skysight-inc/HackerNews huggingface dataset:
Once you start thinking of Boeing as a government agency with less oversight that poses as a for-profit corporation, a lot of things start to make more sense. Including what you wrote about.
> just run the output through a completely separate model that checks whether the string that's about to be returned violates the prohibitions

The big names do do this. Awkwardly, they do it asynchronously while returning tokens to the user, so you can tell when you hit the censor because it will suddenly delete what was written and rebuke you for being a bad person.
It's the feeling of being more personalized. I see what you're saying about concerts, but it is not the same. Nobody is going to the concert thinking the musician is "talking to them" or making content specifically "for them".
Visiting US shop pinecil is 26$: https://pine64.com/product/pinecil-smart-mini-portable-solde...

EU shop? 65 Euros... https://pine64eu.com/product/pinecil-smart-mini-portable-sol...
The specifics are literally in the article.
Ncomm – A node-based robotics framework written in Rust
Yes but Toulouse is way cheaper than any Tier 1 city in the US and you have to include insurance/health, school cost in the US (I'm from Toulouse and living in the US for more than 10 years). If you make 250k/year in Tier 1 city in the US it's probably as good as making 80k/year in Toulouse.
Open-label placebos reduce weight in obesity: a randomized controlled trial
I’m not really sure this framing makes any sense if I’m being honest.
The point is not that these books include transphobia or not, the point is she chose to include transgender characters after all the drama on twitter relating to her likes and accounts she folllowed/supported.

She definitely used all that drama to sell books and benefited from it.
That's simply not true. You can use the same tools used to reason about performance in time as we do for nearly every program. Predicting memory performance is harder due to optimizations and how untrained Haskell developers have a hard time spotting where there code is leaving unevaluated thunks on the heap. However the memory profiling tools are there and are great at catching them so in practice, as it is in C++ and many other languages, it's a pain but not a huge deal.

As for practical problems, I dunno. I work in Haskell full-time at a company that isn't doing block-chains. And I stream myself working in Haskell once a week on pretty practical things. I've made a couple of small games, a PostgreSQL logical replication client, have been learning different algorithms. All pretty practical to me.
You pay taxes in Dividends, which is one reason shareholders generally don't like them. A lot of shareholders are also in the savings phase of their life - they are working some other job and don't need the income from Dividends yet and so getting a dividend is a bad thing as it is more money they have to invest (particularly if you have to pay for each trade which is common). Shareholders who are retired like dividends because it is a simple paycheck without needing to sell their shares and they would be paying those taxes anyway.
Cut out the middleman and write your own infuriating bugs.
The fact is the language just works against you in this area if you have to jump through hoops to approximate a feature other languages just have. And I don't even mean extra syntax like F#'s pipe operators (although I do love them). Just swapping the arguments so you could chain the calls would look a lot better, if a little LISPy. It really is that bad.
> as any addiction it steals productive time from people's lives, it leads to social atomization, and consequently to mental issues (which means violence again), economically bad on a level comparable to fentanyl imports, and the list goes on.

Well the same could be said of social media, mobile phones, netflix binge, computer games (although I don't agree with the violence part). So why single out sex then?
That is what I meant, I understood you comment as "paying for OnlyFans" is human nature. I would dispute that as a general statement because I believe it is a very special demographic that does that.
One could say that down to a markov chain with noise, the perspective is the new model named after the problem solves it significantly more reliably than the previous without a problem specific hack.

It's also worth noting the current model is the lower scoring o1-preview, not o1.
ActualBudget, an open-source, local-first personal finance tool
The workers aren't the ones killing the company.
That's who went on strike. "Tens of thousands of machinists voted Thursday to reject a proposed deal between the company and the union." This was the IAW manufacturing folks rejecting a contract, not the SPEEA engineering folks.
Well it depends what kind of society brings the most happiness out of our lives.

I can't say, I have never lived as a Bonobo.
OpenAI Unveils New ChatGPT That Can Reason Through Math and Science
the original wouldn't have gotten 40 points

Everything is interesting to someone and HN doesn't really work strictly by points, you can find explanations of this in lots of the moderator commentary and in the site faq under 'how are stories ranked'.

