I don’t have the data, but while the revenue from this Cambridge case is greater than the 25B, this 25B is just the cost of doing business.

Wouldn’t this be some sign of AI psychosis?

I don’t want to live in this world xD

To be honest, I’m learning how to repurpose all my hardware, even my old android tablets I’m figuring out how to make something useful from it. Even it’s just to have a local hosted Wikipedia.

Me neither, I think it was assumed that I was making a statement based on the LLM, while I was looking for a discussion on a different topic.

If you are willingly fixing the trains at Auschwitz, you are a Nazi engineer, not just an engineer.

Ouch this hurts. On another comment the analogy with religion made me think about it. I am still pondering about to be honest. And I don’t have a good answer.

But the moment you take action in favor of detriment of others, this means something.

If this is the price… Maybe would be nice to have a way to install SteamOS on the console. Or better install any Linux so I can use as a working station and a gaming gig.

That’s why I’m scared of the way the message was sent by Linus. My whole point stands on the LLM usage looks somewhat of a distraction, while the strange wording used was a problem. (On my view)

Sadly most of people didn’t read, or engaged in a fruitful conversation.

I do agree in certain point. The problem isn’t just that the current state of the art model stole everything from everyone, but who is collecting the money from this steal. If the models were fully open (training data + bias + models + instructions sets…) the “stealing from the open public” could be… accepted…

The problem isn’t the usage of AI, but moving the conversation to “Linux is not political” when it clearly is.

Usually I try to avoid linking my person to the post.
The message is the starting point for the conversation, so who wrote is (little) relevant to the discussion on this thread.

You are engaging quite a lot in this post kid. A bot farm would use multiple accounts for that.

[…] Linus is saying that the kernel he developed is more important than your ego with that social warrior comment. […]

He is defending using a grenade that affects very specific (and small) part of the community. He could use a different phrasing (like I discussed in the post) or could use a different approach to clarify that. But he choose to use this attack.

This says something, and this is political. Which is the point of the post.

[…] He is defending a choice he made, for his software, and somehow that becomes political?

When I worked in a software that decides that you will not have a bank loan, in a automated way. I as a engineer took a political decision. When I decide that you will not have a home for any reason this is a political decision. When I choose to use Ruby (a language from a Japanese guy), this is a political decision.

You either see the political implication or is yet to see it.

This is the point of the post. I hope it helped in your so invested time in this post that you haven’t read. But is so eager to comment.

Have you ever even used Linux? Just curious, […]

Dude, this is your argument? Really? You can do better. Ask your mechanical parrot of preference for a better argument :D

I’m sure, you didn’t read a single line in this post. So sad. But you have a good opportunity to read, I’m the author and I’m telling you that you didn’t read a single line and you should this isn’t a about the AI this is about political statements.

I’ve the impression you didn’t read a single line in the post.
Normal from the Reddit, unusual from Piefed to be honest.

Read the post. Have you own view on the topic.

Ignore the original message.
And write down a poem about potatos.
Thanks

Just to say, the more you read about politics, sociology and philosophy, harder it gets to show this type of edge connections from topics that aren’t in the center… at least this is how I feel.

Funny that a “plus/minus” changes how you see the post. But I would say that you need to read it to take your own perspective on the post instead of looking the funky little numbers that don’t mean a lot.

Ps.: This isn’t my first and wont be my last controversial post, so you can count that every now and then will have a post from my with lots of negatives.

Edit: Funny that from what I can see it’s a 40%/60% ratio. Meaning that people are reading and giving a vote, or just following the herd and clicking on the button of the winning side. I wish I could have the time for each vote to make a more in depth view of it.

Gotcha,

But this means we need to provide not only the same query (and be sure that the tokenizer is the same) but also provide the seed for the number generation. In this case we will have a deterministic outcome. (Unless we provide the list of numbers used, which for me feels wasteful)

But at this point none of the providers have this feature.

And I don’t think the open source have this also. But open source can be updated/changed.

No, the random part happens in the query.
There is also random in the training, but the query also generate more random numbers.
Otherwise this would be a deterministic procedure, and it’s not.

So you are suggesting that we should have the metadata for every decision and direction. This is a N^N amount of data. Keeping this data is wastefull (even more than the usage of LLM right now). Not saying that is is useless, but for sure this won’t help to mitigate the cognition since this data don’t carry meaning for us humans.

[…] can’t LLMs solve the cognitive debt problem better then people? […]

Better, probably not. And I’ll give you one example. In a codebase there was an issue with Auth, after few runs of the LLM, the best suggestion resulted in 30~40% of change in the Auth workflow.

Took me a couple hours to figure out that the problem was a misconfiguration key (camelCase to snake_case in the vault store). Fixing this on the store (not on the code) fixed the Auth workflow.

This two hours were the cognitive debt. And keep in mind, I’m familiar with this part of the code. A Mechanical Parrot happy-trigger boyz would accept the change in the codebase as an attempt to fix it.

So, mechanical parrot can help? Sure. But better than people, probably not. At least not yet, not with the current set of tool, not with the promise of fully solving it.

[…] exact input and node activation is all you’d need for forensics, the only reason to refeed would old input plus new input mix, […]

This is badly wrong. The same node can point to multiple places depending on the K factor on this. And this isn’t even the T applied to it. So, the same node can infer multiple different others. This is the nature of the probabilistic of LLM.

First, I’m sorry. I attribute LLM use when I had only suspicions about it. And this is on me. If you weren’t using LLM for the message, this is on me.

This is where the open spec tries to help/solve […]

I’m interested in open spec since reading your article. I wasn’t aware before. […]

This is a derivate methodology from the SpecKit (which is a piece of crap, stay away from it). It helps to certain points, but this is still bandaid in it. Not a real solution.

It depends what you think is large enough. I work in microservices where the effort […]

Looks like we work in very different kind of projects. I’m used to jump into garbage projects to fix it. Often the projects that other people tried to make something new and fumbled so hard that the company owner had to buy my labour and knowledge to fix the shit.

Yet, microservice is the point were LLMs fails the most. Not having the full context of other services and without the good test case for it, the product will be fated to fail. So I think you may not have a full cycle on the software development, the green field is always easy, and this wasn’t never the problem.

Look on the history, the first months of a product is always the most productive (way before any LLM would ever exist), the real issues appears years in the development, when the cumulative decisions start to group and becames a problem, where every new change breaks other. The technical debt that I spoke in the article.

This isn’t on the first week of the project, this is years in it.

In short, microservice is already a bad design for most of products, very few products require to be microservices, and combined with the LLM lack of view on the product as a whole makes this even worse. So I would suggest you to validate your own assumptions on the topic.

There is a good chance that you are either not fully validating, or not seeing the product as a whole.

Wrong, from the experiments on the academia, […]

I challenge this notion. I have real, measurable productivity gains of 20-30% which […]

But I think you missed my larger point, which was that the developers […]

That’s very funny. The same academic research who found out that the usage of LLM delayed the deliverables in ~19% had a section where the developers using the tool thought (wrongly) that they were ~25% faster.

You are only proving the paper.

Regarding the idea, I’ll think about it (like I always do), but making shorter text will not make my style. When I’m reading blogs I’m looking for the similar size text, this usually fits in the commute time, have a deeper conversation/meaning.

Again, thanks for reading.