skysight-inc/HackerNews huggingface dataset:
install tiktok (if you do not have it) and disable everything, no mic/camera/photos/contacts/… nothing. then ask you partner/friend/… to send you some text messages about purchasing an ebike for instance. open safari and do some searches for ebikes (https://blue.bike perhaps and others)… the head on over to tiktok and scroll a bit and see if any ebikes start showing up…
Yes, but not 99% of traffic like we experienced after the great LLM awakening. CF Turnstile saved our servers and made our free pages usable once again.
How did you learn to work with Z3? I dipped my toes in recently having no prior experience. ChatGPT got me started but once the problem got complex enough I was stumped. I also don’t really have any mathematics ability.
> The construction of the real number system in Hardy's book, using the Dedekind Cut method is overly complicated - the use of the of Least Upper Bound is much simpler and clearer.

A Dedekind cut is a partition of the rational numbers into two sets, A and B, where every number that belongs to A is less than every number that belongs to B.

The cut represents a rational number if B has a least element, and an irrational number if it doesn't. (In full generality, it's a rational number if either (1) A has a greatest element, or (2) B has a least element, but in the case where A has a greatest element, we transfer that element into B, where it's the least element.)

The real number represented by a Dedekind cut is always the least upper bound of A (and the greatest lower bound of B). How does "the use of the Least Upper Bound" differ from Dedekind cuts? They aren't just the same thing in some arcane abstract sense where they both map onto the real numbers - they're the same thing in the most direct sense possible.

(For comparison, my analysis class defined real numbers as Cauchy sequences of rationals. The limit of such a sequence is a real number, but that real number need not be an upper or lower bound to anything.)
Do you know who Simon is?
Also from a license negotiation perspective, gives the buying company the option to threaten to self-host and/or fork. Even if they never do (and I'm sure the source company is very careful to balance the value story), it can act as a ceiling for rate increases or other annoying business practices.

Why would a company ever open-source their product then? Giving up that complete leverage can be a selling point during the purchasing process, making buyers more comfortable that they won't be (completely) locked in, and be a net positive on revenue through faster sales.
> making drones / evs / high end electornics

China does have a current advantage on lithium battery and rare earth materials - dumb technologies that US and allies can replicate fairly quickly, less than a year. EUV and 3nm and below on the other hand, will take decades, since it involves a number of different and deep technologies controlled by dozens of companies. China has thrown $150B on it since 2014, and has only come up with low yield/unprofitable 7nm via existing DUV machines.

> 80% GDP

China's demographics will more than HALF to 500M by 2100, if not earlier, while US grows to close to 400M by then. Someone actually theorizes that China's population is already only 800M right now https://www.youtube.com/watch?v=fR5F_8dSjOw

Also, a lot of that GDP is debatable in 2024, when real estate prices have dropped by more than 50% in tier 2 and below cities, and deflation has raged on.
> delaying a response will slow the bot down

This is a nice solution for an asynchronous web server. For apache, not so much.
2022, though 2019 was marginally lower
https://www.doctorswithoutborders.org
https://www.unrwa.org
https://wck.org
https://www.wearebgc.org
This FidoNet-style experimental messaging network is a good pointer to get started and find more people involved in today’s BBS world:

https://fsxnet.nz/
The best models are always out of reach on desktops. You can have ok models but AGI will come in a datacenter first
System calls take 10x longer on Windows than they do on UNIX.

That's what i/o completion ports are working around.

They solve a problem UNIX doesn't have.
I'm not sure what counts as the "first 25 years", but Dining Philosophers is from 1965.
Aren't they still supporting old Google Voice numbers though? I don't see how they could be making any money on that.
Is it just me, or does the README have the ChatGPT accent? For instance:

Whether you're looking to replicate your hometown, explore urban environments, or simply build something unique and realistic, Arnis offers a comprehensive toolset to achieve your vision.

