Huang’s Law & Moore’s Law

The recent purchase of Arm and NVIDIA’s new developments

This article will take a quick look at Moore’s Law and the emerging discussion of Huang’s Law. First, we have to consider current events.

Nvidia purchased Arm for $40 billion.

This was announced the 13th of September 2020.

Arm Limited is a British semiconductor and software design company owned by Japanese conglomerate SoftBank Group. The Cambridge-based microchip designer makes software and semiconductors that are used in a multitude of consumer favourites, including Apple and Samsung smartphones, Nintendo consoles and many more. Its chip designs are increasingly used in the growing Internet of Things industry.

According to a piece from Hamza Mudassir in The Converation much of its success came from its neutrality, since it did not. compete with companies it licensed its designs to. It focuses on patenting and licensing designs.

This could likely change now.

In the NVIDIA press release on the 13th of September Jensen Huang, founder and CEO of NVIDIA stated:

Christoffer Mims writes a weekly column for the Wall Street Journal on technology. In his most recent article he argues that Huang’s Law is the new Moore’s law and connects this to the recent purchase of Arm.

In his introduction he writes:

“The rule that the same dollar buys twice the computing power every 18 months is no longer true, but a new law—which we named for the CEO of Nvidia, the company now most emblematic of commercial AI—is in full effect.”

He says that in a previous epoch Gordon Moore from Intel Corp laid out a prediction. Moore’s Law held that the: “…number of transistors on a chip doubles roughly every two years. It also meant that performance of those chips — and the computers they powered — increased by a substantial amount on roughly the same timetable.”

This became an often repeated proof of the industry and its great progress forward. This has changed the everyday life for a great deal of citizens across the planet. They now have atomic scale circuitry, but then Mims argues a new law needs to be considered.

In this article he presents a graph:

Graph by Mims of the increase in speed and energy efficiency

One major point here:

  • “Between November 2012 and this May, performance of Nvidia’s chips increased 317 times for an important class of AI calculations.”

For some time the speciality of Nvidia has been GPUs that operate efficiently with many independent tasks to be done simultaneously.

Central processing units, or CPUs are more focused on executing a single, serial task very quickly.

Mims argues that Nvidia isn’t alone in driving Huang’s Law. This is part of the reason for its recent acquisition, purchasing Arm.

This will make range of applications possible. Two examples are in retail and for autonomous vehicles. However, I would recommend you to read his article to explore these in detail. He says as well that the use of AI in mobile is multiplying as well as in smart devices. According to Mims: “Arm Holdings—whose patents Apple, among many tech companies large and small, licenses for its iPhone chips—is at the center of this revolution.”

Consider this for a moment.

How will it change computing?

How will it change your everyday life?

This is #500daysofAI and you are reading article 473. I am writing one new article about or related to artificial intelligence every day for 500 days.

AI Policy and Ethics at Student at University of Copenhagen MSc in Social Data Science. All views are my own.