In the era of AI and big data, new market demands are emerging in the storage industry, and QLC NAND SSDs, which play a critical role in AI training. This suggests that NAND flash may be on the verge of a new growth opportunity.

QLC, or Quad-Level Cells, refers to NAND flash where each storage cell can record 4 bits. Each cell maintains a standard size, and compared to traditional SLC, MLC, and TLC technologies, QLC enables higher data density, allowing more data to be stored in the same space.

The Advantages of QLC Flash

QLC flash offers several key advantages:

• Capacity: Compared to mainstream TLC flash, QLC increases storage density by 33%.
• Cost: With the same number of flash chips cut from a wafer, QLC provides about 33% more storage capacity than TLC, leading to a lower cost per unit of storage.
• Total Cost of Ownership (TCO): QLC-based SSDs offer lower TCO compared to traditional HDDs. TCO includes considerations like storage density, reliability, and power consumption. While QLC’s write performance is somewhat inferior to other technologies, its read performance is strong.

However, QLC technology also faces some challenges. Since data is stored across more charge levels, this increases the risk of data vulnerability, requiring more advanced error correction and data protection mechanisms. QLC storage devices typically need stronger error correction algorithms and robust data protection to ensure integrity and reliability.

Despite these challenges, as technology continues to advance, QLC is expected to play an increasingly important role in the storage field, potentially revolutionizing the entire information industry.

QLC NAND is Entering the AI SSD Battlefield

Many believe that QLC SSDs are a complement to TLC SSDs, particularly suited for read-intensive and mixed read/write workloads, such as those found in AI, content delivery networks, and machine learning.

In AI applications, TrendForce points out that SSDs are used in AI inference servers to help adjust and optimize AI models during inference, especially by updating data in real-time to fine-tune model outputs. AI inference mainly supports Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs), and SSDs can store reference documents and knowledge bases for RAG and LLM to generate richer responses.

As more generated information is displayed as videos or images, data storage demands increase, making large-capacity SSDs, such as 16TB+ TLC/QLC models, essential for AI inference.

Currently, companies like Samsung, SK Hynix’s Solidigm, Western Digital, and Kioxia hold key positions in the QLC SSD market.

Industry experts are optimistic about the future of QLC SSDs, emphasizing their benefits for data centers, cloud storage providers, and enterprises handling massive amounts of data. QLC SSDs are seen as a potential game-changer for the NAND flash market.

TrendForce also predicts that QLC will account for 20% of NAND flash shipments by 2024, with this share expected to rise in 2025. Moreover, QLC is likely to expand into consumer-embedded storage such as eMMC and UFS, with some products already adopting QLC as the storage medium.

Industry forecasts suggest that by 2025, large-capacity QLC enterprise SSDs will rise, and smartphones will start using QLC-based UFS storage solutions.

(Photo credit: Samsung)

Apple introduced the Apple Intelligence feature at WWDC24 back in June. However, according to Mark Gurman from Bloomberg, some Apple employees believe the company is two years behind its competitors in AI development.

The Apple Intelligence includes several features, such as AI notification summaries, intelligent prioritization for important alerts, a new Siri with personal context, Image Playground, Genmoji, and more.

According to a report from 9to5Mac, one of the main challenges facing Apple Intelligence is that it mostly depends on models that can run on-device, which also means that Apple Intelligence has quite high requirements for device.

To run Apple Intelligence, users will need a device equipped with at least an A17 or M1 chipset, and it must have a minimum of 8 GB of memory to support the personal intelligence system, as highlighted by 9to5Mac.

The report from 9to5Mac noted that since the models primarily operate on-device, the volume of information they can process is inherently limited. This is also why Apple has chosen to integrate Siri with ChatGPT.

According to the announcement by OpenAI, Apple will support GPT-4o across iOS, iPadOS, and macOS. GPT-4o will be integrated into Siri and Writing Tools, with the expectation that this integration will help reduce the knowledge gap.

Regarding the knowledge gap, according to Mark Gurman from Bloomberg, Apple’s internal research shows that ChatGPT is about 25% more accurate than Siri and can answer about 30% more questions, leading some Apple employees to believe the company is two years behind its competitors in AI development.

Nonetheless, Gurman believes that Apple still has the potential to catch up, as they can often successfully catch up with competitors in areas where they seem to be lagging behind, demonstrated by its experience with Apple Maps.

Furthermore, Gurman also pointed out that Apple has another advantage in its efforts to catch up: the ability to deploy features across a vast array of devices. Apple can quickly equip its current products with the technology required to support new software. We can expect to see this again soon with the rollout of the M4 Macs, which will accelerate Apple’s AI tasks, as indicated by Gurman.

According to Gurman, Apple Intelligence will be available on nearly every Apple device with a screen by 2026. The iPhone SE is set to receive this feature in March, along with the A18 chip, while the entry-level iPad is expected to be updated later in 2025.

