Profits are privatized, losses are socialized.

Looking closely at it, it is a system that brilliantly combines the disadvantages of capitalism and socialism.

Just to get that straight: Legacy code is practically always large code with countless hidden requirements, and with insufficient or no tests and without documentation. But which works somehow. Any change needs to meet numerous unwritten requirements, and it can often only be tested in the real world. If you have N features, you have N*(N-1)/2 interactions between two features, so it is quadratic growth with N. This is why it is very hard and time-consuming to change.

It shouldn’t be that way, but writing large software - especially in commercial environments - is often like climbing a high roof on a ladder, and then throwing away that ladder. Modifications are only incremental, and usually not documented. Incremental modifications are one of the only two working engineering approaches for software we know - and the only one used for commercial software.

The other way - which is used in aviation for example - is to specify, document, and test everything, right from the start.

Now the problem is you can rewrite legacy stuff as much as you like, but it is near impossible to make sure that large changes work. Because in order to do that, you would need to run the tests that do not exist, or create tests from specifications and requirements which do not exist either.

And GenAI tools are not going to change that. The agentic tools kinda work by filling in missing requirements with assumptions and average observed stuff. It can generate reams of code, fast. But while this kinda works for a small phone app, it doesn’t for large complex stuff. If the code does not fit in the head of one person working for months on it, it will never fit in the context window of an LLM.

These companies advertising methods are becoming a bit too much!

and now they can freely make copies of some really important keys^*

* Communications, which could be you logging in into your banking account. The attacker would be able to see your banking password, for example. Or it could replace a software update your laptop is receiving with malware. A manipulated WLAN router in a cafe or an airport could do that.

Oof. Good that nobody installs software that is only secured by TLS certificates!

this is absolutely solved

How? According to the EU CRA, each connected device should have unique access credentials. How do you solve that in practice, in an organization like this?

I agree that using a VPN is much more secure. And together with not allowing remote temperature control, this would have prevented this specific issue.

Still, if you have a VPN in a large supermarket chain, you need to manage the access keys - in a way that when one user of the VPN quits the organization, their access is revoked.

And also, it isnot a good idea that many people share passwords to devices which give administrative rights. So, you should give a unique password to every user, similar as every guest in a hotel gets an NFC card with a unique code.

The best way I know of to do that would be a PKI and smart cards. This also prevents users from using dumb passwords or using the same ones in multiple places.

But my impression is that very few organizations like supermarkets do that.

It gets even more complex with the modern rush to outsource every little thing.

Well, in Europe this could be a condition for rapists to temporarily leave jail. At the end of their sentence.

You are right. But also, authentication in a distributed industrial infrastructure is hard, and it is not really a solved problem. You would need to set up a public key infrastructure, giving each shop clerk, service worker, and manager a smart card, revoking them when they leave, recover lost access credentials, and so on. For every class of devices.

And it gets even more difficult if you want machines to securely talk with each other (think in administering every smart home thing un your house with a smart card…).

Significant inflation leads to increased interest rates and this makes it more expensive to take on new debt.

Or, if a country has high inflation and does not increase interest rates, this can lead to money flowing out of the country.

Inflation can also affect consumer spending, and therefore, selling of future products. Whether the effect is positive or negative could depend on how much consumer spending is debt-financed.

Worth mentioning here:

https://hermit-tech.com/blog/ai-mania-is-eviscerating-global-decisionmaking

What the article does not even mention is the increasing strength of the much cheaper Chinese OpenWeight models like Qwen.

To be clear, if a genie in a bottle would grant me a free wish, I would request that this technology disappears from existence at least until we have solved the climate problem, found a solution how to compensate creative people and artists, and remedy its impacts on democratic discourse and mental health. But while one is allowed to wish for a better future, this is not the reality we face.

I was requested at work to try out one of the local open weight models yesterday. They are not free, requiring substantial hardware costs, but require less energy than the US models. And it seems with a more modest and more sane approach, companies are not going to pay many hundreds of dollars per month per seat for Claude licences when they can do with far smaller costs.

True that the “weaker” models will still require substantial and qualified human oversight for things like software development, but fully autonomous systems are more like a febrile hypercapitalist pipe dream than something technically desirable.

If only somebody would have told them!

Mark Ma, University of Pittsburgh professor and researcher on the AI layoff study, said leaders are focused on short-term performance, “which is why they tried to rush ahead by investing in AI and laying off workers”.

But companies’ share prices tend to dip after they announce AI-related layoffs, he noted, suggesting that “the stock market also does not think these will work out.”

Firms from Microsoft to McKinsey are limiting usage for employees, as the flood of new tools and rapacious consumption weighs on bottom lines. Others, such as Palantir, Booz Allen Hamilton and Nvidia, are restricting employee use over growing concerns about the security of their organizations’ data with AI companies, Reuters reported.

You don’t say!

C-suite leaders say when it comes to AI, there’s a sense that “we’re driving the truck and building it at the same time, and that’s a problem,” said Johnny C Taylor Jr, president and CEO of the Society for Human Resource Management. “If we could all rewind … we would have introduced [this] in a more thoughtful, slow way.”

They intentionally mix and match properties in portfolios so if one fails, there is less risk to the whole thing.

If AI fails, that is 25% of the US GDP, isn’t it? How can you distribute risk for that?

The sad thing is that the families of teenagers which killed themselves after encouraged by their chatbot might not see a cent of compensation. I would feel better if they were paid from the personal possessions of the ex managers.

The whole “ai” industry is as uninsurable as nuclear power. Maybe that’s why they are so wild after software generation: Software is still in many cases exempt from liability, as long as it is not a Boeing 737 Max that your buggy code crashes.

Also it’s madness that systems like these are connected directly to the internet without read-only permissions implemented.

Water systems in the US are, too. And they have been hacked.

The whole field is evolving, there is the EU Cyber Resiliency Act and some provisions for critical infrastructure.