But we have IPO coming, hence we face that big drama about model that would enable Iran to produce nukes, ok, that card was played, so maybe Taliban producing some magic poison to kill all Americans or some really bad people (Venezuelans?, Cubans? Somalian football referees?) to break into Github and make Github Actions working even worst (if this is even possible).

Firstly, Hetzner is really great, they have good service, good offers, they are rock solid, they shine especially in dedicated servers area - often better than all the cloud fad for many, many applications that does not need to scale crazily.

Having said that...

They expanded to a certain level and... just stopped. They do not have services that are making AWS/Azure attractive (all this identity/security stuff, MS Exchange like functionality), they are not even providing any viable messaging service, etc. Basic stuff.

As a result, companies who would even like to use them because they are solid, reliable, etc. simply can't, as Hetzner is missing basic services from business perspective.

So, they are not able to jump to the first league, have big customers, make big money, be able to invest into custom chips/infra, they are 100% dependent on US and Chinese providers. When something happens, like certain hardware shortage they are on the mercy of others and stop being able to compete.

Frankly, I don't fully get what the problem is. Luck of founders with vision, all those Jobs, Wozs, Zukerbergs, Elons, Bezosses? Luck of boring but effective CEOs (people like Eric Schmidt or Satya Nadella)?

I've looked at the usecases page, obviously there is an AI stunt (which I don't buy at all), for POS applications, well, there are better and less risky (see above) ways to do this, so the only thing that seems to make sense is this real-time sync, if someone is in the restricted environment (but, the point is, that in the restricted environment iroh is going to be blocked anyway by firewalls, z-scaler, etc.).

So I am wondering what kind of tooling would be able to somehow spot the right people among flood of AI slops.

Yup, tokens are eaten, money are paid. I am wondering how much energy/money is being burnt everyday by all of those LLM Agents on some useless activities like trying to recreate web application just to fix CSS bug.

And I would not call it proactive, proactive would be to ask for a CSS + HTML file in question, not trying to recreate them from screenshots.

Question is if there will be any competition in this area...

Soon the times of AI for $20/$200 a month will be long gone.

What does it mean? That they have to add "safeguards" not do erase user disc, or, conversely, they are telling the audience that this model COULD be made so powerful to do some crazy stuff that can hurt governments, etc.? Are they showing off or threatening that if government X would not purchase the license the adversaries might do and what's then!

Unless you are not company and you don't have some "enterprise deal". And you need an enterprise deal, as 1) it guarantees that your (and your customers) data will not be sold to someone else 2) you are scared that your competitor will have such deal and become much more productive.

This is what we have now. What will be the future?

Well, soon, if you want something like financial advice or medical advice or job search/CV polishing you will be told, that your $20/$200 is not covering that, you need to purchase additional model to have that. Will you do that? It depends how much you are desperate to get medical advice or find a job.

Anthropic Mythos is an example. Soon, if you are programmer and you will ask AI Agent to spot a bugs, AI Agent will tell you that you need to buy extra model for this. Same with performance analysis, same with the design using tool X, Y or Z.

This is pretty scary, as it will put our well-being, productivity in the hands of few corps. It will be event worst that Google Search monopoly we used to have (until AI chats broke this, replacing Google Monopoly with a few other vendors monopoly).

Can this be prevented? Surely. Hopefully we will have capable open models and consumer-level hardware will catch up. But I think this is the place where governments should step in, invest into alternative models which will be at least comparable with flagships.

Chinese models shows that this is doable, DeepSeek is worst than Chat GPT/Claude/Gemini, but not that much and is clearly better than Grok (which is a huge disappointment for me). I guess India would join this game (especially with nationalist like Modi as the leader).

Europe could join this game, the problem is it kills its capabilities with high energy prices and inability to come out with some reasonable, well financed solution. So the only thing EU was able to come up with is some set of regulations that are blocking fast AI development in Europe...

There is French Mistral, but it is French, it is under-financed, it is only-French, as France would not like to lose control over it.

Germany have totally different strategy, they invest into manufacturing oriented AI, what makes a lot of sense, but does not help with the dangers we are facing.

The rest of the Europe is just too poor to spend billions on AI.

There is still time to buckle up for Europe, but given the course of events, stupidity of Brussels elites who does not see the storm coming I am not optimistic.

Now people want to handle car rental. What are the relevant data that models were trained on for this kind of application? For Python code there is kirjillion examples on Github, for mathematical proofs there is endless stream of papers, books, etc. But for car rental? Mostly adds in the internet that want to trick you into a bad deal. So yes, LLM will be a disappointment, as it tries, well, to trick you into a bad deal. In addition, data are rather scarce so there will be a lot of hallucination, as it gets mixed up with yacht rental, bikes rental, ski equipment rental, etc.

I was teaching a lot of stuff to students: physics, math, statistics (during my university times) now I teach programming and Machine Learning.

I am torn between instructional based approach, which has this advantage that gives people a set of minimal skills to start doing stuff by themselves and the project-based approach, which is probably more interesting, but is very hard to squeeze in a relatively short classes time and also might left gaps, even in the base areas, as there is no time to cover everything end-to-end (think of teaching people about for loop, as it helps working with lists, but do not mention a while loop).

So, there should be some ideal holy grail in between both ways of teaching: show them everything versus let them explore and invent everything by themselves.

The crux is that instructional-based approach works great if it is well tuned to the student's needs. The problem is that every student has different needs and capabilities, so it is hard to do something that will work for everyone. So something is too difficult for some people, while being too easy for others.

That's why we have Bloom's 2 sigma problem - 1:1 learning works orders of magnitude better than in-class learning.

Now, LLM AI enters the scene, as the article is mentioning - individualized instruction could be finally achievable and I am much less skeptical about that than the author, as I tested that on myself, the good thing is I can ask and ask for more and more details if I am not able to grok something and my "teacher" is always patient, has as much time as I need.

It does not mean that teachers are not needed, just the opposite, because the key problem is to know what to learn, LLM will just do what you ask for, nothing more, so one need to know what to ask about. But once someone is on the specific topic and problem, you can really go quite far with LLM as a tutor.

Same with your cloud offering, ridiculous solutions like Azure Service Bus that has pathetic performance, pathetic API and high price.

"Bluetooth speaker name had been set to a "four-letter word, [...] BOMB".

Luckily, it wasn't named "Nuclear Bomb from Cuba" because US Authorities would not have other choice than to nuke Cuba.

Seriously? What those people are doing when they see a fence with "ASS" painted on it? Do they believe that too?

You need an NDA from a candidate (many would not like to risk - what if someone gets job on the competing company and is sued for revealing some secrets from the campfire interview process).

In many cases interviewee would need to get a laptop from the company, as there are specific requirements about data security (disc encryption, usage of solutions like Fortinet or Zscaler), be added to company SAP to get access to the resources (Office, Teams, etc.), company need to purchase licenses for Office, Github, Jira, etc.

Surely hiring is hard, surely there are false positives and false negatives, but fixing this requires hell a lot of resources and organizational changes and costs.

You bet against skilled people who set the stakes, so, yes, by observing numbers you can win in Keno, but if you comply to the TOS you will not win big money. The only chance to be able to "game the system" is to bet on something that lotteries brokers does not have time to look at, like 3rd Bulgarian bocce league matches.

The problem is that you need to somehow become an expert in 3rd Bulgarian bocce league and the money which are there are generally small.

I was investigating this (again) when AI showed up, as in theory it makes easier some analysis, but the big guys are also using AI.