MurphyA/hacker-news huggingface dataset:
by thomashabets2 | 2025-08-22 15:01:16+00:00
The standard library recovers from the panic, and program continues.

This means that if you do:

func (f Foo) String() string { some.Lock() t := get_something() some.Unlock() t = transform_it(t) return t }

And `get_something()` panics, then the program continues with a locked mutex. There are more dangerous things than a deadlocked program, of course.

It's non-optional to use defer, and thus write exception safe code. Even if you never use exceptions.
by _DeadFred_ | 2025-08-22 15:02:42+00:00
Are you an executive who will gain millions by doing it, and you are doing it with company money that your have corporate control over? Then yep.

Maybe executives shouldn't have stock. Then it wouldn't be manipulation.

But they do. That is their main compensation people like to point (the CEO isn't really getting paid those millions, it's stocks). So the CEO is paid in a way that encourage the CEO to commit DIRECT stock manipulation.
by therobots927 | 2025-08-22 15:03:00+00:00
I agree with your first point but regarding your second: I’m as far left as it gets and I don’t think that’s true at all. Most of the influencers I follow despise AI and also are highly skeptical of the outrageous claims made by Sam Altman etc. The reality is that the need for things like universal health care exists today. Tens of millions of people can not get medical care in the US. Insurance companies are allowed to deny claims with no justification. That has nothing to do with AI taking jobs BUT it does involve AI because United Health’s denial rate went through the roof right after they started letting AI determine which claims were covered by policy with no human review. So people on the left are talking about AI in contexts that it doesn’t seem you’re aware of
by tom_ | 2025-08-22 15:03:02+00:00
Because enough people clicked the flag link. If enough of them click the flag link on this one, it'll get flagged too!

Flagging is there for stuff that's off-topic or generating low-quality discussion in the views of the people clicking the flag link. Sometimes the admins will step in to unflag the article if it looks like neither of these apply, and/or if it would be helpful to have a containment topic for discussion of a particularly popular contentious topic.
by taeric | 2025-08-22 15:03:23+00:00
Ok, I take it as an obvious prerequisite that you have to have transit for people to use it. Such that, yes, it isn't enough to just tax the heck out of cars to force them to start walking long distances.

But I point to Atlanta as easy evidence that having transit cover hot spots is clearly not enough. I used it daily for over a couple of decades to get to a job where I was among the only people that used transit. Amusingly, this was among a crowd of folks that loved preaching the virtues of transit. As soon as they made enough money to afford a car, they got one.

Even in Seattle, with what seems like nicer transit to me, I see plenty of people getting a car when they can afford it.

Tokyo, famously, has strict rules on if you can register a car. Despite that, it is amusing that the silly AI answer still ends with "though car ownership remains higher in some affluent neighborhoods." Which was somewhat obvious to see when touristing the place.
by hodgehog11 | 2025-08-22 15:03:55+00:00
Putting aside the dislike of other cultures, you're making several assumptions here. This student was of Asian descent, and was selected for their talents. The student never committed any crime or misdemeanor, was never fined, never spoke out of turn or rallied for any cause, and had no government connections. It's possible a name was mixed up, which isn't surprising as funding is being channeled from legal immigration offices to deportations. He's one of several I've heard about.

Believe it or not, the US enjoys a special status as a prominent place to study and contribute knowledge. I'm talking about students doing fundamental, valuable, possibly even patentable research. The best talent flows through here, and domestic students get to benefit from that. Because of these "mistakes", it is already the case that good talent is choosing not to come to the US. Certain other nations will benefit instead.

If you want a US for existing US citizens alone (immigration "the right way" is rapidly deteriorating), then that is what is happening. One way or another, we'll witness what the US becomes.
by sixo | 2025-08-22 15:04:39+00:00
Well, you missed my point. I'm not talking about "you look at the MRI and see something and say it's a positive", I'm referring to the process of reading MRIs as like a statistical model (even if in practice it exists in the minds of radiologists) which is trained on the corpus of MRI data. That model will depend in some way on the distribution of positive/negative examples in the corpus; if the corpus changes the model has to then be updated to match.

