(bright music)
- Hello and welcome to the IoT Chat,
where we explore the latest technology trends
and innovations.
I'm your host, Christina Cardoza, Editorial Director
of insight.tech, and today we're diving into the world
of high-impact AI-powered spaces
with Christopher Jaynes from Q-SYS.
But before we get started, Chris,
what can you tell our listeners about yourself
and what you do at Q-SYS?
- Yeah, well, thanks for having me here.
This is exciting.
I can't wait to talk about some of these topics,
so it'll be good.
I'm the Senior Vice President for software
and technology at Q-SYS.
So we're a company that enables video, and audio,
and control systems for your physical spaces.
Right?
But in reality, I'm kind of a classical computer scientist.
So I was trained as an undergrad in computer science,
got interested in robotics,
followed a path into AI fairly quickly.
Did my PhD at University of Massachusetts.
And I got really interested in how AI
and the specialized applications that were starting
to emerge around the year 2000 on our desktops
could move into our physical world.
So I went on, I left academics
and founded a technology company called Mersive
in the AV space.
Once I sold that company, I started to think about how AI
and some of the real massive leaps around LLMs
and things were starting to impact us.
And that's when I started having conversations with QSC,
got really interested in where they sit,
the intersection between the physical world
and the computing world,
which I think is really, really exciting.
And then joined the company as their Senior Vice President.
So that's my background.
It's a circuitous path
through a couple different industries,
but I'm now here at QSC.
- Great.
Yeah, can't wait to learn a little bit more about that.
And Q-SYS is a division of QSC just for our listeners.
So I think it's interesting, you say in the 2000s
you were really interested in this
and it's just interesting to see how much technology
has advanced, how long AI has been around,
but how it's hitting mainstream
or more adoption today after couple of decades.
So I can't wait to dig into that a little bit more.
But before we get into that,
I wanted to start off the conversation.
Let's just define what we mean by high-impact spaces
and what are traditional spaces
and then what do we mean by high-impact spaces?
- Yeah, I mean it fundamentally,
I find that term really interesting.
I think it's great.
It's focused on the outcome of the space, right?
In the old days, we'd talk about a huddle room
or a large conference room or a small conference.
Those are like physical descriptions of a space,
not so exciting.
I think what's way more interesting
is what's the intended impact of that space?
What are you designing for?
And high-impact spaces, obviously, call out the goal.
Let's have real impact on what we want to do
around this human-centered design thing.
So typically what you find in the modern workplace
and in your physical environments now after 2020
is a real laser focus on collaboration,
on the support of hybrid work styles, deep teamwork,
engagement, all these outcomes are the goal.
And then you bring technology, and software,
and design together in that space
to enable certain work styles really quickly,
quick and interesting.
I'll tell you one thing that's really, really compelling
for me is that things have changed dramatically.
And it's an easy thing to understand.
I am at home in my home office today, right?
But I often go into the office.
I don't go into the office to replicate my home office.
So high-impact spaces have gotten a lot of attention
from the industry because the intent of a user
or somebody to go into their space
is to find something that they can't get at home,
which is this more interesting higher impact
technology-enabled, things you can do there
together with your colleagues.
Like bridge a really exciting collaborative meeting
with remote users in a seamless way.
I can't do that here, right?
- I think that's a really important point,
especially as people start going back to the office more
or businesses have initiatives to get some more people
more back in the office or really increase
that hybrid workspace.
Employees may be thinking, well,
why do I have to go into the office
when I can just do everything at home?
But it's a different environment, like you said,
a different collaboration that you get.
And of course, we've had Zoom and we have whiteboards
in the office that give us that collaboration.
But it's how is AI bringing it to the next level
or really enhancing what we have today.
- Well, let me first say,
I think the timing couldn't be better
for some of the breakthroughs we've had in AI, right?
I've been part of the AI field since 1998 I think,
and watching what's happened, it's just been super exciting.
I mean, I know most of the people here at QSC
are just super jazzed about where this all goes,
both for me because it can transform your own company.
But what does it do about how we all work together,
how we even bring products to market?
It's super, super timely.