Read more

• [News] Apple Intelligence Is Expected to Arrive on October 28th with the Release of iOS 18.1
• [News] iPhone 16 “Supercycle” in Doubt? Concerns Rise Over Slow Rollout with its AI Platform

(Photo credit: Apple)

Would Samsung finally be able to secure major orders from tech giants, even one of the world’s top AI companies? According to a report by The Information, the most successful and lucrative partnership in AI business, which is formed by NVIDIA and its foundry partner TSMC, is showing signs of strain, while Samsung may turn out to benefit from the development.

However, it is worth noting that the orders Samsung might get from NVIDIA may not be the most advanced AI chips. According to the reports by The Information and SamMobile, the U.S. AI chip giant is mulling to team up with Samsung to produce its new GPUs, which are considered less complex to manufacture than its AI accelerators.

The reports also suggest that NVIDIA is trying to secure discounted pricing from Samsung, as it aims for a 20-30% reduction compared to what it pays TSMC.

According to the analysis by SamMobile, NVIDIA’s move is an attempt to reduce its dependence on TSMC for upcoming chips, which is a positive development for Samsung.

Though the struggling semiconductor giant is said to have several clients for 5nm, 7nm and 8nm nodes, the continuous yield issues for 3nm and 4nm makes it unable to attract major customers, according to SamMobile, while the company now hopes to improve its yields and regain clients like Qualcomm and NVIDIA.

According to The Information, Samsung’s opportunities arise while NVIDIA’s Blackwell chips, built with TSMC’s 4nm, reportedly faced delays due to issues discovered in the testing process. The chips are said to have failed in high-voltage environments typical of data centers, which put strain on the decades-long partnership between the two firms.

For now, the issues have been resolved, and Team Green’s Blackwell chips are expected to ramp up starting from Q4 2024. According to a report by Wccftech, citing the projection by analyst Ming-Chi Kuo, Blackwell’s estimated shipments are expected to be around 150,000 to 200,000 units this quarter, and surging to 500,000 to 550,000 units in Q1 2025.

According to Kuo, Microsoft is believed to be the major customer, with its orders for GB200 in Q4 skyrocketing, rising 3 to 4 times from the previous range of 300 to 500 racks (primarily NVL36) to about 1,400 to 1,500 racks (approximately 70% NVL72).

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• [News] NVIDIA’s Blackwell Overcomes Delays, as GB200 Reportedly Sets for December Mass Production

(Photo credit: NVIDIA)

The People’s Bank of China (PBoC) announced on October 21 a reduction of both the 1-year and 5-year Loan Prime Rates (LPR) by 25 basis points each, bringing them to 3.1% and 3.6%, respectively.

Read more at Datatrack

In mid-September, the PBoC launched a series of large-scale monetary easing measures, including interest rate cuts, reserve requirement ratio reductions, and mortgage rate cuts to support economic growth. Additionally, the 7-day reverse repo rate was lowered by 20 basis points at the end of September, providing guidance for the latest LPR adjustments.

Read more at Datatrack

The September monthly economic data did showed some initial signs of improvement, with retail sales rising by 3.2% year-over-year (previous: 2.1%), exceeding market expectations of 2.5%, and industrial output increasing by 5.4% year-over-year (previous: 4.1%), also above market expectations of 4.6%. Neverthess, the current stimulus plans seem unable to boost the economy.

Read more at Datatrack

China’s third-quarter GDP growth came in at 4.6% year-over-year (previous: 4.7%), with cumulative GDP growth for the first three quarters at 4.8%, still below the annual target of 5.0%, highlighting the increasing urgency for the Chinese government to strengthen policy stimulus.

Read more at Datatrack

According to a report from Reuters, India is set to impose restrictions on the import of laptops, tablets, and personal computers starting in January, aiming to boost domestic manufacturing.

If implemented, the new plan could significantly impact the PC industry, worth USD 8 billion to USD 10 billion. Given that the Indian IT hardware market is heavily dependent on imports, this new plan is likely to transform the manufacturing industry and the local market in India, as indicated by the report.

The report stated that the Indian government attempted to limit imports of laptops, tablets, and personal computers last year. However, these restrictions were lifted in response to backlash from companies and lobbying from the United States.

Currently, laptop importers can freely import products into the Indian market after automatic online registration. According to the report, sources indicated that India’s Ministry of Electronics and Information Technology (MeitY) is developing a new import authorization system that will require companies to obtain prior approval for their imports.

The report highlighted that two-thirds of India’s demand is satisfied through imports, with a substantial portion coming from China. On the other hand, India’s IT hardware market, including laptops, is estimated at nearly USD 20 billion, yet domestic production accounts for only USD 5 billion of that total.

According to the report, India has federal subsidies totaling approximately USD 2.01 billion to encourage domestic production. India’s IT hardware production incentive program has drawn interest from major PC manufacturers, including Acer, Dell, HP, and Lenovo. Last year, India’s electronics minister stated that most of the approved companies are prepared to begin local manufacturing.

(Photo credit: Lenovo)