Seb-C

And it doesn't help that we are getting deeper in the idiocracy timeline everyday.

Exactly, also it lacks a lot of context as to why they did that.

Possible (probable?) scenario:

- Marketing: "we found and fixed lots of bugs thanks to AI"

- Reality: the KPI is now to fix as many bugs as possible with the help of AI, so they used AI to search old and easy bugs in the backlog, and then fixed it manually

Same here, I might actually migrate.

Same here. It's such a shame because I always wanted to invest in SpaceX (even despite it's CEO), but now most of the money would go to AI stuff rather than space exploration, so I'm out.

A little bit more time and people might finally understand why we have formal deterministic languages, and we'll be back full circle to proper programming.

I'm working on assembling a full-stack framework/template that aims at building performant and quality web apps very quickly.

It's going to be 100% statically type-safe across the stack, SQL first for the DB layer(s), and with a minimal amount of boilerplate (just enough for a clean architecture without magic).

In french we have Windaube (pronunced Windob).

Daube is a slang word for something of low quality.

The "vibe thinking" trend where people stop using their brain and rely on whatever random output the LLM tells them is harder to diagnose, but it's certainly there and at least as bad as vibe coding.

Thanks for the insights. I have been in technical leadership positions in the past, but disliked the management part. I think that the other dilemma is that I don't like big companies, as I've only had negative experiences and I get frustrated because even the most tiny thing can take forever to be done.

> it’s very likely you haven’t mastered all layers of the stack - you maybe have mastered the parts you’ve come across though.

I was meaning that in the context of web dev. There are certainly other areas I don't know much yet.

> Would you include Linux kernel development, program proofs, HPC , math-oriented software, compilers, firmwares, fpgas, database internals ( I mean, writing a full database engine ), big iron infrastructure , actual research etc in the list of things you’ve mastered?

Definitely not (except partially a database engine), but I'd definitely like to move down the stack. I like systems programming, low level stuff and optimization problems, so that's maybe the main area that I should explore (and also one of the reasons I like game dev). Translating that into an actual job might be harder thought.

What you say makes total sense. But for some personal reasons the social part of the job has always been my weak side and I'm just not interested in playing that game.

I've had fairly positive successes in the past when being a contractor. I feel like it's easier for me to have legitimacy and influence over the project that I'm doing this way.

> Lastly, make sure whatever it is you work on truly matters to the business, and understand how it ties back to the business and your customers. It can be fun (or necessary at times) to be off in the weeds on something that is technically interesting, but really unimportant to the bottom line and ultimately to advancing your career.

That's something I have also learnt from experience, and I am more often than not the one pushing for boring tech against the last fancy trends. But I have difficulties with the fact that focusing on the business means most of the time being the fastest possible, to the point that businesses would rather save 2 hours of implementation time now, even if it costs weeks of technical debt down the road.

Realistically that is the balance I am hoping to eventually reach through freelancing (more money the freedom to work on things I like and try micro businesses)

Thanks for the insights. But I've already been at this kind of position in the past (tech-lead role involving managing the devs). I hated the management part and even had to recover from a burn-out of a huge and messy project.

Also I care too deeply about the quality of the software being developed and am very much perfectionist, which usually translates into lots of frustration for both me and the team.

I definitely feel that about inefficiencies. I'm also frustrated at the general lack of care for quality, so I might want to find a niche where it matters and where mistakes have consequences.

I've already kind-of tried some management, in the sense that some of my previous tech-lead positions actually involved managing the team as well. But that's really not something I enjoy or want to do.

> Also I question that you've never seen anything new in the past 5-10 years (not being rude here, I understand that someone with 20years experience has seen plenty already but definitely not everything).

That comment was meant to be in the context of web dev, I'm not pretending to know everything about all areas.

> For example, how much do you know about deep learning ? Are you on track with the latest trends in our inudstry ? Can you make a list of best practices to follow when building AI systems ? Maybe try looking into new areas for growth. It will be uncomfortable but worth it I think.