If you look at some of the bad news around 2020
there's some outcomes in learning and employee engagement
that we're all now aware of, right?
There's some studies that have come out that shown, hey,
that was not a good time.
However, if you look back at the history of the world,
whenever something bad like this happens,
the outcome typically means we figure it out
and improve our workplace, right?
That happened in the cholera epidemic
and some of the things that happened way back
in the early days.
What's great now is AI can be brought to bear
to solve some of these,
what I'd call like grand challenges of your space, right?
These are things like, how would I take a remote user
and put them on equal footing, literally equal footing
from an engagement perspective, from an understanding
and learning perspective, from an enablement perspective.
How could I put them on an equal footing with people
that are together in the room working together
on a whiteboard like you mentioned,
or brainstorming around a 3D architectural model.
How does all of that get packaged up in a way
that I can consume it as a remote user?
I want it to be cinematic, and engaging, and cool.
So if you think about AI in that space,
you have to start to think about classes of AI that take,
they leverage generative models,
like these large language models,
but they go a little bit past that into other areas of AI
that are also starting to undergo their own transformations.
So these are things like computer vision,
real-time audio processing and understanding,
control and actuation, so kinematics and robotics.
So what happens, for example, when you take a space
and you equip it with as many sensors,
vision sensors as you want, right?
Like 10, 15 cameras, could you then take those cameras
and automatically track users that walk into the space,
track the user that is the most important
at the moment, right?
Like where would a participant's eyes
likely to be tracking a user if they're in the room
versus people out?
How do you crop those faces and creating an egalitarian view
for remote users?
So that's some work we're already doing now
that was part of what we're doing with Vision Suite,
the Q-SYS Vision Suite, it's all driven
by some very sophisticated template and face tracking,
kinesthetic understanding of the person's pose,
all this fun stuff,
so that we can basically give you the effect
of a multi-camera director experience, right?
Somebody is auto-directing that, the AI is doing it,
but when you're remote you can now see it in exciting ways.
Audio AI.
So it's really three pillars, right?
Vision AI, audio AI, and control or closed loop control
and understanding.
Audio AI obviously can tag speakers
and auto transcribe in a high-impact space.
That's already something that's here.
If you start to dream a little farther, you can say
what would happen if all those cameras
could automatically classify the meeting state?
Well, why would I want to do that?
Is it a collaborative or brainstorming session?
Is it a presentation-oriented meeting?
Well, it turns out maybe I change the audio parameters
when it's a presentation to one to many
versus a collaborative environment for both remote
and local users, right?
Change the speaker volumes.
Make sure that people in the back of the room
during the presentation can see the text on the screen.
So I autoscale
or I choose to turn on the confidence monitors
at the back of that space and turn 'em off
when no one's there to save energy.
Those are things that people used to shy away
from in the AV industry because they're complicated
and they take a lot of programming,
and specialized behaviors and control.
You basically take a space
that could have cost you a $100K
and drive it up to $500,000, $600,000 deployments, right?
Not repeatable, not stepable.
We can democratize all that through AI control systems,
generative models that summarize your meeting.
What would happen, for example, if you walked in,
Christina, you walked into a room and you were late,
but the AI knew you were going to be late
and auto-welcomed you at the door
and said, the meeting's been going for 10 minutes,
there's six seats at the back of the room.
It's okay, I've already emailed you a summary
of what's happened so that you can get back in
and be more engaged.
That's awesome.
We should all have that kind of stuff, right?
And that's where I get really excited.
It's that AI not on your desktop,
not for personal productivity, but where it interacts you
in the physical world with you in that physical space.
- Yeah, I think we're already seeing some small examples
of that in everyday life.
I have an Alexa device that when I ask in the morning
to play music or what the weather is,
it says, oh, good morning Christina,
and it shows me things on the screen
that I would like more personalized
than anybody else in my home.
So it's really interesting to see some of these happening
already in everyday life.
We've been predominantly talking about the business
and collaboration in office spaces.
I think you started to get
into a couple different environments.
because I can imagine this being used in classrooms
or lecture halls, stores, other things like that.
So can you talk about the other opportunities
or different types of businesses
that can leverage high-impact spaces outside
of that business or office space?
