The document introduces Einstein GPT, the first generative AI for CRM. It begins with an agenda that outlines discussing essential AI terminology, what generative AI is, how CRM can use generative AI, and Einstein GPT. It then defines key AI concepts like artificial intelligence, neural networks, deep learning, natural language processing, generators, transformers, large language models, and generative pre-trained transformers. It explains that generative AI can quickly generate new content based on inputs. For CRM, generative AI can personalize emails, product descriptions, marketing pages, and customer service replies to make CRM more powerful.

1. Einstein GPT- World’s
First Generative AI for
CRM
Anmol Verma
Email- v.anmol.verma@gmail.com
Twitter-@anmol_verma__c

2. Kailash Chandra
Salesforce Project Manager@Webkul,
Group Leader, Salesforce Admin Group,
Dehradun
Anmol Verma
Associate Technical Consultant
Salesforce.com Pvt. Ltd.

3. Agenda
● Essential Terminology of AI
● What is Generative AI?
● CRM with Generative AI
● Einstein GPT
● Open Talk/Q&A

4. Essential Terminology
● Artificial Intelligence
● Neural Networks
● Deep Learning
● Natural Language Processing(NLP)
● Generator
● Transformer
● Large Language Model (LLM)
● Generative pre-trained transformer
(GPT)

5. Artificial Intelligence
● Artificial intelligence is the
simulation of human
intelligence processes by
machines, especially computer
systems.
● Specific applications of AI
include expert systems, natural
language processing, speech
recognition and machine vision.

6. Neural Networks
● A neural network is a method in artificial
intelligence that teaches computers to
process data in a way that is inspired by
the human brain.
● It is a type of machine learning process
that uses interconnected nodes or
neurons in a layered structure that
resembles the human brain.
● Creates an adaptive system that
computers use to learn from their
mistakes and improve continuously.
● Example - Summarizing documents or
recognizing faces, with greater accuracy.

7. Deep Learning
● Deep learning teaches computers to
process data in a way that is inspired
by the human brain.
● Deep learning models can recognize
complex patterns in pictures, text,
sounds, and other data to produce
accurate insights and predictions.
● Can be used to automate tasks that
typically require human intelligence,
such as describing images or
transcribing a sound file into text.

8. Natural Language Processing (NLP)
● NLP is a field of artificial
intelligence that focuses on how
computers can understand,
interpret, and generate human
language.
● It’s the technology behind things
like voice-activated virtual
assistants, language translation
apps, and chatbots.

9. Generator
● A generator is an AI-based
software tool that creates new
content from a request or input.
● It will learn from any supplied
training data, then create new
information that mimics those
patterns and characteristics.
● ChatGPT by OpenAI is a
well-known example of a
text-based generator.

10. Transformer
● Transformers are a type of deep
learning programs, and are especially
useful for processing language.
● They’re really good at understanding
the context of words in a sentence
because they create their outputs
based on sequential data (like an
ongoing conversation), not just
individual data points (like a sentence
without context).
● The name “transformer” comes from
the way they can transform input data
(like a sentence) into output data (like a
translation of the sentence).

11. Large Learning Models (LLM)
● Large language models (LLM)
are very large deep learning
models that are pre-trained on
vast amounts of data.
● Consists of encoder and a
decoder with self-attention
capabilities.
● The encoder and decoder
extract meanings from a
sequence of text and
understand the relationships
between words and phrases in
it.

12. Generative Pre-Trained Transformer (GPT)
● GPT is a neural network family
that is trained to generate
content.
● GPT models are pre-trained on a
large amount of text data, which
lets them generate clear and
relevant text based on user
prompts or queries.
● Example- Create Images, Write
Code, Analyse Data, Generate
Learning Materials etc.

13. What is Generative AI?
● Generative AI enables users to
quickly generate new content
based on a variety of inputs.
● Inputs and outputs to these
models can include text,
images, sounds, animation, 3D
models, or other types of data.
● Uses statistical models to
predict what an expected
response might be - and this
generates new content.

20. CRM with Generative AI
● CRM is a technology that keeps
customer records in one place to
serve as the single source of truth for
every department, which helps
companies manage current and
potential customer relationships.
● Generative AI can make CRM even
more powerful — think personalized
emails pre-written for sales teams,
ecommerce product descriptions
written based on images alone,
marketing campaign landing pages,
contextual customer service ticket
replies, and more.

35. Ready for a challenge… Open this link
https://tinyurl.com/genAIDehradun

36. Questions? Ask me Anything!