Dana Blankenhorn

The AI Silly Season

We’re currently in the “silly season” of hype over “Generative AI,” machine learning programs whose output can be text, code, pictures, audio, or video.

There’s a lot of experimentation and there are a ton of bad takes.

Here’s how it’s going to go.

There are two things to know.

First, any software requires training before it becomes useful. Right now programs like ChatGPT are creating garbage. Interesting garbage, but garbage. As people learn how to get value from these tools, however, there will be huge jumps in productivity. The timing and size will differ from industry to industry, and from organization to organization. But it will happen. People will be able to do more, high-quality work in less time. This won’t reduce the need for people. It will give people more things to do.

Run on the Bank

The collapse of Silicon Valley Bank may prove to be a bigger story than it appears.

The reason goes back to a story I ran away from, the 1981 collapse of the Houston oil industry.

I didn’t intend to run away. I finally got a job at a daily in Birmingham, Alabama. It was a job I’d hold only 4 months before being fired. But I left Houston June 1, 1981. The collapse began soon after.

As in this case, the Fed had telegraphed what it was going to do. Paul Volcker was going to raise interest rates until inflation gave up, just as Jerome Powell is doing now. Inflation was much higher than, double digits in fact. Add to that the Reagan Administration jawboning the Saudis for lower oil prices and it was a perfect storm.

That 2002 Feeling

The last tech crash began in 2000 and I was in the center of it, a mid-career writer with a specialty called Internet Commerce.

That year saw denial and bargaining.

The next year saw anger and depression.

It was only in 2002 that acceptance came.

We know what followed. Talented programmers worked on open source projects and standards bodies created what became the Cloud. When proprietary advantage became worthless, and there seemed there was nothing to do, people worked together with technical goals in mind rather than just financial ones.

It was a slow build. In 2002 my gross income was zero dollars. In 2003 it was zero dollars. I got interested in what’s now the Machine Internet, which I christened the World of Always On, and in 2004 I finally made a few dollars. The next year I was asked to cover Open Source, and my career took off. For a time.

I’ve mentioned before how, in every photo of a stock market crash the people in it look similar. Similar age, similar backgrounds. They’re different people. Those who watched the 1987 crash were different from those who saw the 2000 crash, different from those who saw 2008, different from those who saw 2022.

Where Computing Happens

I met my first computer in 1976, in the basement of Herman Brown Hall, on the campus of Rice University in Houston.

The computing happened in a big room, separated from me by a window. I passed a stack of punch cards, tied with a rubber band, through the window. They came back along with my output. Which usually said the program had died on Line 3.

By the time I got out of journalism school, two years later, computing was moving to desktops. A neighbor bought a $20,000 Cromemco machine that could run 3 terminals. She hired friends to work at the terminals, transcribing court records. I think they got 50 cents a page. Computing had come home.

Wintel (1990-2023): Death of a Monopoly

An era ended this week, as the control over technology Microsoft and Intel held with Microsoft Windows and Intel x86 chips crashed and burned.

From the launch of Windows 3.0 in 1990 to this last week, there was an assumption that Wintel, as the two were called, were where computing happened. No more. OEM sales of Windows fell by a third, and so did Intel’s x86 chip sales.

Client computing has moved from your desktop to the palm of your hand. An iPhone or high-end Android device can cost over $1,000 but you don’t need a manual to use them. They’re intuitive. When they fail, you get another, and all your software follows you from the cloud.

Microsoft was ready for this. They became a Cloud Czar during the 2010s, building a huge network of scaled data centers using open source software and cheap hardware. Intel supplied the cloud, and its data center business beat expectations last quarter, but it was not ready for the change. Its stock fell another 10%, and the company is now worth barely one-fourth the new chip leader, Nvidia.

The Other Arms Race

We talk a lot about guns in the US, without doing anything about them.

But there’s another, even more dangerous arms race, going on.

It involves cars.

It’s not just that there are too many of them. They’re too damned big. Spending $60,000 for a pick-up that will never see a trailer hitch, or an SUV higher than an elephant’s eye, is stupid. Especially since these cars are sitting, unused, 90% of the time.

People buy giant cars for the same reason they buy guns. They make you feel safe. They buy as much car as they can afford, like these things are houses.

The Word for 2023 is Efficiency

If you can save costs, in business or consumer markets, you can make money.

This is technology’s big opportunity in 2023.

The cloud has already transformed how people interact. It’s now going to transform how machines interact.

Sensors and network software can be applied everywhere. Thanks to falling chip prices this can now be done cheaply. There is labor available to write the software, build the companies, and reap the rewards.

Consider the water system. Why aren’t sensors monitoring the condition of pipes, warning of potential failures, and identifying leaks the moment they occur? Why are water authorities still depending on people finding cracks in the street with water coming out of them on their own?

Positives of a Tech Recession

Despite some stunning investment losses, I’m enjoying the latest tech recession.

No one likes a recession, but sometimes it’s like spring cleaning, necessary to clear the excess. There were a lot of zombie technologies, zombie companies and zombie assumptions that have been overrun since the Fed decided that money should cost money and there should be less of it around.

Web3, the metaverse, and crypto were all fake from the jump. Advocates for streaming and podcasting didn’t understand that the gating factor is time, not money. A lot of companies were selling themselves based solely on sales growth, ignoring the need for profit.

This means there’s now opportunity, in the form of talent, for new ideas that will power the economy forward. The main trends I described in 2019 – the end of oil, the Machine Internet, and DNA as a Programming Language – they’re still on. But there’s a lot more, too.

The Intranet of Systems

 

A warehouse is a system.

A factory is a system.

A hospital is a system.

The Machine Internet is now ready to take its next step, toward the transformation of systems.

Vendors have been adding intelligence to machines for a decade. My car can now tell me when my tires need air. Many machines can tell their owners when they need preventive maintenance.

An Intranet of Systems would get all the software on these machines working together, the way orchestration software lets a company control its supply chain.

The Time Is Now

Here is what 45 years of studying business cycles has taught me.

Now is the time to work on your next great startup.

Right now. When the whole world is collapsing around us. When old business models are failing. When everyone is worried about their job, or about to lose it.

Look at the opportunities. I detailed them three years ago. The end of oil. The machine Internet. DNA as a programming language.

These boil down to renewable energy, control systems, and medicine.