skysight-inc/HackerNews huggingface dataset:
The reality of software development is that any project beyond a handful of devs requires branching.

This branching can be achieved in at least two ultimately equivalent ways:

- literal branches in your VCS of choice (or forks, clones, etc)

- literal runtime branches, via IF on feature flags

When a feature is ready to merge to prime time, the branches have to be merged, and unexpected interaction with other features can now be found. This is exactly as likely to happen when doing a git merge as when setting a feature flag to true.

Different features working in isolation but interacting badly is a fundamental aspect of software and not some incidental self-caused problem that can be prevented by a better development methodology.

To take a somewhat silly example - if one team is working on a feature to make error messages more readable and another team is working on a feature to make error messages opaque IDs looked up in a manual, these two features will obviously clash when they go live regardless of whether they were each behind a feature flag or on separate git branches. Hopefully few organizations would schedule such an obvious conflict of features, but more subtle versions happen all the time.
> The era of having a personal voice assistant that is capable, adaptable, and intuitive is VERY close and that is something that's exciting.

Intuitive to use? Or has intuition?
Is there a specific type of attorney?
This is what it looks like to me too. Except I do think the tools are significantly more useful than in previous cycles. But I do think the hype cycle model is the right one. And I find it super odd that people keep jumping to the AGI thing. I honestly struggle mightily to see what they're seeing in gpt-4 that makes them feel like we're on the brink of a general intelligence.
I'm guessing that the core idea behind GDPR laws wasn't a to flood internet with banner popups, but to limit excessive and unneeded for honest usage, storage of PII. IIRC GDPR allows for some limited PII storage without any banners, but it is restricted in time and scope, to prevent selling this data. Instead nobody is limiting usage of the data (not even Eurocommission site with GDPR rules) because that is not enforced in reality. So in essence GDPR law was a spectacular expensive failure, because nobody restricted their PII processing and analytics.
Maybe? My wife has been using it to give her recipe ideas. She can’t eat onions and things with sulfites so it’s super user for filtering out ingredients that would make her sick without having to comb over a list.

So far the recipes have been pretty good!
That's part of the problem. People think that using their own human bias to alter the machine is a good thing, when it's clear that human bias leads to negative outcomes. You need a separate thing to remove the human input bias.

Quality is a complex thing that requires design, safeguards, process, as well as iteration. You can't design test suites or checklists with just AI, because you don't know if the AI will decide to override them because of some other instruction or signal. And how do you determine the quality of the signal anyway? The quality of input of each human varies.

It's "too adaptive" for QA. You would need a QA for the QA.
Tech people have an unhealthy obsession with trying to create tech to replace non-tech jobs, without any care as to the impacts on society. Chat and image AI generation is just another example of tech screwing over other people.
GDPR protects individuals 'natural persons' and not businesses 'legal persons'

Recital 14 - The protection afforded by this Regulation should apply to natural persons, whatever their nationality or place of residence, in relation to the processing of their personal data. This Regulation does not cover the processing of personal data which concerns legal persons and in particular undertakings established as legal persons, including the name and the form of the legal person and the contact details of the legal person.
Thanks for this comment, was super interesting! Apparently Matlab uses a similar format (Compressed Sparse Column) to represent sparse matrices.
Funny. As someone within the crypto community, you could switch « AI » with « Crypto » and the meaning would be the same to me. There’s even a worse sentiment, well deserved at this time, regarding cryptocurrencies.

And the answers below, reducing the industry to « drugs » go in the same vein. Stuff like Chainlink working with Swift is not common knowledge and even if it is, it is considered as another nothingburger.
A perfect song to pair with this article is "Jagged Roots", by British electronic trio "Ivy Lab"[1]

1. https://www.youtube.com/watch?v=xJp4MB9PK8A
https://news.ycombinator.com/item?id=36567013
Is this news?

Who said naming was difficult? Obviously all you need to do is make names as short as possible, but no shorter!

