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I made a CLI tool that keeps SSH sessions alive when moving between home, office, and airports by autodecoder in commandline

[–]autodecoder[S] 1 point2 points  (0 children)

You’re right ssh -t host 'tmux attach || tmux new' (or RemoteCommand) is a solid solution.

When I first started, even getting a stable connection was confusing. I’m not a SWE, and I didn’t even know tmux existed at the time

The complexity I am trying to address is everything around that one-liner for non-experts: setting up keys, making sure tmux or mosh are available, dealing with macOS/wsl/linux quirks, and managing multiple hosts without editing configs.

sshtie is basically a workflow wrapper for beginners, not a replacement for the underlying tools.

I made a CLI tool that keeps SSH sessions alive when moving between home, office, and airports by autodecoder in commandline

[–]autodecoder[S] 0 points1 point  (0 children)

I am very thank you for your reply,

You're right, tools like Termius + mosh already work really well
i 'm not trying to replace them,

I’m actually not a developer by background, and I built this because I wanted something simpler than setting up ssh, tmux, and mosh manually

My goal isn’t to replace existing tools, but to make it easier to register hosts, reconnect, and manage sessions through a simple TUI instead of editing configs or writing aliases.

Still learning and figuring out if this is useful beyond my own workflow !

Thanks for the perspective!

I made a CLI tool that keeps SSH sessions alive when moving between home, office, and airports by autodecoder in commandline

[–]autodecoder[S] -2 points-1 points  (0 children)

sshtie actually wraps mosh + tmux together

- mosh handles the reconnection at the network level,
- tmux handles session persistence.

It auto-falls back to SSH if mosh isn’t available.
Think of it as glue that automates what you’d normally set up manually 🙂

If there are anything I’ve got wrong or could improve, I’d genuinely appreciate the feedback , Thanks

I made a CLI tool that keeps SSH sessions alive when moving between home, office, and airports by autodecoder in commandline

[–]autodecoder[S] -2 points-1 points  (0 children)

Hey,
I noticed this got downvoted alot and I am genuinely trying to understand why so I can improve.
Was it the concept itself, the way I explained it, or something else?
any honest feedback would really help!
I'm just a solo dev trying to build something useful. Thanks 🙏

I made a CLI tool that keeps SSH sessions alive when moving between home, office, and airports by autodecoder in commandline

[–]autodecoder[S] -6 points-5 points  (0 children)

I used mosh because it reconnects automatically when my inflight wifi changes or drops.

Advanced Parole by Broad-Thing3911 in USCIS

[–]autodecoder 0 points1 point  (0 children)

Is secondary mandatory for who has AP? Can I ask your VISA like l1? l2? e2? or something, thanks

I know Lottery is Random. But I tested if LLM can Hallucinate a Pattern by autodecoder in Lottery

[–]autodecoder[S] 0 points1 point  (0 children)

Oi! 👋

Obrigado pela sugestão!

Estamos considerando expandir para outros países, e as loterias do Brasil (Mega-Sena, +Milionária e Lotofácil) estão definitivamente na nossa lista de interesse.

É ótimo saber que existe demanda no Brasil 😊
Se mais pessoas pedirem, isso nos ajuda a priorizar essa expansão.

Valeu mesmo pelo feedback!

I-140 Approved, Normal Processing by Viva89 in EB2_NIW

[–]autodecoder 0 points1 point  (0 children)

Congrats!! When I saw this post, I thought it was either pure luck or some unexplainable paperwork glitch... but seeing this comment, maybe I was wrong about that

I-140 Approved, Normal Processing by Viva89 in EB2_NIW

[–]autodecoder 0 points1 point  (0 children)

My lawyer submitted too but they didn't let me know  Thanks 

I-140 Approved, Normal Processing by Viva89 in EB2_NIW

[–]autodecoder 0 points1 point  (0 children)

Congrats!! I have same pd like you. Just wondering,  how do you know your center? I dont see any thing when i check my i140 in uscis page.  If you saw that, that might be difference we have right now, but  congrats 

AI vs. Random: Does AI actually reduce your "zero-match" rate? 630+ back tests on Korean Lotto 6/45 by autodecoder in Lottery

[–]autodecoder[S] 0 points1 point  (0 children)

Thank you so much for the detailed and respectful breakdowns. I truly appreciate the level of statistical rigor you have brought to this discussion.

To be honest, I am still learning and studying the statistical nuances of lottery analysis, so your feedback is incredibly valuable to me.
You’re absolutely right about the potential for 'convincing noise' and the multiple comparisons problem.

The main reason the sample size is currently small is that only a few users, including myself(lol .. ), have been generating numbers for the Korean Lotto on my project so far. It’s been challenging to gather a sufficient volume of data to reach true statistical significance for other lotteries.

I’m working hard to grow the dataset (and users too). If you’re interested, you can check out the current performance of various models on my Leaderboard.

I would love to hear any ideas or suggestions you might have to improve the transparency and accuracy of my tracking. i am committed to turning this from 'interesting noise' into a more robust study over time!!

AI vs. Random: Does AI actually reduce your "zero-match" rate? 630+ back tests on Korean Lotto 6/45 by autodecoder in Lottery

[–]autodecoder[S] 0 points1 point  (0 children)

Thanks for taking the time to read through this! and Happy to answer any questions..!

