Semiconductor & Technology Specialist, Ingenuity

William Keating

Semiconductor & Technology Specialist

Ingenuity

Our focus is exclusively on in-depth research & consulting in the broader semiconductor industry. We focus on the key players, namely Intel, Micron, Qualcomm, Apple, Samsung, NVIDIA, AMD, TSMC & Global Foundries - as well as some of the lesser known, but nonetheless critical, companies such as ASML (for EUV), Mellanox, Cavium, Xilinx etc. We specialise in their products, roadmaps, process technologies, competitive advantages & threats etc. We also help our clients understand the implications of new and emerging technologies, e.g. 3D X-Point, 3D NAND, Carbon Nanotubes, Autonomous Driving, Graphene, Silicon Photonics, Wafer-Level Optics, Artificial Intelligence, FPGA, GPU, ASIC etc. 

Semiconductor Analysis & Research

Thematic (Sector/Industry)

<ul>
<li>If GAA is better viewed as a revolutionary change, it implies that Intel, Samsung and TSMC will transition to GAA with a largely level playing field </li>
<li>If GAA is better viewed as an evolutionary change, TSMC will carry forward its process technology leadership into its GAA transition, leaving it in the #1 position</li>
<li>We think that the GAA transition is evolutionary, not revolutionary and posit that TSMC will continue to maintain its semiconductor process technology leadership through the transition.</li>
</ul>


If GAA is better viewed as a revolutionary change, it implies that Intel, Samsung and TSMC will transition to GAA with a largely level playing field 
If GAA is better viewed as an evolutionary change, TSMC will carry forward its process technology leadership into its GAA transition, leaving it in the #1 position
We think that the GAA transition is evolutionary, not revolutionary and posit that TSMC will continue to maintain its semiconductor process technology leadership through the transition.


Gate All Around Transistors. Evolution Or Revolution & Why It Matters

Equity Bottom-Up

Taiwan Semiconductor (TSMC) / Equity Bottom-Up

Taiwan Semiconductor Manufacturing Company, Ltd. manufactures and markets integrated circuits. The Company provides the following services: wafer manufacturing, wafer probing, assembly and testing, mask production, and design services. TSMC's ICs are used in computer, communication, consumer electronics, automotive, and industrial equipment industries.

<ul>
<li>Q424 revenue forecast of $26.5 billion, up 13% QoQ and the highest Q3 to Q4 revenue jump since Q4 2017</li>
<li>Demand for AI acceleration is real and just beginning. According to a key customer of theirs, "demand right now is just insane"</li>
<li>Overseas fabs progressing well with Arizona yielding well and on track for high volume production in early 2025</li>
</ul>


Q424 revenue forecast of $26.5 billion, up 13% QoQ and the highest Q3 to Q4 revenue jump since Q4 2017
Demand for AI acceleration is real and just beginning. According to a key customer of theirs, "demand right now is just insane"
Overseas fabs progressing well with Arizona yielding well and on track for high volume production in early 2025


ASML Holding N.V. develops, produces, and markets semiconductor manufacturing equipment, specifically machines for the production of chips through lithography. The Company services clients worldwide.

<ul>
<li>ASML reported revenues of €7.5 billion, +19% QoQ and +11.9% YoY. This was €200 million above the high end of the guided range. Q424 guided to €9 billion</li>
<li>Logic Fab delays and a collapse in sales to China caused ASML to reduce their 2025 forecast to the low end of the €30 -€40 billion guided in November 2022</li>
<li>Despite these challenges, ASML's latest forecast still implies 16% YoY growth in 2025</li>
</ul>


ASML reported revenues of €7.5 billion, +19% QoQ and +11.9% YoY. This was €200 million above the high end of the guided range. Q424 guided to €9 billion
Logic Fab delays and a collapse in sales to China caused ASML to reduce their 2025 forecast to the low end of the €30 -€40 billion guided in November 2022
Despite these challenges, ASML's latest forecast still implies 16% YoY growth in 2025


