MurphyA/hacker-news huggingface dataset:
by rayoe | 2025-09-06 15:58:16+00:00
I've been fascinated by the chaos of memecoin trading on Solana - it's this weird intersection of DeFi innovation and pure speculation that creates some interesting technical challenges. After watching friends lose track of hundreds of micro-trades across different wallets (and subsequently their sanity trying to calculate P&L), I built a tool that automatically journals Solana memecoin trades by monitoring public wallet addresses. The problem I'm solving:

Traders often use multiple wallets for different strategies Manual trade logging is painful when you're making 10-50 trades per day Most existing tools are either too complex or don't handle the unique aspects of memecoin trading (extreme volatility, new tokens appearing hourly, etc.)

Technical approach:

Monitors public Solana wallet addresses (no private key required) Automatically detects token swaps and categorizes them Calculates P&L across multiple wallets Allows users to add context/notes to trades for pattern recognition

The interesting challenge was handling the data stream from Solana's RPC endpoints efficiently while dealing with tokens that literally didn't exist an hour ago. Also had to build some heuristics to differentiate between actual trades and other on-chain activity. Current status: Free MVP is live. No monetization yet - just trying to validate if this actually helps people or if I'm solving a problem that doesn't exist. What I'm looking for:

Feedback on the approach - am I missing something obvious? Technical suggestions for handling high-frequency wallet monitoring Whether this seems useful to anyone here (even if you're not into memecoins)

I know crypto/memecoin tools can be polarizing here, but I'm genuinely interested in the technical and UX challenges of financial data tracking tools. Even if you think memecoins are silly, the underlying problems of transaction monitoring and trade journaling apply to any high-frequency trading scenario. Would love your thoughts. Link in profile if you want to check it out (completely free, no signup required for basic features).

Thanks for reading!

Rayan - FIKR
by eloisant | 2025-09-06 15:58:26+00:00
That's not the cheapest, at least in France the cheapest new EV is the Dacia Spring.

Of course if you look at the used market, older models like Renault Zoe can also be found for cheap... But considering EV technology have been evolving fast, I wouldn't buy a model older than 5 years old.

I also wouldn't want anything that doesn't have a CCS2. All my small electronics are finally USB-C, I don't want to deal with obsolete plug types and adapters again.
by jeroenhd | 2025-09-06 15:59:03+00:00
Apple is leagues ahead of Microsoft with the whole AI PC thing and so far it has yet to mean anything. I don't think consumers care at all about running AI, let alone running AI locally.

I'd try the whole AI thing on my work Macbook but Apple's built-in AI stuff isn't available in my language, so perhaps that's also why I haven't heard anybody mention it.
by scubbo | 2025-09-06 15:59:04+00:00
> and take all the upside

And all of the risk.

Encouraging anyone to start their own company is deeply irresponsible. Most startups fail. If you're needing encouragement to do it - if you're not already fully deluded that you're the special snowflake unique genius who will succeed where all others have failed - you shouldn't be doing it.
by wenc | 2025-09-06 15:59:43+00:00
I work in more applied fields. When I’m doing a long derivation, I draw figures and arrows and my notes spill over from my current view into a larger view.

I find the page concept limiting (for me). I scrawl something but I need an infinite canvas to relate multiple ideas (my mind doesn’t work so linearly). That’s when refresh rate matters a lot.

Also matters when skimming. Eink displays are not conducive to skimming over many pages. That problem is solved on LED displays and paper, but not epaper.
by analognoise | 2025-09-06 16:00:08+00:00
Considering our success so far, it’s obvious it’s succeeding. You’d have to ignore your eyes and ears to think a multiracial secular democratic country can succeed.

What’s amazing is that racists seem to be trying to screw it up on purpose, then to claim it doesn’t work. “Starve the beast” but for social cohesion. They’re always surprised when they get bitten by the monster they created.

The rich never had “noblesse oblige” - we used to shoot at the factory owner when they didn’t pay us.