If you have any customer examples you want to highlight
or use cases you can provide.
- We really operate,
I just think about it in the general sense
of what your physical and experience will look like.
What's that multi-person user experience going to be
when you walk into a hotel lobby?
How do you know what's on the screens?
What's the lighting conditions?
If you have an impaired speaker at a theme park,
how do you know automatically to up the audio levels?
Or if somebody's complaining in a space that says,
this sounds too echoy in here,
how do you use AI audio processing
to do echo cancellation on demand?
So that that stuff can happen
in entertainment venues.
It can happen in hospitality venues.
I tend to think more about the educational spaces,
partly because of my background
but also the enterprise space as well.
Just because we spend so much time focusing on that
and we spend a lot of time in those spaces, right?
So I want to make one point though,
when we think about the use cases,
transparency of the technology is always something
I've been interested in.
How transparent can you make the technology for the user?
And it's kind of a design principle that we try to follow.
If I walk into a classroom or I walk into a theme park,
in both of those spaces, if the technology becomes the thing
I'm thinking about, it kind of ruins this experience, right?
Like if you think about a classroom where I'm a student
and I'm having to ask questions about where's the link
for the slides again, or I can't see what's on monitor two
because there's a pillar in the way.
Can you go back?
I'm confused.
Same thing if I go to a theme park
and I want to be entertained
and immersed in some amazing new approach to,
I'm learning about space
or I'm going through a journey somewhere
and I'm instead thinking about the control system
seems slow here, right?
So you need to basically set the bar so high,
which I think is fun and interesting.
You set the technology bar so high
that you can make it transparent and seamless.
I mean, when was the last time you watched a sci-fi movie?
It was kinda like sci-fi movies now
have figured that out, right?
All the technology seems almost ghostly and ephemeral.
In the 60s, it was lots of video people pushing buttons,
and talking, and interacting with their tech
because it was cool.
That's not where we want to be.
It should be about the human being in those spaces
using technology it makes that experience totally seamless.
- Yeah, I absolutely agree.
You can have all the greatest technology in the world,
but if people can't use it
or if it's too complicated, it almost becomes useless.
And so that was one of my next questions I was going to ask
is when businesses are approaching AI
how are they considering the human element in all of this?
How are humans going to interact with it
and how do they make sure that it is
as non-intrusive as possible?
- Yeah.
And the word intrusive is awesome
because that does speak to the transparency requirement,
but then that does put pressure
on companies thinking through their AI policy
because you want to reveal the fact that your experience
in the workplace, the theme park or the hotel
are all being enabled by AI.
But that should be the end of it.
So you got to think through carefully
about setting up a clear policy.
I think that's really, really key, right?
Not just about privacy, but also the advantages
and value to the end users.
So a statement that says, this is why we think
this is valuable to you.
So if you're a large bank or something
and you're rolling out AI-enabled spaces,
you got to be able to articulate why it is valuable
to the user.
A privacy statement that aligns with your culture,
of course, is really key.
And then also allow, like I mentioned,
allowing users to know when AI is supporting them.
In my experience though, the one thing I think
that's really interesting is users will go off the rails
and get worried, and also they should be,
when a company doesn't clearly link
those two things together.
And I mean also the vendors.
So when we build systems, we should be building systems
that support the user from where the data
is being collected, right?
So I mean the obvious example is if I use Uber,
then Uber needs to know where I'm located.
That's okay.
Because I want them to know that,
that's the value that I'm getting.
So they can drive a car there, right?
If you do the same in your spaces, right?
Like you create a value loop that allows a user
as they get up in a meeting and as they walk away,
their laptop is left behind.
But the AI system can recognize a laptop,
that's a solved problem, and auto-email me
because it knows who I am.
That's pretty cool.
And say, Chris, your laptop's in conference room 106,
there's not another meeting for another 15 minutes.
Do you want me to ticket facilities
or you want to just go back and get it?
That kind of closed-loop AI processing is really valuable,
but you need to be thinking through all those steps,
identity, de-identification for GDPR,
that's super, super big.
And if you have this kind of meeting concierge
that's driving you, that's an AI, you have to think through
where that data lives.
