According to an internal SK Hynix analysis, the DRAM supply shortage isn’t just a short-term cycle — it may persist through 2028. With rising AI and server memory demand absorbing capacity, limited production growth, and declining inventories, memory markets are tightening globally. Discover what this means for pricing, procurement, and secondary markets.
Epoch AI’s latest report reveals how inference costs are dropping, frontier AI is becoming accessible on consumer-level hardware, and compute infrastructure is expanding rapidly — fueling broader adoption and demand for AI GPUs, servers, and efficient compute setups. These shifts are reshaping the AI hardware market, creating opportunities for deployment, resale, and strategic lifecycle management.
A leaked roadmap reveals a major pivot for 2026-2027: pulling back from costly, niche bets like immersive AR/VR headsets and instead channeling focus into a foldable iPhone, AI-powered smart glasses, and its profitable core hardware. This isn't a retreat, but a recalibration. Apple is streamlining its ambitions, prioritizing commercial reality over futuristic fantasies, and betting big that the next decade will be defined by practical AI and refined ecosystem devices, not the metaverse. For anyone invested in the tech landscape, this shift signals where the industry's true north is heading.
Memory is no longer a background component—it’s becoming a defining constraint.
As DRAM prices are expected to rise again into Q1 2026, smartphone and laptop manufacturers are facing mounting cost pressure that is reshaping pricing strategies and slowing long-standing upgrade cycles. From entry-level smartphones potentially rolling back to 4GB RAM, to ultrathin laptops struggling with rising LPDDR costs, the ripple effects are moving downstream. In a market increasingly shaped by AI demand and constrained supply, higher prices and more conservative configurations may become the new normal for consumer devices.
The CPU landscape is entering a major shift as 2026 approaches.
Intel’s Panther Lake brings high clocks, integrated Arc graphics, and on-device AI to laptops, while AMD’s X3D CPUs and Zen 6/Zen 7 roadmap hint at the next evolution of gaming performance and AI-ready processors.
From NPUs and AI acceleration to chiplet designs and hybrid CPU architectures, this deep dive explores the most important CPU trends shaping laptops, desktops, and workstations in 2026.
Google is making its proprietary TPUs (Ironwood) available to Meta, directly challenging Nvidia’s 90% dominance. The massive cost of AI compute is forcing tech giants to turn from Nvidia's biggest customers into its fiercest competitors.
This strategic shift will wipe out $150B in market value and signals the end of a near-unbreakable monopoly. Can Nvidia's software moat (CUDA) hold up against the combined might of hyperscalers?
NVIDIA just delivered the biggest CUDA overhaul in 20 years. CUDA 13.1 introduces the new Tile programming model, making GPU development more powerful, portable, and future-proof — especially for Blackwell-class AI workloads.
Is this really offering something new compared to smart glasses? Many advanced smart glasses can already record, transcribe, and assist with memory or focus. I’m curious whether this pendant brings any unique advantages—like better privacy, always-on functionality, or improved AI integration—or if it’s just another form factor for similar tech. Either way, Meta shifting more resources from the metaverse into AI wearables is an interesting move.
AI is reshaping the memory market faster than anyone expected. Hyperscalers like AWS, Google, Oracle, and Microsoft are locking in DRAM, HBM, and NAND supply all the way to 2028, creating a prolonged DRAM supply crunch that’s keeping prices elevated through 2026 (and likely beyond).
For everyone outside the cloud giants — enterprises, AI startups, OEMs — this means higher costs, longer lead times, and the need for smarter IT planning. The secondary hardware market is also becoming a critical option as budgets tighten and demand keeps climbing.
• Why AI is driving historic memory shortages
• How CSPs are securing long-term capacity
• When analysts expect relief (hint: not soon)
• What businesses can do to adapt