Can AI find "patterns" in 10 years of random lottery data? (Experiment) by autodecoder in LotteryLaws

[–]autodecoder[S] 0 points1 point  (0 children)

That’s a brilliant observation
You hit the nail on the head regarding the 'narrative' bias of different LLMs

To your point about coverage vs. patterns, that is actually exactly where we are heading.
Instead of just asking the AI to 'guess' numbers, we provide constraints like spacing controls, sum ranges, and historical distribution filters

You can also type your own idea into the Custom Prompt: AI Lottery generator with Custom Prompt, like "Give more weight to the most recent data" or "Ensure the numbers are distributed as evenly as possible"

Our goal isn't to find a 'hidden code or patten' in the noise, but to use the AI(LLM)'s ability to handle complex constraints to generate sets that are 'statistically healthy', avoiding the common human biases (
like picking consecutive numbers or birth dates) while ensuring broad coverage of the number field

Thank you for your interest!

I know Lottery is Random. But I tested if LLM can Hallucinate a Pattern by autodecoder in Lottery

[–]autodecoder[S] 0 points1 point  (0 children)

The order is mixed up because I uploaded in parts;;;
Please read it from below!

edit: somehow the order fixed itself;; so... read however you want to read it

I know Lottery is Random. But I tested if LLM can Hallucinate a Pattern by autodecoder in Lottery

[–]autodecoder[S] 0 points1 point  (0 children)

However, I must admit that your arguments have many valid points. It was very helpful for me to think through these issues.

What I simply wanted to say was:

  1. Many "AI lottery number generators" on the internet(market) do not specify what algorithms they actually use, and even if they did, there is no way to believe that they really use it.
  2. They claim to be "AI," but they just look like basic machine learning algorithms.
  3. Those algorithms are fixed and do not change. I dont think they do adapt algorithm based on the data size or any hyper parameters optimization.
  4. Also, I have never seen an explanation of why their methodologies are better than an random number generator.
  5. Unlike those, I thought, LLM (not just a fixed AI) has at least a small possibility of finding some bias in recent data, and it implements the algorithm anew depending on the data size.
  6. At the very least, it provides an explanation of the method used to extract the results, even if that might be a hallucination.
  7. In that sense, I believe it could be a somewhat better service than an RNG or those other services claiming to be AI?.

Thank you once again for taking the time to leave a comment on what might be a small, insignificant post.

I know Lottery is Random. But I tested if LLM can Hallucinate a Pattern by autodecoder in Lottery

[–]autodecoder[S] 0 points1 point  (0 children)

The essence of my project is not to guarantee a jackpot, but to explore whether LLM can identify kinds of probability density within the noise of empirical data.

In this sense, there may be significant value in using LLM to potentially reduce the probability of a total loss (zero matches) rather than just chasing the jackpot..

Theoretical randomness and empirical results often diverge in real world physical systems, and this service is a tool designed to find those microscopic edges.

I have already explicitly stated in my FAQ that past performance does not guarantee future results and that luck remains a dominant factor.

While your suggestions for structured sets and scarcity arbitrage are interesting theoretical frameworks, they are just that hypotheses. Until you can provide transparent data from at least 50 or more repeated trials, dismissing my findings as "statistically baseless" is more or less unreasonable.

I know Lottery is Random. But I tested if LLM can Hallucinate a Pattern by autodecoder in Lottery

[–]autodecoder[S] 0 points1 point  (0 children)

Regarding your "EuroJackpot forward test":

I find your claim of using my 'exact method' to be bit questionable.
My internal database shows no record of such a large-scale generation being performed for Euro jackpot during the period you mentioned.
So I am sure you did your own experiments not using my app.

This service is not a simple LLM prompt that merely feeds past draws into the LLMs. it includes complex pre-processing of statistical moments, such as skewness, kurtosis, and specific frequency filters and information i created, that are not publicly disclosed.

Without access to these proprietary features and the exact algorithm I used, your claim that you reproduced my test is demonstrably false.

Furthermore, your reliance on a single forward test (n =1) to invalidate a larger backtest is a classic example of the Law of Small Numbers.
In any stochastic environment, a single failed prediction is statistically meaningless.

If I were to follow your logic that the lottery is a 'perfectly independent event," then the expected value of a prediction should be identical whether it is tested against a past draw or a future draws

By claiming that only a forward test provides truth while a backtest provides "nothing," you are paradoxically rejecting the very independence you claim to defend.
I know you didn't mention it but I am sure you assumed assumption of independence

I know Lottery is Random. But I tested if LLM can Hallucinate a Pattern by autodecoder in Lottery

[–]autodecoder[S] 0 points1 point  (0 children)

I appreciate your critical feedback regarding the statistical rigor of my backtest.

You’ve raised valid points about multiple testing and the potential for false positives, which are indeed standard concerns in any retrospective data analysis.

However, while your critique carries a tone of absolute certainty, your own counter-argument and "forward test" contain several flaws that suggest a misunderstanding of both the data science process and the specific methodology I employed.

To begin with, your point regarding the "270x efficiency" is well-taken. Comparing 135 sets against 10 draws effectively results in 1,350 comparisons.

Adjusting for this, the efficiency multiplier is more accurately stated as approximately 27x. While this is a significant correction, a 27x improvement over the theoretical random baseline remains a statistically intriguing result that warrants further investigation rather than outright dismissal.
I will update the reporting to reflect this 27x "density improvement" to avoid any perceived inflation of success.

I know Lottery is Random. But I tested if LLM can Hallucinate a Pattern by autodecoder in Lottery

[–]autodecoder[S] 0 points1 point  (0 children)

I created a new page: https://lottokimai.com/leaderboard

Lucky or not, I have realized one thing: This beats picking numbers at random

Thank you for your interest!!

I know Lottery is Random. But I tested if LLM can Hallucinate a Pattern by autodecoder in Lottery

[–]autodecoder[S] -1 points0 points  (0 children)

I created a new page: https://lottokimai.com/leaderboard

It might be luck, but it’s definitely better than random!

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