inappropriate or
biased responses.
Governance &
Security measures
ChatGPT is designed to follow
strict security measures to
prevent unauthorized access
or use. This includes
measures such as access
controls, encryption, and
regular security audits.
13. ChatGPT for Intelligent Automation
A guide to consider when you’re developing GPT models
Use diverse, relevant, and
unbiased data to train the
model for better
performance.
Select the appropriate version
of GPT model.
Once you have trained your GPT
model, you need to fine-tune it for
your specific use case. Fine-tuning
involves adapting the model to the
domain and style of language used
in your application.
Integrate the trained and
fine-tuned GPT model into
your application.
A chatbot’s success is largely
determined by the user experience
it provides. You should consider
how your chatbot will interact with
users, the tone and style of
responses, and how to handle
difficult or unexpected situations.
Consider how if the
automation you create is
scalable to meet future
demand.
Consider privacy
regulations and
ethical issues
around chatbot
use.
17. Implementing ChatGPT with UiPath
Request Body
Model ID of the model to use
Prompt
The prompt(s) to
generate completions
for, encoded as a
string, array of strings,
array of tokens, or
array of token arrays.
max_tokens
Max number of Model’s
Context length.
Temperature
Sampling temperature
to use.
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