At the moment not that big a threat and not something that has just appeared, a threefer.
First up, from Trefis via Nasdaq, January 5:
....MUCH MORENvidia stock (NASDAQ:NVDA) had a stellar 2024, rising by almost 3x to about $135 per share. Business has boomed led by the surging demand for graphics processing units (GPUs) which have emerged as the backbone of the generative artificial intelligence era. That said, over the last month or so investors appear to have their eyes on another sector of the semiconductor market, namely ASICs (application-specific integrated circuits) that could play a bigger role in AI computing.
This comes after two major ASIC players, Broadcom and Marvell Technology, reported a surge in demand for their ASICs from large cloud customers in the most recent quarters. Do Custom AI Chips Make Marvell Stock A Buy? For instance, Broadcom’s sales from its custom AI chips and networking processors surged by 220% to $12.2 billion in 2024, up from $3.8 billion in revenue that the company generated from AI silicon in FY’23. To be sure, Nvidia’s sales are head and shoulders above, estimated to come in at about $129 billion this fiscal year, but its growth rates are slowing. So could ASICs threaten Nvidia’s AI dominance as the market matures? Separately, if you want upside with a smoother ride than an individual stock, consider the High Quality portfolio, which has outperformed the S&P, and clocked >91% returns since inception.
ASICS vs GPUs
ASICs have been around for more than five decades. However, they are seeing renewed interest in the AI era. While GPUs from companies such as Nvidia are pretty versatile and can be programmed for AI as well as other tasks, ASICs are custom-designed semiconductors built to perform specific tasks giving them certain advantages versus general processors. By focusing on targeted functionalities these chips offer several advantages versus GPUs for AI. For instance, these specialized chips could be more cost-effective than GPUs, which are designed for a wider range of applications.
ASICs also consume less electricity and this makes them ideal for data centers aiming to reduce electricity costs – a key cost of operating large AI systems. ASICs can also achieve higher performance for dedicated tasks than general-purpose GPUs from Nvidia or AMD as they are purpose-built. These chips could be well suited for large cloud computing providers given that they operate at a scale that can justify the design and development costs of ASICs. For instance, Broadcom, a company that is viewed as the biggest beneficiary of a potential pivot toward ASICs, recently said that three of its hyperscaler customers intend to build clusters of 1 million custom chips across a single network.
Change In The AI Space Benefits ASICs....
Next up, from TechRadar via Yahoo Finance January 12:
Nvidia is preparing for the post-GPU AI era as it is reportedly recruits ASIC engineers to fend off competition from Broadcom and Marvell
- ASICs are far more efficient than GPUs for inference, not unlike mining cryptocurrency
- The Inference AI chip market is expected to grow exponentially by the end of this decade
- Hyperscalers like Google have already jumped on the bandwagon
Nvidia, already a leader in AI and GPU technologies, is moving into the Application-Specific Integrated Circuit (ASIC) market to address growing competition and shifting trends in AI semiconductor design.
The global rise of generative AI and large language models (LLMs) has significantly increased the demand for GPUs, and Nvidia CEO Jensen Huang confirmed in 2024 the company will recruit 1000 engineers in Taiwan.
Now, as reported by Taiwan's Commercial Times (originally published in Chinese), the company has now established a new ASIC department and is actively recruiting talent.
The rise of inference chips
Nvidia’s H series GPUs optimized for AI learning tasks have been widely adopted for training AI models. However, the AI semiconductor market is undergoing a shift toward inference chips, or ASICs.This surge is driven by the demand for chips optimized for real-world AI applications, such as large language models and generative AI. Unlike GPUs, ASICs offer superior efficiency for inference tasks, as well as cryptocurrency mining.
According to Verified Market Research, the inference AI chip market is projected to rise from a 2023 valuation of $15.8 billion to $90.6 billion by 2030.
Major tech players including Google have already embraced custom ASIC designs in its AI chip "Trillium", made generally available in December 2024....
....MORE
And some previous posts at Climateer Investing:
December 12, 2018
A Dip Into Chips: "AI Chip Architectures Race To The Edge"
We'll be referring back to this piece, it's the next big thing.
Chips: NVIDIA Begins To Embrace the Move Toward More Specialized Chips (NVDA; INTC; AMD; GOOG; XLNX)
See I told you I wasn't crazy. Something we've been babbling about for a couple years.
July 1, 2022
Crypto Mining Market Pullback Hits Nvidia, Others (NVDA)
Just to pound the message home, the high-end miners switched to ASICS years ago.
That said, this is a nice overview of what's been going on with GPU's.
February 9, 2024
Nvidia Is Developing A Custom Chip Design Unit To Address $30 Billion Niche (NVDA)
Yes, a big niche but still a niche. Nvidia really, really wanted to own ARM's design capability but when the regulators said 'ummm no', Mr. Huang didn't stop trying to address the fact that Google, Microsoft, Amazon Tesla and Facebook are all producing their own data center chips....
And many more. If interested use the 'search blog' box, upper left.
The stock is trading at $137.17, up $0.93 (+0.68%) still a ways away from the January 7 all-time-high, $153.13
