Ostensibly written about Nvidia’s plight of having to move to bigger and bigger silicon as Moore’s Law ("the number of transistors per square inch on integrated circuits doubles approximately every two years”) is dead – this is, of course, much bigger than a single chip manufacturer.

Advancements in process technology have slowed to a crawl in recent years. While there are still knobs to turn, they're getting exponentially harder to budge. Faced with these limitations, Nvidia's strategy is simple: scaling up the amount of silicon in each compute node as far as they can.

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In any case, Nvidia's path forward is clear: its compute platforms are only going to get bigger, denser, hotter and more power hungry from here on out. As a calorie deprived Huang put it during his press Q&A last week, the practical limit for a rack is however much power you can feed it.

Link to article.

BloombergNEF’s deep dive into the insane costs of building super-scale data centers for AI is quite the eye-opener:

Microsoft and OpenAI are in discussions about a $100 billion, 5GW supercomputer complex called Stargate. Amazon has said it plans to spend $150 billion in the next 15 years on data centers. Last month KKR and energy investor Energy Capital Partners entered an agreement to invest up to $50 billion in AI data centers. BlackRock has launched a $30 billion AI infrastructure fund.

These huge data centers will be as complex and expensive as aircraft carriers or nuclear submarines. The building alone for a 1GW data center will set you back up to $12 billion – for vibration-proof construction, power supply, UPS systems, cooling, and so on. 100,000 GPUs could cost you another $4 billion, and that’s before you have installed chip-based or immersive liquid cooling, and super-high-bandwidth, low-latency communications.

Reading the report makes you realize that the old adage of “selling shovels to the gold diggers” is as true for AI as it was for most other technologies before that. Everyone in the datacenter space—rejoice! Your future is bright. ;)

Link to report.

In the US, car rental company Hertz is becoming increasingly desperate to reduce its EV fleet:

Hertz has contacted multiple electric vehicle renters recently with interesting low-cost offers for cars like Teslas, offering them the option to buy their rental EVs instead of returning them. One 2023 Model 3 renter shared on Reddit that they were offered a price of $17,913, which is similar to deals currently showing on the Hertz Car Sales site. However, the rental they were in had about 30,000 miles on it — fewer than other current listings.

This is a trend that has been ongoing for a while for the company:

Last year, Hertz decided to scale back its big ambitions to electrify its rental fleet due to low customer demand and repair difficulties on some models, including the Tesla Model 3. Then, in February, Hertz said it would no longer buy Polestar 2 vehicles either before marking 30,000 Teslas to sell off from its rental fleet.

Meanwhile, in China, the picture looks dramatically different – recent headlines include “China’s EV sales to surpass traditional cars by 2025 amid slower U.S. and Europe adoption” and “China’s EV adoption projected to reach 80% by 2035.”:

Links to Hertz article and China EV report.