Simple!
Technically, we are surveillance cameras on feet.
On the “Sumar” proposal of the so-called “universal inheritance”
How to create Azure Prometheus datasources with Ansible
Job Has 685 Applicants
https://weworkremotely.com/remote-jobs/toggl-database-reliability-engineer-2

I wish job postings and application tracking systems showed the number of applicants in a position. Then I would know if it's worth putting time into applying or if it's a waste of time.

I want job application software to show more info about what's going on.
PoS can do offline transactions and sync them later, if the merchant is willing to accept the risk.
Java's Project Valhalla vs. ray tracer: will it go faster?
It’s called “the soft bigotry of low expectations”. I’ve come to believe that although progressives mean well, they end up hurting things more than helping. They’re blinded by what “ought to be” that they don’t consider the consequences of what “actually is”. You can’t deny reality in the end.
I wonder if there are linters that can check if a method/function name starts with a spell-checked English verb.
Well it was infinity and then it was 1000s and then 100s. And these changes happened in a few years.

This is why the endless talk about PE is so incredibly dumb and misleading when elevating companies.
While I'm totally for the debt forgiveness, anyone who saw that this was going to the Supreme Court should have planned for it to be overturned (i.e. plan for the worst, hope for the best), especially considering the judges known conservative leanings.

This has been known to be going to the Supreme Court since around January, I think, so people should have had about 8 months to prepare to start paying back their loans, and not just the two months since this judgement was passed.

Personally, while I did hold off on making payments for about eight months at the start of Covid, I resumed making payments during the pandemic and actually managed to pay off my student loans completely back in November of last year (although I was getting pretty close to paying them off anyway).

Other people could have started making small payments during this team, taken advantage of the zero interest to start making a larger dent in their payments, and increased slightly how much they were paying each month to ease the transition to full payments again when this kicks off again.

I'm aware that's easier said than done, though. My wife has student loans she hasn't made full payments on this entire time (I think she's been making half payments), so we're going to have a slightly rough transition also, but at least we no longer have the $400/month payments I was making on mine before the pandemic.
I tend to agree with the comment you replied to, but I also agree with this. It isn't too be ignored that lots of people see something different this time. But I don't see the same thing as they do...
> which youplot can't

But you could feed them through `textimg`[1] to generate PNGs.

[1] https://github.com/jiro4989/textimg
I whole-heartedly disagree, but on a more technical note: "echo chamber" is a pajorative that implies a bunch of people "sniffing their own farts and enjoying it" - more accurately, a group of people believing in a false because of groupthink.

To expand and to tell of a very recent story: For work I used ChatGPT to help me write a 500 line bash script to automate a bunch of stuff. It took me around 1 day versus the 5 it would have taken me if I would go the google/ddg/stack overflow route of slowly crawling through outdated content and SEO noise to find the signals.

It worked, completely!

Solely from that experience, I'm convinced that it's not just farts and kool-aid. To go one step further, even, i'de say that anybody who doesn't at least have a cursory awareness or AI is in fact the one in the "echo chamber", isolated from the possible.

It's not the do-all solution, of course, but in certain scenarios, it's quite obviously, trivially demonstrably, revolutionary.
Where ChatGPT then wins is the ability to progressively tweak the output until it is exactly what you want.
In the late 90's I got a Master's degree, specializing in neural networks. This caused me to learn about the hype cycle in AI, and since then I have seen it continue. Remember Watson, IBM's AI technology that was going to drive its growth? IBM got lots of press by making computers that could play chess and Jeopardy, which seemed impressive to people at the time, but they never found a way to make money from it. "AI winter" is the term for the trough of the AI hype cycle.

Note that every "AI summer" prior to this one has produced something useful, just never all that world-changing compared to people's expectations. Most people think that if it can BS (excuse me, generate convincing text), then it can do lots of other jobs. Well, in previous AI summers, people thought that if it can play chess, or answer Jeopardy questions, it could do many other things that it turned out, it could not do (or could not do well enough).

