8. Let’s talk about AI
aka.ms/semantic-kernel 8
Check out the
resources here to
learn about the latest
on AI at Microsoft.
You dream it. AI
helps build it.
Microsoft is
empowering the
world to achieve
more with AI and
its copilot ecosystem.
9. Modernized & augmented
flagship products with copilot
aka.ms/semantic-kernel 9
AI-based search
with Microsoft
Copilot
Biometric identity
verification
Personalized
recommendations
Copilot for Work
across Office 365
Copilot
assisted coding
10. S E M A N T I C K E R N E L / Microsoft confidential
At the center
of it all is
Semantic
Kernel
AI orchestration
Copilots
Plugin extensibility
Apps
AI infrastructure
Foundation models
10
11. What is Semantic Kernel?
aka.ms/semantic-kernel 11
An open-source SDK that lets you
easily build agents that call your
existing code. As a highly extensible
framework, it can be used with models
from OpenAI, Azure OpenAI, Hugging
Face, and more!
By combining your existing C#, Python,
and Java code with these models, you
can build agents that answer questions
and automate processes.
.Net
Java
Python
12. A bridge between LLMs and
your code
ML RESEARCHER APP DEVELOPER
keepingupwith advances
cutting edge models
e x p e r i m e n t a t i o n
stable and performant
efficient to deliver
e a s i l y s c a l a b l e
m a i n t a i n a b l e
algorithm analysis
Your
models
Your
code
Your
memories
Your
prompts
13. Plugins &
aka.ms/semantic-kernel 13
Planners &
Personas
These are the core
building blocks of
Semantic Kernel. By
customizing these key
components, you can
create solutions to suite
exactly your needs.
14. Plugins
aka.ms/semantic-kernel 14
Plugins encapsulate
capabilities into a single unit
of functionality. When you
build a plugin for Semantic
Kernel, you can leverage it on
other services, like ChatGTP,
Bing, and Microsoft 365.
Likewise, any plugin built for
those services can seamlessly
import to Semantic Kernel.
Semantic Kernel
Your app
Plugins
Other AI apps
15. Semantic or native?
aka.ms/semantic-kernel 15
To make a plugin, you'll need
to create some functions.
These are either semantic or
native – you decide.
Endpoint
Semantic Kernel
Semantic functions Semantic functions
Time plugin
16. Planners
aka.ms/semantic-kernel 16
A Planner is a function that takes the initial
request and returns a list of steps needed
to fulfill the request. AI is used to mix-and-
match plugins registered in the kernel so it
can recombine them into a series of steps.
Semantic Kernel
Person has a request
Plugins
Plan
18. Personas
aka.ms/semantic-kernel 18
Personas are what defines an agent's role, like
a set of instructions. They hold their own
memories which provide broader context to
the requests made.
This is what empowers multi-agent systems
where specialists are defined to execute
requests they were designed to fulfil.
Project manager agent
Researcher agent
Copywriter agent
Designer agent
20. Memories
aka.ms/semantic-kernel 20
This is what provides context to the initial request. Memories are fed into
Semantic Kernel in a few different ways.
• Conventional key-value pairs: Just like you would set an environment variable in your
shell, the same can be done when using Semantic Kernel. The lookup is
"conventional" because it's a one-to-one match between a key and your query.
• Conventional local-storage: When you save information to a file, it can be retrieved
with its filename. When you have a lot of information to store in a key-value pair,
you're best off keeping it on disk.
• Semantic memory search: You can also represent text information as a long vector of
numbers, known as "embeddings." This lets you execute a "semantic" search that
compares meaning-to-meaning with your query.
21. Prompts
aka.ms/semantic-kernel 21
This is how you communicate with model. It serves as the input
which elicits a response from the model. Selecting the right words,
phrases, symbols, and formats that guide the model in generating high-
quality and relevant results.
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33. 3 membership tiers
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