MurphyA/hacker-news huggingface dataset:
by graycat | 2025-06-14 23:52:35+00:00
NP-hard is really hard, but it is hard for (a) polynomial running time, (b) for exact solutions, (c) on worst case problems.

One might suspect that fast enough on specific problems for approximate solutions that still make/save a lot of money might also be welcome. Ah, perhaps not!

E.g., in NYC, two guys had a marketing resource allocation problem, tried simulated annealing, and ran for days before giving up.

They sent me the problem statement via email, and in one week I had the software written and in the next week used the IBM OSL (Optimization Subroutine Library) and some Lagrangian relaxation. In 500 primal-dual iterations with

600,000 variables

40,000 constraints

found a feasible solution within 0.025% of optimality.

So, I'd solved their problem (for practical purposes, the 0.025% has to count as a solving) for free.

They were so embarrassed they wanted nothing to do with me. We never got to where I set a price for my work.

The problem those two guys had was likely that, if they worked with me, then I would understand their customers and, then, beat the guys and take their customers. There in NYC, that happened a second time.

If a guy is in, say, the auto business, and needs a lawyer, the guy might want the best lawyer but will not fear that the lawyer will enter the auto business as a powerful competitor. Similarly for a good medical doctor.

For an optimization guy saving, say, 5% of the operating costs of a big business, say, $billion in revenue a year, all the management suite will be afraid of the guy getting too much power and work to get him out -- Goal Subordination 101 or just fighting to retain position in the tribe.

After having some grand successes in applied math where other people had the problem but then being afraid that I would be too powerful, I formulated:

If some technical, computing, math, etc. idea you have is so valuable, then start your own business exploiting that idea -- of course, need a suitable business for the idea to be powerful.
by gjm11 | 2025-06-14 23:53:08+00:00
He doesn't say "that LLMs based on transformers can't create anything truly novel". Maybe he thinks that, maybe not, but what he says is that "today's systems" can't do that. He doesn't make any general statement about what transformer-based LLMs can or can't do; he's saying: we've interacted with these specific systems we have right now and they aren't creating genuinely novel things. That's a very different claim, with very different implications.

Again, for all I know maybe he does believe that transformer-based LLMs as such can't be truly creative. Maybe it's true, whether he believes it or not. But that interview doesn't say it.
by hundchenkatze | 2025-06-14 23:54:37+00:00
I’ve never had to get a new card/number after a chargeback.

You just get the charge removed or some amount deducted if it’s approved. You aren’t requesting a new card.

edit: This was for a purchase I made but didn’t receive exactly what I paid for. Now for fraudulent charges I didn’t make, yes they send a new card. I’m in the US, maybe it’s different elsewhere.
by kgeist | 2025-06-14 23:55:14+00:00
GPT4o isn't considered an "advanced" LLM at this point. It doesn't use reasoning.

I gave your prompt to o3 pro, and this is what I got without any hints:

Historic shipwrecks (1850 → 1970) • ~20 000 deep water wrecks recorded since the age of steam and steel • 10 % were passenger or mail ships likely to carry a cabin class or saloon piano • 1 piano per such vessel 20 000 × 10 % × 1 ≈ 2 000 Modern container losses (1970 → today) • ~1 500 shipping containers lost at sea each year • 1 in 2 000 containers carries a piano or electric piano • Each piano container holds ≈ 5 units • 50 year window 1 500 × 50 / 2 000 × 5 ≈ 190 Coastal disasters (hurricanes, tsunamis, floods) • Major coastal disasters each decade destroy ~50 000 houses • 1 house in 50 owns a piano • 25 % of those pianos are swept far enough offshore to sink and remain (50 000 / 50) × 25 % × 5 decades ≈ 1 250 Add a little margin for isolated one offs (yachts, barges, deliberate dumping): ≈ 300 Best guess range: 3 000 – 5 000 pianos are probably resting on the seafloor worldwide.
by robocat | 2025-06-14 23:55:40+00:00
I've driven or motorcycled in Chile, Mexico, Indonesia, Vietnam, Philippines. Too many situations where the roads are just nonsense and the other drivers are insane or homicidal: I can't imagine how a self-driving car could work in the worst traffic without AGI.

Plus drivers will learn the weaknesses of self-driving cars and then abuse those weaknesses.

