According to a report from Bloomberg, Jun Young-hyun, head of Samsung’s chip business, recently sent a stern warning to employees about the need to reform the company’s culture to avoid falling into a vicious cycle.

Jun stated that the recent improvement in Samsung’s performance was due to a rebound in the memory market. To sustain this progress, Samsung must take measures to eliminate communication barriers between departments and stop concealing or avoiding problems.

Earlier this week, Samsung announced its Q2 earnings, showcasing the fastest net profit growth since 2010. However, Jun Young-hyun highlighted several issues which may undermine Samsung’s long-term competitiveness.

He emphasized the need to rebuild the semiconductor division’s culture of vigorous debate, warning that relying solely on market recovery without restoring fundamental competitiveness would lead to a vicious cycle and repeating past mistakes.

Samsung is still striving to close the gap with its competitors. The company is working to improve the maturity of its 2nm process to meet the high-performance, low-power demands of advanced processes. Samsung’s the first-generation 3nm GAA process has achieved yield maturity and is set for mass production in the second half of the year.

In memory, Samsung is beginning to narrow the gap with SK Hynix in high-bandwidth memory (HBM). According to Bloomberg, Samsung has received certification for HBM3 chips from NVIDIA and expects to gain certification for the next-generation HBM3e within two to four months.

Jun emphasized that although Samsung is in a challenging situation, he is confident that with accumulated experience and technology, the company can quickly regain its competitive edge.

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• [News] Samsung Sees Solid Demand for 3nm in 2H24, Aiming a Ninefold Increase in AI/HPC Sales by 2028
• [News] Samsung’s Q2 Profits Soar to USD 7.5 Billion, Seeing Strong Demand for HBM, DDR5 and Server SSD in 2H24

(Photo credit: Samsung)

According to a report from Commercial Times, IC design giant MediaTek is making its move into the AI accelerator sector. MediaTek CEO Rick Tsai emphasized that MediaTek aims to be the best partner for edge AI, focusing on advanced technologies and 3nm process to optimize the power consumption and efficiency of its SoCs (system-on-chips).

Tsai mentioned that MediaTek will unveil its Dimensity 9400 flagship series of chips in October, designed to perfectly support most large language models on the market. He expressed confidence in achieving a more than 50% year-over-year revenue increase for flagship devices.

For the ASIC (Application-Specific Integrated Circuit) market, MediaTek has confirmed its entry into the AI accelerator field and will integrate CPUs as needed. ASICs are expected to start the revenue contribution  in the second half of next year.

Additionally, the TAM (Total Addressable Market) for generative AI is still in its early stages. MediaTek focuses on providing leading interconnect capabilities, such as SerDes IP and Ethernet PHY.

Regarding AI technology in the smartphone sector, Rick Tsai believes that flagship smartphones are seeing an increase in ASP, and there is a gradual shift towards high-end smartphones in the Chinese market. He noted that Chinese brands are actively developing AI, particularly in model development, such as open-source models like LLaMA 3.

At MediaTek’s earnings call on July 31st, Rick Tsai noted that the company anticipates a return to normal seasonal patterns in the second half of the year. The outlook for the fourth quarter will largely depend on consumer product demand.

Regarding the outlook in the third quarter, MediaTek expects the revenue to be flattish, ranging from NTD 123.5 billion to NTD 132.4 billion, compared with NTD 127.27 billion last quarter. Gross margin is projected to slide to 45.5-48.5%, from 48.8%, down 3.6 percentage points quarter over quarter and up 1.3 percentage points year-over-year.

Aside from the boost expected from the Dimensity 9400 flagship release, the company’s fourth-quarter market demand is projected to be relatively moderate, which is why the annual outlook remains unchanged. MediaTek expects its full-year gross margin to be between 46% and 48%.

Regarding TSMC’s pricing adjustments, Rick Tsai remains unperturbed, noting that all industry peers face similar cost pressures. MediaTek aims to reflect cost increases through pricing, with a gross margin target of 47% for new products. Progress has also been made in 3nm and 2nm processes, and MediaTek has secured its capacity needs for 2025 with TSMC.

Moreover, MediaTek and NVIDIA are collaborating on automotive chips, with plans to launch their first chip in early 2025. Rick Tsai mentioned that details are yet to be disclosed, but significant advancements in the automotive sector are expected between 2027 and 2028.

