Today my research note is a little bit more of a meta level analysis than usual. We are going to dig into the process a little bit and consider how to establish and maintain coverage in a space that is rapidly changing. Most of what I do is based on news feeds and academic article searches. However, my workflow also includes both ChatGPT and Gemini and both of them support deep research requests.
One of the things I have prompted both to do is to round up all the quantum achievements that have been announced in the last 90 days. I actually like to kick off both sets of deep research at the same time and see what overlap exists between the two outputs. Gemini actually will spit out a large report and you can quickly share it out to Google Docs which is something that I do to read the content that was produced. For better or worse, I tend to just read the content from the ChatGPT desktop app without exporting it. That means between the two outputs I’m reading a ton of content and trying to synthesize it back down to a research note format. That is where the value add comes into the picture.
This type of prompt analysis is not something you can do every week and expect vastly different results. So much news related to quantum computing gets released all the time that the online marketplace of ideas is exceedingly flooded. It’s not as bad as the content soup that exists related to AI which is good. Part of that is that most of the breakthroughs end up being hardware announcements or achievements which are easier to follow and understand. It’s clear we did this thing and we think it’s good because of something they try to clearly explain. Obviously, that is not always the case and sometimes announcements seem to be just for the sake of announcing something. It’s actually very difficult to figure out what is a signal and what is noise in the quantum space based on just the flood of announcements.
We can breakdown all this ongoing series of announcements into 9 categories:
Fundamental academic breakthroughs
Commercial quantum hardware and software milestones
Geopolitics, governmental/institutional strategies, funding, and infrastructure
Cross-industry and technology partnerships
Quantum sensing and metrology
Quantum networking and infrastructure development
Application-level demonstrations and domain use cases
Standards, policy, and international coordination
Education, workforce development, and ecosystem programs
Previously, I had explained that ultimately development within the quantum computing space could be analyzed by looking at the various parts of what a fab needs to build, iterate, and drive the actual manufacturing process forward.
Cleanroom infrastructure & environmental isolation
Advanced lithography systems
Precision deposition tools
Etching & material removal
Metrology & in-line inspection
Wafer packaging & 3D integration
Cryogenic test infrastructure
Photonics & optical control systems
Supporting utilities & safety systems
You probably have realized that the parts of the technology stack do not easily line up to the categories of announcements that are coming out on a regular basis. Most of the actual system advancements seem to get less coverage than other easier to consume and share bigger picture articles. A lot of the coverage ends up getting compressed down to a single company and how it drives the industry forward in terms of investment or fundraising. That makes sense given that a lot of the ongoing daily coverage is from an economic viewpoint. Some of the more zoomed out and higher level coverage includes geopolitical analysis about the quantum space. That lens tends to let the coverage get wider and include a longer time horizon.
Ultimately, I’m interested in this space to see where the ecosystem ends up getting built and how it drives the future of computing. We are at a critical point where key players are going to emerge and the technology really is moving from research to practical use cases. Put bluntly, we are about to see what quantum computing can really do and it’s going to be interesting.