Taxi drivers know not to stop in certain unsafe locations - good luck for self-driving cars to learn how to read for dangerous situations because of criminals.
by BugsJustFindMe | 2025-06-14 23:56:32+00:00
> the eye tracking does not work on mobile.

Isn't that a function of platform and not screen size?

> All the components needed to be big enough for eye tracking "selection" to consistently work.

Isn't this also a function more of angles and not pixels? A phone close to my face has the same apparent size as a computer screen farther away.
by ghaff | 2025-06-14 23:56:45+00:00
Shared van services got ridiculous sometimes and then I had a couple of incidents related to driving/parking at the airport (like a 10pm cold weather flat). So I just started using a car service at a new job (I think) and the company never flinched. Now--especially as I'm usually taking longer but fewer air trips even if it's usually on my own nickel these days--just keep doing so.
by jsemrau | 2025-06-14 23:58:33+00:00
>The goal is to avoid penalizing people for their skin color [...]

That's not correct. The goal is to identify and flag fraud cases. If one group has a higher likelihood to perform that, then this will show up in the data. The solution should not be to change the data but educate that group to change their behavior.

Please note that I have neither mentioned any specific group and do not have a specific group in mind. However, an example for such a group that I have seen in my professional life could be female 20 year old CEOs of construction companies (often connected to organized crime)
by ksec | 2025-06-14 23:59:04+00:00
I believe they can also do Dual Socket, which means in a single server unit, We could have

2 x 256 = 512 CPU Core, or 1024 vCPU in cloud computing terms.

16 Memory Channel. 1.6TB/s memory bandwidth.

200GB/s SSD RAID System.

That is more computing power in a single 2U server than a whole rack of servers in 2010. I am only hoping Zen 6 will actually improve IPC, performance / watt compared to ARM counterpart is still so far off.
Show HN: Paper trading that simulates real market dynamics and broker rules
by andrenorman | 2025-06-15 00:00:21+00:00
Hey HN! I built Paper, a paper trading platform that actually simulates the messy reality of trading - slippage, partial fills, market impact, and real execution logic. The Problem: Most paper trading platforms give you fantasy fills at perfect prices. You develop a strategy that works great in simulation, then lose money when you go live because it never accounted for real market dynamics. What Makes Paper Different: - Simulates 22 real brokers with their exact rules, restrictions, and fee structures - Real market dynamics: slippage, partial fills, market impact - Configurable latency profiles: Retail (50-250ms), Institutional (20-100ms), Colocated (0.5-5ms), or Custom - L1 NBBO price feeds with realistic fill prices - Extended hours trading (4am-8pm ET) - Full margin trading (Reg T and Portfolio Margin with SIMPLE/SPAN/TIMS) - Short selling with proper locate requirements - Real PDT rule enforcement First Trading Platform with MCP (Model Context Protocol): We're the first to ship MCP support! Test your trading strategies with Claude directly: - npm install @paperinvest/mcp-server - Build and backtest strategies using AI - Claude can place trades, check positions, analyze performance - Full API access through MCP tools Tech Stack: - NestJS backend with PostgreSQL, Redis, Kafka - Next.js 15 frontend - SSE for real-time order streaming - REST API + MCP server - AWS deployment Pricing: - Free: 5 trades/day, basic orders, cash account - Pro ($20/mo): Unlimited trades, all order types, margin accounts, extended hours - Commercial ($500+/mo): Multi-account support for businesses Coming Soon: Options trading (full multi-leg strategies) and futures I'm a solo developer. Built this because I was tired of strategies that worked perfectly in ThinkorSwim's paper trading but failed with real money due to unrealistic fills. Try it: https://paperinvest.io API Docs: https://docs.paperinvest.io Would love feedback! What broker rules or market dynamics do you wish paper trading platforms simulated better?
by muzani | 2025-06-15 00:01:57+00:00
Many of them violate this guideline:

"Comments should get more thoughtful and substantive, not less, as a topic gets more divisive."

I'll try to pull a random recent example that isn't flagged: https://news.ycombinator.com/item?id=44204767 https://news.ycombinator.com/item?id=44205060

I mean here in the title, we have court, DOGE, data. Good comment to votes ratio. It should be a better source for intellectual gratification compared to most political news.

