Welcome back to vertex AI.
Now we're going to dive into the tool which is part of Google Cloud and will give you a tour of the
main AI features and what you can do with them.
So as you log into vertex AI, you will arrive at the dashboard.
Here, you will be prompted to proceed with your accounts, next steps, tutorials, or the main components
which we will soon go through.
Inside Google's cloud and even inside vertex AI, there are many tools to assist in model development
and deployment.
We will mostly focus on vertex AI's studio features, but before we head into vertex AI studio, let's
take a look at the model garden.
Here you can access different models such as Gemini, and then quickly open them on vertex AI studio.
If you have already enabled the required APIs, you may also open them on your notebooks.
Since this aspect is too technical for most of our audience, we recommend that if this interests you,
investigate more on your own.
If you go for the foundation models from Google, you will be able to access most directly from the
AI studio.
Others, such as llama 3.1 or clod three, require setting up keys or deploying using deployment quotas.
Again, if this is too technical for you, just stick with the foundation models that show open in vertex
AI studio, which directly takes you to this playground user interface.
It's very reminiscent of open AI's playground and Claude's Workbench.
From those experiences, many of you will understand how that knowledge and skill transfer to this tool.
At the top you will have untitled prompt, since this is how these interactions with the models are
organized.
After you edit this prompt, give it a name, instructions and save it.
It should be inside the saved prompts.
Now let's head to overview and focus on vertex AI's studio capabilities.
At the time of this video, it looks like this.
At the top, we have our project name, the search feature, which searches through Google Cloud's products
and resources.
And in this AI icon we have Gemini for Cloud Console.
Once enabled, it acts as your assistant answering questions about Google Cloud optimization strategies,
and can also take contextual data such as your project to provide more accurate answers.
Cool, right?
You can have it on the side of your screen or full tab by clicking here.
Going down on our overview screen, we have quick access to the multimodal Gemini Tri.
Gemini takes us to that playground or Gemini Vision editor, as it's named here in the tool tip.
By clicking the second button, we are taken to the multimodal tab with options to use the Vision Editor
with a single turn prompt design, which is ideal for prompting the model and receiving a response with
no conversion history, or the multi modal turn prompt design, which allows you to have a continuous
conversation and use conversation history as context when generating responses.
There is also quick access to documentation, API resources and tutorials.
You can also find a prompt gallery.
We love this resource as it allows you to start from an existing prompt and quickly fine tune it to
your liking.
There is a search bar with filters for task type, features and prompt type, or you can just click
on some of these categories at the top.
Lets search for newsletter and see what we find.
Great.
We have a prompt to start from.
As we click on it we are taken to the Gemini Vision Editor.
This is obviously a multi-turn prompt.
As we can see there is a chat.
Let's save it just to show where you can find this prompt later, edit the prompt name and hit save.
It will be saved in the Saved prompts section.
Let's cover what you can do in the language section.
You can fine tune models in the tuna model section and use the language model for translation code or
text through the single prompts or chats.
At the bottom, you're provided with quick access to API code, tuning models, and some sample prompts.
Notice that the prompts in the language section differ from those inside multimodal at the time of this
lesson.
Vision is available for a limited amount of customers, but you can request early access so you can
try it as soon as it comes out.
Lastly, one of our favorite features here is the speech tab.
You can do text to speech and speech to text in text to speech.
Let's type in here.
Change the voice settings and hit submit.
Then here inside speech you can play the generated voice or download the file.
Hello everyone!
For speech to text, you can upload an audio file from your computer or record with your own voice.
Let's do a quick example with a simple recording to try out this capability.
Testing.
Testing 123.
Now choose the language over here on the right and hit submit.
What I love the most about this feature is that it uses chirp, a version of Google's universal speech
model USM, with more than 2 billion parameters that can transcribe in over 100 languages.
After the text is transcribed, you can see it over here in the text section.
That was a lot to cover, and there's still so much more in the world of vertex AI.
In the lessons to come, we're going to be diving into more key features and showing some detailed use
cases.