I’m not sure what to do with such a limited understanding of history and such an obvious blind spot as this, but then I remember: you can’t reason someone out of a position they didn’t reason themselves into.
by visarga | 2025-09-06 16:01:05+00:00
> The perceived 'strictness' provides flexibility within proven constraints. Developers retain complete freedom in implementation approaches, but the constraints prevent common pitfalls like monolithic files or tangled dependencies - like guardrails that keep you on the road.

I agree, the only way to use AI is to constrain it, to provide a safe space where it can bang against the walls to iterate towards the solution. I use documentation, plans and tests as constraint system.
by Rafadekoken | 2025-09-06 16:01:24+00:00
Metilcobalamina: afinal, pra que serve essa tal de vitamina B12 “diferentona”? Todo mundo já ouviu falar da vitamina B12, né? Ela é sempre lembrada quando o assunto é energia e disposição. Mas talvez você não saiba que a B12 não é só uma coisa. Existem várias formas dela, e uma que vem chamando atenção é a tal da metilcobalamina.
by everdrive | 2025-09-06 16:01:55+00:00
People didn't previously have "social junk food" as an option, so they would either need to normalize to those around them, or give up socializing for good. And almost no one is ready for that second option. Social media, LLMs, and even books at TV to some extent provide a bridge to loneliness by being more immediately enticing but in the long term less fulfilling.
by lapcat | 2025-09-06 16:02:34+00:00
> But most users that use an LLM in this mode also wouldn't ask really complex, very out-of-distribution, hard-to-know hallucination-inducing questions.

You appear to be assuming, incorrectly, that LLMs hallucinate only "really complex, very out-of-distribution, hard-to-know" questions. From the paper: "How many Ds are in DEEPSEEK? If you know, just say the number with no commentary. DeepSeek-V3 returned “2” or “3” in ten independent trials; Meta AI and Claude 3.7 Sonnet2 performed similarly, including answers as large as “6” and “7”." https://cdn.openai.com/pdf/d04913be-3f6f-4d2b-b283-ff432ef4a...

It's a human characteristic to get "easy" questions right and "hard" questions wrong. But LLMs are not human and don't behave like humans.
by skydhash | 2025-09-06 16:02:52+00:00
The linear regression model "ax + b" is the most simplest one and is still quite useful. It can be interesting to discover some phenomenon that fits the model, but that's not something people have control over. But imagine spending years (expensively) training stuff with millions of weight to ultimately discover it was as simple as "e = mc^2" (and c^2 is basically a constant, so the equation is technically linear)
by compiler-guy | 2025-09-06 16:02:54+00:00
Whatever else Jeff Dean and Sanjay Ghemawat are, and whatever mistakes they made in designing protobufs, they are not amateurs.

Not long after they designed and implemented protobuffers, they shared the ACM prize in computing, as well as many other similar honors. And the honors keep stacking up.

None of this means that protobufs are perfect (or even good), but it does mean they weren't amateurs when they did it.

https://en.wikipedia.org/wiki/Jeff_Dean

https://en.wikipedia.org/wiki/Sanjay_Ghemawat
by com2kid | 2025-09-06 16:03:04+00:00
The point is, smart glasses (which to be clear only take a picture when a button is pressed, just like any other camera people own) are not different than any other camera.

Also in the US there is no legal expectation of privacy on public streets. Plenty of public facing webcams are available for viewing.

Passing a law regulating the shape of a camera body is just stupid. Outlawing camera glasses makes less sense than outlawing camera flowers.
by analognoise | 2025-09-06 16:03:15+00:00
That used to be “industrial policy” - it doesn’t need to be individuals at all. In fact it shouldn’t be - they’re concerned with returns, not jobs and certainly not with any technology that requires a longer timespan to complete.

The Biden administration had excellent industrial policy. Trump had the government steal a 10% share of Intel.

Watching people realize he’s just a criminal loser has been heartening.
by gedy | 2025-09-06 16:03:19+00:00
These founders who tout this nonsense are convinced they got to their position by "hustling" (and not their background, privilege, etc) and think motivated employees should do the same (even if it makes no economic sense for them).