I don’t have a lot of issues with people using LLMs to generate documentation, but it does seem to have a lot of nothing-sentences.
Has your car never had a recall, or are you simply unaware of any software recalls that have been done to it? Recalls are often done with software updates these days, so if you're not applying updates you're deliberately choosing not to apply safety fixes.
comparing google to claude 3.5 is like comparing tesla s plaid with a horse
I wonder to what extent the dedicated hardware is essentially implementing the same steps but at the transistor level.
Lots of mousetraps
That's sort of the point. The operative word is "just." In reality, it adds a huge subsystem that needs more resources than the overall system does. Rather than solve the underlying problem directly, they introduce (more interesting) problems to solve transitively via these complexities.
Facebook and Instagram to Unleash AI-Generated 'Users' No One Asked For
a) There is no evidence that Apple is sharing messages with third parties.

b) You are simply confirming my point which is that when you visit a website it is able to tie you to an consistent identifier through the APIs your browser supports.
Large concept models are really exciting
It's amazing this is still an opinion in 2025. I now ask devs how they use AI as part of their workflows when I interview. It's a standard skill I expect my guys to have.
Review: Planecrash
So you think there a conspiracy and that TikTok for iOS has been able to break out of its sandbox and read your text messages?

This would have made news if so.
ironically it doesn't work for HN main page
California grid ran on 100% renewables for a record 98 days
It is a very low grade nutrition that produces a lot of unhealthy results. Not really a benefit.
It’s an unholy combination of C, C++, and Microsoft extensions at worst. But apart possibly from some COM-related DLLs, the spirit is clearly C, and C++ exceptions are generally not expected. (There may be use of SEH in some parts.)

Of course, you can write C++ without exception safety too, but “C++ as a better C” and exception-safe C++ are effectively like two different languages.
Production Twitter on One Machine? 100Gbps NICs and NVMe Are Fast
That’s the domain you’d have saved, then. You can also save multiple domains on a credential.
I think I'm on safe ground saying printing the names of criminal suspects is a longstanding norm in American print journalism.
I haven't looked at this lately and so don't have a specific recommendation, but there are small libraries for helping iOS learn how to add PWAs using the standard Share → Add to Home Screen mechanism.

https://github.com/khmyznikov/pwa-install (Try on device: https://khmyznikov.com/pwa-install/)
"When it's running" also means when it runs in the background, and apps can wake themselves up any time they want when you allow them to send you notifications.
I don’t have anything against them. I was born and raised in one. I just find it ironic that someone would fail to see this parallel.
So just like in FL, they’ll abandon the state. And insurance for everyone will skyrocket as those few insurers who do decide to stay have to raise rates through the roof in order to avoid bankruptcy.
For what it's worth, and obviously I could have been clearer about this: what's interesting about that link is the description of Threema's design, not the specific vulnerabilities the team found.
The same can be said about most large scale have man engineering efforts.

https://en.m.wikipedia.org/wiki/1975_Banqiao_Dam_failure
MiSTER is going strong and the recent release of the excellent-but-confusingly-named MiSTER Pi [1] board has brought the cost of entry down considerably. After I do some more SD card shuffling and verify game compatibility I plan on selling my N64 and Saturn and using OEM controllers with my MiSTER Pi. Unfortunately the Altera Cyclone FPGA in it doesn't have the horsepower to run anything beyond fifth-gen systems so a new platform would be required for the Dreamcast, Gamecube, and PS2. The common refrain from FPGA enthusiasts regarding these systems is that because the hardware has many more layers of abstraction they're less dependent on cycle-accurate timing than older consoles so the juice might not be worth the squeeze as far as building HDL cores for them is concerned.

[1] https://retroremake.co/pages/store
I think most tech folks struggle with it because they treat LLMs as computer programs, and their experience is that SW should be extremely reliable - imagine using a calculator that was wrong 5% of the time - no one would accept that!

Instead, think of an LLM as the equivalent of giving a human a menial task. You know that they're not 100% reliable, and so you give them only tasks that you can quickly verify and correct.