The first link delivers (how we handle leaked social security data and PII), the second doesn't.

There's some thoughtful comments at the bottom of the second link if you have showdead on, and these seem to get downvoted hard. I'm not American and don't have the context for DOGE. But rude responses are being upvoted and the polite calm ones are being downvoted to death. This feels a lot like censorship.
by starchild3001 | 2025-06-15 00:03:46+00:00
We built planes—critics said they weren't birds. We built submarines—critics said they weren't fish. Progress moves forward regardless.

You have a choice: master these transformative tools and harness their potential, or risk being left behind by those who do.

Pro tip: Endless negativity from the same voices won't help you adapt to what's coming—learning will.
by londons_explore | 2025-06-15 00:04:00+00:00
In my view, we need to move the goalposts.

Fraud detection models will never be fair. Their job is to find fraud. They will never be perfect, and the mistaken cases will cause a perfectly honest citizen to be disadvantaged in some way.

It does not matter if that group is predominantly 'people with skin colour X' or 'people born on a Tuesday'.

What matters is that the disadvantage those people face is so small as to be irrelevant.

I propose a good starting point would be for each person investigated to be paid money to compensate them for the effort involved - whether or not they committed fraud.
by jgerrish | 2025-06-15 00:06:41+00:00
Well, you wouldn't have to sell the car. You could also setup a licensing / loan / dedicated car system.

It would work well for local municipalities that want to provide low-cost door-to-door service for the elderly.

We have a bus service here, The ART, and a dedicates "paratransit" bus service that provides door-to-door service to eligible riders.

And a couple private large-scale developed and managed neighborhoods that have driverless non-automated (remote controlled) transit systems.

If you know a large portion of your riders have disabilities, dedicated buses or vans make sense.

I'm sitting here advocating for this, and it's a great service that I'm glad they have it for those in need, and yet I need fucking plywood for hurricanes myself.

Yeah, it is Florida. But honestly, the transit system here and bike infrastructure development and traffic planning is good.
by elcritch | 2025-06-15 00:06:57+00:00
> It's an embarrassment that the leading video platform, belonging to a multi-billion-dollar company, has a worse user experience than a simple video file with only the web browser's built-in UI controls.

You're surprised because you view Youtube as a video platform. It was that once but now it's an advertising platform that happens to show videos.

Luckily for now you can pay for YT premium. It makes the experience so much better. no checking for ads every-time you skip.
by ryao | 2025-06-15 00:07:00+00:00
You can predict the token generation performance of a GPU or CPU by dividing the memory bandwidth by the size of the active parameters. By definition, that is a memory bandwidth bottleneck. I have no idea why you think it is not.

Anyone who has worked on inference code knows that memory bandwidth is the principal bottleneck for token generation. For example:

https://github.com/ryao/llama3.c
by kurthr | 2025-06-15 00:08:31+00:00
This is a really key result. You can't effectively be "blind" to a parameter that is significantly correlated to multiple inputs and your output prediction. By using those inputs to minimize false positives you are not statistically blind, and you can't correct the statistics while being blind.

My suspicion is that in many situations you could build a detector/estimator which was fairly close to being blind without a significant total increase in false positives, but how much is too much?

I'm actually more concerned that where I live even accuracy has ceased to be the point.
by fasterik | 2025-06-15 00:08:35+00:00
I think this depends highly on your mouse skills. Most of the top bullet players I've seen play on stream (Andrew Tang, Hikaru Nakamura, and Daniel Naroditsky) use drag-to-move.

A notable exception is Magnus Carlsen. He uses click-to-move, but I think his skill in bullet comes from his baseline chess skill and not his ability to move fast.
by fernirello | 2025-06-15 00:09:22+00:00
Clarification question, having read OP yet having missed some fine details: I presume you mean that software could set some CIA-II register to keep the NMI line to the CPU down indefinitely. Since what triggers the handling of an NMI is the transition from high to low, that means no other handler (in particular the Freeze Frame's) would get executed. And one'd also need to redirect the NMI vector, which normally is in Kernel ROM, to a dummy handler consisting of an RTI or little more. Correct?
by FINDarkside | 2025-06-15 00:09:38+00:00
Right, I agree there. Also that's something LLMs can already do. If you give the problem to ChatGPT o3 model, it will actually write python code, run it and give you the solution. But I think points 1 and 2 are still very valid things to talk about, because while Tower of Hanoi can be solved by writing code that doesn't apply to every problem that would require extensive reasoning.
by shoo | 2025-06-15 00:10:50+00:00
have a read through the case studies:

gurobi case studies: https://www.gurobi.com/case_studies/

some cplex case studies: https://www.ibm.com/products/ilog-cplex-optimization-studio/...