Point is, the false positive concern is only a concern if you use the old model with the new corpus. Don't do that! That's dumb!

The net effect of MRIing everyone on public health would likely be enormously positive as long as you don't do that.
Show HN: Tabwise – AI data analyst that outperforms ChatGPT and Claude
by abhegd | 2025-08-22 15:04:54+00:00
Hey HN! I'm Abhishek. I’m a designer and product builder. I’ve been building AI products for the past year after leaving my design job, where I worked on dev tools being used by 1M+ engineers.

Previously I built Allyce AI (https://allyce.ai/), which helps answer questions, qualify leads, and handle complaints on websites (AI for sales/SDR + CS). When I started as an independent builder, the first thing I built was a sophisticated GraphRAG pipeline that powers Allyce. The customers using Allyce needed something to analyze sales data and ad performance data, which wasn't possible with RAG - that's what led me to build Tabwise as a separate product.

The key insight was that general AI tools fail at data analysis because they skip three critical steps: 1. Pre-processing: Cleaning data, inferring schema and structuring context specifically for analytical queries 2. Context engineering: Crafting prompts that understand data relationships, business context, and expected output formats 3. Post-processing: Converting raw LLM outputs into properly formatted charts, executive summaries, and actionable insights

This pipeline is why Tabwise can consistently outperform ChatGPT (GPT-5 Thinking) and Claude (Sonnet-4) on data analysis tasks - it's not just the model, it's the entire system.

Tech stack: Next.js, Vercel AI SDK, E2B, I automatically route tasks to the best model based on complexity (Powered by Claude sonnet-4 and OSS models via Fireworks AI)

Right now I'm focused on nailing spreadsheets (.xlsx, .csv), but have more data source integrations planned based on what users actually need.

Would love your thoughts.
by linuxftw | 2025-08-22 15:05:13+00:00
That's true only in a vacuum. For example, should I run gpt-oss-20b unquantized or gpt-oss-120b quantaized? Some models have a 70b/30b spread, and that's only across a single base model, where many different models exist at different quants could be compared for different tasks.
by rerdavies | 2025-08-22 15:05:13+00:00
The question is going to be: is it a USEFUL signal. I suspect not. And frankly, to be honest, as a senior developer who uses AI assistants routinely, I would consider it a serious disincentive to actually submit a PR in the first place to a repository that has such a policy. Submitting a good PR is hard work. Often an order of magnitude more work than the fix itself. If I think that a repository is going to not accept my PR just because I use a coding assistant, I'm going to be much less inclined to submit a PR at all.
by nasretdinov | 2025-08-22 15:05:48+00:00
I've found that when you need this it's easier to move stuff offheap, although obviously that's not entirely trivial in a GC language, and it certainly creates a lot of rough edges. If you find yourself writing what's essentially, e.g. C++ or Rust in Go, then you probably should just rewrite that part in the respective language when you can :)
by vidarh | 2025-08-22 15:06:02+00:00
The left is generally extremely sceptical to UBI, as its main proponents tend to be classically liberal groups (so not "US liberal") pushing it as a means to contain and limit welfare systems by dropping welfare programs in favour of a general, low UBI.

The more leftist position ever since the days of Marx has been that "right rather than being equal would have to be unqueal" to be equitable given that people have different needs, to paraphrase from Critique of the Gotha Program - UBI is in direct contradiction to socialist ideals of fairness.

The people I see pushing UBI, on the contrary, usually seems motivated either by the classically liberal position of using it to minimise the state, or driven by a fear of threats to the stability of capitalism. Saving capitalism from perceived threats to itself isn't a particularly leftist position.
by RyanOD | 2025-08-22 15:06:25+00:00
That's one way. The approach I take is more of a "Hey, AI, here is what I'm trying to accomplish and here is the approach I plan to take. What do you think of this approach? Does it support my broader goals? Etc."