For that matter, the ability to do math, at one time, was thought of as a sign of great intelligence. But, it turned out that computers could do math, long before they could do anything else. Our intuition about, "if it can do this, soon it will be able to do that", is not very good.

I have heard ChatGPT described as a better autosuggest, which sounds about right. It's not that autosuggest isn't useful, it can be very useful, but it's not a thing that is going to change the world, and the jobs which it will automate are neither numerous, nor very well paid even now.

If you're trying to pump that VC hype machine for $$, though, cryptocurrency is not going to work anymore, so they need something.
Anymore. At the top of bubble they were way more than bitcoin has ever been

>e best of tulips cost upwards of $1 million in today’s money (but with many bulbs trading in the $50,000–$150,000 range

https://www.investopedia.com/terms/d/dutch_tulip_bulb_market...
https://noyb.eu/en/telesign-profiles-half-worlds-phone-users

I did not gave my data to TeleSign but apparently they have it. And my operator did not tell me.
Using the most expensive service at scale to handle "huge bursts" or "spam filters" seems like a fantastic idea!
So the BBC does product placement now?
What point are you even making?

Are you talking about trivial e-commerce transactions that you could make with Shopify? Yes, you could embed a payment gateway here. However, this is hardly universal or the norm.

In an actual application, you're going to have some API layer over the processor you use. You don't store these credentials, but you do pass them over your API layer and could easily intercept them.
Having driven these cars before. I will never understand the hype. TSLA marketing and PR department is very good if they have people frothing at the mouth and shilling their products.
I teach college, and in the beginning days, everyone was screaming about "the students will have chatGPT write papers now".

Well, apart from the fact that chatGPT is really incapable of developing a thought, and also apart from the fact that half will fail to delete sentences like "I'm a language model, so I can't..." (insert gist of question here), it's painfully obvious if something is LLM generated.

The moment a sentence like "it's crucial to remember" pops up, I know what this is. Then, there's also the element that it always sounds like it's speaking to a child, and it avoids actually saying things unequivocally without some sort of disclaimer, as the legal department's CYA filter will ensure.

I remain thoroughly unimpressed by the entire venture. If this is Skynet 1.0, we're all safe for centuries to come.
What do you think your brain does when deciding the next word to speak? It is scoring words based on the appropriateness considering context and all the relevant known facts, as well as your communicative intent. But it is not obvious that there is nothing like communicative intent in LLMs. When you prompt it, you are engaging some subset of the network relevant to the prompt that induces a generative state disposed to produce a contextually appropriate response. But the properties of this "disposition to contextually appropriate responses" is sensitive to the context. In a Q&A context, the disposition is to produce an acceptable answer, in a therapeutic context, the disposition is to produce a helpful or sensitive response. The point is that communicative intent is within the solution space of text prediction when the training data was produced with communicative intent. We should expect communicative intent to improve the quality of text prediction, and so we cannot rule out that LLMs have recovered something in the ballpark of communicative intent.
The plaid has upgraded brakes, and they work just fine. What’s not safe about them?

Also, if you had fit issues (honestly more rare the past few years) you should have reported this at delivery, just like any other car. The finish, well, that’s personal preference.

Ultimately I think you just don’t like Elon, and that’s ok - but Tesla is not Elon
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They’re useful for tasks that are easy to verify but hard to generate, and code is one meaningful example. It seems trite to say after so many others, but I built a web app in one day by pair coding with GPT-4, which I am sure would have taken weeks, mostly learning the quirks of the various frameworks involved by sifting through the noise of the web. The LLM wasn’t correct 100% of the time, but I could iterate with it when there was a problem and debug. It probably helps that I was using hugely popular libraries, but I think this means there’s a ton of promise in fine-tuning these models on internal codebases/docs.
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Your payment processor and the network has to trust you if you're reusing the Apple Pay cryptogram for a subscription payment. You _can_ do anything (e.g. you can represent yourself as an open loop transit network reader and get a card number without any authentication from express mode cards!), but the network will not allow you to succeed doing that for very long, if at all.
Yep you got it. Forge, aka GitHub, GitLab, Bitbucket, etc
Maybe “months-long” was hyperbole, but the (former) CEO of ERCOT has stated that it would take weeks, if not longer, to do a black start of the grid. I’m inclined to believe that as a baseline since statements like that make him personally look bad.

