WSJ Warning on Quantum - Four Important Things to Add

Great article from the smart folks at WSJ. The headline is:

Quantum Computing Is Closer Than Ever. Everybody’s Too Busy to Pay Attention.

That is 100% correct.

Four Things to Add

I. The Horizon Isn't What It Used To Be

It is hard to see unless you are watching at the right level and breadth, but the last 12 years or so are characterized by three things:

• In science and technology, big developments that are on the horizon four to five years out are moving faster than most insiders think and getting here much sooner.

• Over the near horizon, many things that the insiders feel are less likely than green men from Mars landing in New Jersey are happening. Some of these are not broadly known in the business world because they aren't everyday watercooler chats (GenZ, please look that up). Examples include CRISPR, Rapamycin, Higgs Boson, LLMs/GenAI, mRNA, Synthetic Genome, and DeepSeek. This is accelerating because every branch of everything absorbs the windfalls from AI advances.

• This is happening beyond science and technology, such as geopolitics, warfighting, etc.

As the promise of the 4th Industrial Revolution lands, a key characteristic of our times will be a massive acceleration in high-impact breakthroughs/advances.

Of course, this applies to Quantum.

Like prior Industrial Revolutions, this creates a massive cycle of Creative Destruction. The winners are often not the inventors but the business model redesigners who smartly leverage innovation.

II. Steal Now Use Later (SNUL)

The article from WSJ says you will need a really big Quantum Computer to crack most public key encryption. That's how 99% + of 'secure' data is stored. Yes, that's true. But three key points:

• Bad actors, some with nation-state-level skills, are already stealing and storing the data.

• The efforst in progress to make really functional Quantum Computers will scale fast once they break a minimum threshold.

• Building a robotic quantum-enabled decryption platform to harvest everything interesting, such as kompromat, industrial intelligence, design specs, financial information, and complete personal data, is not difficult.

Yahoo was fantastically good at IT and Cyber. I would easily put them in the top 5% globally. They had a 1.4 Exabyte majestically well-engineered Big Data / Analytics stack. That was bigger than anything outside of the Intelligence Community. Their Cyber team, The Paranoids (I still have the T-shirt), were brilliant. A month after I joined Verizon (08 2016), Yahoo, which we had agreed to acquire, announced the theft of the data for 500 million users from two years prior! In December, they discovered another hack where they took a billion users' information three years prior. Yes, they detected it three years later. Usually, 'detected' means you get a call from the Secret Service or the FBI (who were told by the NSA) saying they found your stuff for sale on the Dark Web.

Encrypting data so it can't be cracked by the advanced mathematics capabilities of a Quantum Computer is not hard, and that technology has existed for several years. For example, you can't do tech work with the NSA unless you do that. Arqit is my favorite investment in that space, and it is easy to use and works today.

III. Quantum is Not What You Think

Many business people think of Quantum computing as a four-orders-of-magnitude more powerful computer. It is, however, not that.

Quantum Computing is computing that works on a completely different model than your iPhone, Amazon's Cloud Infrastructure, ChatGPTs massive GPU farms, or El Capitan, the 2.7 Exaflops supercomputer out at Larence Livermore National Labs. Think of Quantum as doing thousands if not millions of steps simultaneously, whereas the others have to do it sequentially.

That means it can use algorithms that take advantage of this, which really means it can solve certain types of problems that would take all the regular computers on earth my lifetime to solve (literally).

The traveling salesman problem is a great example. FedEx has a lot of stations, hubs, jets, humans, and trucks; the optimum 'network' design for all of that is beyond all the computing on earth. Quantum is particularly good at solving giant optimization problems. So that is things like FedEx, which is all supply chain/logistics. But parallel problems exist in chemistry, materials science, drug discovery, financial modeling, climate science/weather prediction, and high energy physics. That last one is more important than you think, including cancer treatments, superconductivity, and materials breakthroughs.

Just over the horizon, five to ten years away, are a set of combinatorial impacts where scale Quantum Computing and the advances in AI take a tag team approach.

IV. The Big, Big Picture

Ten years ago, the smart tech core of folks that built Cleversafe and sold it to IBM for around $2B went off in a dark cave and reworked the entire Big Data stack to do petabyte/exabyte analytics 1000x faster. Tech always moves forward fast, but not that fast. 1000x is 15 years of Moore's Law. Deepseek R1 has 671 billion parameters. Supercomputers are 700x ahead of where they were 15 years ago. Google's PaLM2 was trained on 3.6 trillion tokens. You really don't have to know what those last two mean technologically. It is just that we are entering a new era of massive scale and speed. Humans have difficulty understanding or visualizing a trillion anything; it is just so large. 3.6 trillion feet is the same as 2,800 trips to the moon, at the speed of Apollo that's about 24 years in space at top speed with no breaks for lunch or fuel or crew changes.

The point is that in the distant future, like Q4 of 2026, we will begin a new era of scale analytics, where we can computationally manage massive data sets. We will pursue things we have ignored because we just had to. This will be the beginning of things like ecosystem/industry sector intelligence, full domain/theatre-wide defense intelligence and simulation, and real demand shaping/inventory optimization versus the clunky approach to supply chains we have today. The complexities of what happens in our cells at the base level require such scale to model.

It will be the beginning, but remember that things on the horizon behind that beginning are coming faster than you think.

Then Quantum and boring old regular superscale AI will start to interact, but probably not for a long time, like a decade.

Why a Picture of Eli Whiney's Invention and a Quantum Computer?

There were a lot of primary and secondary impacts when Eli Whitney invented the Cotton Gin in 1793. In about 17 years US cotton exports grew 20,000%. (and 10x on top of that in the next 50 years). Of course, part of that was labor arbitrage in the worst way imaginable.

There have been many 'Eli' advances of various sorts since 1793 on the way to the Quantum Computer. Over the next twenty years, we will see decidedly more than all of them combined.

The next decade or two is almost unimaginable.