But, much of what I spend my time on are already solved problems (building retro video game clones) so AI has a LOT of high-quality content to draw upon. I'm not trying to create new, original products.
by ryandrake | 2025-08-22 15:06:32+00:00
Most of the most charismatic, confident know-it-alls I have ever met have been in the tech industry. And not just the usual suspects (founders, managers, thought leaders, architects) but regular rank-and-file engineers. The whole industry is infested with know-it-alls. Hell, HN is infested with know-it-alls. So it's no surprise that one of the biggest products of the decade is an Automated Know-It-All machine.
by redshirtrob | 2025-08-22 15:07:18+00:00
Ummm, are you saying that C is the grandparent of C, or do you have a typo in your example? Sure, the initial comment is not necessarily the grandparent, but in your ABCDE example, A is the grandparent of C, and C is the grandparent of E.

Maybe I'm just misreading your comment, but it has me confused enough to reset my password, login, and make this child comment.
by Adonia | 2025-08-22 15:07:26+00:00
I’ve been working on Stock Portfolio Tracker for the last 3 years. Stock Portfolio Tracker is a comprehensive platform for long-term investors, offering 30+ years of historical data, advanced analytics, and precise performance calculation through the Money-Weighted Rate of Return (MWRR) methodology. It supports a wide range of assets across 85 exchanges, ensuring accurate insights with seamless dividend and corporate action tracking.
by pradn | 2025-08-22 15:07:42+00:00
All this points to "personality" being a big -- and sticky -- selling point for consumer-facing chat bots. People really did like the chatty, emoji-filled persona of the previous ChatGPT models. So OpenAI was ~forced to adjust GPT-5 to be closer to that style.

It raises a funny "innovator's dilemma" that might happen. Where an incumbent has to serve chatty consumers, and therefore gets little technical/professional training data. And a more sober workplace chatbot provider is able to advance past the incumbent because they have better training data. Or maybe in a more subtle way, chatbot personas give you access to varying market segments, and varying data flywheels.
by cyberpunk | 2025-08-22 15:07:58+00:00
I've written a fair chunk of go in $dayjob and I have t say it's just... Boring. I know that sounds like a weird thing to complain about, but I just can't get enthused for anything I write in go. It's just.. Meh. Not sure why that is, guess it doesn't really click for me like other languages have in the past.

It's a good language for teams, for sure, though.
by woodruffw | 2025-08-22 15:08:03+00:00
I don't think Linux would be better with a `cu` prefix for coreutils, but I do think git would be worse without a `git` prefix. I think it's ultimately a question of user expectations, and I think user expectations around packaging tooling in particular have shifted towards the Go and Rust styles of providing a "namespace" tool that provides a single verb-style interface for developer actions.
by Fergusonb | 2025-08-22 15:08:21+00:00
I agree, it's like they looked at GPT 3.5 one time and said "this isn't for me"

The big 3 - Opus 4.1 GPT5 High, Gemini 2.5 Pro

Are astonishing in their capabilities, it's just a matter of providing the right context and instructions.

Basically, "you're holding it wrong"
by Terr_ | 2025-08-22 15:08:25+00:00
> They really can't overpromise much more than they did with the AI hype-cycle.

While I agree that "replace all human labor" is already pretty high up there on the overreaching u/dis-topian promise list, there are still a few things left.

Perhaps the next dream to sell will be digitizing the minds of Valued Shareholders so that they can grasp immortality inside the computer.
by mrweasel | 2025-08-22 15:08:43+00:00
Also visas expire, so why not simply implement better checks for new visas. Most of the 55M visas are probably fine, so you have to spend an exorbitant amount of resource on finding very few issues. It's much cheaper to add additional check to new visa applications.

55M is also just a crazy amount of visas for a country with 350M citizens. Especially given that I'd guess that a large amount of people travel to the US on a visa waive program.
by HarHarVeryFunny | 2025-08-22 15:08:56+00:00
Sure, a real neuron activates by outputting a train of spikes after some input threshold has been crossed (a complex matter of synapse operation - not just a summation of inputs), while in ANNs we use "continuous" activation functions like ReLU... But note that the output of a ReLu, while continuous, is basically on or off, equivalent to a real neuron having crossed it's activation threshold or not.