https://www.kut.org/energy-environment/2021-08-05/if-the-tex...
In that case it could be worth mentioning CSS, by the Norwegian Håkon Wium Lie.

I often feel like the beginning of the 90s was a missed opportunity by Scandinavian companies. There were many great companies and individuals that were innovative, but could not compete due to the lack of VCs from Silicon Valley and a smaller domestic market
> Here I think you are thinking about this wrong. AI is going to be built directly into Excel so I think it will harm a lot of especially entry level type work for analysts.

I think AI will probably eliminate almost all future knowledge worker jobs through simple attrition. In 20 years, perhaps 1 human knowledge worker will be doing the work of 100 (measured by todays productivity) augmented by integrated AI in the tools they use.

I am convinced that short of certain trades, we will watch AI erode everything. Personally, I am on a mission to convince my 2 year old grandson that becoming a plumber is the key to his future wealth.
You can, but then you have to setup and build the libraries in debug mode. You can then debug with gdb or visual studio. It is just a lot more work than debugging pure python.
I would agree partially. My python experience wasn't even as actual web applications until 3-4 weeks ago and mostly used python for scripting and such. But sure, this means that I know things like dependency management, deployment and similar topics around the language.

But this is also where I'd disagree partially: The backend world moves a lot slower and feels a lot more settled to me. Sure, I'm relying on experiences as a sysadmin and a python developer, but: (i) If you need a VPS, you still have the 4-5 choices you had for years, Hetzner (Cloud by now), Digital Ocean, Linode, AWS Free Tier. (ii) SSL-Fronting had the same answer for I think 10 - 15 years by now. Front it with an Apache or Nginx proxy with Lets Encrypt. LE was the biggest change there. (iii) The ancient good old python3 -m venv + activate + pip is still very much valid and recommended. I'm currently trying out poetry, but even that uses venvs and pip in the background. (iv) And then assets, templates, and even production deployment guidelines are mentioned e.g. in the wonderful quickstart of Flask [1]. And there are several really solid and stable development tools around there for linting, formatting, typecheckind. VSCode for example recommends them quickly.

Most of this has been stable for years while being carefully improved. On a similar page, I haven't been working as an active java developer in like 6 years. I can still readily understand pretty much all java builds in the company because the tooling is just stable.

The 2-3 tries I had to get into the JS ecosystem meant I had to reset most of my knowledge because all of the frameworks, toolings had been deprecated, replaced, rewritten and anything else.

1: https://flask.palletsprojects.com/en/2.3.x/quickstart/
Definitely mixed opinions in this discussion. I am actually curious whether the hard skeptics in the tech circle actually gave ChatGPT and other tools a fair shot. I was into AI/DL before the rise of ChatGPT and thought that it's way overhyped and too unreliable at first, that meant I only played with several toy examples. Across the last few months though, I have increasingly found greater uses for LLMs.

Not saying that it's still not overhyped, but maybe the AI skeptics among the tech community are in their own echo chamber too?
Smart thermostats can do things like turn off A/C when you leave the house.
I bet that if they really wanted to try to maintain what they have while not basing it on race specifically they could just base it on zip code or poverty metrics and still predict race correctly about 80-90% of the time.

