A collection of amazing new AI tools for game development has dropped; building and administering
online course labs gets a comprehensive update from Azure; and the release of new AI tools
for code completion raises some interesting questions.
Hi, I'm Erik Gross.
Welcome you to another episode of Azure This Week.
Azure's Cognitive Services for Speech offering has been used by many to leverage the power
of the cloud to transcribe speech to text, create realistic voice output from text, and
translate spoken audio.
Recently, however, Microsoft has turned their attention to the convergence of two major
elements of the modern tech landscape: gaming and artificial intelligence.
They're calling this use case for Azure Cognitive Services for Speech "AI Gaming", and they've
put together some really excellent guidance on how to leverage it in game development.
Some of the more interesting possibilities include prototyping your game dialogue using
text-to-speech.
Voice talent is expensive, why not try out new dialogue using a cloud service?
You can even swap out dialogue using various emotional voices to explore game dialogue
changes inexpensively.
Improving game accessibility by using text-to-voice, translation, and transcription services to
open up a rich gameplay experience for a diverse audience.
Enhancing the NPC aspect of your games by creating voice characters that use a consistent
"branded" speaking style.
You can add emotions, accents, laughter and more to your non-player characters, giving
your players a truly immersive experience.
If you're in game development, check these new tools out, but don't go overboard with
them.
We're not quite ready for the singularity quite yet.
Moving on to an entirely different area of tech.
Let's explore how Azure can improve online training.
Azure Lab Services has been around for a while, providing you with tools to create and deliver
effective online courses and to administer your training services.
The cloud can offer some tremendous advantages in teaching.
The ability to create precisely configured training environments on demand, for example,
opens up a lot of possibilities.
Managing the training system though, can be a lot of work and training departments often
lack deep technology experience.
So IT departments get pulled into the mix.
The recent developments to Azure Lab Service should be great news for course designers
and IT administrators both.
There's a lot to this update, so you should take the time to explore in detail.
Some of the most exciting new features deserve special mention though, including: Canvas
LMS integration, improved cost tracking, VM redeploys without losing student data, and
brand new roles like Lab Assistant and Lab Operator giving you more control over how
you manage the learning experience for your students.
As the world moves online, our teaching tools need to follow suit and Azure Lab Services
just took a big step forward.
Keen to start your cloud journey?
We've just launched a new limited time offer for our Personal Annual Plans saving you 40%.
These plans give you access to great course features like hands-on labs and practice exams,
making it easier to kickstart your cloud career.
If you're interested, scan the QR code on the screen or click the link in the description.
Let's wrap this week's episode up with some brief thoughts about the use of AI in the
development process.
Now you've likely heard about the release of GitHub's Copilot tool, which touts itself
as your AI pair programmer.
AWS is now in the game as well with their Code Whisperer offering that debuted earlier
this year.
While the benefits to development here seem obvious, I can't help but think about a couple
of potential negatives.
For me, the main thing here is trust.
If you're going to accept a recommended code snippet, or even a complete function, and
you didn't write it, what are the risks?
We've all had problems using third-party libraries, mainly because there's no way we can realistically
go through the entire code base on those external packages.
Code we use from Copilot or Code Whisperer may be smaller in scope, but will we have
the time to peruse it for any vulnerabilities?
The other aspect to have attention on here is code quality standards.
Even if an AI-generated code block works, will it conform to the code quality standards
your team wants to put in place?
How will this affect code readability and onboarding in the future?
Now I'm interested in your thoughts on this.
Have you used these tools a lot?
What's the experience been like?
I'd like to hear from you.
Meanwhile, I'll keep trying them out myself.
Looking to leverage AI in your game development work?
Thinking about how you could raise the bar for your online training efforts?
Let me know what you think.
Also jump on the Discord channel to discuss the news from this episode, interact with
other students and ACG people, and get help for your cloud journey.
You'll find a link below in the description.
See you next week and keep being awesome Cloud Gurus.