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Lexar's Regional Manager for Australia & New Zealand predicts that RAM prices will double by the end of the year due to high demand for memory chips in AI build-outs. While some retailers are offering discounts on RAM modules, this is mainly to clear old stock before new, more expensive supplies arrive. Industry experts now expect RAM prices to keep rising throughout the year, with shortages affecting not just desktops and laptops but also smartphones and other devices. Consumers are advised to purchase RAM now as prices are unlikely to decrease anytime soon.
Taiwanese startup FormulaV Line unveiled two new PC cases at Computex 2026: the Air Power G10 with tilting fans for customizable airflow and the Crystal Z3 featuring a unique bottom-intake chamber design. The Air Power G10 can accommodate ATX motherboards and offers various fan configurations, while the Crystal Z3 provides a panoramic view and detachable bottom fans for easy maintenance. These cases are expected to hit the US market later this year on Newegg, with the Air Power G10 priced around $150 and the Z3 around $80. Additionally, FormulaV Line showcased other products like a 1000-watt PSU and cooling solutions at the event.
G.Skill showcased new memory kits at Computex with AMD's EXPO Ultra Low Latency (ULL) support, aiming to reduce memory latencies for improved CPU performance. The EXPO ULL program allows memory makers to adjust sub-timings within primary timings for lower latencies, enhancing memory performance. While faster memory speeds above 6000 MT/s can add latency on AMD platforms, EXPO ULL kits aim to optimize latency without the need for manual adjustments. These kits require stricter binning during production, potentially making them more expensive but appealing to gamers seeking optimal CPU-bound gaming performance.
A research group led by Huawei Technologies has successfully post-trained DeepSeek's V4-Pro, a 1.6-trillion-parameter model, using a cluster of 1,000 Ascend 910C chips. This achievement showcases Chinese accelerators' capability to handle training-class workloads on domestic silicon, a significant development amid U.S. export controls. While Chinese chips have excelled in inference tasks, they have historically struggled with training, making this accomplishment noteworthy. However, the team's claim lacks specific benchmarks or comparisons with Nvidia hardware, leaving some aspects of the achievement unverified.