LOOKING AHEAD, HOW WILL INNOVATIONS LIKE AI-DRIVEN COMPRESSION, EDGE COMPUTING AND 5G IMPACT LATENCY – AND WHAT CHALLENGES MIGHT THEY POTENTIALLY PRODUCE?
MATTHEW WILLIAMS-NEALE: AI-driven compression will optimise bit-rate decisions dynamically, reducing buffer requirements and improving quality under constrained conditions. Edge computing localises processing, compression, packaging and decision-making, cutting down end-to-end delay. 5G, particularly private networks, offers predictable, high-bandwidth wireless contribution, ideal for remote and pop-up productions. However, these innovations bring complexity: ensuring interoperability across AI models, managing orchestration at scale and maintaining consistent QoS on shared infrastructure. Broadcasters must implement effective and purpose-built solutions that offer end-to-end workflow visibility, adaptive resource allocation and robust security measures – supporting latency reduction without adding operational complexity. EVAN STATTON: Of the three, edge computing likely has the greatest near-term impact on latency because it reduces round-trip time between the player and origin, pushing content and processing closer to the viewer. AI may bring gains, but many of the big wins – like encoder and buffer tuning – are already well addressed through existing methods. That said, AI could play a bigger role at the edge, making real-time decisions about routing, quality or protocol to minimise latency further. A major future opportunity lies in data replication and distribution models that bypass traditional CDN caching. Additionally, with increased bandwidth, I-frame only or JPEG encoding could eventually be used to further reduce latency at both ends. VENUGOPAL IYENGAR: These technologies will be game changers. AI-driven compression
reduces bit rates without degrading quality, cutting processing and delivery times. Edge computing brings content closer to the user, and 5G radically improves last-mile connectivity, enabling true mobility in low- latency streaming. But these come with challenges: managing distributed edge nodes increases complexity, AI workflows demand robust training data and 5G integration raises questions around infrastructure interoperability. Our response has been to develop modular, API-first systems that allow plug-and-play with these emerging technologies, under the NexC umbrella. This ensures clients can evolve without being locked into rigid architectures. Latency is no longer a fringe concern – it’s central to the future of streaming and broadcast. Through platforms like NexC, Planetcast is pioneering cloud-first, AI- augmented and protocol-flexible solutions that redefine the latency equation. Whether for IPL-scale events or interactive OTT formats, we’re enabling media companies to meet real- time demands with speed, scale and stability. CIRO NORONHA: None of these technologies directly help the latency; most of them may actually have detrimental effects. For compression, the more time you have to compress something, the better job you can do. Using AI-driven compression can perhaps increase your quality, but it is very likely increasing your latency. Really, the only thing that can help is high-quality bandwidth availability all the way to the edge. If you have that, you have a chance at reducing latency by playing with protocols. If you don’t have that, the battle is pretty much already lost. For this, the technology that can help is 5G, simply because it will give you more bandwidth.
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