skysight-inc/HackerNews huggingface dataset:
> If it was a threat vector, it clearly wasn't a very big issue.

By the same token, patching the apps to use the new API is not a very big issue either. Or is it? Why?

If you have the sources, neither is a problem. If you do not have sources, both are problem. A matter of fact is, that users are going to use apps that they do not have sources for, and can neither audit, nor update the apps.

> If they wanted to not break existing apps, simply intercept attempts to share screens or inputs, and pop up a dialog box asking the user for consent?

Because there was no API before; there were hacks. Some of them worked only due to circumstances of how the given functionality was implemented, but spec-wise, it wasn't guaranteed at all.

Now there are APIs. Just like there is a virtual memory or filesystem permissions. These weren't given years ago either. They also "broke" apps.

> major linux distributions were already pushing it.

RHEL8 is Wayland-default on non-Nvidia GPUs. Old relase of a freaking RHEL, which itself moves as molases.

> I'd be much more forgiving if the wayland devs said 'hey guys, we're working on a new display server but it's very experimental and no one should use it unless they want to help us work out the kinks'.

You missed that phase by some 10 years or so.

> Instead, it was 'this is the future, x11 is abandonware'

That's how it is. If linux wants to stay relevant and not became another Amiga, that's how it is going to be.
"The African-American plague killed a third of Europe"
I'm not a professional in VFX, but I work in television and do a lot of VFX/3D work on the side. The quality isn't amazing, but it looks like this could be the start of a Midjourney-tier VFX/3D LLM, which would be awesome. For me, this would help bridge the gap between having to use/find premade assets and building what I want.

For context, building from scratch in a 3D pipeline requires you to wear a lot of different hats (modeling, materials, lighting, framing, animating, ect). It costs a lot of time to get to not only learn these hats but also use them together. The individual complexity of those skill sets makes it difficult to experiment and play around, which is how people learn with software.

The shortcut is using premade assets or addons. For instance, being able to use the Source game assets in Source Filmmaker combined with SFM using a familiar game engine makes it easy to build an intuition with the workflow. This makes Source Filmmaker accessible and its why theres so much content out there made with it. So if you have gaps in your skillset or need to save time, you'll buy/use premade assets. This comes at a cost of control, but that's always been the tradeoff between building what you want and building with what you have.

Just like GPT and DALL-E built a bridge between building what you want and building with what you have, a high fidelity GPT for the 3D pipeline would make that world so much more accessible and would bring the kind of attention NLE video editing got in the post-Youtube world. If I could describe in text and/or generate an image of a scene I want and have a GPT create the objects, model them, generate textures, and place them in the scene, I could suddenly just open blender, describe a scene, and just experimenting with shooting in it, as if I was playing in a sandbox FPS game.

I'm not sure if MeshGPT is the ChatGPT of the 3D pipeline, but I do think this is kind of content generation is the conduit for the DALL-E of video that so many people are terrified and/or excited for.
If anyone reading this hasn’t heard this before, I encourage you to read the do’s/dont’s of protobufs for some other good best practices.

https://protobuf.dev/programming-guides/dos-donts/
https://en.wikipedia.org/wiki/Prometheus ?
>Hypotheticals are irrelevant.

You don't get to decide what I think is relevant.

I dont think the current system in Sweden is relevant to the question of if tokai think Judges should be able to boycott cases.

The fact that the current system has existed for 75 years doesn't even mean anything about the postnord case (which hasnt been decided) or if the Swedish government is required to ensure equal accesses to government services or law.
What became universal in the industry is an item on the checklist saying that you have safety checks to prevent this. How seriously that item is taken, i suspect, varies quite a bit.

In my experience, you aim for multiple extremely simple checks, with minimal logic and minimal calculation, so you can have confidence they won't have surprising behaviour in an unusual situation like this.

The classic example is an order count limit - initialise a counter to some value at startup, and every time the machine sends an order, try to decrement it. When it hits zero, it can't send orders any more. Just throw an exception or return early or something. You display the value of the counter to human operators, and give them a button which resets it to the initial value. In normal operation, you are sending orders at a steady trickle, and humans will have to press the button every now and then. If something goes insanely wrong, as here, the counter will run down quickly, and then the humans hopefully won't push the button, because something is obviously wrong. It's a very crude safety, but it is a simple one.

Another is a limit on message rate. You could use a token bucket filter. Does not affect normal operation, but stops a machine which is spraying out excessive orders. You could have it so that if the bucket runs out, it turns off until a human explicitly turns it back on.

You have limits on net position too, to stop you running up huge positions in anything, but those are higher-level, and not quite the same kind of last-ditch safety check.

I don't really know that either of these would have helped in Knight Capital's situation, because the precise mechanics of the "power peg" aren't clear. It sounds like a kind of explicitly-managed iceberg order, which these safeties would have caught. But another writeup [1] says it was a testing tool, not intended to be used on a real exchange at all, in which case who knows.