hexaly (formerly localsolver) case studies: https://www.hexaly.com/customers
by jbombadil | 2025-06-15 00:11:49+00:00
There's still a "wow factor" associated with this. I live in a city that doesn't have Waymo. I recently had a work trip to a city that does. Waymo was 25% more expensive than Uber (~15 vs ~20). I still took Waymo because I don't get to experience it often, so it's fun to be in a driverless car. If I had constant access to Waymo, I would have probably chosen the cheapest option.
by nerdponx | 2025-06-15 00:12:47+00:00
That doesn't seem true to me at all. Let's say you fit y=c+bx+ax^2 on the domain -10,10 with 1000 data points uniformly distributed along x and with no more than 1% noise in observed y. Your model will be pretty damn good and absolutely will be able to generate "synthetic a priori" y outputs for any given x within the domain.

Now let's say you didn't know the true function and had to use a neural network instead. You would probably still get a great result in the sense of generating "new" outputs that are not observed in the training data, as long as they are within or reasonably close to the original domain.

LLMs are that. With enough data and enough parameters and the right inductive bias and the right RLHF procedure etc, they are getting increasingly good at estimating a conditional next token distribution given the context. If by "synthetic" you mean that an LLM can never generate a truly new idea that was not in it's training data, then that becomes the question of what the "domain" of the data really is.

I'm not convinced that LLMs are strictly limited to ideas that they have "learned" in their data. Before LLMs, I don't think people realized just how much pattern and structure there was in human thought, and how exposed it was through text. Given the advances of the last couple of years, I'm starting to come around to the idea that text contains enough instances of reasoning and thinking that these models might develop some kind of ability to do something like reasoning and thinking simply because they would have to in order to continue decreasing validation loss.

I want to be clear that I am not at all an AI maximalist, and the fact that these things are built largely on copyright infringement continues to disgust me, as do the growing economic and environmental externalities and other problems surrounding their use and abuse. But I don't think it does any good to pretend these things are dumber than they are, or to assume that the next AI winter is right around the corner.
by magicalhippo | 2025-06-15 00:13:47+00:00
Start by assuming they could potentially be all different, so denote the currents i_1 to i_12.

However note the problem is symmetrical about the vertical axis, so flip the figure. The current passing through the flipped paths should be the same as before the flip, so note down which i's equate to each other due to this.

Note that the problem is symmetrical about the horizontal axis, and do the same there. Note that the problem is symmetric when rotated 90 degrees, so do that. And so on.

In the end you'll have a bunch of i's that are equal, and you can group those into two distinct groups. Call those groups alpha and beta.

edit: Another way to look at it is that you can't use the available symmetry operations to take you from any of the alphas to a beta. This is unlike alpha to alpha, or beta to beta.
by sandworm101 | 2025-06-15 00:13:57+00:00
It does, but most of the needed dV is harvested from the planets during gravity assists. The probe is accelerated/turned several hundred or thousand m/s and in exchange the planets it passes are shifted/slowed/turned by maybe 0.00000000000000000000001 m/s. In this case, the probe largely needs to slow down, to bleed of the speed it got from being at earth's orbit, so the planets are probably being accelerated.
by pirmoradianS | 2025-06-15 00:14:44+00:00
من عاشق افکار شما هستم با تشکر از پیش من در حال تلاش برای ارزیابی تقاضای واقعی قبل از رفتن اعماق عمیق تر وجود خوش تر دارد
by pchangr | 2025-06-15 00:14:55+00:00
Look, what I can tell you is this: …. 7am is the starting time of school classes in Guatemala City. It’s 7am so it doesn’t clashes with office hours.. which start at 8am.. most of the time. But if you’re lucky you can choose to start at 7am. So you can avoid a bit of the traffic.

The only parts of the world were I have lived were people mostly work 9-to-5 are what you would call “the developed world”. And that includes Germany.

