Okay. Good afternoon, everyone.
We're going to be starting a cognitive labs in action
Session. I will talk about a specific new
Lab that's valuable today in preview
Called [ inaudible ] i will walk you through a couple
Demos and show you how the technical works.
This is a full summary of all the other similar talks you
Might be interested in in the ai space and all of these are after.
Let's dive in. Let's talk about bots today.
Bots today are really great as you've seen doing process,
Answering faq and what we've done with personality chat is
Enhance that doing the ability shah.
-- Chat. So what does that mean?
Enhances your bot's capabilities and doing this in a way that is
In line and consistent with your bot's personality specifically.
An example of how that would look.
A bank bot talking about questions about how do i get my
Log in information. In that flow users the end to
Go -- tend to go on a tangent by helpful.
A nice conversation trying to interact with the bot.
If you're able to handle that wet well and in -- that well.
And creates a good end to end user experience.
One of the ways to create a good user engagement story for your
Bot without having to worry about writing for it.
It will give it to you right off the bat.
>> So there's a couple of different enpoints how to use
It. How will you use it for your bot?
I will show you two ways of two end points.
The sfirs -- first -- a list of
Responses hand crafted for certain default personas and you
Can integrate that. I will show you how to do that.
The second that we have is the cognitive services lab space.
You saw the cognitive lab page and you can head there and try
Out our personality chat demo available as a demo.
That includes the editorial piece
And the dynamically generated responses.
I will show you how that's done. You can try it out today.
Like right after this talk maybe. So let's dig into the editorial.
We have more than 100 common
Small talk scenarios. They have been hand crafted.
Ready for you to put in your bot hitchat
People do with bots. Button up and formal.
Say you're doing a bank bot. Friendly. And right down to humor rows.
Which is more causal, fun. Say you're doing a weather bot
That is fun or witty and you might want to use that persona.
How do these look different? some scenarios, the common
Scenarios like thank you. You see a tone difference
Between you're quite welcome and you bet.
Will you marry me and the professional
Says let's stick to the professional relationship and
The humor rows bot says so let's go to city hall.
>> How do you get this in your bot today? three ways.
Er as [ indiscernible ]
You can see that your bought. Add the personality chat to your
Bots middleware and i will show you the cord.
Add it to your bot's middleware. Middleware.
And you don't want to call out
Api specifically. You can import it add it to your
Qa maker bot as another knowledge base and you don't
Need to call a package. There's a personality chat
Dialogue that you need to add to your bot's base dialogue and
It's available and simple. We share these links and
Documentation so you can get started. Like i said, i'll show you --
This is a quick example. How exactly you will include it.
You include the package on top. Then in the middleware add the
Personality chat. There's a few things you can do
To customize it. If you say respond only if the
Chat is true it means we have the query understanding model.
It checks to see if the query given is a chitchat or small
Talk. And only responds.
This prevents it from interrupts task flows or information flows.
The second we talked about. The persona setting.
You can set it to funny, professional or funny.
This gives a threshold. Along with every response.
You can choose the flesh hold depend -- threshold.
The higher the score the more the precision will be.
Recall. You can choose who -- what is
Suitable for your bot. >> I'm going to quickly switch
Mo and show how it works.
Hopefully the monitor switch should
Work. Okay. So
This is -- this is a sample weather bot with two personas.
This is the funny one. High hi, i'll be your weather man.
I will say hi and see what it says. It says what's cooking?
That's personality for you right off the bat.
I will ask it what the weather is because that's sample task
That we've trained it to do for now. So even if you can see the
Weather bot itself has personality in it.
I will respond to what i says. And say i am not silly.
And it -- says alert the media. From our editorial curated set.
I can continue and respond and say haha.
Very funny and it will continue. So you see this is the tone of
The funny bot. We can have a similar
Conversation with the professional bot.
I say hi. More formal.
To the point. Lit respond to all of it.
It says what i do for you. And i say that's what weather.
So it just gives me the weather without much personality
Associated and i say thank you and it resfondz that.
-- Prere responds to that. You can see how much depth the
Editorial has. 100 Plus scenario so it covers
Quite a few. So i say who made you.
It says, tech people. Let's ask, do you like them?
He -- you see the edges of how much
Curated data can do. It understand you're asking.
It doesn't understand exactly what you're asking.
