I really can't get over the way almost every piece of consumer technology/software has gotten worse in the last half decade. These companies are killing every goose they can get their hands on because they are so convinced there is some golden goose out there that will be worth more than all those regular geese combined.
People in this thread are massively underestimating the level of financial illiteracy in the general population.
We've had multiple people try to convince us to set up bank accounts for our kids, so that they could accumulate interest over 18 years.
More that tried to convince me to gamble on random pump and dump shitcoins.
More still that talked about "investing" in random collectables like Funko Pops or Pokemon cards - they're not a bubble, Logan Paul told me so!
You could replace the AI with a piece of paper that says "set aside 10% of your income and invest it in an ETF" and it would outperform the financial "advice" that people receive on a daily basis.
The Internet in the early 2000s felt a little more special as compared to today, when 99.999 % of content is locked in a handful of walled gardens. I mean sure everything we had then is still possible but let’s be honest everything about the web is fine tuned to deliver ads to our eyeballs, browsers, operating systems and even protocols are being designed with ad delivery in mind. Even the privacy friendly browsers just exist to serve ads when I think about it. Kind of sad really, but I guess you could be happy as it’s so big now and there’s so much to do. Just makes you wonder what stuff would thrive if ads didn’t exist. As of now every niche thing that gets successful will be invariably pulled into the ad ecosystem as it’s very hard to say no to money.
RSS wasn’t in the interest of the big platforms as it’s decentralized and there’s no good way to deliver ads through it, simple as that.
I'm about to throw away multiple months of LLM generated code for one of my side projects. I was really careful writing design specs and it wasn't even a new code base the LLM worked on, but still after several months of AI changes I feel my code degraded more and more into a subtle mess. Hard to explain, each individual change looked good and logical and on the surface the codebase looks fine, but looking at the whole picture everything is subtly wrong in multiple ways. The same goes for where I used AI for existing commercial code bases. I would love to have AI write production ready software for me, but it's just not there yet, there simply are things that good programmers and architects do that cannot be captured by the training loop of current generation LLMs.
I notice the same pattern when using LLMs to write longer text like reports or scientific papers, individually each section they write makes sense but overall the whole document feels off in a hard to describe way. I think it's where you can see the difference between human intelligence and whatever it is LLMs have, it's not the same thing. We are much slower and less able on the small scale but seems we can do some higher level reasoning that is still impossible for LLMs. That always becomes clear when you point an LLM at an obvious flaw it produced and it goes "You are absolutely right!" as if it's obvious in hindsight but when running multiple "Please look for issues" iterations it would never have spotted the issue by itself.
That said I think it will be absolutely fine writing a simple CRUD app for you e.g. using some popular JS framework, Tailwind for styling and a regular ORM, there's more than enough training data available for these things. But then again such software could be purchased before already e.g. as a SaaS template, I don't think LLMs are so revolutionary here, they just replace the template (but to be honest a good hand-written SaaS boilerplate is probably still better than a vibe coded one).
Seriously, that's all it was. Just Ian alone proposed and rejected a half dozen of his own different approaches to generics. Finally a language + implementation plan came together that people all liked.
This is not at the top as it is actively flagged by people that can't psychologically cope with the advances of AI. Hacker News is no longer a web site of an elite.
I don't think it's a bad way to benchmark new models, I just find it concerning that the author implies that "pelican on a bicycle" has been exhausted.
At the risk of making overly broad, unfalsifiable claims I think multi-year exposure to AI content has dramatically raised our expectations for speed and volume but lowered them for quality.
We see a very janky pelican and declare the problem solved.
Google’s obviously fake excuse for killing their RSS reader (declining usage) was especially maddening at the time because they were pushing Google+ - which _nobody_ used.
Great way to tank a brand. Part of BMW's value is/was the expectation of an upper middle class snob driving it, but having your car force ads on you is something people wouldn't even expect from a Kia Soul leased off a used lot.
In a way the most remarkable thing about this is that it isn't even at the top of the HN homepage. Even if this is a step up from what we've seen before, we're no longer astonished by the idea that AI can make significant advances in mathematics and computer science.
I know that we're discouraged from meta-comments, but what is going on in this thread? It's a nearly 800-page book about the art of programming. A huge amount of work on a topic that should be dear to our hearts. News for hackers, right?
But somehow, the discussion has three themes. It's 50+ comments of "I don't like the first sentence of the marketing copy", "I don't like the tool the author is using", and "what would happen if we train an LLM on this book?". Has anyone read the sample chapter? Did you like it? Anyone here owns volume 1 and has opinions about that?
Brian Gilbert, 56, of San Jose, Calif., former Senior Manager of Special Operations for eBay’s Global Security Team, was sentenced to time served, one year of supervised release with the special condition that he have no contact with either of the victims in the case and a $20,000 fine
Jim Baugh, 47, of San Jose, Calif., eBay’s former Senior Director of Safety and Security, was sentenced to 57 months in prison
David Harville, 50, of Las Vegas, Nev., former Director of Global Resiliency, was sentenced to 24 months in prison
Stephanie Popp, 34, of Louisville, Ky., former Senior Manager of Global Intelligence, was sentenced to 12 months in prison
Philip Cooke, 56, of San Jose, Calif., a former Senior Manager of Security Operations, was sentenced to 18 months in prison and 12 months of home confinement
Stephanie Stockwell, 28, of Redwood City, Calif., a former Manager of Global Intelligence, was sentenced to one year in home confinement
Veronica Zea, 28, of San Jose, Calif., a contract intelligence analyst, was sentenced to one year in home confinement
This is such a bikeshedding debate. While you don't recommend it, projects with Tailwind work. Over years. You can onboard new developers to it, able to contribute productively immediately. Likewise, you can pick up work after months or years and don't have to remember or rediscover how your styling layer works.