[1] https://www.henricodolfing.com/2019/06/project-failure-case-...
The problem with solar and wind is that you also need to build sufficient storage infra for those days when it's cloudy and not windy.
I can't wait to find old surplus custom ARM silicon from this period at the recycler or on eBay.

As a kid I always wanted one of those yellow google search appliances and now you can find them everywhere being used as like lawn ornaments.
Ask HN: What are your experiences with Apple Card?
General inquiry about how people are finding this new card service. Do people use it for more than just purchasing Apple products for the 3% cash back? Can Android users load the card into their digital wallets (seems you can't - yikes). Does anyone regret getting the card?
Yep, I would occasionally spend a week in Colorado in August which is a nice respite, so it's a good suggestion and reminder.

And you're right about the surgery, though sadly it's not necessarily a one-time thing, but a part that could require future surgeries to maintain (though the hope is that current materials will mean it will last decades). Nevertheless I try and tell myself what you said, that it's a few weeks or months of life to recover and then on with it. The what ifs are indeed the worst, but both people I've talked to online and in my life have gone through with it much success. A therapist would say to focus on the good outcomes rather than the negative, and the statistics really do bare that out too.

Anyway, I truly appreciate the kind words.
Show HN: AI driven website roasts
I really liked ThreadX when I was working with it a while ago. Calling it an "operating system" is charitable in the sense that it's an interrupt service routine and a bunch of functions to handle 'creating threads' and managing memory allocations.

It was super light weight and quite nice to get stuff done. You call tx_thread_create or some such and then tx_malloc and so on and then they have tx queues and semaphores and mutexes and so on.

Neat to see it's still living on.

In our case we were doing real-time power/fan/thermal control loops so we needed control over when certain actions were happening and needed to be able to guarantee that we could sense a problem and then (within X ticks) issue commands to respond, or make the system safe to prevent damage.
Thanks. Forgot this version. There's also a "slightly" different version of "we exist in a different timeframe / timespeed / dimension."

Star Trek TNG "Time's Array Part 1/2" had the alternative overlaid dimension variation.

TNG "Timescape" had the alternate timeframe / timespeed with the Warbird / Enterprise existing in a different time than the runabout, as well as fruit that rapid aged / decomposed relative to the crew members (and the fun issue of accidentally walking into a bubble of AGE+50yrs).
This is sort of a distinction without a difference. It's an autoregressive sequence model; the distinction is how you're encoding data into (and out of) a sequence of tokens.

LLMs are autoregressive sequence models where the "role" of the graph convolutional encoder here is filled by a BPE tokenizer (also a learned model, just a much simpler one than the model used here). That this works implies that you can probably port this idea to other domains by designing clever codecs which map their feature space into discrete token sequences, similarly.

(Everything is feature engineering if you squint hard enough.)
This is the first time the FDA (any part) has allowed a drug for the indication of longevity / lifespan. That's a big deal.
As they say, the devil is in the details. I'm interested in reading the actual clinical trial whenever it gets published. In particular I'm curious about this so-called "accelerated aging model", and whether this drug actually extended lifespans or are claims based solely on owner and vet reported health observations...

> Our interventional studies with LOY-001 showed that the drug improved clinically-relevant aging parameters. We assessed these in laboratory studies using a dog model that represents accelerated aging. We then correlated those results with quality of life scores in the observational study, as independently measured by dog owners, and health outcomes as measured by veterinarians. This was key to show that the biological benefits of the drug are linked to clinically relevant outcomes.
Azure has a much better approach to organizing things on their website without inventing meaningless words and abbreviations like EC2.
The "victim" class has become a political and social weapon. It's label can be used to shame and force others into making accommodations, even if it is to the detriment of others. Coupled with righteousness indignation it has become a potent weapon to silence critics.
> Even though yt-dlp is probably actually what you want for a tool to download video from YouTube.

Is it though? My guess would be that a web app - one that doesn’t require visiting a github project page or downloading anything - would be more user friendly and more appealing for most users. As of now that seems to be the top result.
At that point why do we even need Google? Any search will lead you to the same circle of mega-sites. If only sites that are already popular get exposure that's not a search engine, that's a directory. May as well go back to "Jerry & David's Guide to the World Wide Web"
I’m not sure how safe networking and similar folk are either.

You’ll still need experts who understand the generated network code, and experts who can untangle the generated code, but not so many.

