The Ultimate Guide to AI Infrastructure
A curated Irish edition of TechDay news, analysis, interviews, reviews, job moves, and related resources for AI Infrastructure.
What to know about AI Infrastructure
AI Infrastructure explores the hardware, software, and systems that make modern artificial intelligence possible. This tag covers everything from compute and storage architectures to networking, data pipelines, and observability stacks that keep AI workloads reliable and efficient.
Stories here dig into practical questions: how to design scalable training and inference clusters, choose between GPUs and emerging accelerators, manage feature stores, and orchestrate distributed workloads. You’ll find discussions of MLOps practices, cost optimization, performance tuning, and the trade-offs behind different infrastructure patterns.
Whether you’re building a new AI platform or evolving an existing stack, this tag helps you understand the components, constraints, and design decisions that sit underneath AI products. Reading these pieces will give you concrete examples, architectural patterns, and lessons learned that you can apply to your own systems.
Irish AI Infrastructure News
Regional stories with direct local relevance
Analyst Insights
Research and market analysis connected to AI Infrastructure
Tencent rolls out Hy3 internationally for enterprise AI
Ethyca launches Astralis to govern enterprise AI data
Fortinet launches FortiGate 1200G with FortiSASE Outpost
Dell forum in Dublin to tackle AI scaling challenge
Vultr adds AMD MI455X GPU & Helios rackscale support
Featured News
John Margerison on the new class of employee: AI managers
Businesses should treat AI like a new hire, as weak oversight could expose sensitive data and leave staff needing fresh skills to stay relevant.
Exclusive: Virtuozzo sees GPU clouds reshape AI infrastructure
AI demand is pushing cloud providers towards GPU-as-a-service models, with efficiency and utilisation emerging as key differentiators.
Marvell targets AI connectivity bottleneck with NVIDIA boost
AI data centres are hitting copper limits, pushing Marvell and Nvidia towards optics as clusters grow larger and more distributed.
Expert Columns
Interviews
Interviews and video coverage from the networkRecent AI Infrastructure News
Enlightra uses Yokogawa analysers for AI data-centre links
Demand for denser AI data-centre links is pushing Enlightra to validate comb-based laser chips with high-resolution spectrum testing.
AHEAD opens Reading Foundry as European production hub
Local AI infrastructure deployments in Europe should get faster, with customers able to build, test and ship racks from Reading.
Enterprise SSD prices jump 5% as AI storage costs soar
AI cloud operators face sharply higher storage bills, with a mixed-fleet design costing almost USD $39 million less than all-flash over three years.
AHEAD opens Reading Foundry as European production hub
The Reading site gives European customers a local hub for AI infrastructure build-outs, cutting deployment risk and delays.
Everpure wins second top-five hyperscaler storage deal
The agreement could lift revenue from fiscal 2028 as cloud operators seek denser, more power-efficient storage for AI-heavy data centres.
QumulusAI lands Blackwell GPU deal with hedge fund
The deal ties QumulusAI's returns to a hedge fund's trading gains, adding profit sharing to standard compute fees and heightening revenue risk.
Google adds BigQuery search tools for unstructured data
Customers can now keep document search and embedding work inside BigQuery, as Google rolls out AI search tools to cut extra pipelines and indexes.
Secureframe launches hosted AI server for compliance
Defence contractors could cut compliance overhead as Secureframe's new tools flag federal obligations, gaps and costs for CMMC and FedRAMP.
NVIDIA expands open world models for physical AI development
Open models matter because robots and vehicles need task-specific tuning, and Nvidia is betting on Cosmos 3 to fill that data gap.
Google expands on-premises AI for sovereign data needs
Nearly half of senior IT leaders now prioritise data residency controls, as regulators and governments push AI workloads into local environments.
Mirendil taps Google Cloud AI hypercomputer for research
The startup gains faster access to scarce AI compute as it prepares to scale model training across both TPU and Nvidia systems.
AWS adds vector search to DynamoDB for AI retrieval
Businesses can now keep AI retrieval and live app data in one place, as the service cuts data copying and extra sync pipelines.
Ofgem weighs tougher rules for data centre grid queue
Tighter queue rules could speed grid access for legitimate projects, but risk pushing more data centre operators towards pricier off-grid power.
UiPath expands Google Cloud use for shared GPU fleet
Higher availability and more predictable GPU access will support UiPath's AI workloads as scarce H100 chips become harder to secure.
Runware launches modular AI inference pods in weeks
The modular units aim to ease AI compute bottlenecks by bringing 1 megawatt of capacity online in weeks, not years.
OpenSearch 3.8 boosts vector search & observability
Up to 4.16 times faster vector ingestion could help OpenSearch customers cut AI search latency and reduce storage overhead.
Semtech backs linear pluggable optics for AI data centres
Lower power draw in dense AI networks is driving interest in linear pluggable optics, though Semtech says the design is not a universal replacement.
Nvidia opens cuFile APIs to speed AI storage access
The open-source move could cut latency to microseconds as AI systems increasingly need storage to act like part of the compute path.
Bitzero adds Vertiv to data centre partner network
The partnership is meant to ease power and cooling bottlenecks as AI data centre demand forces operators to secure specialist systems earlier.
Rehlko warns AI data centres need dynamic power checks
Operators face reliability risks as AI workloads strain generators, batteries and UPS systems beyond the limits of installed capacity.