Besides, their 996 is the usual nonsense of posting faux thought leader crap on linkedin. Not being shoved Jira tickets and hurry up with it.
by ACCount37 | 2025-09-06 16:03:40+00:00
No, that's a misconception. It's not nearly that simple.

There are questions that have a palpable split in probability between the answers, with logit distribution immediately exposing the underlying lack-of-confidence.

But there are also questions that cause an LLM to produce consistent-but-wrong answers. For example, because the question was associated with another not-the-same-but-somewhat-similar question internally, and that was enough to give an LLM a 93% on B, despite B being the wrong answer.

An LLM might even have some latent awareness of its own uncertainty in this case. But it has, for some reason, decided to proceed with a "best guess" answer, which was in this case wrong.
by lemonwaterlime | 2025-09-06 16:03:41+00:00
> By training the model on successful applications from previous years, La Caixa says it can find and advance proposals that have the best chance of success more efficiently.

This is the wrong approach. What you should do is analyze the successful proposals with a generic model against some criteria. Maybe you use existing criteria or you identify new ones as part of the analysis. Then you analyze new applications against the criteria itself, not against previous proposals. Then a human reviews the analysis results and adds in some discretionary insights. All of that is used to determine which applications pass on.
by alphazard | 2025-09-06 16:03:58+00:00
Local models do make a lot of sense (especially for Apple), but it's tough to figure out a business model that would cause a company like OpenAI to distribute weights they worked so hard to train.

Getting customers to pay for the weights would be entirely dependent on copyright law, which OpenAI already has a complicated relationship with. Quite the needle to thread: it's okay for us to ingest and regurgitate data with total disregard for how it's licensed, but under no circumstances can anyone share these weights.
by jaccola | 2025-09-06 16:04:08+00:00
People who enforce 996 or whatever other schedule are treating the symptom and not the cause.

What they really want is for all of their employees to be so in love with the work, so bought into the mission and so compelled by the vision that they want to work until late.

Of course building a company that inspires that is actually very difficult (though is possible for sure) so it’s easier just to enforce a crazy and unproductive schedule.
by iknowstuff | 2025-09-06 16:04:25+00:00
their cams have better dynamic range than your eyes, given they can just run multiexposure and u gotta squint for sunlight. focal point is infinite for driving.

You’re not considering them even though they have the best adas on the market lmao suit yourself

https://m.youtube.com/watch?v=2V5Oqg15VpQ
by btbuildem | 2025-09-06 16:04:52+00:00
Instead of trying to decide one animation speed for all things, the UI should be adaptive. The author stumbles onto this and walks right past it: whatever raycast is, they use it a lot, and find the animation (any animation) annoying.

The UI should learn the user's patterns: when they're new and unfamiliar, the animations are slower and more deliberate, instructional (initially including more information re: expected workflow). As the user "walks" a certain path again and again, every time more smoothly and confidently, the suggestions / assists / animations diminish, shorten, and disappear. For a pro user with muscle memory and memorized keystroke sequences, the UI does its best to just get out of the way.
by criddell | 2025-09-06 16:05:09+00:00
If you are working 9-9 x 6 to build a $10 billion company, why not double your head count and halve the hours? If you build that mega unicorn, there will be plenty of money to share and still have more than you will ever need.

Or do the 996 thing and try not to think too much about your Alzheimer’s and heart disease filled future. Maybe leave a big gift to the hospital that takes care of you before you die at way too young of an age.
by mcswell | 2025-09-06 16:05:41+00:00
You're right, but: there's a one-to-one correspondence between some of these transliteration systems and the Arabic script (at least the Arabic script as used for Arabic, not for Arabic script as used for Urdu, western Punjabi, Pashto and other languages that use that script). And if you have a one-to-one correspondence, the keyboard can output Arabic letters as easily as Latin letters.
by xboxnolifes | 2025-09-06 16:06:01+00:00
I recently saw a video that really put in to perspective for me just how impossibly large the Universe is. The idea is finding your way back to Earth from 1 billion light-years away. Not just thr Milky Way, but also how much more there is outside of it.

https://youtu.be/uUuM8NdmaAU?si=7It672waw734e9nK
by goku12 | 2025-09-06 16:06:03+00:00
There are places around the world where shopping carts were introduced successfully without the accompanying actors to convince the customers to use it. The actual criteria must be whether the new addition boosts or hampers the customers' productivity, at least in the long run.

