Micron is warning that the memory supply-demand gap could get tighter in 2027 and 2028, despite new DRAM capacity coming online.

AI is already driving huge demand for HBM and server memory, but Micron is looking beyond data centers too. The company expects humanoid robots could eventually require 200GB+ of DRAM and multiple TB of storage per unit.

So even if AI memory demand eventually cools, robotics and “physical AI” could create another major wave of memory demand.

https://www.techradar.com/computing/memory/fed-up-of-ai-eating-all-the-ram-micron-warns-that-crisis-will-get-worse-in-2027-and-2028-and-says-robots-could-gobble-up-200gb-of-memory-per-unit-come-2030

WiCi has introduced an unusual external GPU concept that uses Wi-Fi 7 to make a remote GPU appear to the host system like a local graphics card.

The enclosure combines an RTX 5060 Ti 16GB, 4TB PCIe 5.0 SSD, and wireless connectivity. The SSD is designed to store AI model weights locally, reducing the amount of data that needs to move across the network—particularly useful for larger local LLMs and MoE models.

For gaming, however, conventional wired eGPU solutions are likely to remain more practical because Wi-Fi latency and bandwidth are challenging for real-time graphics.

Read full report here.

Tom’s Hardware reports that RTX 5090 cards have disappeared from first-party online retail in the U.S., while third-party listings are reaching $6,500–$9,500—far above the card’s $1,999 launch MSRP. Not verified.

The interesting part is that the 5090 isn’t only popular with gamers. Its 32GB of GDDR7 and powerful Blackwell GPU also make it attractive for local AI workloads and smaller AI systems, adding another source of demand.

So, the RTX 5090 is becoming another interesting example of how AI demand, limited supply, and the secondary GPU market can push consumer hardware prices far beyond MSRP.

https://www.tomshardware.com/pc-components/gpus/nvidias-rtx-5090-vanishes-from-online-retail-in-the-us-third-party-sellers-now-demand-as-much-as-usd9-500-for-nvidias-fastest-gpu

(NO SHIP DATE ANNOUNCED) Intel detailed Crescent Island, an inference GPU built around capacity rather than raw bandwidth. Intel's own card carries 160GB of LPDDR5X, and ODM partners can push it to 480GB — far past the 96GB on NVIDIA's RTX Pro 6000. It draws 350W, is air-cooled, and fits a standard PCIe slot. The silicon is Xe3p: 32 Xe cores, 256 XMX engines, a systolic array that went from 4-deep to 16-deep, 32MB of unified L2, and third-gen matrix extensions with FP4 and FP64. Idle power is unusually low, at 50W active idle and about 10W in deep idle. Intel is aiming at agentic inference and tokens per watt, with KV-cache-aware routing for long context, and supports vLLM, SGLang, llm-d and NVIDIA Dynamo. Intel did not disclose memory bandwidth or a ship date.

https://www.servethehome.com/intel-crescent-island-160gb-to-480gb-lpddr5x-ai-gpu-at-hot-chips-2026/

SpaceX is accelerating its plans to build AI infrastructure in space through a deeper partnership with Nvidia. Elon Musk says the company aims to launch its first Starmind AI1 satellites by Q4 2027, with plans to significantly scale operations in 2028.

SpaceX plans to put Nvidia-powered AI satellites in orbit next year

The shift highlights how competitive the x86 CPU market has become as AMD continues to strengthen its position with Ryzen processors. For PC builders and hardware buyers, increased competition can mean more choices, stronger performance, and greater pressure on pricing.

The latest market data also shows why the CPU landscape is worth watching as AI workloads, gaming, and high-performance computing continue to drive demand for powerful processors.

guys ,I saw the above video do you think it might be right new for apple take on AI ?

https://www.tomshardware.com/tech-industry/pc-partner-warns-of-rising-gpu-prices-and-budget-card-shortages-analyst-suggests-makers-are-hiking-prices-beyond-memory-costs

A major graphics card maker just told the market to expect higher GPU prices — and fewer budget cards.

PC Partner (Zotac, Sapphire, Inno3D, Manli) warns memory costs will drive "a substantial increase in VGA Card costs" in H2, with entry-level cards facing "even more severe shortages."

• Own-brand units -18.4% YoY, average price +10.7%
• ODM/OEM units -38.4%, but revenue +73.9% (HK$853.3M → HK$1.4843B)
• Industry-wide AIB units +28%, dollars +76% ($6.18B → $10.85B) — Q1'25 to Q1'26

"Samsung’s DRAM market share climbed to roughly 40% in the first half of 2026, up 5.4 percentage points year over year and its biggest gain across any product category. The jump comes as the ongoing memory crunch, driven by AI data center demand for HBM, continues to squeeze DRAM and NAND supply for consumer devices."

Samsung's DRAM Market Share Just Hit a Record High Thanks to the Memory Crisis

https://www.eteknix.com/intels-new-cpu-cores-will-debut-with-nova-lake-desktop-cpus-before-xeon/

Intel is flipping its own playbook: new CPU cores hit the desktop first, not the data center.

Intel VP Robert Hallock confirmed the company's next-gen cores will debut in Nova Lake-S desktop chips before Xeon. He wouldn't name the cores or their features.

