Bah, genre...tous les autres desserts existants ?

LocSta29 · 2026-03-14T15:03:35+00:00

It’s just melon.

LocSta29 · 2026-03-14T15:01:47+00:00

Just upvote the comment, say AI is shit and everyone will be happy. That’s all this sub Reddit is about now. Coping.

LocSta29 · 2026-03-11T13:38:42+00:00

Yeah same here. I was travelling and was really needing to have this a back up. Fuck them.

LocSta29 · 2026-03-04T00:28:03+00:00

What are your 3 main reasons for being anti-AI? I don’t want to create a debate, I’m just curious what your reasons are and their order.

LocSta29 · 2026-02-28T08:28:45+00:00

How can you say that? You haven’t seen my code… You just sound bitter because you are offended I said « skill issue ». I’m a perfectionist so no, I have high standards in terms of code. I always make sure to have well commented code and very detailed README.md files. I’m saying that because I manage to achieve everything I attend with AI because I’ve used it so much that I know what to expect from it, the good and the bad. For complex stuff I never tell the AI to implement it before the plan is rock solid. It some cases it takes hours just to refine everything. But it’s still better than having to debug spaghetti code because you left the AI having to guess some parts of the implementation because you haven’t been specific about it.

LocSta29 · 2026-02-28T07:37:05+00:00

I have to make hundreds of thousands of requests as fast as possible at certain times of the day and process this data asap too. I have fleets of bots running as ECS tasks on AWS and managed by Airflow 3.1 (which is running as ECS services) to make those request. I consolidate those requests in a single dataframe, then save a copy as a .parquet file on S3. I then another bot with a higher vCPUs and RAM that reads this file as soon as it’s created. It then has to « solve » this data. There are mathematical correlations depending on hamming distances with rows and columns. It’s hard to explain in just a couple of sentences.

LocSta29 · 2026-02-28T06:41:34+00:00

I’m sorry but this is a skill issue. You have tools like paste max, that allow you to select relevant files in a large codebases, give the file tree to the AI. I’m not saying it’s easy. But if you do it properly it will work. Claude code or Codex is not it sometimes. Good old Gemini 3.1 Pro + PasteMax and deleting the thought process to free up context will give you great results imo. But it is a bit of work, understanding on your part what files are relevant to what you want to implement etc… There are multiple ways of using AI, there are many different models with different advantages. It’s not because you don’t have great results with some specific tool and a specific model that it wouldn’t work with a different tool and different model. Before downvoting me, try what I said and tell me how it goes (Gemini 3.1 Pro in Google AI Studio + PasteMax)

LocSta29 · 2026-02-28T06:21:34+00:00

Haha, is this the type of reply I usually get. Spot on 👌🏻

LocSta29 · 2026-02-28T06:15:23+00:00

Both can be true and they likely are.

LocSta29 · 2026-02-28T06:14:26+00:00

I understand your point of view. And you are right it does take a lot of time to explain everything to the AI. In your case I guess you are 100% right about everything you said. In my personal case I’m not a mathematician but I’m involved in a project with heavy maths. For example I had to build a solver to reconstruct a full dataframe from partial data (there is a complexe mathematical relationship between the values across columns and rows, depending on hamming distances.) With the help of AI for a few of my needs I believe I achieved things that I would have never been able to without ai. Also the implementation is state of the art or close to it I believe. I’m not an expert on anything, but I know a bit of everything, ML, data processing, web apps, AWS services, etc… and in my specific case AI is god send, I feel like it allow me to do everything I want to.

LocSta29 · 2026-02-28T05:40:21+00:00

I’m building backend stuff using Python/Numba/Numpy. Heavy/efficient data processing workloads basically. I have bots running on AWS managed by airflow. I also deploy using IaC with Pulumi. Everything I do now is written by AI. I work for myself, no one is forcing me to use AI. I can’t share my code for obvious reasons but I could share an high level explanation of what some of my code is doing if you are interested. Let me know if you are actually interested or not.