I'm not sure places like harvard want rich families to not be able to game the system, in some ways I think that's why they exist. I think rather it's closer to how pay-to-win mechanics work in games, if people can realistically earn what was paid for many will confuse their spending for skill, if it can only realistically be achieved via payment then it becomes a thing to mock because the only way it translates to success was by opening the wallet and there is no skill to be praised. By making an ambigious merit based system that can also be gamed by the wealthy it makes the wealthy seem they are entering due to merit rather than wealth, thus making it praisworthy while also meeting the needs of the wealthy, and in many ways I think that's the real point of most colleges.
If you happen to review few places on Google Map you are holding superpowers. Idk if that works for new accounts too. But yeah, at least if you do some activity then you report a place as closed, they are "checking" it for 1h, then you get the e-mail that the place got removed from Maps.

I use that for good purpose - I fix a lot of invalid information on Google Maps around my home town, and they apply the changes without batting an eye. This is good for society. But I can clearly see how that could be used for abusive purposes.
All that means is that you don't believe your own story.

People said this all the time about Tesla a few year ago. But the stock value back then is easly justified by what they have achieved since.

So the reality is that 'Tesla fans' were not irrational, but they were simply correct. And the people who endlessly repeat the 'market can stay irrational longer then you can sty solvent line' were simply wrong.

Its also an absurd fantasy that Tesla stock is only carried by irrational Musk fan boys. When in reality is mostly large institutional investors who do the same financial analysis on Tesla as anything else they buy.
Fighting Flies
undefined couldn't be minified. If you assigned it to an undefined variable early on, any minifier could easily convert it to yet another single-character variable name.

undefined became U (for example). An 8-byte or more reduction per reference. What can I say? Size used to matter. (Been doing JS since 1996.)
Really? I feel like Javascript has been more or less the same since we got `class` keyword. People have been using “FP” words like monad or Either in Javascript for more than 10 years. They weren’t mainstream then and they aren’t mainstream now even if you see them written in an HN thread.
> Replacing pieces can be an industrial endeavor to set up a factory line to craft new copies of the needed pieces.

Somehow I'm imagining that manufacturing parts for 60s small-volume car would be comparatively simple, considering that the original manufacturing processes could not have been that complex or specialized either? And I think cars in general were quite a lot simpler back then, especially this sort of light-weight race car would have been very much no frills?
> I'd have to imagine that most of them would have obliterated the spot where they could grow these hypothetical new teeth by getting implants

Maybe not. Apparently implants are not common everywhere. I have a Chinese friend who recently got them in the US after an accident, he had some medical connections back home who said the procedure isn't very available in China.
>”… Make every name tell.”

>That last sentence is poetry.

It’s a borrowing from Strunk & White, “make every word tell.”
Probably should save/download whatever you want to keep now...
right, but now a great tulip is $15
Not sure I would call this a "backdoor," but nice of them to do that.
The autobahn where I have driven is quite straight. Track performance depends a lot on the tires, and weight can help with right turns due to friction enhancement. Also, tracks through mountains are where EVs shine.
YouGov did a poll[0] of 1500 US adult citizens, and it reflects what a lot of people in this thread have said anecdotally. 43% say they have never used AI tools, with only 24% reporting they "very often" or "somewhat often" use them.

Interestingly, there's a big age component in this poll, and rather than being a smooth grade like most tech, there's a very strong divide at 45yo—those younger than 45 are over 4x as likely to report they often use AI tools than those over 45.

https://docs.cdn.yougov.com/ifywkae5dt/econTabReport.pdf#pag...
Nim is partially case-insensitive:

https://nim-lang.org/docs/manual.html#lexical-analysis-ident...

Sadly, not every developer understands why that’s a good or bad design, i.e. the global pool of developer talent is partially stupid.
People working in tech believed this. Hell, people directly working on the tech seemed to think this a few years ago, and are only now admitting reality.

Of course, one tends to be optimistic of these things when they work on them.
If you're not going 200 mph, how can you enjoy a book!!!?