Tesla first began to equip its Model S with self-driving technology in October 2014 and announced the launch of its "Autopilot" software to take advantage of those sensors exactly one year later. In separating the sensors from the software, and making that software incrementally available via over-the-air (OTA) updates, the company heralded an entirely new approach to autonomous driving that has since come to be both derided and admired in equal measure. Tesla's autopilot capability was widely regarded as ground-breaking when it was first introduced and many would argue that it was the catalyst for its peers and competitors to rapidly accelerate their autonomous driving investments and roadmaps.Since that time, Tesla's self-driving roadmap has seen many twists and turns. Their partnership with MobilEye, upon whose chips their initial autopilot roll-out critically depended, ended abruptly and acrimoniously in the wake of a fatal crash involving one of their Model S vehicles in May 2016. Their backup plan, the development of a custom ASIC chip to replicate MobilEye's functionality, was still in its infancy, forcing Tesla to turn to NVIDIA for its DRIVE PX platform. That same fatal crash was the impetus for a total redesign of their sensor suite. The new hardware platform was launched in October 2016 with the announcement that all future Tesla cars would be fully equipped with the hardware &amp; sensors required for full self-driving capability.As automobiles equipped with the new self-driving hardware rolled off the production lines, they were missing the software to make them work, meaning that they lacked basic advanced driving features such as automatic emergency braking (AEB), adaptive cruise control (ACC) etc. Tesla promised to deliver those capabilities incrementally in the following months, but inevitably, delays ensued and reliability concerns arose when they were initially released. Only in recent months has Tesla's "Enhanced Autopilot" begun to approach the same level of capability as its original launch version. Tesla CEO Elon Musk's commitment to demonstrating fully autonomous driving from US coast-to-coast by the end of 2017 failed to materialize, although he has recently stated that it should happen within 3-6 months. Meanwhile, the rapidly growing availability of new safety features such as AEB, the launch of competing driver assistance features such as General Motors (GM)"Super Cruise" and the publicly announced plans for driverless taxi pilots by both Waymo and GM have eroded Tesla's leadership. Indeed, one research firm, Navigant, doesn't even rate Tesla in its latest top ten leaders list.   In this Insight, we review the history of autonomous driving at Tesla, tracing its roots from the original autopilot launch to the present day. We examine the technology behind Tesla's self-driving platform and highlight their steadfast refusal to incorporate LIDAR in their sensor suite as every other competitor has done. Finally, in the wake of another fatal Tesla crash, we ask the very important question, how safe is Tesla Autopilot?

Tesla first began to equip its Model S with self-driving technology in October 2014 and announced the launch of its "Autopilot" software to take advantage of those sensors exactly one year later. In separating the sensors from the software, and making that software incrementally available via over-the-air (OTA) updates, the company heralded an entirely new approach to autonomous driving that has since come to be both derided and admired in equal measure. Tesla's autopilot capability was widely regarded as ground-breaking when it was first introduced and many would argue that it was the catalyst for its peers and competitors to rapidly accelerate their autonomous driving investments and roadmaps.Since that time, Tesla's self-driving roadmap has seen many twists and turns. Their partnership with MobilEye, upon whose chips their initial autopilot roll-out critically depended, ended abruptly and acrimoniously in the wake of a fatal crash involving one of their Model S vehicles in May 2016. Their backup plan, the development of a custom ASIC chip to replicate MobilEye's functionality, was still in its infancy, forcing Tesla to turn to NVIDIA for its DRIVE PX platform. That same fatal crash was the impetus for a total redesign of their sensor suite. The new hardware platform was launched in October 2016 with the announcement that all future Tesla cars would be fully equipped with the hardware &amp; sensors required for full self-driving capability.As automobiles equipped with the new self-driving hardware rolled off the production lines, they were missing the software to make them work, meaning that they lacked basic advanced driving features such as automatic emergency braking (AEB), adaptive cruise control (ACC) etc. Tesla promised to deliver those capabilities incrementally in the following months, but inevitably, delays ensued and reliability concerns arose when they were initially released. Only in recent months has Tesla's "Enhanced Autopilot" begun to approach the same level of capability as its original launch version. Tesla CEO Elon Musk's commitment to demonstrating fully autonomous driving from US coast-to-coast by the end of 2017 failed to materialize, although he has recently stated that it should happen within 3-6 months. Meanwhile, the rapidly growing availability of new safety features such as AEB, the launch of competing driver assistance features such as General Motors (GM)"Super Cruise" and the publicly announced plans for driverless taxi pilots by both Waymo and GM have eroded Tesla's leadership. Indeed, one research firm, Navigant, doesn't even rate Tesla in its latest top ten leaders list.   In this Insight, we review the history of autonomous driving at Tesla, tracing its roots from the original autopilot launch to the present day. We examine the technology behind Tesla's self-driving platform and highlight their steadfast refusal to incorporate LIDAR in their sensor suite as every other competitor has done. Finally, in the wake of another fatal Tesla crash, we ask the very important question, how safe is Tesla Autopilot?  

