AI Weekly Malaysia

CoreWeave CEO Mike Intrator says the company has signed A100 GPU contracts extending into 2029, demonstrating that Nvidia's 2020-era GPUs remain profitable nine years post-deployment. Power constraints and legacy infrastructure costs make older GPUs economically viable even as newer chips arrive.

Why: If you're budgeting GPU compute for AI workloads, don't assume older GPUs like the A100 will become cheap or obsolete soon — CoreWeave is locking customers into multi-year A100 contracts through 2029, which signals sustained pricing power for legacy hardware. This affects cost planning for anyone renting cloud GPU capacity or deciding whether to wait for next-gen capacity versus contracting now.

An opinion piece arguing that hyperscalers are using AI-driven demand to lock up the enterprise hardware supply chain, leaving businesses little choice but to rent compute back from them. Nutanix CEO Rajiv Ramaswami noted the fastest way to get a new server is now to rent from a hyperscaler; Micron, SK Hynix, and Seagate have long-term supply deals favoring their largest customers; AMD has sweetheart deals with OpenAI and Meta. AWS CEO Andy Jassy says AWS recoups server spend in under three years on assets with 5-6 year useful lives, with datacenters designed to last 30 years.

Why: If hyperscalers continue cornering hardware supply, bootstrapping or cost-sensitive Malaysian startups that planned to own on-prem or colo gear will face longer delivery times and higher prices, making cloud rental the de facto path. Founders should model infrastructure costs assuming hyperscaler pricing power persists rather than betting on cheaper self-hosted hardware, and consider locking in longer-term cloud commitments if AI compute is core to their product.

OVH Cloud CEO Octave Klaba warned of server rental price hikes up to 87% (gaming servers) and 40-59% (other recent servers) starting September 2026, driven by RAM costs rising 6x (heading to 12x next year), NVMe drives up 7x, HDDs up 3.5x, and CPUs/motherboards up 15-20%. OVH is also decoupling storage (€0.000146/GB/h) and IP addresses (€0.0027/h) from Gen3 instances starting October 1st, and dropping 1-month, 6-month, and 24-month saving plans.

Why: If you run on OVH or any budget European cloud, lock in 12 or 36-month saving plans now before September, and recheck your October bill for newly separated storage and IP line items. More broadly, the AI-driven hardware cost inflation Klaba describes is not OVH-specific—expect similar upward pressure across all non-hyperscale providers, which matters for SaaS unit economics and infrastructure cost projections.

Analyst Claus Aasholm estimates that Amazon, Alphabet, Meta, and Microsoft collectively hold nearly $2 trillion in purchase commitments for AI hardware and memory as of Q2 2026, with Alphabet leading at $811 billion and Apple trailing at $57 billion. A significant portion targets memory components, reflecting a shift from Apple's historical dominance in long-term component contracts to hyperscalers driving the market.

Why: If you're budgeting for GPU or AI inference costs over the next 1-2 years, this signals sustained pricing pressure and scarcity for AI hardware and memory — hyperscalers are locking up supply years ahead. Malaysian founders and developers relying on cloud AI compute should expect continued high costs for GPU-backed services and may need to weigh smaller-model or CPU-based inference strategies sooner rather than later.

Oracle is reportedly planning another round of layoffs after already eliminating 21,000 full-time positions and spending most of its $2.1 billion restructuring budget. Some teams face double-digit percentage cuts, though the report does not specify which product lines or geographies are affected.

Why: If your stack depends on Oracle Cloud, Oracle Database, or Oracle-owned technologies (MySQL, Java via support contracts), continued deep restructuring raises the risk of degraded support response times and product roadmap uncertainty. Builders should evaluate whether critical workloads have viable migration paths or multi-cloud fallbacks before any service-level changes materialize.