I think it's an enabler for everyone.

So many people benefit from basic things like sorting tables, searching and filtering data etc.

Things were I might just use excel or a small script, they can now use an LLM for it.

And for now, we are still in dire need for more developers and not less. But yes I can imagine that after a golden phase of 5-15 years it will start to go down to the bottom when automaisation and ai got too good / better than the avg joe.

Nonetheless a good news is also that coding LLMs enable researchee too. People who often struggle learning to code.

When a company lays off a chunk of the workforce because the increased productivity due to LLMs means they don't need as many people, how is it an enabler for the laid off people.

What happens when most companies do this?

During the 10s, every dev out there was screaming "everyone should learn to code and get a job coding". During the 20s, many devs are being laid off.

For a field full of self-professed smart and logic people, devs do seem to be making tons of irrational choices.

Are we in need of more devs or in need of more skilled devs? Do we necessarily need more software written? Look at npm, the world is flooding in poorly written software that is a null reference exception away from crashing.

> What happens when most companies do this?

It also means it becomes easier to start new company and solve a problem for people.

People get laid off when money is expensive. When money is expensive, running companies is harder. Starting a new company is even harder. Without capital, all you can offer is some words, a broken demo of your v1 prototype and some sweet words. You can't start a company with just that when money is expensive.

Right now we have not enough software developers at least based on surveys.

So now LLM helps us with that.

In parallel all the changes due to AI also need more effort for now. That's what I called golden age.

After that, I can imagine fundamental change for us developers.

And at least we're I live, a lot of small companies never got the chance to properly become modern due to the good developers earning very good money somewhere else.

I like to think that AI is to code what digital electronic was to analog electronic: a step backward in term of efficiency and 10 steps forward in term of flexibility.

Some of us will always maintain code, but most will move higher in the stack to focus on products and their real world application.

The flaws of crypto were clear very early on.

Major issues, still existing, were never solved

The surest way to get flamed out of any crypto mailing list was to ask what the effective clearance rate for the coin was, then following it up with how it could be sped up.

Today the bitcoin network is still stuck at ~7 transactions a second.

This is not what the white paper promised.

Thus, other blockchains emerged

Yes, we only need checks notes 3,500 other coins to match the clearance rate of Visa.

And adding more confusion and more problems.

Btw. Criss chain transaction is the major problem this strategy added.

requiring much higher resources to run a node and making them much less decentralized.

Which one are you referring to? What do you want to get all the freedom in the world and no effort for running a decentralized node? Staking blockchains don't require much resources.

The ones that allow hundreds of txs per second, making verification of the entire tx history orders of magnitude harder. The limited tx throughput of bitcoin is a feature, not a bug.

There are very good performance tools for GPUs.

I don't think GPU utilization is a real bottleneck in most cases.

Yet DeepSeek managed to get huge improvement by optimizing GPU code.

I want that for privacy reasons and for resource reasons.

And having this as a small hardware device should not add relevant latency to it.

Privacy isn't a concern when everything is local

Yes it is.

Malware, bugs etc can happen.

And I also might not want to disable it for every guest either.

If the AI is local, it doesn't need to be on an internet connected device. At that point, malware and bugs in that stack don't add extra privacy risks* — but malware and bugs in all your other devices with microphones etc. remain a risk, even if the LLM is absolutely perfect by whatever standard that means for you.

* unless you put the AI on a robot body, but that's then your own new and exciting problem.

There is no privacy difference between a local LLM listening versus a local wake word model listening.

Light studies have different expectations on their numbers and doesn't mean crossing that is a health risk.

For me, MDMA was definitely a crazy positive experience. It def helped against my depression in sense of letting me experience and remembering the experience something I haven't known existed before.

If it's ok to ask: what was it that you experienced that you hadn't known existed before?

At the moment of taking it, a huge amount of empathy and happiness.

After that the memories of that day and feeling

Wow. And thanks. I don't mean to pry, but did this make you want to take it repeatedly?

I ask because I've seen people get in trouble this way. They have a first experience which is amazing and then get into chasing it.

I'm only aware of a handful good use cases

Navigation and speed in a car for example

With 39 Billion in spending and 30 Billion into humanity would have done a lot more to society

I have not.

And at a certain level of criticality, you do not do this at all

You have security measures in place to prevent this.

Not that the ketaman cares about it.

If you don't know about argocd, try it out! It also shows you the logs of containers.

Otherwise check out grafana with Loki (kube-stack)

Hui for the activation word?

Shouldn't there be some hardware module be available similar to how Alexa, Siri and Google do it?

Whith a ring buffer detection the word without recording everything?