(gentle etheric music)
- [Michelle] Hi, my name is Michelle.
Welcome to this lesson on using natural language
to analyze your data using Select AI and GenAI.
Oracle can bring AI to the enterprise
at every layer of our stack.
We have the cloud with Nvidia
to train foundation GenAI models.
We have the enterprise data management
and privacy security knowhow
to manage the risk associated with this technology.
And now, we have the platform services.
So just like Oracle,
you can build enterprise grade GenAI
into your business and products.
We have the industry experience
and partner connections customize these models
to specific verticals and functions.
We have the application stack
that employees and business users live in.
We're embedding our GenAI technology
to radically transform their productivity.
We're going to tackle a couple of areas in this lesson.
We're going to discover what Select AI is
in the Oracle Autonomous Database,
demonstrate how easy it is
to query your data using natural language,
and then tie it all together
by looking at the SQL query generation process flow.
Autonomous database Select AI makes it easy
to get answers about your business using your language,
and you don't need to know the structure of your data
or how to query that data
to gain those valuable insights of your data.
Select AI is the simplest way
to get answers for your business.
Just ask your question.
Autonomous Database will then manage
the entire query process to get that answer.
This includes connecting to a large language model,
engineering a prompt that's optimized
for the Oracle database sources,
and delivering to the app, a result set,
a narrative, or just the SQL.
We're going to illustrate how you can build this
into an app on Autonomous Database
that uses your data.
Because remember, these models know nothing
about the data within your organization.
The language models are trained on public data
and will use natural language and AI
to query your data, summarize the content,
and generate innovative responses.
Unleash the creativity of generative AI
on your data to develop new solutions.
This demo is going to show you with a simple Apex app
how we built Select AI to respond
and give us answers from our database.
We can simply start to ask questions
about top 10 streamed movies, actors,
and returns the result set
without even knowing a table name
or a column that we're selecting from
or even how to write the SQL.
I can also reach out to the internet
to get additional information.
So that ask the database is going strictly to my data
where unchecking it allows me to go
and get additional information about this.
If I want to drill into the result set,
I can do that using Apex interactive forms
and reporting so I can get additional information
about the columns and the tables
and do different filters and sorts.
I can even download this result set
to an Excel spreadsheet and pull that out.
These are all built in tools when I'm using Apex
that allows me to see this data even faster.
Behind the scenes, the data, again, was brought
to a result set from actually
just asking the database of what we got.
We can rename show charts,
get different information from those charts.
And now I want to see the SQL
that was generated when I first asked that question.
So when I asked about the total streams,
it went out and found the movies table,
joined it on two other tables
to get the information and filter by Paul Rudd
and Stan Lee, and return and group those by title.
So you can see how it writes the SQL for you.
It can pull back the SQL with Select AI, show a SQL,
and it can also pull back the result sets,
and building those into an app allows you
to actually leverage the power of Apex
for interactive reports and viewing the different SQL.
And since we are demonstrating this app we created in Apex,
you can also simply take it on the move
with you using the same Select AI capabilities
to use large language models
to return the results and SQL query about your data.
As you can see from the questions that were being asked,
Select AI takes the questions and natural language
and translates into SQL language.
Using AI large language models,
it breaks up the question, infers the details being asked,
and formulates the SQL query.
Large language models are different,
and there are models that are better writing SQL
by inferring intent and being loaded
with the information about the objects in the database.
Now you can review the query to verify developing apps
with Select AI is simple
so that you can use Generative AI capabilities
with existing applications and build new.
It is future-enabled because you can choose
from array of large language models
and pick the best suited for your business.
There are also new models being trained,
and you can leverage models that you've fine tuned.
Using Oracle database, the security protects your data.
Using Autonomous Select AI with OCI Generative AI,
your data stays in the tenancy
and not sent to another large language model provider
or seen by other customers.
Let's take a quick look under the covers
to see how this works and how simple it is
to query the database with natural language.
Using a tool like SQL Developer to query the database,
you see the statements that run against the database.
It is a standard select statement followed by AI,
your question instead of the from and where clause.
IT processes the select AI statement
just like other SQL statements.
You can also use the Select AI show SQL command
and you'll see the query that is created
to return the results.
You can keep refining your questions to get more details
or other answers that you need from the data.
One of the major design principles
for Select AI is plugability,
and this encapsulates in an AI profile.
Depending on your use case, you may want to use Cohere
or OpenAI or Llama.
You choose which provider and model you want to use.
You also specify that schemas, tables,
or views participate in the process.
To configure the database, you can use one
or more AI profiles with a large language model
that best fits your business.
You specify the schemas, tables,
and views you are going to include in the processing
using dbms_cloud_ai PL/SQL package
that is provided in the database.
To wrap up, let's put it all together.
To generate SQL query,
you simply can ask your database using Select AI,
find the top three customer segments
for George Clooney movies.
The AI profile uses large language models
to find what the database metadata
to produce the prompt from the question asked
and generates the SQL
using the model and returns the result
or SQL to a SQL tool such as SQL Developer or to an app.
Easy to build AI into your apps
using Oracle Autonomous Database with Select AI
to get answers from your data using large language models.
This is secure at every layer to protect your data
and future enabled to use new available models
or fine tune models that meet your business needs.
I hope you enjoyed this lesson on Select AI
and are looking forward to building AI-powered apps
with the Oracle Database.
(air whooshes)