If you really wanted to train artificial spiking neural networks in biologically plausible fashion then you'd first need to discover/guess what that learning algorithm is, which is something that has escaped us so far. Hebbian "fire together, wire together" may be part of it, but we certainly don't have the full picture.

OTOH, it's not yet apparent whether an ANN design that more closely follows real neurons has any benefit in terms of overall function, although an async dataflow design would be a lot more efficient in terms of power usage.
by nasretdinov | 2025-08-22 15:09:20+00:00
I think it's only a real issue when you're coming from a language that has different rules. Block-scoping (and thus not being able to e.g. conditionally remove a temp file at the end of a function) would be equally surprising for someone coming from Go.

But I do definitely agree that the dynamic nature of defer and it not being block-scoped is probably not the best
by NullHypothesist | 2025-08-22 15:09:45+00:00
"Waymo has been granted a permit to test its autonomous vehicles in New York City, the first such approval granted by the city. The company told TechCrunch it plans to start testing “immediately.”

The company is allowed to deploy up to eight of its Jaguar I-Pace SUVs in Manhattan and Downtown Brooklyn through late September. Waymo’s vehicles must have a trained safety operator in the driver’s seat, with at least one hand on the wheel at all times. The company cannot pick up passengers (since it would need a license from the city’s Taxi and Limousine Commission) and it has to regularly meet with and report data to the city’s Department of Transportation (DOT), according to the mayor’s office."
by anonymars | 2025-08-22 15:09:47+00:00
2012 was a long time ago. I'm more inclined to Value myself, but has it held up?

I threw together a quick comparison with that tool (handy, thanks) of Vanguard Growth vs Vanguard Value and it's not too pretty. Sure, Value is less volatile, but...

https://www.portfoliovisualizer.com/backtest-portfolio?s=y&s...

I mean I guess we'll see what happens when the music stops again, but it resembles the same issue as being "right" about a market drop -- that you can be right, but the timing is such that it nevertheless would have been more lucrative to be invested the whole time anyway
by chpatrick | 2025-08-22 15:09:51+00:00
> Humans don't think in tokens or even write in tokens so obviously what you wrote is not a fact.

Doesn't matter what they think in. A token can be a letter or a word or a sound. The point is that the box takes some sequence of tokens and produces some sequence of tokens.

> You wrote "The text that comes out follows some statistical distribution". > At the risk of being over my head here did you mean the text can be described statistically or "follows some statistical distribution". Are these two concepts the same thing? I don't think so. > A program by design follows some statistical distribution. A human is doing whatever electrochemical thing it's doing that can be described statistically after the fact.

Again, it doesn't matter how the box works internally. You can only observe what goes in and out and observe its distribution.

> Regardless my point was pretty simple, I know this will never happen but I wish tech people would drop this tech language when describing humans and adopt neuroscience language.

My point is neuroscience or not doesn't matter. People make the claim that "the box just produces characters with some stochastic process, therefore it's not intelligent or correct", and I'm saying that implication is not true because there could just as well be a human in the box.

You can't decide whether a system is intelligent just based of the method with which it communicates.
by taeric | 2025-08-22 15:10:15+00:00
I went for over a decade without a car in Atlanta. More, I think financing the first car I got was among the worst decisions I have ever made in my life. It was shocking how bad that monthly payment screwed up my financial planning.

All of which is to say, it amuses me to find myself defending that people will buy cars. I am not trying to push it as the correct answer. I personally think people should understand the expense of owning a car far better than it seems most people do. I just also can't deny that a car is far more convenient than not, if you can afford one.
by CWuestefeld | 2025-08-22 15:11:21+00:00
It happened 20 years ago, so some folks around here might be too young to remember the Sony rootkit fiasco [1]. Sony decided it would be a good idea to put on their music CDs an auto-run program that would install a rootkit on your Windows computer, whose job it was to be a watchdog for Sony's copyrights.

[1] https://en.wikipedia.org/wiki/Sony_BMG_copy_protection_rootk...
by lenerdenator | 2025-08-22 15:12:06+00:00
Unfortunately the representatives in Congress gave the tariff power to the Presidency.