You'd have to be responsible about privacy policies
and scrubbing it.
And then if a company is compliant
with international privacy standards,
make that obvious, right?
Make it easy to find and articulate it cleanly
to your users.
And then I think adoption rates go way up.
- Yeah, we were talking about the sci-fi movies earlier
where you had all the technologies, and pushing buttons,
and then we have the movies about the AI
where it's taking over.
And so people have a misconception of what AI
or this technology is really, how it's being implemented.
So agree, any policies or any transparency
of how it's supposed to work,
how it is working just makes people more comfortable with it
and really increases the level of adoption.
You mentioned a couple of different things
that are happening with lighting
or echo cancellation computer vision.
So I'm curious what the backend
of implementing all of this looks like that technology
or infrastructure that you need to set up
to create high-impact spaces.
Is some of this technology and infrastructure
already in place?
Is it new investments?
Is it existing infrastructure you can utilize?
What's going on there?
- Yeah, that's a great question.
Yeah.
because I've probably thrown out stuff that scares people
and they're thinking, oh my gosh,
I need to go tear everything out
and restart, building new things.
The good news is, and maybe surprisingly this sort of wave
of technology innovation is mostly focused on software,
cloud technologies, edge technologies.
So you're not necessarily having to re-leverage things
like sensors, actuators, cameras, and audio equipment,
speakers and things.
So for me it's really about, and this is something
I've been on the soapbox on for a long time.
If you can have a set of endpoints,
this is one reason I even joined QSC,
endpoints, actuators and connect those
through a network, right?
Like a commodity true network, not a specialized network,
but the internet, and attach that to the cloud.
That to me is the topology that enables us
to be really fast-moving.
So that's probably very good news
to the traditional AV user or integrator
because once you deploy those hardware endpoints,
as long as they're driven by software, the lifecycle
for software is much faster, right?
A new piece of hardware comes out
once every four or five years.
We really can release software two, three times a year
and that has new innovation, new algorithms,
new approaches to this stuff.
So if you really think about those three pillars,
the endpoints, like the cameras, the sensors,
all that stuff in the space connected to an edge
or control processor over the network,
and then that thing talking to the cloud,
that's what you need to get on this sort of train
and ride it to software future, right?
Because now I can deliver software into the space.
You can use the cloud for deeper AI reasoning
and problem-solving for inference generation analytics,
which we haven't talked about much yet
can happen there as well.
So insights about how your users are experiencing
the technology can happen there.
Real-time processing happens on that edge component
for low latency, echo cancellation, driving control
for the pan tilts, so the cameras in the space,
and then the sensors are already there and deployed.
So that to me is those three pieces.
- And I know the company recently acquired Seervision
and insight.tech
and the IoT Chat also are sponsored by Intel.
So I imagine you're leveraging a lot of partnerships
and collaborations to really make some of this,
like the real-time analytics happening,
those insights be able to make better decisions
or to implement some of these things.
So wanted to talk a little bit more about this,
the importance of your partnership with Intel
or acquiring companies like Seervision
to really advance this domain
and make high-impact spaces happen.
- Oh, that's an awesome question.
Yeah.
I should mention that the QSC, the Q-SYS product,
the Q-SYS architecture and even the vision behind it
was to leverage commodity compute to then build software
for things that people at the time
when it was launched thought, no, you can't do that,
you need to go build a specialized FPGA
or something custom to do real-time audio, video,
and control processing in the space.
So really the roots of Q-SYS itself
are built on the power of intel processing really,
which was at the time very new.
Now I'm a computer scientist so for me
that's like, okay, normal.
But it took a while for the industry to move out of that,
the habit of building very, very custom hardware
with almost no software on it.
With Intel processors, we're able to build, be flexible
and build AV processing, even AI algorithms now
with some of the on-chip computing stuff that's happening,
can be leveraged with Intel.
So that's really, really cool.
It's exciting for us for sure and it's a great partnership.
So we try to align our roadmaps together,
especially when we have opportunity to do so,
so that we're able to look ahead
and then deliver the right software on those platforms.
- Looking ahead at some of this stuff, wanted to see,
because things are changing rapidly every day now.
