[MUSIC].
>> Now I'm sure you're wondering to yourself, "Gee, self,
how is Microsoft delivering
new intelligent Cloud-native app experiences
by harnessing the power of data and AI?"
Because we all think like that.
First of all, great
question, and second of all, you're in luck.
I'm thrilled to welcome Xuedong Huang,
a Microsoft Technical Fellow,
and Azure AI's Chief Technology Officer.
Xuedong has led
Microsoft Speech Technology Group for
nearly three decades and
holds over 170 AI-related patents.
He now leads the team
developing Azure Cognitive Services,
and internally we lovingly call him XD.
Thanks for joining us, my friend.
>> Thank you, Seth.
Looking back, what is top of
mind for you when it comes to AI at Microsoft?
>> Well, there are really three key things that we
have been driving in the last few years.
The number 1 is really AI quality.
Without quality, nothing really matters.
The second one is really how we can really scale
with efficiency and latency performance.
Of course, the first two things would lead to happy customers.
So, how we delight customers,
drive adoption to amplify their productivity,
those are the three key things that we are focused on.
>> You mentioned two, quality and scale.
How do you measure quality of AI products?
That's an interesting question, I'd love your thoughts.
>> We have the human parity milestone
a number of research and
benchmarks in the last few years.
That is really trying to drive the horsepower on
the line technology to reach
the same level of a human's quality.
Let's take the Switchboard Speech Recognition as example.
In the speech recognition research community,
they have been working on this task for over 20 years.
Firstly, funded by the US government.
When two people are having
a conversation over the telephone line,
we want a computer to transcribe
that as accurately as humans.
There was such a hard,
difficult task 20 years ago.
We never imagined we could have
reached the human level of performance.
For the first time in the history of speech research,
Microsoft deliver the human quality
on that research benchmark.
Then we'll push that technology
into Azure Cognitive Services.
It's fantastic to see speech recognition today on Azure,
it's really offering a fantastic performance
in transcribing humans' conversation.
The latest example is Twitter Spaces took
a full advantage of
Azure Cognitive Services deployed this
for transcribing live conversation on
Twitter Spaces that really
improved accessibility of their product features.
The addition to speech recognition,
we're making progress on the human parity,
and we're the first to reach
human parity not only on speech recognition,
but also on machine translation,
on the natural language processing such as
SuperGLUE, and most recent one is
the image captioning and the image
captioning nocaps (XD).
That had nothing to do with my name,
it's really the open research challenge to see if
computers can transcribe and describe
the image as good as any humans.
All those human parity breakthroughs are fantastic.
The foundational pieces that we
got incorporated into the production services,
the Azure Cognitive Services.
If you just use the API today,
you will find amazing quality
not only on speech recognition,
but also on machine translation,
image captioning and the language processing.
>> This is really cool. This kind of functionality,
what does it mean for folks,
for developers in real life to be able
to access this functionality in their applications?
>> Any developers, anyone in
the world can really take full advantage of this one.
I want to cite one great example
of the European Union Parliament.
There are 24 languages spoken.
In order to really bring the citizen
closer in the European Union,
European Union Parliament has started
this international bidding process.
They incorporated 15 systems
in the first phase of benchmarking,
focused on lively translate the member of the Parliament
having a debate in German, French, and English.
Among 15 international companies,
Microsoft was ranked on the top in terms of
overall quality in translating
those three languages live in the parliament.
Now that speaks on the quality of Azure AI,
whether it's speech recognition or translation.
Now we are working with
other companies to try
and to finalize on the second phase evaluation,
they've broadened this to 10 languages.
The ability of our AI quality
in terms of reaching human parity,
really truly finding its way in
live production to delight the customers.
>> This is awesome.
When I was doing research so many years ago in this,
I used Europarl datasets and other trilingual datasets.
This is awesome. Moving forward.
What are we investing in now and in the future?
>> We are investing in computer vision.
Of course, we're leading on speech services,
whether it's a neural
text-to-speech or voice recognition.
We're really trying to gather the computer vision and
video processing understanding and
the language and the high level
to understand the reality,
understand the object, create
a unified platform that can
further delight our customers.
I think that there would be a fantastic
high value scenarios such as ambient
intelligence and that will
really truly, truly unleash productivity for all of us.
So it's not only speech recognition,
not only hearing, but also eyes, thinking and listening.
That four pillars of cognitive services would be
fantastic with improved underlying technology.
>> I love the phrase "delight customers"
because you can do that by literally
plugging in to all of this good research.
Just to finish up, we have about a minute,
where can people go to find out more?
>> People can come to azure.com, really
see the Azure Cognitive Services capability.
Also Azure Applied AI Services that
were designed for a specific set of scenarios.
The underlying future is fantastic.
We are optimizing multi-model,
multi-sensory dimensions, just like humans.
This is what we call XYZ-code.
Speech, vision and multilingual: Those
are the dimensions we are optimizing
to serve our customers and delight them.
Awesome. Well, XD, it's always a privilege
sneaking in on meetings and
listening to you and then now getting to talk to you.
This has been awesome. Thanks for being with us.
My pleasure. Thank you so much.