I have studied deep learning and neural networks, and found-out that it's not something I'm interested to work with. I am more interested into moving down the stack. Maybe systems programming, but also video games, because it involves low level concerns, optimization problems and a huge creative/artistic part. But yeah, I know that working in video games might involve lots of other sacrifices I'm not willing to make.

I envy you for being in this position. I'm definitely interested in entrepreneurship, but it's not so easy to get started.

Thank you. That is mostly what I have been leaning toward recently, and why I'm interested in freelancing. I want more time for my own projects, and freelancing seems to be the only way that I can find a better balance between money and free time.

Thanks for the answer. That is definitely why I have such dilemma, because I know that I don't want to be in the management. Hence why I'm leaning more towards freelancing or creating my own business for now (easier said than done however).

I liked my X1 carbon gen 7, but the motherboard died after 2 years and was not repairable, so it's my biggest regret recently.

Except that the bubble's money is not being invested into cutting-edge ML research, but only into LLMs. And it has been obvious from the start to anyone half-competent about the topic that LLMs are not the path to AGI (if such a thing ever happens anyway).

They have pretty much already won cold war 2, and achieved this by using US capitalism and tech against itself.

GitHub is implemented in Ruby (on Rails), and now there is apparently a strong internal push from Microsoft to code everything using AIs/LLMs.

IMO mixing a dynamically typed language, a framework based on magic conventions and vibe coding sounds like the perfect recipe for a disaster.

Are you suggesting that we use an LLM as an interface between the AI and the player?

Why would anyone choose to awkwardly play using natural language rather than a reliable, fast and intuitive UI?

And having a better understanding of psychology is a good thing, isn't it?

The Manhattan project was an engineering project, not so much a scientific one. It was only made possible because the science and theories behind it were discovered first.

I originally put quotes around "know" and somehow lost it in an edit.

I'm precisely trying to criticize the claims of AGI and intelligence. English is not my native language, so nuances might be wrong.

I used the word "makes-up" in the sense of "builds" or "constructs" and did not mean any intelligence there.

I don't mean it in a philosophical sense, more in a rigorous scientific one.

Yes, we do have reliable datasets as in your example, but those are for specific topics and are not based on natural language. What I would call "classical" machine learning is already a useful technology where it's applied.

Jumping from separate datasets focused on specific topics to a single dataset describing "everything" at once is not something we are even close to doing, if it's even possible. Hence the claim of having a single AI able to answer anything is unreasonable.

The second issue is that even if we had such a hypothetical dataset, ultimately if you want a formal response from it, you need a formal question and a formal language (probably something between maths and programming?) in all the steps of the workflow.

LLMs are only statistical models about natural languages, so it's the antithesis of this very idea. To achieve that would have to be a completely different technology that has yet to even be theoretized.

Hallucinations are not a bug or an exception, but a feature. Everything outputted by LLMs is 100% made-up, with a heavy bias towards what has been fed to it at first (human written content).

The fundamental reason why it cannot be fixed is because the model does not know anything about the reality, there is simply no such concept here.

To make a "probability cutoff" you first need a probability about what the reality/facts/truth is, and we have no such reliable and absolute data (and probably never will).

Don't bundle your JS then, problem solved. Vanilla JS and CSS written 20 years ago still works except maybe for a couple of obscure deprecated things.

Rot is directly proportional to the amount of dependencies. Software made responsibly with long term thinking in mind has dramatically less issues over time.

Saying that a natural language based interface will replace dedicated graphical UIs makes no sense to me.

It will never be as intuitive or efficient, not even mentioning the reliability.

A picture is worth a thousand words, and no LLM is going to change that.

I don't think that anyone is dismissing machine learning itself. This bubble is more about generative AI, and especially language models.

Machine learning has been there for quite a while and is a useful tool. But it's only a tool among many other ones, like programming languages and libraries. It's not a product. At most it can be the engine of a specific feature.