As conference and collaboration spaces are evolving, artificial intelligence is playing an ever-expanding role in their effectiveness. Where those AI functions happen, though, is becoming a point of concern: It can’t all be cloud-based. Cara Shannon, senior manager, product marketing, Crestron, explains.
Some of these tools need to live on the edge: in the room and on devices that capture and deliver sound and images.
Just over a year ago, the Crestron blog featured a story that included info on a collaborative project between Crestron and Microsoft, the latter’s Signature Microsoft Teams® Rooms. In that article, Crestron’s EVP of Customer Success and Marketing, Brad Hintze, noted that in an installation such as this one, AI was absolutely an integral part of the space: “You need to have the equipment in the room that will deliver a great experience to enable things like Microsoft Copilot, right?” says Hintze. “You need to be able to facilitate that but that’s one side of it.”
“The other side of it is that AI embedded into devices can improve the experience for that solution,” he explains. “One of those that we talk about frequently at Crestron is the intelligent video experience. How do you ensure the person speaking is framed accurately? You're following them around the room; they stand up and go to the whiteboard. You want to switch automatically to that view, following that individual. All that's enabled by Visual AI, which we've been making investments in for quite some time. The AI can improve the experiences of the technology, but then it can also help enable these new AI tools when it's deployed appropriately.”
In those two paragraphs, Hintze had summarily noted the many ways that artificial intelligence, from Visual AI to tools such as transcription, translation, and meeting summation, was now an integral part of collaboration spaces.
In short, AI is no longer a “nice to have.” It’s a must.
AI Is No Longer Optional
AI-powered features are now standard in leading video conferencing platforms. For example:
- Zoom Rooms® video conferencing has introduced Smart Gallery, “which displays multiple video feeds from a single conference room. This allows the Zoom Rooms cameras to focus more closely on groups of participants and display these people more clearly to remote attendees.” The platform also offers AI Companion transcription and voice command options that are constantly being updated and enhanced.
- Microsoft Teams Rooms now offers Cloud IntelliFrame, “a new experience that allows online meeting attendees to see people in Teams Rooms more clearly through the smart video feeds of in-room participants. These smart video feeds are created by zooming into the faces of the in-room participants and by eliminating distractions, thereby enhancing the hybrid meeting experience.” Many users are likely already familiar with the platform’s speaker recognition capabilities and Microsoft® Copilot software integrations, too.
These features are cloud-enabled, but many are performance-critical; they require real-time responsiveness (especially for functions such as framing and speaker switching), demand low latency and high reliability, and require local data handling for privacy and compliance.
That’s why spaces need AI that operates at the edge, in the device, in the room.
Where Edge AI Makes the Difference
In fact, there are some projects where edge AI solutions are an absolute must. The reasons become abundantly clear when you consider use cases such as:
- Executive boardrooms: In these installations, you need instant speaker recognition and real-time transcription with zero lag, even in fast-paced discussions. These systems need to handle multiple cameras, mics, and streams simultaneously without “round trips” to the cloud or performance degradation.
- Hybrid classrooms: These projects require live captioning that stays accurate without falling behind.
- Government or finance: Local processing ensures compliance and data sovereignty, in addition to offering offline functionality for secure or air-gapped environments.
There’s another issue with the expanding adoption of these solutions; namely, most existing processors weren’t built for AI workloads. They struggle to run multiple AI models, such as audio, video, and transcription; they can overheat or lag in environments where they’re always “on, and they can deliver inconsistent performance under heavy data loads.
The Crestron Collab Compute
After taking all of this into consideration, Crestron developed a new purpose-built solution made for AI at the edge: the Collab Compute with Intel® Core™ Ultra processor. Designed with AI-enhanced collaboration in mind, this powerful “brain in a box” features an integrated Neural Processing Unit (NPU) that offloads AI tasks from CPUs and GPUs, enabling platform-native AI features without overtaxing the system.
Crestron built the Collab Compute with future-readiness in mind, giving it the power to handle next-gen AI features from Microsoft Teams, Zoom, and more. We made sure that those who invest in our edge-ready hardware can be confident in its compatibility with future platform updates.
When it comes to AI solutions, the cloud is critical but it’s not enough, especially as user demands evolve and hybrid workers return to the office. As we mentioned elsewhere in the blog post we quoted above: “This technology is raising people’s expectations for when they go into a collaboration space,” says Hintze. “If I’m used to sitting in my own home office getting meeting transcription notes and all the other benefits of the attendant AI technology, and then I go into the office and meet with people in person, I'm going to expect the benefits of having that agent AI helping and facilitating that meeting.”