Code will be a tool used by non-experts; fewer special-case experts will be needed. Where we’ll be when the experts die out, I’m not sure.
That's a great way of looking at it, and touches on why I have the most fond memories of the most difficult of trips with the family. The challenges unite to find a shared purpose and a shared identity that persists long after the trip is over.
You can use quite a lot of STL even with -fno-exceptions. Things that you probably need to ditch are:

std::vector

std::list

std::map

std::unordered_map

std::set

std::unordered_set

std::sort

std::transform

std::merge

std::string

std::regex

std::swap

std::function

std::stable_partition

But there are much more than that in STL.
Hey! That’s right, Cap is still under active development, working towards launch of v1.
> Should we expect this trend to continue, or will we ("educated" "sophisticated" people in Western society) return to celebrating the powerful and the successful like most other societies before us?

This feels like a false dychotomy. There are various possibilities, not just two. I'm not in favor of celebrating the powerful and successful as many of them turned out to be sociopaths. I prefer to celebrate people of science, who through their talent and hard work advance our civilization, including victims, the powerful, and all the rest of us.
Sure they will, they'll just be trying to tinker with firewalld settings on Ubuntu servers, or ufw on RHEL.
Synthetic imagery sets new bar in AI training efficiency
Not nefarious. Its incentives cause it to overvalue safety relative to avoidable mortality and morbidity.

You could do worse than starting here:
https://www.propublica.org/article/heres-why-rapid-covid-tes...
Two major pillars of NXP's sales strategy are their security architecture and integration with other NXP devices (primarily connectivity ICs since the Marvell Wi-fi acquisition).

They are typically more expensive than competitors (Infineon, TI, ST, etc). This is due to their strategy to only compete in markets where they believe they can command a healthy profit margin.

Going to be a difficult strategy to maintain in a few years when there are identical products from China for 1/2 the cost...
This is fantastic. What a blast from the past!
So, 70% accuracy with 100% confidence?
SIMD is pretty intuitive if you’ve used deep learning libraries, NumPy, array based or even functional languages
> It would be good if you could select a list of sites that you trust, so the sites they link to (and the sites those link to and so on) get boosted in your own personal search results.

Kagi _kinda_ supports this with "Personalized Results", you can see the most popular personalizations at [1]. To my knowledge, it doesn't do the "links to sites you trust" piece, but is still really useful.

Note: I work with Kagi in a part-time role.

[1] https://kagi.com/stats?stat=leaderboard
> Put all your data in "the cloud", give up control, and be subjected to the whims of big tech.

I try but I wish I could make more people understand the implications of this. If your data is in any "cloud", it is entirely at the whim of those companies whether you can lose access permanently at any moment.

For any data that you actually care to be able to access in the future with some reasonable assurance, you must have either a local copy in your control or an enterprise-level support contract with SLAs with the cloud provider. The latter is expensive so for personal use of personal data, local copy is the only practical answer.
Some might not see how much work it was to maintain xorg server
I don't think he gets the point of a hype cycle. The point is to overinflate the value of a business, to suck up the dollars by the idiotic investors rushing to be part of the next Google, take all the cash you can as quickly as you can, and either exit, or shut down the business, after having pocketed millions/billions. The more and faster you grow, the more you can pocket. Whether this is sustainable or not is beside the point. Actually, if it seems sustainable, that's kind of bad for business. You'll get more money from the inept VCs if you tell them you'll have insane, impossible growth.

Yes, AI startups are doomed. So what? Founders can make millions with a doomed startup.
I thought Microsoft bought the threadX company very recently. Interesting change of strategy?
From the article:

> A leaked document has talking points for the president of the United Nations climate conference, who is an oil executive in the United Arab Emirates, to advance oil and gas deals.
I’d love to know more. Anything you can point to?
> you don’t need to be economic illiterate to think something fishy will happen

It’s not the city’s job to make good things illegal because they are too good to pencil out.

But by “economic illiteracy”, I was referring to tenant groups’ reasons for opposing unsubsidized housing. Excuses such as that San Francisco had increased vacancies during the pandemic and thus not need any more housing. Or that San Francisco already met its RHNA housing quota for 2014-2022 (which was way too low since it was calculated based on outdated population growth trends rather than rents). Or denial that housing construction has any affect on rent. These are not fringe positions; these are the canon of the self-proclaimed “progressive” faction in San Francisco (see Supervisor Peskin’s statements in https://sfgov.legistar.com/LegislationDetail.aspx?ID=6412806... and https://twitter.com/_fruchtose/status/1729280621313511602 and basically any article on 48hills.org). The set of policies they support are basically to reduce for-profit apartment development by increasing neighbor veto points, ask for increased funding for favored nonprofits, increase tenant protections, and watch as rents rise.
a mistake is an accident... this probably required more effort than actually finding women to speak at the conference... it was willful and harmful
I was just talking normal overwintering. I assume cold storage would need feeding, but I don't have any large scale commercial experience.
Offloading the use of your brain to proprietary and legally murky third party services that can deny you access for any reason whatsoever seems shortsided. What happens when you don't have access to these services and you find out you don't actually know how to do most of what you need to do?
Hah, I formatted by girlfriend's thesis in Latex, I was so annoyed at the whole process that I did mine in MS Word.
The impressive part of AIs like ChatGPT is their natural language understanding, they can infer things that aren't explicitly said and ask follow up questions if needed. They aren't powerful enough to write complex programs yet, though.
This is certainly the reason for OpenAI's codename.
I would not allow any company's AI product near my company's private info.
Fortran compilers can assume that (many) dummy arguments to a particular procedure reference do not alias each other, true. But there are many other ways in which aliasing can happen in a conforming Fortran program.
Posted in a prior thread, but here's a trade-by-trade recap

