Latest AI and tech news
New Nscale research of 500 U.S. AI-native leaders shows how infrastructure choices shape product velocity, engineering capacity, and compliance
Nscale is exploring how simulation can inform the way it designs, deploys, and operates AI data centers with NVIDIA Omniverse Libraries and NVIDIA DSX Sim.
Nscale backs security for agentic AI, with NVIDIA OpenShell and Sentry on BlueField-4 providing continuous, in-silicon protection across the Vera Rubin platform.
New research shows how much engineering time infrastructure consumes and what to do about it.
AI teams keep control of the application and compute while Nscale takes care of the serving layer.
Run NVIDIA’s open multimodal model, Nemotron 3.5 Super VL, for agentic AI on reserved GPU capacity with Nscale Dedicated Inference.
NKS gives AI teams managed Kubernetes on Nscale GPU infrastructure, keeping APIs, manifests, and RBAC they already use while Nscale handles the control plane, cluster lifecycle, and infrastructure beneath it.
Kubernetes runs containerized workloads across a fleet of machines. Here's how that works for AI, and what managed Kubernetes handles for you.
NVIDIA Vera CPUs on Nscale will deliver extreme CPU performance, memory bandwidth, and efficiency needed to power the next generation of agentic AI workloads.
Time to first token (TTFT) brings infrastructure performance closer to what users actually feel.
VAST Data Co-Founder, Jeff Denworth, on building the AI grid, a distributed, interconnected AI infrastructure network.
How Nscale automated GPU fault diagnosis and remediation across the fleet.
Insights from Nscale, NVIDIA, and VAST Data on why time to first token (TTFT) is becoming one of AI infrastructure's most useful metrics.
AI infrastructure is more than GPUs and megawatts. See how product is key to turning compute capacity into successful workloads, usage, and growth.
Time to first token (TTFT) explained: what it measures, why it has become one of AI infrastructure's defining metrics, and what drives it up or down across the stack.
Serverless inference lets teams deploy AI models without managing GPUs or serving infrastructure. Learn how it works and why it matters.
AI costs are shaped by more than model pricing. Here's how infrastructure, agentic workloads, and model strategy combine to determine the economics of AI at scale.
As AI moves into production, the right level of infrastructure abstraction becomes a competitive advantage. Here's why control matters at scale.
AI-native companies build infrastructure differently. Here's how that approach improves the economics of serving AI.
Nscale has achieved NVIDIA Exemplar Cloud status on GB300 NVL72, validating large-scale AI training performance, reliability, and reproducibility across its production fleet.
Token prices are falling yet enterprise AI bills keep rising. Organizations that optimize for inference economics will be better positioned to scale AI efficiently.
Token economics, performance consistency, and data residency are now product decisions. Not every infrastructure provider can optimize them.
How Nscale built an AI software engineering agent designed for control, quality, and operating infrastructure at scale.
As AI scales, the biggest competitive advantage is shifting from models to the infrastructure beneath them. Here’s why the AI stack now determines who wins.
Europe faces a false choice on AI compute. The real answer lies in geography and Portugal is positioned to be one of the most important hubs.
When the starting point is AI rather than general-purpose cloud, every layer of the stack changes, and so does the relationship with the customer building on top of it.
How to deploy sovereign AI without compromising speed, control, and cost.
Kimi K2.5 brings advanced agentic reasoning, design-to-code capabilities, and production-ready performance to fully managed inference endpoints on Nscale.
Explore how Telcos can federate national AI grids into a global AI fabric without losing control.
Learn how AI is changing network infrastructure and the evolving role of telecom operators.
Telcos built the infrastructure that makes edge AI possible. The next step is turning that foundation into sustainable AI revenue.
AI workloads are pushing cloud-native tooling beyond its design limits, challenging long-held assumptions about abstraction, and redefining what modern infrastructure needs to deliver.
Explore how distributed AI infrastructure will redefine cloud, telecom, and enterprise architecture.
Nscale ranks as Overall Leader, Top Innovator, and Top Implementer in ABI Research’s neocloud provider assessment of 14 companies.
Nscale is redefining how the AI era is built, powered, and scaled through record growth, global partnerships, and resilient infrastructure.
Explore how Nscale’s Fleet Operations transforms the complex lifecycle of a GPU node into a predictable, high-performance pipeline.
Explore how our internal automation and observability systems bring reliability, scale, and intelligence to GPU infrastructure.
In Glomfjord, Norway, the future of AI is built on community, purpose, and shared progress.
Explore our data center in Glomfjord, Norway, where innovation, design, and renewable energy are transforming how compute is built and powered.
We are building the AI supply chain for continuous compute to keep up with the pace of demand and innovation.
Organizations across Europe are rethinking what resilience means in an AI-driven economy.
Nscale are proud to share the opening of our new office in the heart of Mayfair.