Chips design is expensive. Partly because of engineering costs, partly because of manufacturing costs.

If costs go down enough,because of LLM's and possible manufacturing innovations, more chips will be designed, so maybe this will partially offset job loses.

For each Design Engineer, there are 3 Design Validation Engineers because going to fabrication is very expensive and it is unlike software where you can just do a git push and wait for the CI/CD pipeline to deploy code within minutes at no additional costs.

So let's see.

The wish granting machine won't need the engineers for that. You'll just end up paying for the devices.

When TSMC capacity is already sold out for a couple of years, and demand just for plain RAM is through the roof, where will these "more chips" be actually fabbed?

> more chips will be designed, so maybe this will partially offset job loses.

This is HN mentality. But it is not how it always works. The first thought isn't we can make more money tomorrow by building more faster. It is we can make more money today by laying off all the people that we don't need now. Short-termism is the rule.

I think that’s more the norm in stability, where the economy when not a lot is happening/changing/improving, and so the economy is focused on efficiency as a method of competition. We are squarely not in efficiency mode right now, we’re in explore as fast as possible mode, as a lot of old underlying assumptions have changed, and there’s a huge amount of work to be done in reworking everything for the new assumptions. That means lots of opportunities, lots of money flying around, and bean counters getting outcompeted by people who’re focused on doing new things. Being too conservative does not serve you well in this regime. My two cents, anyway, I don’t think overall massive job losses are on the menu anytime soon, but massive job displacement/swapping, very likely.

Maybe LLM's should be integrated with the software, so they could optimize to the real hardware and workload ?

//There's a continuum between "vibe coded by someone with no technical knowledge or inclination" and "hand written domain driven design development".

Somewhere in the middle of that continuum sits - "domain driven specifications, described using high level english concepts(that are well defined) from the domain , combined with a selection of a few standard architectures"

Take this tool. Feed it a ton of biology/chemistry/engineering/psychology books.

Than ask it to seek vulnerabilities in modern technologies and systems.

Hardware restrictions aren't restrictive for criminal organizations.

But than it's possible to add the knowledge post training, either via RAG, qlora, etc.

I'm curious, how well do z.ai reverse engineers protocols ? Is it good enough that we'll see Chinese device makers creating low cost hardware clones, that connect to western software ?

I had it do the opposite: reverse engineer the protocol for the Eufymake E1 UV printer so that I can connect my own software to it.

It did a pretty good job.

Have you published this anywhere? I've been thinking about doing the same thing.

At least Deepseek V4 Flash does it very good.

Like they've outlawed drugs? Illegal weapons? Hacking?

Let's say the goal is doing something for work, so accuracy is important, and you prefer for it to be a nice reading experience, like a good translation.

As long as cloud model are somewhat better in these things, it's good that users would have the option to use cloud models.

Dont use this for work unless it has been verified by your corporate security and legal teams. Sharing business data with a company with which you dont have a enterprise agreement can land you in serious trouble.

>> Most of the bottleneck in business isn't building the things or sourcing, it's mostly advertising/sales.

That may also change with llms - they can help the buyers compare every product available, and find the best.

Is the LLM going to order all the shower caps produced by Chinese factories and try them out?

You're thinking about this all wrong. Just step into this cranial MRI scanning booth to livestream the structure and composition of your skull straight to the cloud, then we'll fire up 10000 agents to find the perfect cap for you.

It depends on what you produce if you make something in demand it may sell itself. For example if you operate oil wells or an ice cream stand. On the other hand if you manufacture bullshit advertising and sales may be key. What I do get about these llm SAS start ups is LLMs instrinsicaly mimic what is in the corpus so if your goal is to compete in an established product pace sure LLMs may be great autopilot but deterministic programs would be even better on the other hand if you are doing something genuinely innovative them you can expect an llm product manager to containmente it with what is already out there or alternatively make unhinged predictions. Llms have poor judgement for what is not already in the corpus.

So due to self-bias, people who shop absently with LLMs will mostly be the ones buying products from LLM-run businesses. Fitting.

I hope so. All the LLM based sales tools I've see have been shit