A logic board with water damage is generally regarded as e-waste because, unless some people can salvage the components, it’s as good as useless. However, one Redditor didn’t lose hope when his M1 Max motherboard suffered a burn hole as he decided to perform a “transplant” of the Apple Silicon using a donor board. The problem is that these chipsets are typically locked to their original board, but luckily, the adventurous tinkerer had a workaround for this obstacle. The donor board would not recognize the M1 Max, so every important component on the original board was transferred to the new […]
The past few months in PC hardware have been eventful by any measure. Apple shipped the M5 Pro and M5 Max, Intel clarified its core architecture roadmap, and anyone trying to build a new PC has been quietly suffering through DRAM pricing that refuses to behave. These stories look separate on the surface. They are not.
The thread connecting all of them is memory, specifically the growing gap between what compute silicon can do and what the memory feeding it can keep up with.
Start with Apple. The M5 Pro and M5 Max are genuinely interesting chips, not just because of the performance numbers but because of what Apple was forced to do architecturally to get there. Fusion Architecture, Apple’s move to a dual-die SoC design, exists primarily because a single monolithic die cannot accommodate 40 GPU cores, 614 GB/s of unified memory bandwidth, and 18 CPU cores without hitting yield and cost walls. The memory bandwidth figure is the one that matters most for AI workloads running locally, and Apple knows it. The M5 Max at 614 GB/s is not chasing gaming benchmarks. It is chasing large language model inference throughput, and bandwidth is the bottleneck that determines how fast it runs.
That bandwidth problem is not unique to Apple. It is an industry-wide crisis, and the full picture of why is considerably more complicated than most coverage lets on. The AI memory crisis running through the data centre right now traces back to physics: DRAM scaling has not kept pace with compute scaling, HBM production is constrained by TSV fabrication yields and advanced packaging capacity, and the most powerful AI systems on the planet spend more time waiting for data than actually processing it. That is not a software problem. It is a silicon and packaging problem, and it does not have a quick fix.
For anyone building a PC right now, the consequences land differently, but they are still real. DRAM pricing has been pulled in two directions simultaneously: AI infrastructure demand is bidding directly on supply at the high end, while consumer DDR5 pricing has been volatile enough to meaningfully change the calculus on a new build from one month to the next. If you have been holding off on a memory upgrade, waiting for prices to settle, the honest answer is that the market dynamics driving this are structural rather than cyclical. Prices may ease, but the pressure from AI demand on overall DRAM supply is not going away.
On the Intel side, there has been a lot of noise about the company killing off its hybrid core architecture in favour of a unified core design. The reality, as is usually the case with Intel roadmap speculation, is more nuanced. Intel is not killing P-cores, at least not in the timeframe the headlines suggest. The unified core concept is a longer-term architectural direction, and the practical implications for anyone buying an Intel platform in the next year or two are limited. What matters more right now is whether Intel’s current generation delivers the performance-per-watt improvements it needs to stay competitive, particularly in a market where Apple Silicon has reset expectations for mobile efficiency and AMD’s desktop Zen 5 parts are putting pressure on the high end.
The bigger picture across all of this is straightforward: memory is the constraint that determines where performance goes next, whether that is Apple designing a new packaging approach to get more bandwidth, hyperscalers paying premiums to secure HBM allocation, or a consumer trying to figure out whether now is a sensible time to buy a 32 GB DDR5 kit. The compute side of the industry has never been more capable. The memory side is struggling to keep up, and that tension is shaping every major hardware decision being made right now.
Apple has launched a major update across its Mac lineup, introducing the M5 Pro and M5 Max chips alongside refreshed MacBook Pro and MacBook Air models. The new processors bring Apple’s Fusion Architecture, higher CPU and GPU performance, and expanded on‑device AI capabilities.
The M5 Pro and M5 Max are built from two 3nm dies connected into a single SoC, enabling higher bandwidth and more parallel compute. Both chips feature an 18‑core CPU with six ‘super cores' and twelve performance cores, which Apple says deliver up to 30% faster performance in professional workflows. GPU configurations scale up to 40 cores, each with a Neural Accelerator, resulting in more than 4x the peak GPU compute for AI compared to the previous generation.
These chips power the updated 14‑inch and 16‑inch MacBook Pro models, which retain the same design but gain faster SSDs, Wi‑Fi 7 and Bluetooth 6 via Apple’s N1 wireless chip, and higher base storage. The 14‑inch MacBook Pro with the M5 Pro starts at $2,199, while the 16‑inch version starts at $2,699. Configurations with the M5 Max begin at $3,599 (14‑inch) and $3,899 (16‑inch).
Apple also introduced the new MacBook Air with M5, available in 13‑inch and 15‑inch sizes. The M5 chip features a 10‑core CPU and up to a 10‑core GPU, with each GPU core also including a Neural Accelerator for AI workloads. The MacBook Air now starts at 512GB of storage, replacing the old 256GB baseline. The newer model can be upgraded to up to 4TB of storage and it also gains the new N1 wireless chip, providing support for WiFi 7 and Bluetooth 6. Pricing starts at $1,099 for the 13‑inch model and $1,299 for the 15‑inch model.
KitGuru Says: Are you thinking of getting a new-gen MacBook this year?
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