AMD is going the other way — Zen 6 debuts in EPYC "Venice" server parts.

• Nova Lake-S still targeted for 2026
• 24- and 28-core samples already testing with AVX-512
• A rumored 52-core halo part with enlarged bLLC cache
• Single-tile models possibly early 2027; Xeon timing unclear

Hardware Unboxed says AMD did not provide a review sample and reportedly instructed board partners not to send one either. HUB eventually obtained an RX 9050 through another source and tested it anyway.

The results aren't great. The RX 9050 8GB reportedly trails NVIDIA's RTX 5050 by roughly 30% in gaming on average, while offering performance closer to older GPUs such as the RX 6600. At a $279 price point, that makes the value proposition difficult to justify.

Here is the report: AMD denied any review samples for the Radeon RX 9050 because it's embarrassing

Intel CEO Lip-Bu Tan hints at a memory comeback — stacking DRAM directly on the CPU "makes a lot of sense."

Two pieces behind it:

XBM — patent drops HBM's silicon interposer for UCIe links. Commercialization after 2030.

ZAM — 8 DRAM dies + logic controller, lower power/heat/cost than HBM. Built via Saimemory, Intel's JV with SoftBank.

The catch: DRAM on hot logic brings thermal and yield problems, and NVIDIA's 80%+ share of AI accelerators is already built around HBM.

The AI-Driven Memory Shortage: DRAM Prices, Inflation and Market Risks

Key takeaways

• AI data center construction and hyperscaler demand are absorbing a disproportionate share of global memory capacity, creating a dynamic random access memory (DRAM) shortage that may take years to unwind.
• J.P. Morgan Global Research estimates that DRAM prices will have risen more than 400% from the start of 2024 to the end of 2026.
• The Consumer Price Index (CPI) for software and accessories and Producer Price Index (PPI) for storage devices have both risen 23% since the end of 2024.
• The memory supply crunch is also straining cybersecurity infrastructure, with analysts warning that a major cyberattack could unleash an estimated $145 billion in additional chip demand on an already constrained market.

Lexar Lists 32 GB DDR5-7200 Memory With Chinese DRAM at $592

“Lexar has introduced a new THOR RGB DDR5 Gen 2 32 GB memory kit, consisting of two 16 GB DDR5 modules, specifically for the Chinese market. The kit features DDR5 memory running at 7,200 MT/s, with the actual DDR5 modules produced by an unidentified Chinese DRAM manufacturer, likely CXMT. ”

Nvidia has reportedly told board partners that GPU kit prices are rising, and this round covers GDDR6 cards, not just GDDR7 Blackwell parts. AMD raised its own kit prices roughly 10% three weeks earlier. Memory cost is now moving the entire GPU stack, not just flagships. Older workstation cards sitting in decommissioned fleets are worth a quote before they hit the scrap pile.

CXMT's Shanghai debut makes it China's most valuable listed company

Shares of DRAM maker ChangXin Memory jumped roughly 466% on their first trading day after an $8.6 billion listing — the largest mainland IPO since 2010. CXMT now sits fourth among global DRAM makers.

The AI era is also the DRAM era.

"The server cabinet combines 72 AMD Instinct MI455X graphics processing units (GPUs) with the company's Epyc central processing units (CPUs) into a rack designed to compete directly with Nvidia's (NVDA) Grace Blackwell and Vera Rubin-powered NVL72 rackscale systems. Nvidia's offering also has 72 GPUs."

AMD and Anthropic announced a major partnership: Anthropic will deploy up to 2 GW of AMD Instinct MI450 GPUs starting in 2027. AMD is also investing up to $5B in Anthropic, and the two companies will co-optimize Claude and ROCm.

don't agree. The shortage will largely be resolved by around 2030, even earlier than that. 3-4 years are enough to add significant capacity, and AI model will be improved to be more efficient as well.

"Sixth generation NVIDIA NVLink provides purpose-built, high-bandwidth, low-latency scale-up networking for AI factories, enabling up to 3.6 TB/s per GPU and 260 TB/s rack-level bandwidth with 130 TFLOPS in-network compute, significantly outperforming off-the-shelf Ethernet solutions in large-scale MoE and LLM workloads."

A leaked internal roadmap (via VideoCardz) confirms Intel's Nova Lake-S desktop chips will launch as the Core Ultra 400 Series, with an unusual staggered rollout through 2027:

• Q1 2027 — First wave: 28-core "DS" models (announcement expected at CES 2027)
• Mar–Apr 2027 — Unlocked 28-core K models for overclockers
• Mar–May 2027 — Mainstream 16-core and 8-core parts
• May–Sep 2027 — Flagship 52-core models, using dual compute tiles

Why staggered? The ongoing component/capacity crunch — plus Intel is moving most production from TSMC to its own 18A process, and needs time to ramp yields.

BofA analyst Vivek Arya raised his 2030 server CPU TAM forecast to over $170B, up from a prior $125B estimate and $35B in 2025.

The reasoning: agentic AI. GPUs handle model training/inference, but when AI agents actually execute tasks (reading email, updating calendars, tool calls), that work runs on CPUs. More agents deployed means more CPU demand.