The opinions are only mine.
Can Nvidia sustain its meteoric rise?
The new Nvidia Blackwell chip appears to be encountering ongoing challenges. Following design flaws that delayed its release, the chip is now facing overheating issues, making the servers less reliable and reducing their performance. Nvidia has requested its suppliers to modify the design of the 72-chip racks multiple times, causing anxiety among customers about potential further delays. And delays may be worsened because large cloud providers need to customize the racks to fit into their vast cloud data centers. It seems Nvidia is facing the same challenges with the smaller 36-chip racks. In the meantime, customers have decided to buy more Hopper chips.
Nvidia becoming a cloud and AI software provider
Nvidia has been quietly building its own cloud and AI software business (Nvidia AI Enterprise) and is already close to generating USD 2 billion in revenues annually. This is not surprising when we know that all major cloud providers (e.g., Microsoft, AWS, Google) are developing their own AI chips to become less dependent on Nvidia. The AI Enterprise suite includes all the necessary tools and frameworks to accelerate AI developments and deployments, including but not limited to PyTorch and TensorFlow for deep learning, NVIDIA RAPIDS for data science, TAO for model optimization, industry-specific solutions, NVIDIA RIVA for speech AI and translation, and much more. But don’t be mistaken, Nvidia is still far behind the major cloud providers and will continue to operate Nvidia DGX, their AI supercomputer, on the infrastructure of its competitors. Does Nvidia have a hedge compared to other big tech firms due to its proximity to AI hardware? Some believe so. Nvidia still has a long way to go before becoming a cloud and AI software business provider, but it definitely has the means to succeed, and that could become another major revenue stream.
Apple moving in AI chips with Broadcom
Apple is working with Broadcom to develop its own AI chips for servers, aiming for mass production by 2026. These chips are expected to be used internally rather than entering the consumer market, highlighting Apple’s effort to reduce reliance on Nvidia and other competitors. This trend mirrors a broader industry shift, as many tech companies seek to create custom AI processors to cut their dependence on Nvidia. However, designing AI chips is a complex undertaking, and most firms continue to rely heavily on Nvidia, with Google being a notable exception. In most cases, tech companies collaborate with chip makers to leverage their intellectual property, design services, and manufacturing capabilities. The deal between Apple and Broadcom seems to be different from other deals; Apple is still managing chip production with TSMC (it seems). Read
Other readings
> A look at why the world’s powers are locked in a battle over computer chips. How will Europe continue to compete against China from an investment perspective? read
> Broadcom chief Hock Tan says AI spending frenzy to continue until end of decade, read
> Perplexity’s value triples to $9bn in latest funding round for AI search engine, read, read about Perplexity here
Digital Transformation of Asset Managers and Wealth Managers 