Zenlayer expands edge infrastructure with distributed inference for global AI scaling
Hyperconnected cloud company Zenlayer recently released “Distributed Inference,” a global AI inference platform for high-performance processing at Tech Week in Singapore
By using the global edge infrastructure of Zenlayer, the platform solves pain points such as wasted GPUs, unbalanced loading and high latency.
It incorporates optimization for scheduling, routing, networking and memory management which will improve edge AI performance and simplify AI deployment.
“Inference is where AI delivers real value, but it’s also where efficiency and performance challenges become increasingly visible,” says Joe Zhu, founder and CEO of Zenlayer. “By combining our hyperconnected infrastructure with distributed inference technology, we’re making it possible for AI providers and enterprises to deploy and scale models instantly, globally, and cost-effectively.”
It includes elastic GPU access, automatic orchestration across 300+ points of presence (PoPs) and a private backbone reducing latency up to 40%. In addition to that, the solution is able to accommodate various types of AI models out-of-the-box for easy accessibility and comes with real-time monitoring features making it easier for global scaling.
Zenlayer is working toward facilitating worldwide real-time AI through which the firms may concentrate on innovation rather than deployment complexity.
Zenlayer has more than 300 edge nodes in over 50 countries, serving over 85% of the world’s internet users with less than 25ms latency and a fully redundant global network. The company is further extending its AI-ready service offerings to accelerate the full potential of AI at the edge.
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Article Topics
AI inference | AI/ML | edge AI | GPU | Zenlayer
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