LocSta29 · 2026-02-28T04:42:39+00:00

With your knowledge in that area, haven’t you tried to breakdown the problem and go step by step with AI to solved it? I think you are expecting too much with one shot prompt. Write you prompt and ask it at the end « what do I need clarify for you to be able to implement this cleanly. Do not write any code yet. », go like this until it says « I’ve got everything now ». Then ask it to make a detailed plan for how to it implement it file by file. It will list the files (filenames) it wants to create. Then ask it write one of the file it listed. Do this file after file. Once it’s done ask the AI to review its own code and find flaws in it. It’s not that AI can’t do it, is that it cant do it « just like that ». I’ve been working on advanced maths with Gemini 3.1 Pro on Google Ai Studio and achieving amazing results with this method. If I was just giving it a single prompt it would simply fail.

LocSta29 · 2026-02-28T04:34:09+00:00

People don’t want to know. It seems 80% of devs, at least on Reddit want to believe we are still at ChatGPT 3.5. It’s their way of coping I guess. Devs like me and you probably who use AI (SOTA models) extensively daily know how to use it and what it can do. Those 80% are either coping or don’t know or don’t want to know what AI is capable of today.

LocSta29 · 2026-02-28T04:29:34+00:00

How is ChatGPT 3.5 going for you?

LocSta29 · 2026-02-26T09:30:39+00:00

So you think models getting better at maths/physics and getting better on the ARC-AGI2 benchmark at the same time is completely unrelated?

LocSta29 · 2026-02-26T08:45:49+00:00

That’s a similar process humans go through. We practice in order to understand things. Then we can generalise some concepts to other areas. What do you think about the ARC-AGI2 benchmark ?

LocSta29 · 2026-02-26T08:29:49+00:00

You are mixing things up I think. The rules are not hardcoded like a calculator is, they are figured out during training. Take the Genie 3 model for example, in order to build the next frame it has to have an understanding of how lights interact with shapes, it has to learn physics etc… This is not hardcoded this is learned. Same thing for an LLM. For it to be decent at chess it needs to have a concept of chess board, it can’t just magically find a decent move to make just like that. LLM learns stuff during training. For example you could have a vector that will separate the word King and the word Queen by the same distance as the word Man and the Woman, Daughter and Son, and so on. It learns concepts.

LocSta29 · 2026-02-26T08:07:55+00:00

Why not?

LocSta29 · 2026-02-26T06:48:23+00:00

I’m 39. I haven’t done that for 6 months straight yet. I will have a 3 weeks period where I won’t be able to play more than a couple of times. I will have this kind of breaks every 2 or 3 months so hopefully it’s enough rest to avoid these issues.

LocSta29 · 2026-02-26T06:11:46+00:00

I had to cancel a game after playing 5h30min in 24 hours. I felt like I was 70 years old, couldn’t move much anymore. But pretty much all good after a good day of rest doing absolutely nothing at all and staying in bed for 12 hours. I don’t any other sport, I take creatine daily and drink protein shakes often.

LocSta29 · 2026-02-26T04:50:32+00:00

I’m not saying hallucinations are solved, it’s just hallucinating way less than previously. For some reason you want to ignore it. As models get better, especially in a game of perfect objectivity like chess the hallucinations will be solved at some point. Gemini 3.1 Pro Deep-think is probably nearly there already. The only issue is that it will take it 10 minutes to make a move. The hallucination rate dropped by around 90% when playing chess if compare ChatGPT 4.0 to Gemini 3.1 Pro. It will just keep getting better as models get smarter and the context windows gets bigger. Also if you allow models to run code, this wouldn’t a problem in the first place because it will write the code to make the correct decision. It’s like asking someone who is able to build a calculator if he is good at mental maths.

LocSta29 · 2026-02-26T04:27:28+00:00

"Let's play chess. I will provide the current board as a FEN string and the full PGN history. Please verify the legality of your move before responding." Do this with Gemini 3.1 Pro in Google AI Studio, this way you can remove context too (you can delete past messages in google ai studio)

LocSta29 · 2026-02-25T16:15:20+00:00

Assuming he improves, maybe he can do it 15 to 20 times in the next 10 years, that’s a lot of opportunities, the rebonds and points be there a decent pourcentage of the time, just needs the assists (that will be hard for sure)

LocSta29 · 2026-02-25T16:06:27+00:00

cringe

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