The machine tools were all made 50+ years ago. Changing anything was a dangerous thing to do, because you might cause jobs that have known and reliable setups that are done a few times a year in quantity, to fail, erasing the profits for the job, and possibly losing customers.

The rush to fill brand new high energy intensive data centers with hardware that has commercially useful lifetimes measured in months (instead of decades for machine tools) seems quite short sighted to me.

source: visit any Chinese tier 1 city (Beijing, Shanghai, Guangzhou, Shenzhen) and it will blow your mind if you've only lived in the West.

And if you haven't visited, for example this is tier 1 China: cashless society, amazing public transportation, clean streets, no homeless, practically zero crime, drone food delivery (in Shenzhen, certain spots only), high-speed rail to every major city in China (and even to smaller tier-2, tier-3 cities), wonderful infrastructure that gets built in years (vs decades in the West), extensive subway systems with protective barriers at every single station (so you can't suicide or push someone on the tracks) etc.

We used to talk about AI as having no moat (easy for other players to accomplish similar AI achievements). China has made that clear. Some open weight LLMs are fine and can run on laptops. It seems the new moat is model parameter size and VRAM requirements. I would bet on innovation in hardware or disruptive algorithms changing that game so better LLMs can run on more personal computers. Remember how bitcoin miners all used GPUs then ASICs came along and made that no longer profitable?

There are many ways the AI industry can be disrupted which makes it that much more volatile.

I don't really know what the lesson here is.

"Our goal is to create a company that can do anything short of manufacturing physical objects directly, but will be able to do so indirectly, much like Apple has other companies manufacture their phones."

In other words, we are a knowledge economy and outsource like it's the 1990s with a bit of "AI" fantasies thrown in. The crash cannot come soon enough.

[1] "Private sector spending on equipment, adjusted for inflation"

Now there's a populist making political hay, throwing out numbers about trade deficits, which ignores revenue from services. Yes, there is have a trade deficit on goods, that was a long-term strategy because services were a superior investment.

Manufacturing is an inferior way to make money unless you're planning to go to conventional war, and since the US is a nuclear superpower it's never going to get into an existential boots-on-the-ground Serious War again unless it just wants to cosplay. Nukes make conventional war for survival irrelevant.

So: it took decades to burn the boats with manufacturing, and trying to rebuild them in a few years is a hilarious folly. It absolutely will not go anywhere, and honestly shouldn't anyway. There is real danger, however, that the US burns the boats on the carefully crafted service sector as well.

"Ford CEO Jim Farley said Chinese cars have "far superior" technology, lower costs and great quality."

Ford is working on fixing this and getting a $30,000 EV out the door.[2]

[1] https://insideevs.com/news/764318/ford-ceo-china-evs-humbled...

[2] https://archive.is/kUbEW

Industries in the US are at an inflection point, with govt / global market giving conflicting signals. For example car manufacturers need to decide whether to invest in EVs, which is a huge capital investment they won't see return on for maybe a decade. If they dont invest, they won't be relevant outside the few markets clinging religiously to ICEs

Do you layout a billion dollars to try to stay relevant outside the US? Or stick to reliable, if soon shrinking, domestic internal combustion engine business model?[1]

Contrast this with AI where signals are unambiguous from government and investors.

1 - As an example, this $1.6B charge GM is taking https://www.bloomberg.com/news/articles/2025-10-14/gm-to-tak...

No, it's not.

It's actually because China is lowring the requirement/quality for delivery and makes everthing for the comsumer market to degrade rapidly so that the manufacturers has the chance to involve because of the involving needs for newer/better products.

It is a common sense here in China that a lot of manufactural products have better quality from imported sources, it is the growing needs from the comsumers that require products to have newer/more functionality even if it has shorter lifetime, or event 'better', the product is looking for growth so they are designed to be short lifetime so the manufacturer and the customer both willing to upgrade in the future.

Excuse my language/grammer.

A lot of younger people it seems like value flexibility over higher pay. They’d rather work casual jobs that are dead ends. At the factory you start with a decent wage and benefits and within a year you’re promoted and salary increases noticeably. If you can put 5 responsible years in you’re certainly recruited to the management development path. These skills are highly transferable between companies.

I'm not saying he's wrong just yet, I'm just pointing out that he owns a propaganda mouthpiece and is willing to lie on a grandiose scale to protect his business interests.

That's 0.3%.

The narrative claims that AI will make everyone far more productive, but in reality, I see people working harder than ever and burning out while maintaining this slop in production.

AI search and summarization have been a flop, and most people I know hate them. LLMs are undoubtedly useful, but despite all the supposed productivity gains, I’m not seeing any measurable impact. I used to spend hours reviewing human-written PRs, and now I spend even more time because of lazy AI-generated garbage creeping into the codebase.

Some AI parrots will say, “Oh, I never push code I don’t understand,” but that doesn’t stop others from doing it, and now you have to be extra vigilant during PR reviews.

The gist is that everyone claims to be more productive, but the numbers say otherwise. Even so, LLMs are genuinely useful, just not nearly as much as the investment would suggest.

The new superpowers will be the EU, which was smart enough not to make the same gamble, and China, which will structurally survive it.

I started, grew, and exited a modern manufacturing-based business, and I can confirm that almost everything about modern capitalism in this cycle is biased -against- any business that manufactures in 1st world economies. The business, Spoonflower, was and is an innovative marketplace of textile design, mated to on-demand manufacture, and had factories in Durham NC and Berlin Germany.

Three factors made this very difficult:

-- raising funding or debt to support old-fashioned capital equipment. Building factories was once the backbone of the US economy but is now pretty close to impossible for an entrepreneur. Raising money to write software is straightforward and well understood. Raising money to purchase industrial equipment the size of a city bus is not what our startup economy is optimized for, or even understands or has models for. Confusion about this is nearly universal.

-- operating a labor-intensive (anything where the largest component of cost is the labor component) manufactory. As others have noted, making stuff is physically demanding. Some people love hard work, but culturally this is rare. If you are crazy successful, the reward is another shift of harder, potentially more efficient work.

-- exiting investors / providing ROI. Our business fit in two categories: creative digital marketplaces (Ebay, Etsy...) valued at 4-6x revenue, or makers like Cimpress or Shutterfly at .5 to 1x revenue. Who buys factories.... even really interesting ones? The short answer: only those that already own factories. When you have a very short list of potential acquisitors, its hard to create an auction market for your equity.

In general, we did okay. But every step from launch to growth to exit felt very much like swimming into a strong current. The same very hard working and resourceful group of colleagues could have done anything. I'm proud of the work, but a lot of that pride is sheer contrariness at having executed on something so unlikely and having survived.

This would be much harder now.

Sourcing is harder. Friends working in the space now rely on a global sourcing network just as we did, that is in utter disarray. Operating on thin margins with a factory that must be fed raw materials to make money is terrifying on a normal day. These days the threat to supply chains is existential.

Launching consumer brands is harder. As has been widely noted, access to the top of the funnel has now been fully monetized (or fully enshittified) by Google, Facebook etc, and because of AI, that funnel now shrinks. Something will break loose here, but nothing has yet.

A post-pandemic employment environment is even more difficult for manufacturers. I think it is safe to say that demand for jobs that require 8-12 hours of physically demanding work surrounded by colleagues and industrial machinery is at an all time low.

I spent 15 years in service to a vision of domestic making, and while we were not defeated, I understand deeply the uphill battle any manufacturing entrepreneur faces.

The AI crash will be a catalyst for general instability and chaos with a fascist at the helm.

Using LLMs to generate texts for inefficient communication (to other humans or machines) is just so wrong.