Abstract that out a bit further, and realize that most managers don't expect their reports to be 100% reliable.

Don't use LLMs where accuracy is paramount. Use it to automate away tedious stuff. Examples for me:

Cleaning up speech recognition. I use a traditional voice recognition tool to transcribe, and then have GPT clean it up. I've tried voice recognition tools for dictation on and off for over a decade, and always gave up because even a 95% accuracy is a pain to clean up. But now, I route the output to GPT automatically. It still has issues, but I now often go paragraphs before I have to correct anything. For personal notes, I mostly don't even bother checking its accuracy - I do it only when dictating things others will look at.

And then add embellishments to that. I was dictating out a recipe I needed to send to someone. I told GPT up front to write any number that appears next to an ingredient as a numeral (i.e. 3 instead of "three"). Did a great job - didn't need to correct anything.

And then there are always the "I could do this myself but I didn't have time so I gave it to GPT" category. I was giving a presentation that involved graphs (nodes, edges, etc). I was on a tight deadline and didn't want to figure out how to draw graphs. So I made a tabular representation of my graph, gave it to GPT, and asked it to write graphviz code to make that graph. It did it perfectly (correct nodes and edges, too!)

Sure, if I had time, I'd go learn graphviz myself. But I wouldn't have. The chances I'll need graphviz again in the next few years is virtually 0.

I've actually used LLMs to do quick reformatting of data a few times. You just have to be careful that you can verify the output quickly. If it's a long table, then don't use LLMs for this.

Another example: I have a custom note taking tool. It's just for me. For convenience, I also made an HTML export. Wouldn't it be great if it automatically made alt text for each image I have in my notes? I would just need to send it to the LLM and get the text. It's fractions of a cent per image! The current services are a lot more accurate at image recognition than I need them to be for this purpose!

Oh, and then of course, having it write Bash scripts and CSS for me :-) (not a frontend developer - I've learned CSS in the past, but it's quicker to verify whatever it throws at me than Google it).

Any time you have a task and lament "Oh, this is likely easy, but I just don't have the time" consider how you could make an LLM do it.
The problems with that skill is that:

* Most existing LLM interfaces are very bad at editing history, instead focusing entirely on appending to history. You can sort of ignore this for one-shot, and this can be properly fixed with additional custom tools, but ...

* By the time you refine your input enough to patch over all the errors in the LLM's output for your sensible input, you're bigger than the LLM can actually handle (much smaller than the alleged context window), so it starts randomly ignoring significant chunks of what you wrote (unlike context-window problems, the ignored parts can be anywhere in the input).
That article describes the exact behaviour you want from the AI crawlers. If you let them know they’re rate limited they’ll just change IP or user agent.
Just curious, but what AI related skills do you expect them to have?
Indeed. Very similar to the grace + hopper, grace + dual hopper, and grace + dual blackwell.
Building Game Prototypes with LÖVE
I can't say about gaming, but a huge chunk of popular apps out there are PWAs with a native wrapper. If built well people aren't even going to notice.
Since TODAY GribStream.com now also leverages the NOAA Rapid Refresh (RAP) model https://rapidrefresh.noaa.gov/. It enables SkewT LogP charting for which I added a python example on the github repo. I hope you will find it useful.

You can check the example here: https://github.com/GribStream/python-client
> A complex initiative requires picking the right tech that gives you a good benefit/cost ratio.

That choice should never be a one way door, you don't control your customers or the future, it is the frame problem.

The idea is to be able to iterate and adapt, not get things perfect from the start.

It is fine and expected that one will use past experience as a starting point, but you always have to reflect and check your assumptions along the way.

It is a complicated topic ruled by nuances and contexts, but if you cannot pivot away from your initial assumptions over time, that lets you know you are leaking implemention details.

While time is limited and abstractions have a real cost, you need to apply them where they make sense.

Some, like just breaking code onto two files in the same directory are fairly low cost, others are much more expensive.