I personally don’t consider Germany an early rising country and it took me quite some time to adjust myself to not having “normal” stores open before like 10. And then.. they are all closed by 6pm.. like.. cool that the developed world has work regulations but it’s hardly the norm.
by gruez | 2025-06-15 00:15:33+00:00
>It's literally called a "living" wage, and I guarantee you in reality it's nothing more than that

Did you read the methodology page or even my comment? I made specific objections with the methodology and you didn't even address them.

>Life tends to always have unexpected costs. I shouldn't need to tell anybody that, including you.

I shouldn't have to tell you that if you read the methodology page, you'd see there's a specific category for "Other necessities" and "Civic engagement" (whatever that means), and I'm not objecting to those categories.
by rayxi271828 | 2025-06-15 00:16:37+00:00
I've been taking these rides 5-6 days a week, everywhere, and also in other countries outside the US. What I've come to realize is this: what matters to me the most is the consistency of the lowest bar of the experience.

I get that sometimes with human drivers, when I'm lucky, I get someone who goes above and beyond, someone who's fantastic to talk to along the way, and so on.

But if I can trade all that with a guarantee that there's a consistent, predictable floor to my worst experience, I'll take it in a heartbeat.

At the end of it, I take a ride to get from point A to point B. I'd rather have a machine does it for me very efficiently, without all the messy human element, with the ups and the downs, because it's the downs that ruin my day.
by xKingfisher | 2025-06-15 00:16:57+00:00
I've had the opposite experience recently.

Going from downtown Los Angeles to Santa Monica is $30s for a Waymo and runs up to $50s for Uber/Lyft (sometimes). Otherwise, they tend to be within a few dollars.

I figured it was a combination of Google subsidizing rides and a lack of a "traffic tax".

They're a significantly better experience for 45+ minute rides.
by ksec | 2025-06-15 00:18:50+00:00
Part of the reason is the PCIe 6 differ from PCIe 5 so much there will be a learning curve involved.

Another reason being power consumption is already an issue with PCIe 5, took them 2-3 years to get the controller to under 10W while serving double the bandwidth of PCIe 4 SSD.
by brunoarueira | 2025-06-15 00:20:12+00:00
Once during the first year of the covid pandemic, I requested a couple meals for me and my wife through the Uber eats for lunch, my wife was accompanying in the hospital my mother-in-law on Sunday, then after suddenly the place informed the meals was delivered, but I didn't received anything. After I tried to discuss with Uber eats, I had appealled for the credit card, they full refund me.
by londons_explore | 2025-06-15 00:20:57+00:00
> Two people who are identical except for their nationality face the same probability of a false positive

It would be immoral to disadvantage one nationality over another. But we also cannot disadvantage one age group over another. Or one gender over another. Or one hair colour over another. Or one brand of car over another.

So if we update this statement:

> Two people who are identical except for any set of properties face the same probability of a false positive.

With that new constraint, I don't believe it is possible to construct a model which outperforms a data-less coin flip.
by bryant | 2025-06-15 00:21:07+00:00
The query was exactly as you described. Gemini returned the details of the Dreamliner Air India crash, including capturing the number of people aboard the flight, the date of the flight, the location of the flight and crash - yet Gemini somehow managed to hallucinate the wrong plane, an Airbus A330-243.

Air India doesn't even have any A330s, so it's not even immediately obvious how the hallucination happened. It just straight up included the wrong plane.

This specific failure seems more egregious than most.
by ryandrake | 2025-06-15 00:21:08+00:00
Typical small US airports still don't charge landing fees to light aircraft, but things are changing. Now that ADS-B[1] is deployed widely, airports are looking at automated landing fee charges as another way to soak pilots, just because they now can. A number of companies are sprouting up to meet this demand and offer airports their turnkey systems to monitor and charge everyone who lands, sharing the profit with the airport.

1: https://www.wingsmagazine.com/monetizing-ads-b-data/
by gylterud | 2025-06-15 00:23:48+00:00
I love the make reimagination in plan 9: mk. In my experience ok is easier and slightly saner than make. On unix like systems you can get it from plan9port, along with other gems, such as acme.

https://plan9.io/sys/doc/mk.html

https://9fans.github.io/plan9port/