Steve Jurvetson shared on Twitter that Tesla now holds the mantle of Moore’s law in the same manner NVIDIA took leadership from Intel a decade ago. He noted that the substrates have shifted several times, but humanity’s capacity to compute has compounded for 122 years. He shared a log scale with details.
Tesla now holds the mantle of Moore’s Law.
Just as NVIDIA took leadership from Intel a decade ago.
While the substrate has shifted several times, humanity's capacity to compute has compounded for 122 years as if on rails.It's surreal. Log scale details: https://t.co/WekzWo9MGU pic.twitter.com/2t1246m1si
— Steve Jurvetson (@FutureJurvetson) August 21, 2021
The link Jurvetson shared included a detailed article explaining how Tesla holds the mantel of Moore’s Law. Tesla’s introduced its D1 chip for the DOJO Supercomputer and he said:
“This should not be a surprise, as Intel ceded leadership to NVIDIA a decade ago, and further handoffs were inevitable. The computational frontier has shifted across many technology substrates over the past 120 years, most recently from the CPU to the GPU to ASICs optimized for neural networks (the majority of new compute cycles).
“Of all of the depictions of Moore’s Law, this is the one I find to be most useful, as it captures what customers actually value — computation per $ spent (note: on a log scale, so a straight line is an exponential; each y-axis tick is 100x).
“Humanity’s capacity to compute has compounded for as long as we can measure it, exogenous to the economy, and starting long before Intel co-founder Gordon Moore noticed a refraction of the longer-term trend in the belly of the fledgling semiconductor industry in 1965.
“In the modern era of accelerating change, it is hard to find even five-year trends with any predictive value, let alone trends that span the centuries. I would go further and assert that this is the most important graph ever conceived (my earlier blog post on its origins and importance).
“Why the transition within the integrated circuit era? Intel lost to NVIDIA for neural networks because the fine-grained parallel compute architecture of a GPU maps better to the needs of deep learning. There is a poetic beauty to the computational similarity of a processor optimized for graphics processing and the computational needs of a sensory cortex, as commonly seen in neural networks today. A custom chip (like the Tesla D1 ASIC) optimized for neural networks extends that trend to its inevitable future in the digital domain. Further advances are possible in analog in-memory compute, an even closer biomimicry of the human cortex. The best business planning assumption is that Moore’s Law, as depicted here, will continue for the next 20 years as it has for the past 120.”
In the detailed description of the chart, Jurvetson pointed out that in the perception of Moore’s Law, computer chips are compounding in their complexity at near-constant per unit cost. He explained that this is one of many abstractions of the law. Moore’s Law is both a prediction and an abstraction this abstraction is related to the compounding of transistor density in two dimensions. He explained that others related to speed or computational power.
He also added:
“What Moore observed in the belly of the early IC industry was a derivative metric, a refracted signal, from a longer-term trend, a trend that begs various philosophical questions and predicts mind-bending futures.
“Ray Kurzweil’s abstraction of Moore’s Law shows computational power on a logarithmic scale, and finds a double exponential curve that holds over 120 years! A straight line would represent a geometrically compounding curve of progress.”
He explained that, through five paradigm shifts, the computation power that $1,000 buys has doubled every two years. And it has been doubling every year for the past 30 years. In this graph, he explained that each dot represented a frontier of the computational price performance of the day. He gave these examples: one machine used in the 1890 Census, one cracked the Nazi Enigma cipher in WW2, and one predicted Eisenhower’s win in the 1956 presidential election.
He also pointed out that each dot represented a human drama and that before Moore’s first paper in 1965, none of them realized that they were on a predictive curve. The dots represent an attempt to build the best computer with the tools of the day, he explained. And with those creations, we use them to make better design software and manufacturing control algorithms.
“Notice that the pace of innovation is exogenous to the economy. The Great Depression and the World Wars and various recessions do not introduce a meaningful change in the long-term trajectory of Moore’s Law. Certainly, the adoption rates, revenue, profits, and economic fates of the computer companies behind the various dots on the graph may go through wild oscillations, but the long-term trend emerges nevertheless.”
You can read Jurvetson’s full post here.
Some Thoughts
By taking on the mantle of Moore’s Law, Tesla is achieving something that no other automaker has achieved. I used the term “automaker” since Tesla is often referred to as such by the media, friends, family, and those who don’t really follow the company closely. Tesla started out as an automaker and that’s what people remember most about it: “a car for rich people,” one of my close friends told me. (She was shocked when I told her how much a Model 3 cost. She thought it was over $100K for the base model.)
Jurvetson’s post is very technical, but it reflects the truth: Tesla has done something unique for the auto industry. Tesla has progressed an industry that was outdated and challenged the legacy OEMs to evolve. This was is a hard thing for them to do, as there hasn’t been any new revolutionary technology introduced to this industry since Henry Ford moved humanity from the horse and buggy to automobiles.
Sure, over the years, designs of vehicles changed along with pricing, specs, and other details, but until Tesla, none of these changes affected the industry largely as a whole. None of these changes made the industry so uncomfortable that they laughed at the idea before lated getting scared of being left behind. The only company to have done this is Tesla, and now new companies are trying to be the next Tesla or create competing cars — and do whatever they can to keep up with Tesla’s lead.
For the auto industry, Tesla represents a jump in evolution, and not many people understand this. I think most automakers have figured this out, though. Ford and VW especially.