Now, did they do that with the approval of the voters? Ostensibly, yes, but in reality, it's not that clear-cut.

This would be more like if the Thirteen Colonies had MPs and those MPs still voted in favor of the Stamp Act, or they voted to delegate the power to tariff to someone with a severe personality disorder.
by hodgehog11 | 2025-08-22 15:12:23+00:00
Wow, that was fast.

I've thought for a while that ensembling approaches would become the next stage of LLM development after CoT, since it provides yet another effective, independent axis for scaling laws. Great to see that perspective is taking off. The open weight community has an opportunity to take these ideas and run with them better than OpenAI has.
by mellosouls | 2025-08-22 15:12:54+00:00
I read your link and it describes the suppression of conservative voices while far left voices posting genuine messages of hate were supported.

Surely you read your own link before posting it?

I've additionally given you several examples which counter your original claim that it's basically just Nazis whining about being cancelled, which you've dismissed flippantly.

This is a serious subject; if you can't address it in good faith I will leave it at that.
by xg15 | 2025-08-22 15:13:01+00:00
Not sure I read that formula right, but isn't the data loss limited to the last 100ms (worst case)?

I don't see many single user/desktop application use cases where that kind of time range would be risky.

Maybe if you used this as the main production database with thousands of concurrent sessions. But that doesn't seem to be their main use case, is it?
by IFC_LLC | 2025-08-22 15:13:08+00:00
Here are some thoughts from a U.S. citizen whose wife is an immigrant.

I have spent more than two and a half years filing forms and preparing paperwork for the U.S. government. I handled everything myself, without any “special” help or legal advice. I simply downloaded the forms from USCIS, filled them out using the required information, and submitted them.

What I can tell you is this: there is a massive market in the United States built on gray-area schemes, semi-legal shortcuts, and so-called expert advice. For example, there are companies charging $30,000 to submit a form that costs only $745 to file. Many “helpers” sell visa “upgrades.” The idea is that you arrive on a tourist visa and then follow a specific sequence of steps to convert it into a green card - something packaged and sold as a premium service for an extraordinary price.

This is a very large and lucrative slice of the pie that most people know little about. Both the U.S. visa process and tax filing system are riddled with gray practices and questionable “solutions.” Too often, the end result is that people are told to outright lie about their visa status or their taxes because they were instructed to do so.

From what I have observed, I would not call these practices outright foolish. Overblown at times? Yes, perhaps. But unnecessary? Not really.
by slipperydippery | 2025-08-22 15:13:09+00:00
My wife's seen this at multiple non-tech companies, and it's a disaster every single time. Most (like... 95+% of) folks can't use these things very well, being forced to use them kills morale because they're frustrating as fuck (and managers largely have no idea what they're actually capable of doing productively, so expectations are all over the place and often fantastical) and dealing with the output of co-workers who can't use them well is even more frustrating than the LLMs themselves are. It's sometimes coupled with attempts to realize the increased "efficiency" before it's even proven it exists, by firing significant chunks of staff at the same time as adopting "AI processes", further stressing out remaining employees and ruining ability to actually get things done.

It's trashing whole departments. The come-down from this high (which high is being experienced pretty much only by the C-suite and investors) is gonna be rough.
by jamager | 2025-08-22 15:13:09+00:00
Yes, thou the main problem stated in the article ("memorizing the rectangles") is very real. Now, I don't think you need much magic / LLM stuff to overcome that problem:

1. Instead of the usual "1 new word, 1 card" have 2 - 3 new words on each card, and have each new word in 3 - 4 different cards (ideally with different inflection, meaning, nuance, etc) 2. Review cards fast and very few times each. Like 5 - 8 times / card (max) instead of usual 15 - 20. 3. Don't punish yourself, keep moving on even if you just half-remember. First familiarize and then internalize language patterns instead of just memorize words.

Review intentionally, totally concentrated on the task. 10 mins / day well done >>> 30 mins / day mindlessly.

Outcome: more fun, more effective learning, no memorizing rectangles.