Read more

• [News] MediaTek Reportedly Designing ARM-Based Chips for Microsoft’s AI PCs, Launch Expected by End of Next Year
• [News] MediaTek Reportedly Partners with Meta, Entering the Battleground of AI against Apple and Qualcomm

(Photo credit: MediaTek)

NVIDIA’s next-generation Blackwell architecture AI superchip is about to ship. According to a report from Commercial Times, on July 29 during the SIGGRAPH conference in Denver, USA, NVIDIA announced a series of software updates and revealed that samples of the new AI chip architecture Blackwell have been distributed, sparking optimism about the company’s continued record-breaking performance.

Industry sources cited by the report have indicated that the Blackwell series is regarded by Jensen Huang as the most successful product in history. It is expected to drive a new wave of AI server data center construction by cloud service providers (CSPs).

The report notes further that in addition to TSMC’s 4nm process being in high demand, the increasing penetration of water cooling technology, which is projected to reach up to 10%, is likely to benefit Cooling Distribution Unit suppliers such as Vertiv, as well as companies like Asia Vital Components, AURAS Technology, Delta Electronics, and Cool IT.

Furthermore, the new AI superchip is expected to start shipping to clients in the fourth quarter, with full-scale production set for 2025. Assembly plants will also benefit, including Wistron, Foxconn (through its subsidiary Ingrasys), which are involved in front-end manufacturing of substrates, computing boards, and switch boards.

Companies such as Wiwynn, Quanta (Quanta Cloud Technology), Inventec, GIGABYTE, ASUS, and ASRock are also expected to see increased orders for their rack-mounted systems. Among these, Quanta, Wiwynn, and Inventec have indicated that their related products are expected to start shipping in the fourth quarter, with further increases in volume anticipated in the first half of next year.

The NVIDIA Blackwell platform is set to become the main solution for NVIDIA’s high-end GPUs. TrendForce estimates that GB200 NVL36 shipments are expected to reach 60,000 units in 2025, with Blackwell GPU usage between 2.1 to 2.2 million units, making Blackwell the mainstream platform and accounting for over 80% of NVIDIA’s high-end GPUs.

TrendForce observes that the GB200 NVL36 architecture will initially utilize a combination of air and liquid cooling solutions, while the NVL72, due to higher cooling demands, will primarily employ liquid cooling.

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• [News] NVIDIA Reportedly Developing Tailored Version of the Blackwell Series for Chinese Market
• [News] NVIDIA CEO Jensen Huang Estimates Blackwell Chip Price Around USD 30,000 to USD 40,000

(Photo credit: NVIDIA)

Apple’s latest technical document reveals that the two main AI models behind Apple Intelligence are trained using Google’s Tensor Processing Units (TPUs) instead of NVIDIA GPUs. According to a report from Commercial Times, this suggests that the demand for NVIDIA chips has outstripped supply, prompting some tech giants to seek alternatives.

Apple first introduced an AI technical document in June, briefly stating that its AI models were trained using TPUs. The latest technical document, which spans 47 pages, provides a detailed explanation of how Apple’s foundational models (AFM) and AFM servers are trained in Cloud TPU Clusters. This indicates that Apple rents cloud servers from cloud service providers to train its AI models.

In the document, Apple stated: “This system allows us to train the AFM models efficiently and scalably, including AFM-on-device, AFM-server, and larger models.”

Apple further mentioned that the on-device AFM models for iPhones and iPads are trained using a total of 2,048 TPUv5p chips, which are currently the most advanced TPU chips on the market. The AFM servers are trained using a total of 8,192 TPUv4 chips.

Google initially launched TPUs in 2015 for internal training use only and started offering TPU rental services to external clients in 2017. These TPUs are currently the most mature custom chips used for AI training. According to Google’s official website, the rental cost of their most advanced TPUs is approximately USD 2 per hour based on a three-year contract.

Though NVIDIA’s GPUs are currently dominating the high-end AI chip market, the enormous number of chips required for AI model training has led to a severe shortage. This is because major tech companies like OpenAI, Microsoft, Google, Meta, Oracle, and Tesla all use NVIDIA chips to develop their AI technologies.

Since the rise of ChatGPT at the end of 2022, which spurred the generative AI market, Silicon Valley tech giants have been racing to invest in AI research and development. In contrast, Apple has lagged behind its competitors and now has to intensify its efforts to bolster Apple Intelligence. On July 29th, Apple released a preview version of Apple Intelligence for certain devices.

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• [News] NVIDIA’s H200 Order Delivered from Q3, Boosting Server Supply Chain with Strong Demand
• [News] US Government Reportedly Investigating Microsoft, NVIDIA, and OpenAI for AI Industry Monopolization

(Photo credit: NVIDIA)