TSMC’s angstrom-level A16 process is creating a buzz even before mass production. According to a report from the Economic Daily News, not only has major client Apple already booked the capacity for TSMC’s A16, OpenAI has also joined in to secure TSMC’s A16 capacity due to its long-term need for self-developed AI chips.

Regarding this matter, TSMC stated on August 30 that the company does not comment on market rumors or on business dealings with individual customers.

Despite that TSMC’s A16 process is scheduled to enter mass production in 2026, the report has hinted that the first batch of customers has already surfaced.

In addition to Apple, which has been in continuous collaboration with TSMC, the most notable new customer of TSMC’s A16 is said to be OpenAI, the developer of ChatGPT, which is actively investing in the design and development of its own ASIC chips.

Industry sources cited by the same report reveal that OpenAI had initially been in active discussions with TSMC about establishing a dedicated fab. However, after assessing the potential benefits, the plan to build a dedicated facility was shelved.

Strategically, OpenAI is now partnering with U.S. companies like Broadcom and Marvell to develop its own ASIC chips, and potentially emerging as one of Broadcom’s top four customers.

Since both IC design giants are long-term clients of TSMC, the ASIC chips they are helping OpenAI develop are expected to be produced using TSMC’s 3nm process family and the subsequent A16 process, according to the chip design roadmap.

It is worth noting that OpenAI not only holds a critical position in the development of AI applications beyond Apple’s ecosystem but also contributes to the advancement of AI applications in Apple devices.

In June of this year, Apple unveiled its personalized intelligent system, Apple Intelligence, which has integrated ChatGPT. This strategic move has led observers to believe that OpenAI plays a key role in Apple’s AI development.

As OpenAI continues to invest in the design and development of its own ASIC chips, it is reportedly expected to maintain its influence in the AI computing field.

TSMC unveiled its angstrom-class A16 advanced process during the company’s 2024 North America Technology Symposium on April 25, set to be mass-produced in 2026.

Per TSMC, Compared to TSMC’s N2P process, the A16 offers an 8% to 10% speed increase at the same Vdd (operating voltage), a 15% to 20% reduction in power consumption at the same speed, and a density increase of up to 1.1 times, supporting data center products.

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While NVIDIA is likely to face accusations from the French antitrust regulators, the Non-NVIDIA Alliance like the UALink (Ultra Accelerator Link) Alliance and the UXL Foundation are reportedly launching a counterattack, significantly increasing their efforts in developing specialized ASICs.

According to a report from Commercial Times, relevant semiconductor intellectual property (IP) is expected to be widely adopted. The sources cited by the report point out that Taiwanese manufacturers, benefiting from their leading position in wafer foundry and comprehensive ASIC and IP layout, are poised to capitalize on the rise of the Non-NVIDIA Alliance.

The report further cites sources, indicating that major Taiwanese ASIC manufacturers such as Global Unichip, Faraday Technology, and Progate Group Corporation (PGC), along with silicon IP companies M31 Technology Corporation, eMemory, and the Egis Technology Group, are actively expanding in this field.

In order to challenge NVIDIA’s dominance in the market, UALink (Ultra Accelerator Link) Alliance, led by tech giants such Intel and AMD, was formed in May. The alliance aims to establish a new standard for AI accelerator links, aiming to challenge NVIDIA’s  NVLink.

Furthermore, the UXL Foundation’s Open Source Software Project, supported by tech giants Qualcomm, Google, and Intel, is said to be looking to rival NVIDIA’s CUDA software. By providing alternative software solutions, it aims to diminsh NVIDIA’s dominance in the AI field.

Semiconductor industry sources cited in the same report also note that CSPs are accelerating the development of their own chips, with Taiwanese manufacturers actively entering the market.

Although Broadcom and Marvell currently offer diversified design services, Taiwanese manufacturers have an advantage due to the tightly-knit semiconductor supply chain. This enables complete solutions for both chip manufacturing and packaging within Taiwan, giving them a strategic edge over competitors by being close to both the market and factories, thereby enhancing their position in the ASIC sector.

Global Unichip and PGC leverage TSMC as a strong ally. Reportedly, Global Unichip holds AI-related ASIC orders from Microsoft and is gradually finalizing collaborations with major South Korean companies, with business operations expected to improve in the second half of the year.

On the other hand, Faraday Technology closely collaborates with Intel, developing SoCs using Intel’s A18 process. Meanwhile, industry sources cited by the report suggest that Intel’s Gaudi series AI chips might seek collaboration opportunities beyond just working with Alchip.