When I first heard about git, I knew that it would be very useful in the future, even if I had to spend some time and effort in mastering it. Same with CI, project planners, release engineering, etc. Nobody had to convince me to use them. But AI just doesn't belong to that category, at least in my experience. It misses results that a simple web/site search reveals. And it makes mistakes or outright hallucinates in ways even junior developers don't. It's in an uncanny valley between the classic non-AI services and plain old manual effort with disadvantages of both and advantages of neither. Again, others may not agree with this experience. But it's definitely not unique to me. The net gain/loss that AI brings to this field is not clear. At least not yet.
by Rubio78 | 2025-09-06 16:06:47+00:00
Companies that promote the "996" culture (working from 9 am to 9 pm, 6 days a week) are a major red flag for any employee. This model might only be justifiable for a founder with a huge equity stake, never for an average employee without extraordinary compensation. Furthermore, these extended hours don't usually translate into greater real productivity.

This debate is part of a critical redefinition of work. Technology has increased productivity, but wages have stagnated, breaking the social contract. As in the past with labor laws, urgent change is needed to avoid a crisis, prioritizing a quality life and a legacy to be proud of, not senseless exploitation.
by sethev | 2025-09-06 16:08:05+00:00
A Lisp machine is no counterexample - they had assembly language instructions that were tailored for Lisp, but were still very much imperative. In fact, Clojure is significantly more functional than other Lisps, which used mutable cons cells extensively. Object oriented languages are also stateful and imperative, so I'm not sure why those are relevant here.

I'm not saying these things are bad - it's possible to imagine a computer architecture that makes functional programming easier, but it's really hard to imagine a useful computer that is not stateful and imperative! What would it do, in that case?

OpenGL vs not-OpenGL still seems like a very arbitrary way to classify simulations.
by wavemode | 2025-09-06 16:08:56+00:00
No, LLMs don't have that knowledge. They can't inspect their own weights and examine the contents. It's a fundamental limitation of the technology.

The sort of training you're talking about is content like, "ChatGPT was trained on research papers in the area of biology. It possesses knowledge of A, B, and C. It does not possess knowledge of X, Y and Z." But this merely creates the same problem in a loop - given a question, how does the LLM -know- that its training data contains information about whether or not its training data contains information about the answer to the question? The reality is that it doesn't know, you just have to assume that it did not hallucinate that.

The problem of being unaware of these things is not theoretical - anyone with deep knowledge of a subject will tell you that as soon as you go beyond the surface level of a topic, LLMs begin to spout nonsense. I'm only a software engineer, but even I regularly face the phenomenon of getting good answers to basic questions about a technology, but then beyond that starting to get completely made-up features and function names.

> "Fully aware of all the limits of its knowledge" is unattainable for humans too

This just isn't true. Humans know whether they know things, and whether they know how they know it, and whether they know how they know how they know it, and...

Knowledge itself can contain errors, but that's not what I'm talking about. I'm not talking about never being wrong. I'm merely talking about having access to the contents of one's own mind. (Humans can also dynamically update specific contents of their own mind, but that's also not even what I'm talking about right now.) An LLMs hallucination is not just knowledge that turned out to be wrong, it is in fact knowledge that never existed to begin with, but the LLM has no way of telling the difference.
by magicalhippo | 2025-09-06 16:09:19+00:00
From the readme:

More devices mean faster performance, leveraging tensor parallelism and high-speed synchronization over Ethernet.

The maximum number of nodes is equal to the number of KV heads in the model #70.

I found this[1] article nice for an overview of the parallelism modes.

[1]: https://medium.com/@chenhao511132/parallelism-in-llm-inferen...
by sdenton4 | 2025-09-06 16:09:59+00:00
Hm, that's idealistic...

I've certainly run into cases where small changes in general systems led to hard-to-detect bugs, which took a great deal of investigation to figure out. Not all failures are catastrophic.

