Teaching kids to spot when AI confidently makes things up is genuinely useful. Frankly, plenty of adults could use that class too. The real test is whether schools teach children to question the machine, or just train the next generation to accept whatever a chatbot says with excellent grammar.

The founders got their Google exit, investors got their hype cycle, Disney gets the leftovers, and families get the consequences. Character.AI managed to automate companionship, monetize next to nothing, and somehow make bankruptcy look like the least disturbing part of its business model.

AI was supposed to make everything cheaper and more productive. Instead we get higher power bills, pricier computers, fewer workers building homes, and inflation. Turns out the productivity miracle is mostly Big Tech finding a remarkably efficient way to make everyone else subsidize its server farms.

Apparently the solution to public outrage over Flock cameras is to replace them with a system that connects every camera, drone, dispatch call, and sensor into one giant police dashboard. Brilliant. We complained about Big Brother watching us, so they gave him a second monitor and a searchable archive.

We were promised a frictionless, intelligent future. Instead we’re building gas plants so a chatbot can confidently invent court cases and recommend glue on pizza. Apparently the cloud was just a smokestack with better branding. Big Tech gets the profits, everyone else gets the asthma.

Trump’s war with Iran has given the world a fascinating new infrastructure strategy: route the internet around the mess Washington helped create. Apparently »America First« now means American tech companies paying extra to keep Europe and Asia online. The cloud has never looked so dependent on one man’s foreign policy tantrums.

Same here. Local is not the problem. Control is.

And the irony is that China has moved far beyond copying Western technology. It’s now a global leader in research output, including fundamental research in materials science, chemistry, and physics. The West outsourced manufacturing, underestimated the transfer of expertise, and somehow assumed China would remain the world’s assembly line forever. That assumption aged spectacularly badly.

It isn’t.

Absolutely, outsourcing manufacturing gave China a massive head start. But the West also outsourced decades of expertise, supply chains, and industrial know how while congratulating itself on becoming a service economy. China didn’t just inherit factories: it invested, learned, innovated, and built an industrial ecosystem. We handed them the starting line, not the finish line.

The US is busy figuring out how to charge a monthly subscription for an AI that summarizes emails. China is making the batteries, solar panels, and drones everyone actually needs. At some point Silicon Valley will announce a breakthrough: a chatbot that explains why manufacturing moved overseas.

Apple used to brag that its products just work. Now your expensive Mac comes with a bloated AI experiment you didn’t request, can’t fully remove, and are expected to thank Tim Cook for. When customers start writing tools to delete your flagship feature, that’s not innovation.

Walmart spent billions replacing warehouse workers with robots, only to discover the robots can’t lift dog food and the engineers cost more than the workers did. Apparently the automation revolution has reached its greatest technical challenge yet: doing the job it was supposed to automate. Somewhere, a PowerPoint deck is quietly being deleted.

Personally, I use older, smaller models, provided they are adequate for the task at hand. My theory is that at least 80% of companies are using a sledgehammer to crack a nut. Not only is that incredibly expensive, but it’s also incredibly ignorant.

The funniest part is that the thing that could actually make AI useful at scale might be what wrecks the investment thesis: cheap, local, open weight models. Wall Street funded a trillion dollar server farm to discover that sometimes the answer is a smaller model running on your laptop. The technology might win while the investors lose. Nevertheless, companies such as Google, Amazon, and Microsoft – as well as Nvidia and AMD – are a very long way from simply going under.

Exactly. And cheap open weight AI is the wildcard. If people can run capable OWAI locally for pennies, the trillion dollar moat starts looking like a very expensive puddle. AI could thrive while the companies betting on permanent scarcity discover they funded their own competition.

Exactly. The bubble isn’t AI existing: it’s the assumption that every company needs to spend billions renting GPUs to reinvent autocomplete. The irony is that if open models keep improving, the technology could become more useful precisely as the companies selling it become less valuable. Great for users, catastrophic for anyone who priced their stock as if competition had been abolished. - PS: Before any of the Frontier providers go bust, Apple will simply use its cash reserves to buy a good Siri.

The funniest part is that the dot com crash didn’t kill the internet. It killed a lot of terrible business plans. AI may follow the same script: useful tools survive, investors discover that a chatbot isn’t worth infinite money, and taxpayers get stuck with the data center power bill. The technology can be real while the valuation is pure casino. - PS: You didn’t mention the smartphone. And that’s exactly what people mainly use these days.

Big Tech calls AI data centers an economic boom. The Senate investigation suggests a different business model: privatize the profits, socialize the electricity bills, collect tax breaks, and make everyone sign NDAs. A 100 MW facility may power through the equivalent of 100,000 homes while creating about 100 permanent jobs. That’s not a jobs program: it’s a subsidy program with servers.

Good point. It is important to keep things in perspective.