I find intellij a great IDE, modern frameworks are fun to use, ai helps me doing things i don't want to do or things i just need (like generate a good README.md for the other people).

Containers are great and mine build fast.

My Startup has a ha setup with self healing tx to k8s and everything is in code so i don't need to worry to backup some random config files.

Hardware has never been that cheap. NVMs, RAM and Compute. A modern laptop today has a brilliant display, quite, can run everything, long batterytime.

Traffic? No brainer.

Websphere was a monster with shitty features. I remember when finally all the JEE Servers had a startup time of just a few seconds instead of minutes. RAM got finally cheap enough that you were able to run eclipse, webserver etc. locally.

Java was verbose, a lot more verbose than today.

JQuery was everywere.

Google makes money with ads and at least takes this serious.

Apple just exploits.

A normal person wouldn't think 'hey lets use k8s for the low stakes deployment over here'.

You would not be able to operate hundreds or thousand of any nodes without operation complexlity and k8s helps you here a lot.

If you do anything professional, you better choose proven software like kubernetes or managed kubernetes or whatever else all the hyperscalers provide.

And the complexity you are solving now or have to solve, k8s solved. IaC for example, Cloud Provider Support for provisioning a LB out of the box, cert-manager, all the helm charts for observability, logging, a ecosystem to fall back to (operators), ArgoCD <3, storage provisioning, proper high availability, kind for e2e testing on cicd, etc.

I'm also aways lost why people think k8s is so hard to operate. Just take a managed k8s. There are so many options out there and they are all compatible with the whole k8s ecosystem.

Look if you don't get kubernetes, its use casees, advantages etc. fine absolutly fine but your solution is not an alternative to k8s. Its another container orchestrator like nomad and k8s and co. with it own advantages and disadvantages.

There are indications that Open AI is doing this but nothing official as far as i know and i have not heard anything from Anthropic.

Also certain companies normally don't like to do things themselves if they don't have to.

Nonetheless nvidia is were it is because it has cude and an ecoysystem. Everyone uses this ecosystem and then you just run that stuff on the bigger version of the same ecosystem.

I don't.

I know their models, but not because i constantly read about it

Regarding world models: All the big ones. LeCun, Demis Hassabis, Fei-Fei Li too. And they are all working on it.

LLMs will definitly play some type of role in AGI. After all you can ask an LLM already a lot of basic things like 'what are common tasks to make a tea'. A type of guide, long term fact memory or whatever this can be called.

Everything.

They can easily just do this for more optimized Chips.

"easily" in sense of that wouldn't require that much investment. Nvidia knows how to invest and has done this for a long time. Their Ominiverse or robots platform isaac are all epxensive. Nvidia has 10x more software engineers than AMD

People don't assume LLM will be AGI, people assume that World Models will lead us to AGI.

I personally never asumed LLM will become AGI, i always assumed that LLM broke the dam for investment and research into massivce scale compute ML learning and LLMs are very very good in showing were the future goes because they are already so crazy good that people can now imagine a future were AGI exists.

And that was very clear already when / as soon as GPT-3 came out.

The next big thing will probably be either a LOT more RL or self propelling ai architecture discovery. Both need massive compute to work well but then will potentially provide even faster progress as soon as humans are out of the loop.

I helped a collegue to migrate to germany, your job can easily be optimized away by an LLM.

Biggest issue he had was communication/translations. Second one was finding the right information.

Try perplexity and it will find good resources. Make pictures and use google lense for translation. Talk to ChatGPT to get explanaitions on how things work in germany.

I also have no clue what you mean by 'connections and infrastructure'. You know the number of some Ausländerbehördenmitarbeiter?

And an EU company can't be forced by the US Gov to hand over data.

Deepmind is not an UK company, its google aka US.

Mistral is a real EU based company.

USA vs. China. If USA stops research on AI right now, China will leapfrog even further.

And companies like Google and Microsoft can easily affort the current AI spend.

That image generation is already disrupting industries and jobs today.

My mother! (non technical) had a call with a support ai agent just a few month ago.

AI is also not a fad. LLMs are the best interface we had sofar. They will stay.

AI Coding helps non developers to develop a lot faster and better (think researchers who sometimes need a little bit of python or 'code').

I'm using AI to summarzie meetings i missed, i asked chatgpt to summarize error logs (successfully).

AlphaFold solved protein folding.

Nearly all roboters you see today are running on Nvidias Isaac and Groot.

The progress has not stoped at all. When Nano Banana came out, Seedream 4 came out a week later. Now we have nano Bananan Pro and Gemini 3.

After Gemini 3 came out, Opus 4.1 came out and now Deep Seek v3.2. All of them got better, faster and/or cheaper.

Feel free to tell me what your industry is so we can continue our discussion.

This will leap frog cancer research, material research etc.