For several years I was jumping in to save failed cloud migrations.

Whenever tech was the 'blocker' it was because of a myth that there was only one way to do things.

But lets say you are writing machine code for Apple silicon? Do you really think those registers are concrete? They aren't. They are a facade hiding 100s behind a legacy interface.

Vendor mitigation important and often neglected and also results in people producing balls of mud.

But there are a lot of distributed monoliths pretending to be micro services out there. And we had decades of people producing fragile enterprise service buses that were built because people wanted to future proof their systems.

The sizing of components and balancing integration and disintegration drivers is incredibly hard, you will never get it right.

You have to leave options open, no matter if that is through abstractions or keeping biz logic centralized to assist in a easy rewrite of context boundaries that arise from scale or changing needs.

Obviously choices have benefits and costs, but for most needs you can keep options open, if not it is probably best to reevaluate the reason for choosing a solution.

Obviously there are predatory vendors like Oracle that base their entire income on captive customers, but that relates to the vendor mitigation above.

I think the US federal government de-risking guide is a good overview of that topic. Microsoft is a strong driver for this BTW.

https://guides.18f.gov/derisking-government-tech/
Great write up! Unfortunately, I think this article accurately reflects how we've made little progress on the most important aspects of LLM hype and use: the social ones.

A small number of people with lots of power are essentially deciding to go all in on this technology presumably because significant gains will mean the long term reduction of human labor needs, and thus human labor power. As the article mentions, this also comes at huge expenditure and environmental impact, which is already a very important domain in crisis that we've neglected. The whole thing especially becomes laughable when you consider that many people are still using these tools to perform tasks that could be preformed with a margin of more effort using existing deterministic tools. Instead we are now opting for a computationally more expensive solution that has a higher margin of error.

I get that making technical progress in this area is interesting, but I really think the lower level workers and researchers exploring the space need to be more emphatic about thinking about socioeconomic impact. Some will argue that this is analogous to any other technological change and markets will adjust to account for new tool use, but I am not so sure about this one. If the technology is really as groundbreaking as everyone wants us to believe then logically we might be facing a situation that isn't as easy to adapt to, and I guarantee those with power will not "give a little back" to the disenfranchised masses out of the goodness of their hearts.

This doesn't even raise all the problems these tools create when it comes to establishing coherent viewpoints and truth in ostensibly democratic societies, which is another massive can of worms.
That can still happen today.

One of my Cambridge professors was Mr. Phil Woodland, an international authority on automatic speech recognition. When I asked him why he had no Ph.D., he shrugged and said he was too busy with his research work, so he "never found the time". Meanwhile, he got promoted to Professor [1].

Another noteworthy fact about Oxford and Cambridge that people from elsewhere may not realize is that they award an M.A. "for free" to Bachelor students after 5 years have passed, so you effectively get two degrees for the price of one.

[1] https://www.eng.cam.ac.uk/profiles/pw117
My first thought is yes yes yes, finally it's once against just like the good ol' days of bleem! emulator!

My second thought is this is what you get when fighting with Nintendo's lawyers alone doesn't give enough kick, and want to pull in Sony too
Not to mention nearly every Intel and AMD desktop that has a small iGPU on board, even for the chips not marketed that way.
Perhaps plain `curl_chrome` could use the latest available `curl_chromeNNN`
> why can't I tell one to buy chocolates and send them to my wife?

I'm pretty sure that's been possible for a while. There was an example where Claude's computer use feature ordered pizza for the dev team through DoorDash: https://x.com/alexalbert__/status/1848777260503077146?lang=e...