I mean when you probably first got into this in 1998
and back in the 2000s things that we have today
was only a dream back then and now it's reality.
And it's not only reality but it's becoming smarter
and more intelligent every day.
So how do you think the future of high-impact spaces
is going to evolve or change over the next couple of years?
- I feel like you're going to find that there is a new employee
that follows you around and supports your day,
regardless of where you happen to be
as you enter and leave spaces.
And those spaces will be supported by this new employee
that's really the AI concierge for those spaces.
So that's going to happen faster than most people,
I think, even realize.
There's already been an AI that's starting to show up
behind the scenes that people don't really see, right?
It's about real-time echo canceling
or sound separation,
audio scene recognition's a great one, right?
That's already almost here.
There's some technologies and some startups
that have brought that to bear using LLM technologies
and multimodal stuff that'll make its appearance
in a really big way.
And, the reason I say that is,
it'll inform recognition in such a powerful way
that not only will cameras recognize what a room state is,
but the audio scene will help inform that as well.
So once you get to that,
you can imagine that now you can drive
all kinds of really cool end-user experiences.
I'll try not to speculate too much
because some of 'em we're working on
and they'll only show up in our whisper suites
until we actually announce them.
But imagine the ability to drive to your workplace
on a Tuesday, get outta your car, and then get an alert
that says, hey, two of your colleagues are on campus today
and one of them is going to hold the meeting
on the third floor.
I know you don't like that floor
because of the lighting conditions,
but I've gone ahead and put in a support ticket
and it's likely going to be fixed for you before you get there.
So there's this like, in a way, you can think about
the old days of the your spaces as being very reactive
or even ignored, right?
If something doesn't work for me or I arrive late,
like my example I gave you earlier to a class,
it's very passive.
There's no you in that picture,
it's really about the space and the technology.
What AI's going to allow us to do is have you enter the picture
and get what you need out of those spaces
and really flip it so that those technologies
are supporting your needs almost in real-time
in a closed-loop fashion.
I keep saying that closed loop, what I mean is,
the sensing that happened and has happened,
maybe it's even patterns from the last six, seven months
will drive your experience in real-time
as you walk into the room or as you walk into a casino
or you're looking for your hotel space.
So I think there's a lot of thinking going into that now
and it's going to really make our spaces far more valuable
for far less, way more effective,
for a far less cost really,
because it's software-driven, like I mentioned before.
- Yeah, I think that's really exciting.
I'm seeing that employee follow around a little bit
in the virtual space when I log into a Zoom
or a Teams meeting, project manager
always has their AI assistant already there
that's taking notes, transcribing it,
and doing bullet points of the most important things.
And that's just on a virtual meeting.
So I can't wait to see how this plays out in physical spaces
where you don't have to necessarily integrate it yourself.
It's just seamless, and it's just happening,
and providing so much value to you in your everyday life.
So can't wait to see what else happens,
especially from Q-SYS and QSC,
how you guys are going to continue to innovate
from this space.
But before we go, just want to throw it back to you
one last time.
Any final thoughts or key takeaways
you want to leave our listeners with today?
- Well, first let me just say thanks a lot
for hosting today.
It's been fun.
Those are some really good questions.
I hope that you found the dialogue to be good.
I guess, the last thought I'd say is don't be shy.
This is going to happen.
It's already happening.
AI is going to change things,
but so did the personal computer.
So did mobility and the cell phone.
It changed the way we interact with one another,
the way we cognate even, the way we think about things,
the way we collaborate.
The same thing's happening again with AI.
It'll be transformative for sure.
So have fun with it.
Be cautious around the privacy and the policy stuff
we talked about a little bit there.
You got to be aware of what's happening
and really I think people like me,
our job in this industry is to dream big at this moment
and then drive solutions, make it an opportunity,
move it to a positive place.
So it's going to be great.
I'm excited.
We are all excited here at Q-SYS
to deliver this kind of value.
- Absolutely.
Well, thank you again for joining us on the podcast
and for the insightful conversation.
Thanks to our listeners for tuning into this episode.
Until next time, this has been the IoT Chat.
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