Original Thread: https://news.ycombinator.com/item?id=37459495
---

If you want to see how it looked like from the tick scale, take a look here: http://www.nanex.net/aqck2/3522.html
Ps. Anyone know of any other sites / places that does comparable level of research that's open to the public?
Even if it doesn't work for humans, I'm sure this company will earn a lot of money from people like OP who will be buying it "for my dog, wink wink" for 10+ years before it's proven not to work for humans.
Restricting AI tools in development work is pointless. However, the person using them should still be smarter than those tools. They should use the tools to boost their own efficiency.

In ask people to describe me the code they are going to write verbally. Or reason through an algorithm verbally. Depending on the role, I sometimes start with FizzBuzz, with a spoken answer.

They can use a notepad. They can take time to think. But they will get "why" questions and need to understand the code or constructs they suggest.

This feels safe from ChatGPT, at least for the moment.
So many developers are fungible, it makes sense for everyone involved.
In my opinion the root cause is pretty clear: they had a network protocol update that was not backwards compatible and didn’t verify the runtime versions or have versioning.

Everything else isn’t really core to the issue [even that the update script silently failed].
TLDR: The underlying basis is the same for everyone:

# the whole internet to scrape

# the largest amount of gpu compute you have ever seen

# more or less open source fundamentals

thus "ai" will become a commodity, unless you have specific non-public useful data.
You could just use CUDA, which is C++ designed for GPUs, the ultimate SIMD machine of today.

Or ROCm (basically CUDA but for AMD).

I always was a fan of Microsoft's C++AMP though. I thought that was easiest to get into. Too bad it never stuck though.
Good search requires language models. GPT is a really good language model.
Of course, I ask because of my own annoying experience just now.

Last week I ordered a new macbook, one of the higher end models. At checkout there is an offer for the Apple Card, and so I do it for the 3% cash back. Surprisingly the credit limit given was _less_ than the order purchase amount, so the Apple store ended up canceling the order a week later.

Attempts to raise the limit w/ Goldman Sachs (who I understand have never done consumer credit cards until now) hit a deadend as the card is too new. The limit on the card is surprisingly low, I have other cards (albeit with history) >10x the Apple Card's limit. It seems odd to receive a limit of ~2500 from a bank when you present them with a tech-industry salary + high credit score.
People make a lot of claims. Lots of people once thought the world was flat. Science has little to do with what people say.
Author concludes the only moats for an AI start-up are captured compute and proprietary data. I'm disagreeing.

Good execution remains differentiated. It just requires continuous iteration, evolution and improvement.

If you build an MVP over a weekend and then pivot 100% of your efforts to fundraising and marketing, as has been the trend over the past decade, yes, you're screwed. You're building dollar apps for another App Store.

Most of the arguments the author levels would have worked against the first waves of computerization, digitisation and the emergence of the Internet, in some cases more powerfully. Yet the prediction didn't hold. Capex and IP weren't sole, or even strong, predictors of new-entrant success. For Exhibit A to the first part, see Softbank.
Ben Nadel: The RegEx of Everyday Things
I can't help but chuckle a little bit when I'm out on the NYC streets with my dog and we pass a great dane - such great temperament for small apartments, such a wildly awkward size for small apartments
I don't think domain expertise is a competitive bottleneck. These LLMs started with the sum total of human knowledge in their training data, but (currently) lack the ability to synthesize that knowledge, to reason and plan to achieve goals. GitHub Copilot and ChatGPT-4 have roughly the same breadth of knowledge, but Copilot can only make superficial suggestions, while ChatGPT-4 is smart enough to write basically any toy script as long as it fits in a page and doesn't require inventing anything new.

The difference between the average bootcamp graduate and the average engineer isn't intelligence, it's knowledge. Once AI makes bootcamp graduates obsolete, I see no reason why engineers in general won't be obsolete too.
This is why I've never really understood the focus on optimizing typing speed in IDEs with shortcuts and similar things. It just isn't a bottleneck I've ever faced. I do understand the desire to customize one's own tools, and optimize things for its own sake ... but I don't get the thought process that proclaims this as some source of meaningful productivity improvement.