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(Photo credit: Shutterstock)

At the Google I/O 2024 developer conference on Tuesday, Google unveiled its 6th generation custom chip, the Trillium TPU, which is scheduled to hit the market later this year, according to the report by TechCrunch.

According to the information provided by Google on its website, compared to TPU v5e, Trillium boasts a 4.7x peak compute performance increase per chip. Google has also doubled the High Bandwidth Memory (HBM) capacity and bandwidth, along with a 1x increase in Interchip Interconnect (ICI) bandwidth between chips.

Additionally, Trillium features the third-generation SparseCore, a dedicated accelerator for processing large embeddings, aimed at handling advanced ranking and recommendation workloads. Moreover, Trillium achieves a 67% higher energy efficiency compared to TPU v5e.

Trillium has the capacity to expand up to 256 TPUs within a singular pod boasting high bandwidth and low latency. Additionally, it incorporates multislice technology, allowing Google to interlink thousands of chips, thus constructing a supercomputer capable of facilitating a data center network capable of processing petabits of data per second.

In addition to Google, major cloud players such as AWS, Meta, and Microsoft have also made their way to develop their own AI Chips.

In late 2023, Microsoft unveiled two custom-designed chips, the Microsoft Azure Maia AI Accelerator, optimized for AI tasks and generative AI, and the Microsoft Azure Cobalt CPU, an Arm-based processor tailored to run general purpose compute workloads on the Microsoft Cloud. The former is reportedly to be manufactured using TSMC’s 5nm process.

In May 2023, Meta also unveiled the Meta Training and Inference Accelerator (MTIA) v1, its first-generation AI inference accelerator designed in-house with Meta’s AI workloads in mind.

AWS has also jumped into the AI chip market. In November, 2023, AWS released Trainium2, a chip for training AI models.

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(Photo credit: Google)

Novatek has unveiled its AI and related domain strategies during its year-end investor conference. According to a report from Taiwanese news outlet Tai Sounds, Novatek anticipates that the demand for AI will drive an enhancement in display specifications and necessitate the integration of edge devices such as security systems.

Transmission interfaces stand as the core focus of Novatek, with subsequent products extending towards high-speed transmission. In both its driver IC and SoC product lines, Novatek maintains customized product lines, with expectations for growth in customized chips this year.

As per sources cited by Taiwanese news outlet Tai Sounds, Novatek is rumored to be venturing into the IP domain and may have opportunities to collaborate with ARM, a subsidiary of SoftBank Group.

Further clarification from the source also indicates that Novatek specializes in customized power management chips for mobile devices, while Realtek offers USB4 hub solutions.

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(Photo credit: Novatek)

TSMC is set to conduct an investor meeting on the 19th, with Morgan Stanley, UBS, and Bank of America Securities releasing their latest reports ahead of the event. These reports highlight five main areas of interest:

1. Q4 Operational Outlook
2. Future Gross Margin Trends
3. Potential Adjustments to Full-Year Revenue Estimates and Capital Expenditure
4. Economic and Operational Outlook for the Coming Year
5. 2nm Production Plans

Despite market uncertainties surrounding factors such as end-market demand, the Chinese mainland’s economic trajectory, and semiconductor industry cycles, Morgan Stanley Securities anticipates a 10% QoQ increase in TSMC’s Q4 revenue. They attribute this to strong demand for AI GPUs and ASICs, urgent orders from products like smartphone system-on-chips (SoCs) and PC GPUs, as well as sustained demand for Apple’s iPhones. Additionally, the gross margin is expected to benefit from the depreciation of the New Taiwan Dollar, potentially reaching 53%, surpassing the market consensus of 52.2%.

Bank of America Securities similarly projects a 10% QoQ revenue growth for TSMC in Q4, with a gross margin estimate of 52.7%. UBS Securities, on the other hand, has adjusted its Q4 revenue growth forecast from 10% to 7% while maintaining their expectation of a 10% YoY decline in full-year revenue.

In terms of capital expenditures, Morgan Stanley Securities, taking into account factors such as Intel’s 3nm outsourcing and delays in the U.S. factory expansion, estimates that TSMC’s capital expenditures will remain around $28 billion for both this year and the next. UBS Securities, however, believes that due to a slower short-term business recovery, capital expenditures for this year and the next will be adjusted to $31 billion and $30 billion, respectively.

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(Photo credit: TSMC)