I don't think the released version of the feature can do it, but it should be possible with today's tech.
Some amount of LLM gullibility may be needed. Let's say I have a RAG use case for internal documents about how my business works. I need the LLM to accept what I'm telling it about my business as the truth without questioning it. If I got responses like "this return policy is not correct", LLMs would fail at my use case.
I just shoved the whole .webvtt file in the header of a audio Response from the server so that I don't have to implement another API just for subtitles [1][2]

1. While building https://gitpodcast.com

2. Code snip: https://github.com/BandarLabs/gitpodcast/blob/main/backend/a...
As someone who has written a free book on the topic, I don't disagree:-) https://s3.amazonaws.com/bitmasons.com/packagingbook.html
this article is based on misunderstanding of many things.

llms have already shown value and usage in genomics, as did previous sequence models.
It's not just "you can't do DNS compression", or "you probably can't do general-case string comparisons". It's much more fundamentally that anything you "detect" in eBPF code, even in the extremely rare cases where it's offloaded into NIC chipset, has to get plugged right back into the kernel to do anything with that data. You can't write a general-purpose eBPF program; eBPF is just an telemetry and packet processing offload.

That eBPF firewall is a perfect example of what I'm talking about. It relies not just on the kernel but on a cooperating userland process to do all the "interesting" bits.
I love your breadth-first approach of having an outline at the top.
Related to this but little theoretical question - If you add an intelligent predictor of market which wins over other consistently by X% - then the market will start using that information and wouldn't that make our intelligent predictor lose it's edge?

More simply what i mean to ask is -> the moment market knows about your advantage, shouldn't you lose it because everyone else will use that information to balance the market?
Currently it is never updated again with new info, this is one of the things at the top of my list to implement
However, the medallion fund has averaged 66% for 30 years before fees. Analyzed naively, that would be $4T from $1M - but it's not, because in order to keep it working, they have to cap the size. Many strategies only work when you don't affect the market too much. So for the rare continually successful, market beating funds, it's probably better to think of them as generating something like a fixed dollar return per year. So they have a very effective money machine, but it's minting billions, not trillions.
Not sure why that would be true. Slow UMA (like the vast majority of Intel and AMD desktop chips with 128 bit wide memory) hurts GPU performance.

However the M4 Pro has 256 bits wide, M4 max 512 bits wide, and M2 Ultra has 1024 bits wide. GPU workloads are latency tolerant and embarrassingly parallel, don't see how allowing a CPU to make random accesses is going to hurt the GPU much.
Running location triggers an icon in the UI which puts it in a list of apps that have run location recently. An app abusing this in the background will eventually cause the operating system to ask you “hey, are you okay with this?” alongside a map of your current location as your phone sees it.
Done with Alpaca API, not trading fees

I only trade stocks that support fractional shares
A Deep Dive into Bitcoin and Web3
Right? It's generic, nothing far from the stereotypes; no specific information. I also found it repetitive at the end.
Hi there! Yes, I will switch to a more distinctive icon in the future once I can afford to hire a new designer.

Multiplayer was quoting the correct reason. I also exeplained more about the timeline here: https://github.com/nuttyartist/notes/issues/690#issuecomment...

Tldr: The FOSS version earned a stable revenue through Google Ads placed on the website, since the website ranked high on Google searches. Two years ago, that changed since the website got de-ranked, so I created a different, proprietary version of the app based on the FOSS version but with a totally revamped block editor that I wrote from scratch - that I worked on full-time for a whole 1 year.
Hey ttul, can you try again? I fixed the issue, hit my API limit with my account on mailgun
Well if that last step is what made it feel honest, many of these tools are basically a way to bypass that. I think it crosses into dishonesty when you include an AI cover letter that says you want the job/would be good at it but you haven’t even looked at the post or evaluated the company. For example if you don’t actually want the job (have seen this).
Punishing people with more work doesn’t make sense in a well run organization. Work is continuous and more work only affects the backlog, not the actual developer’s life or experience.
We'll have two entirely separate (dead) internets! One for real hosts who will only get machine users, and one for real users who only get machine content!

Wait, that seems disturbingly conceivable with the way things are going right now. *shudder*
What a hilariously absurd statement. You might want to actually try it.
Going to follow along to see how the results look in the months to come.

I've been working on the same concept for the past 2y now and have our performance results here:
https://trend.fi/performance