Category: Cloud

The week on AI – December 22, 2024

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

2023 Gartner Emerging Technologies and Trends Impact Radar

Gartner has released its 2023 Gartner Emerging Technologies and Trends Impact Radar. Let me try to give it a read with the eyes of a wealth
or asset manager.

Artificial Intelligence is all over the radar, with Foundation Models, Self-Supervised Learning, Generative AI, and more. Wealth and asset managers must seriously look into Artificial Intelligence and understand how it can be leveraged across their value chain, from investments to operations, risk management, and compliance. Part of the solution will come from their solution providers, like Bloomberg, BlackRock Aladdin, or State Street Alpha, to name a few providers. But wealth and asset managers cannot only rely on their providers. Instead, they must acquire the necessary skills and talent and play with artificial intelligence technologies. War for talent will make it complicated.

Blockchain is also quite present with Web3 and Tokenization, both being in the 3-6-year horizon. Most wealth and asset managers are already testing tokenization in one way or another, and they should continue. Tokenization will have many benefits for the industry, from speeding up transactions, eliminating some intermediaries and therefore reducing costs, making some asset classes available to smaller investors, improving the liquidity of some assets, and more. Tokenization will require some industry alignment and standards.

No surprise, Digital Twins are here too. Gartner is probably thinking more about Digital Twins in the context of manufacturing and industrial activities. But as discussed in this blog, the potential for digital twins in the financial industry is real and massive.

Then, there are hardware and infrastructure with Neuromorphic Computing, 6G, and Hyperscale Edge Computing. If wealth and asset managers continue to move to the cloud, they’ll be able to leverage these latest hardware technologies as they become available in the cloud.

Wall Street continues to move to the public cloud

All big Wall Street players like JPMorgan, Citadel, Point72 continue to move to the public cloud. As INSIDER puts it, “who they are and what they do is now more important than ever.” While the business case is not evident, even if the move to the cloud is just break-even, elasticity, the ecosystem, and innovation are key drivers for moving to the public cloud. Not to mention that with today’s supply chain challenges, probably the only option to access some infrastructure quickly. And most likely the only way to continue to compete in the future. For those still skeptical about security, I wonder what makes them believe on-prem is safer? Who can compete with the USD 20 billion and USD 10 billion Microsoft and Google will respectively spend on security over the next five years?

And Wall Street is not alone in moving to the public cloud. Microsoft and the London Stock Exchange Group have just signed a new deal, where Microsoft will buy a GBP 1.5 bn stack of the LSEG, LSEG is committed to spending GBP 2.3 bn at Microsoft, and both will leverage advanced technologies like machine learning and native Azure solutions to improve LSEG’s data and analytics capabilities. And more. This follows similar partnerships between Google and CME, and AWS and Nasdaq.