The conventions and class names come really naturally fast, and you can always look it up. It's just not as a big of a problem people make it.
But the most ridiculous part of the article I found the cascade complaint:
<p class="text-red-500 text-green-500">I am some text</p>
Yes, this does not work. Why should it?! There is not a single use case where this is a good idea! In classic CSS, you might want to override something based on modifier classes, but that is just not a thing with Tailwind! If you end up programmatically layering class names, you're looking at a code smell. Instead, you want to use attribute or state modifiers, like `aria-hidden:opacity-0`.
Some people here think Wikimedia Foundation's mission is to keep Wikipedia up. That's a subset of their mission. I attribute nearly all of the blame to WMF, because their donation ads are quite deceptive.
The actual, public mission of Wikimedia Foundation:
> The mission of the Wikimedia Foundation is to empower and engage people around the world to collect and develop educational content under a free license or in the public domain, and to disseminate it effectively and globally.
As such, WMF spends a lot money (combined) on a splatter of projects, like funding photographers to go to events like Fifa World Cup and Cannes, and take (CC or public domain) portraits for Wikimedia Commons (https://www.wikiportraits.org); etc.
What remains to be seen is whether Google also introduced more Chrome bugs in June than over the past two years, thanks to AI.
The big problem is that AI output can be very convincing and look "right", even appear to work, until you examine it in detail and realise all the edge-cases it didn't handle.
All this ostensibly to keep teenage boys from watching Pornhub (when parental controls already exist).
The real reason, of course, is to force people to connect strong real-life identifiers to online activity. Mobile first, then Windows. Then Linux is too weak to oppose on its own, and will adapt or die.
I see you have a .button, cool! So did you load the entire context of your project into your mind, and calculate every possible iteration of kind, size, color etc this button may have? And once you did that, did you come up with a semantically correct naming scheme that is clear and will not succumb to the inevitable .button_checkout_special_page_cta_widget a particular page will end up requiring?
No? Neither did I. I stopped thinking about CSS entirely almost a decade ago. Thanks Tailwind.
My main gripe here is the lack of transparency around the total experiment and construction. I doubt that they simply pointed their model at these ten specific problems alone and gave the model one shot; therefore the $2000 number could be completely misleading, similar to P-value hacking by not disclosing the total experimental setup.
I want to know:
1. How many total problems were given to the model, and what percent were left unsolved at what cost before giving up?
2. How many attempts did you give the model at solving these problems?
3. How expensive was the harness, e.g. did the model have access to a job cluster?
Discs don’t matter. The whole “bring back discs” thing is pointless. They’re gone. Period.
Rights matter. If we had the same rights with digital purchases we had with old physical games the disc thing would be a much much smaller issue. Would many care outside true collectors?
Don’t confuse the two. If you do, and you complain loudly enough, you’ll get the monkey’s paw version of discs. All the downsides of both, no upside at all.
Even in the Era AI, GGPlot's API is still the best charting API. The name "Grammar of Graphics" isn't just marketing, they literally sought to write a god damn grammar to was capable of expressing all possible qualitative graphics.
I actually stumbled upon this book when I was trying to look up how draftsmen (with pens and pencils on paper) did qualitative graphics as I found they had a lot of charm as opposed to modern charting libraries. It's something I noticed when looking through a bunch of historical RBA (Reserve bank of Australia) annual reports, the 1960-1980 charts had a lot of character, but then you go into the early 2000s and its a stale chart from excel.
Anyways ggplot doesn't really recapture the magic of those older charts, but it seems use quite a few of those as a baseline for how to communicate information. Like in figure 20.1 they talk about efforts to replicate older inforgraphics that showed Napoleon’s March on Russia, this graphic here (I think the example in the book is a bit nicer than the one in this blogpost IMO)
On top of the charts just look nicer than anything you could produce with pyplot (and any API built on top of it) as pyplot seems to be have some really limited raster based rendering or something and the text handling is incredibly limited, I've never had this issue in ggplot.
I feel like most software engineers aren't exposed to because it exists in the R ecosystem which is more so data scientist, econometricians, statisticians and other quantitative data professions, but it definitely one of the nicer APIs and I wish more people in the node and python ecosystem copied their homework. I see vega's full name is something to do with grammars, but idk it's for the same reason.
I'm hardly a fan of the WMF, but the headline is clickbait. The WMF has used a law firm called Jones Day for brand and trademark management for over a decade. The firm is one of the largest legal firms in the US and it also does union busting, but a) the WMF does not appear to have engaged them for that, and b) the relationship long predates the current kerfuffle.
Japan holds a huge amount of US treasuries, and I guess was considering a mass sell off to raise cash to defend the Yen.
US treasury bond yields are already dangerously high for the US and Japan selling treasuries would push yields up even higher, and could trigger more panic selling from others.
I guess this is Bessent's scheme to try and kick that can down the road.
I’m not sure where this idea came from that farming was idle and only industry required constant work. Every hundred-year old book I’ve ever read that features farming includes themes of how the farmer’s work never ends and runs from dawn to dusk.