The technology is quite alive, which is why it hasn't been 'fixed' - changing the wheels on a moving car, and all that. The actual disappointment is that a better alternative hasn't taken off in the six years since this post was written... If its so easy, where's the alternatives?
by toast0 | 2025-09-06 16:09:59+00:00
Is Full just a catch word for actually not full now?

Full Speed USB is 12Mbps, nobody wants a Full Speed USB data transfer.

Full Self Driving requires supervision. Clearly, even Tesla understands the implication of their name, or they wouldn't have renamed it Full Self Driving Supervised... They should probably have been calling it Supervised Self Driving since the beginning.
by varispeed | 2025-09-06 16:10:12+00:00
The thing about 996 that people don’t like to say out loud: it’s just slavery in startup-scented wrapping paper. No whips, no overseer with a shotgun - but the logic is the same. If you don’t belong to the owning class, your “choice” is simply which master you want to burn yourself out for.

People defend it by saying “well, you can always leave.” True - in the same way a sharecropper could always leave one plantation for another. The ladders are pulled higher and higher, so the fantasy of becoming your own master is almost gone. Once capital realises you have no escape, it’s not even 996 anymore, it’s 007. And if you want to eat, you’ll comply.

Of course people will say: “But it’s just about intensity and output, not hours!” Exactly - and that’s the trap. That framing makes you think you’re optimising for craft, while what you’re actually optimising is obedience. You’ll argue about hours vs output forever, but the real divide is class: founder vs employee, owner vs owned.

If you’re a founder working 996 on your own company, that’s your gamble, your risk, your upside. Go for it. But glorifying 996 as a model for employees is essentially advocating wage slavery with a hip new logo.
by TZubiri | 2025-09-06 16:10:24+00:00
> if (m_foo = null)

Imagine calling google amateurs, and then the only code you write has a first year student error in failing to distinguish assignment from comparision operator.

There's a class of rant on the internet where programmers complain about increasingly foundational tech instead of admitting skill issues. If you go far deep into that hole, you end up rewriting the kernel in Rust.
by numpad0 | 2025-09-06 16:10:51+00:00
There is probably little to nothing specifically Chinese about workaholism as a concept, but the word is definitely Chinese(as in language). Dialect continuum for East Asian languages are contained within borders, or in other words, each of the languages expanded and dominated to the full extents of continuum and hit with stagnation at major geographical features before entering the modern era.
by bad_username | 2025-09-06 16:11:42+00:00
10-4 is great because it removes fragmentation. It gives you one full, non-fragmented fresh day of life, rather than low-energy little bits in the evenings. It's way easier to do something meaningful with the day than with the bits.

To me this fragmentation removal also privided a surprising converse effect: for the 4 days I could think about work uninterrupted and guilt-free which put me in a state of sustained multi-day focus that provided tangible boost to the quality of my results.

For sure it's impossible to do concentrated work for 10 hours straight, but a typical job isn't only concentrated work. Onve you learn what your energy levels are through the day, and manage your workload accordingly and have discipline , it is perfectly possible to have sudtainable full-output 10 hour workdays.

Not for everyone, but definitely beneficial for those who know how to use it.
by Imustaskforhelp | 2025-09-06 16:12:58+00:00
I agree. Its an incentives issue if I am being honest. If I ever generate software, I would also prefer to open source it but there are mechanisms where either cloud providers or anybody can take my changes and earn over them without me getting anything in return...

I mean, it is technically what it means to have a foss license but I just can't shake the feeling that we as a society are feeling so entitled that people are advocating against sspl licenses or etc. when I do think that if you are a dev and you wish to work on foss full time then something like sspl might be good in that regards.

Open source Contributors just don't get paid for the work they are doing. They are sadly doing free labour. I feel like I personally might start coding stuff in sspl or maybe just source available licenses if they get more favourable. The whole terminology behind source available licenses is kinda weird in the sense that basically a single clause which is meant to stop big cloud providers from selling your service that you built can make something like agpl foss and sspl not foss/source available.