And i can continue saying, why not? and it just -- it loses because
You can't have too much of a long conversation with just
Editorial. This is where the second piece comes in.
I will switch back to my presentation.
So the second piece. The cognitive service lab piece.
If you go to cognitive lab space. You will see project personality chat.
Click on that. It takes you to a demo page.
On the demo page, chat with the bot, choose a persona and see
What response comes up based on the persona.
This is real time generated responses.
Not editorial responses. It gives the responses along
With the scores of how it calculates the responses.
Today we have a demo as we're scaling out.
You can -- there's a way for you to contact us to get go ahead --
Get early access once we have it.
Let me take a few seconds to talk about what is a response generation.
How are our response generated? we use a sequence to
Sequence -- it's trained on large volumes of
Speaker conversational data. Every time you give it a new
Query, it has learned and has a vocabulary available for it.
It's learned typical versional patterns. When you say, how are you?
The next response. Based on a cognitive
Distribution given that particular query.
So no matter what you change, you change a comma, the way you
Re -- you phrase it. The response can be different.
This is the response in generally works.
Where does personality comes? in the way we've trained the model.
When we train model we have different speakers.
Which are represented as a vector in the vector space.
We take the different speakers and cluster the ones that speak
And cluster them in that vector space.
Persona. Once we have a persona, we
Define that characteristics of that persona based on the people
In how they behave. Without
The persona. When you say are you smart it
Looks in the vocabulary and generates words one by one.
Now you'll add persona id. Added as an input.
And that affects the probability itself.
What that does is gives higher weight for words and patterns
Similar to the ones in that persona space.
You can come talk to us for more details on the page itself the
Toppings gives references to the talk.
In the future you can see -- we have default personas.
You can see how in the future you can come and say i wanted --
I want it to talk like this. We can find the closest cluster
Retrain in needed in the future. Today we have defaults.
Into having it talk really like a
Specific person or persona. All right. I will quickly switch to a demo
Of how this really works. >> Like i said, you'll go to the
Microsoft cognitive services page, on that home page you'll
See project personality chat. And it tells you about it.
And an important thing to note, because you want to stay focused
On only answering the chitchat, we are trying to make it focus
Only on specific small talk so it doesn't
Derail business bot conversation.
So try -- let's try friendly. I'm going to do the same
Conversation we started with the weather bot.
Saying, who made you.
And it says lots and lots of people.
This is different from the other responses. Do you like these people?
It says, yes i do. This is generated on the fly.
Autogenerated responses. You can see why there's a value.
Editorial could never be this specific.
It's able to be super specific. Yes, i do.
They're very nice people. You can see at this side, the
Other responses that could have come up.
Like don't mind them. I love them. Of course i do.
And so you can see the kind of things this bot would say.
Let's continue and say why? this is another thing that
Context is hard to do with editorial.
So this model says yeah. Because they're very nice people.
Specifically -- so usually context doesn't matter too much
But if you give a query with low information like, why it takes a
Lot of information from the previous context.
It says because they're nice people.
And we can continue to you hang out with
Them? you can see how specific it's
Being by staying true to the persona and not going into
Difference. So it doesn't hang out with us.
Why not? i don't know.
I just don't see them. So you can continue as long as
You're still doing small talk and chitchat and not trying to
Ask for information. Time.
That's friendly. I can take a second and talk to
The professional bot for a
Second and just say hi. How are you?
Again, this is coming from the autogenerated.
Says fine, thanks. How are you?
You can see it being professional and formal plop say
I'm good. -- I will say i'm good.
Excited to be here. >> It says me too.
I hope you have a great time. It's trying to understand and continue.
Let's ask it about the conference.
Do you like being at the conference?
It says, yes. It's a great conference.
So you can see how it just is able to do that in that tone
Versus the same funny bot would be slightly
Different. You see it's starting to use
Smile liz which is the other -- smiles which the other bot was
>> Do you like being at the conference?
Right? so you can see the tone different.
Feel free to try this out. Check out the demo plop share
The page -- i will share the nudge just a second.
>> Like a lot of things you can check out in the space.
The one i've highlighted. Will lead you to the denominator
Demo i -- there's presentations. References to papers as well.
I think we have a few minutes for qa andly call out my awesome
Theme. Ask us questions.