<ul>
<li>Seven Taiwan semi companies from our list of sixteen are now showing negative YoY monthly growth as of September 2024, up from just three a month earlier</li>
<li>Companies with a strong exposure to the AI Acceleration market are on track for strong revenue growth YoY in 2024. ASPEED is on track to double revenues this year. </li>
<li>For many of the remainder, what tepid growth they had been experiencing may be starting to stall. Watch this space. </li>
</ul>


Seven Taiwan semi companies from our list of sixteen are now showing negative YoY monthly growth as of September 2024, up from just three a month earlier
Companies with a strong exposure to the AI Acceleration market are on track for strong revenue growth YoY in 2024. ASPEED is on track to double revenues this year. 
For many of the remainder, what tepid growth they had been experiencing may be starting to stall. Watch this space. 


Taiwan Semi Monthly Tracker Red Flags Double MoM In September 2024

Dr. William Keating is a highly experienced senior executive with over 25 years experience in the IT/Semiconductor Industry. The majority of Dr. Keating's career was spent at Intel Corporation where he held senior leadership positions in Europe, the US and Asia from 1992 through 2014. He served as Intel's IT Director for APAC, China & Japan from 2005 through 2014 when he was based in Hong Kong and was responsible for the IT systems (Infrastructure, Networks, Data Centres, ERP, Sales & Marketing systems, Business Intelligence etc. ) for all of Intel's offices & factories through the region. From 1998 through 2005, he was the founder & director of an internal IT Consulting Organisation (IT Flex Services), a 500-person team which remains a core part of the Intel IT Organisation to this day. Dr. Keating's first 6 years at Intel were spent in charge of the Factory Automation Systems (Robotics, Databases, Networks, Servers, Clients etc.) supporting Intel's then state-of-the-art 200mm factory network. Since leaving Intel in 2014, Dr Keating established his own Technology Research & Consulting Company (www.ingenuity.hk) where he focuses on the products, roadmaps & technologies of companies such as Intel, AMD, Samsung, Apple, Micron- as well as the key equipment suppliers to those companies e.g. ASML, AMAT, Canon, Nikon etc. Dr. Keating specializes in niche topics of high significance within the semiconductor industry. These include the future of Moore's Law and in particular the significance of Lithography in maintaining Moore's Law (EUV, SDA, NanoImprint), the role & growth of the GPU in specialised applications such as Deep Learning (Neural Networks) for Voice, Image & Pattern recognition at companies such as Facebook, Google & Baidu. He also holds regular discussions on the future of memory, in particular the rise of 3D NAND and the emergence of new memory technologies such as 3D Xpoint.

William Keating
Semiconductor & Technology Specialist
• Ingenuity

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