Gcore

Looking forward to our Gcore community event in Luxembourg tomorrow 🇱🇺 🙌 Our goal is simple – bringing together startups, engineers, geeks, founders, and entrepreneurs to connect, exchange ideas, and build a stronger local tech community together. Excited to reconnect with familiar faces, meet new people, and spend a great evening together! See you tomorrow?

Most of the market still treats AI as a data center problem. It isn’t. AI is becoming as well a network, latency, sovereignty, security, and economics problem. Interesting point raised in The Register: many neoclouds scaled compute first, but networking is now emerging as the real bottleneck. My view: Most neocloud players focus on building larger GPU clusters and more megawatts. That is only phase one. The future is an AI Grid: • Distributed inference across regions and edge locations • High-performance backbone connectivity between sites • Low-latency routing for real-time AI workloads • Built-in DDoS and security resilience • Data sovereignty and workload mobility across jurisdictions • Automated traffic engineering at global scale And one more point many underestimate: the cost of being off-network at this investment scale is massive. If you invest billions into GPUs and power, but rely on weak transit, poor peering, congested routes, or fragmented security, you create: • Lower GPU utilization • Higher inference latency • Lost enterprise workloads • Expensive idle capacity • Revenue leakage during outages or attacks • Structural margin pressure from third-party network dependency At hyperscale economics, even small inefficiencies become very expensive. Many AI Neoclouds came from a compute / crypto-native mindset: rack the hardware, power it, monetize it. But enterprise AI needs more than compute. It needs a carrier-grade global AI ready fabric. Gcore’s mission is to build the AI Grid by combining compute, network, security, sovereignty and AI Factories in partnership with telecom providers. https://lnkd.in/d-qZx2HY