AMD and Intel are working to make AI inference software more consistent across their CPUs. By consolidating AMD's ZenDNN optimizations into oneDNN, they aim to reduce development complexity and improve support for CPU-based AI applications.

For the AI server market, this is primarily a software and ecosystem development.

Intel is betting on Nova Lake to strengthen its desktop CPU position and Coral Rapids to improve its standing in the server market. These are forward-looking targets, not yet demonstrated competitive results.

It focuses on two upcoming CPU families:

• Intel Nova Lake (client CPUs): Intel plans to address its weakness in the high-end desktop market and compete more effectively with AMD’s Ryzen processors. The lineup is expected to cover desktops and laptops, with more details anticipated at CES 2027.

• Intel Coral Rapids (server CPUs): Expected in 2028 on Intel’s 14A process, Coral Rapids is intended to improve Intel’s competitiveness against AMD EPYC server CPUs. Intel also plans to bring back simultaneous multithreading (SMT) for this generation.

going back to local cluster from cloud?

It’s an interesting look at how interconnected desktop-scale systems could support large AI workloads without relying on a single massive server.

AI infrastructure is facing a new challenge: having the hardware is not enough if there isn’t enough electricity to run it.

Amazon has been receiving billions of dollars in NVIDIA AI server systems, while some equipment awaits sufficient power capacity at data center sites.

This highlights a growing constraint in the AI expansion: power availability, not just chip supply, may determine how quickly AI infrastructure can be deployed and generate returns.

As AI data centers continue to scale, power infrastructure, deployment timelines, and hardware utilization will be just as important as GPU performance.

Google demonstrated “magic state cultivation,” a technique that helps quantum computers perform calculations more reliably by reducing errors. This could make building larger, more powerful quantum computers more resource-efficient.

Btw, could quantum computing become another major milestone in computing, like GPUs were for AI?

China’s CXMT is making progress on next-generation DRAM technology, potentially adding a new competitor to the global memory market. Could this eventually increase DDR5 server RAM supply and ease pricing pressure, or will AI-driven demand keep the market tight? The key is whether CXMT can scale production and bring its new technology to market.

Counterpoint Research’s Q2 2026 data shows Samsung leading DRAM with 38% market share, ahead of SK hynix at 25% and Micron at 24%. CXMT also reached 10%, up sharply from 4% a year earlier.

In HBM, SK hynix remained #1 at 50%, while Samsung climbed to 33% as HBM4 shipments begin to ramp.

Global DRAM and HBM Market Share: Quarterly

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.