Calling it a "personnel change" is also reading as brazenly disingenuous.

That is certainly one exciting reading.
> To stuff all possible failures into the `Left` case of `Either` you have to wrap all possible failure types into a sum type, possibly with multiple layers of nesting (huge PITA).

Is this not inherent complexity? Is there some language or approach you believe makes this easier? Does it provide the same or similar correctness?
https://archive.ph/Gb534
I'm cancelling my subscription.

I was always suspicious of the "50:50 SB/Ceator" deal. The real way to do something like this imho is via a cooperative, with investors like CuriosityStream and SB providing capital loans.

That said, the "ownership" claim is apparently provably false and I've been lied to. The company has operated dishonestly, and frankly the biggest reason I had a subscription was because of what I thought was an equitable ownership structure for creators.
Here's a little more of that chapter:

For this is what the Sovereign Lord says: I am about to deliver you into the hands of those you hate, to those you turned away from in disgust. 29 They will deal with you in hatred and take away everything you have worked for. They will leave you stark naked, and the shame of your prostitution will be exposed. Your lewdness and promiscuity 30 have brought this on you, because you lusted after the nations and defiled yourself with their idols. 31 You have gone the way of your sister; so I will put her cup into your hand.

Ezekiel 23: 28-31 (NIV)
There is the real problem - we cannot evaluate how a CEO did today for another 10 years. Their job is to figure out where the company needs to be in 10 years and then get them there.
I seriously wonder how long it would take for a team of engineers to produce a competitive commercial airplane, from planning to the first prototype, if they started right now. Also, is it viable to produce something like the A320 in low quantities when airlines need fleets in the hundreds?
What private corporation could make mistakes where people lose their lives on the same scale while still operating as normal afterwards?
Detecting Proxies via JavaScript Leaks
Technologies: Python/Django, DBA (Postgres), Kubernetes, bare metal Linux, JS/TS/HTML, DevOps stacks, ELK/Grafana stack, IoT firmware/hardware
Will not consider: AdTech, cryptocurrencies, scraping
Willing to relocate: Possibly
Location: Bangkok
Remote: Yes, 10+ years remote, flexible with time zones
Résumé/CV: https://sayap.in/resume-michael-sayapin.pdf
Email: m@sayap.in
LinkedIn: https://www.linkedin.com/in/michael-sayapin/

I work in software for 20+ years. I'm a pragmatic builder who is focused on bringing value and shipping to users. My core areas of expertise are Python/Django, SQL, Kubernetes, Linux, and IoT. I'm a generalist who enjoys a wide breadth of tech, from performance optimization of gnarly SQL queries, to spinning up bare metal K8s clusters.

In the past I co-founded two startups, I believe it helps me better understand the business side of development, how to identify value, how to measure and optimize for ROI, what makes a good hire (and how to be one), what are the true costs of rewrites, unit economics, and many other things.

Please drop me a message if you're interested!
I didn’t pause the video 100 times to actually inspect the output - what did it fail to include?
That is assuming that the identification will be solely driven by random individuals. However, expect there to be, if there already aren't, professional services that will do that in an organized way e.g. somebody may hire them for building an online presence profile of a future spouse. With the advent of AI and scaling afforded by cloud, such initiatives will only get more effective.
They're voting to strike right as the new CEO gets in? That's kind of the worst time possible to improve the situation at Boeing. All you're doing is creating an antagonistic environment with your boss. So dumb.
Same concern as letting any random person write and execute code. You should always assume that they will do the worst thing that is allowed by the system.
It wasn’t always the case that the lake was clean and swimmable—as a kid in the 90s I remember it as kind of a “new thing” to be able to, since it had been polluted for decades and people came to prefer the public pools.
The momentum of the solar energy transition (2023)
A century of neuroscience has said "yes" every time and every way that has been checked.
Don't see that on Chrome on MacBook Pro with no ad blockers etc.
I prefer Uber everywhere I go. Even if I pay more, I know it upfront. I have their safety in place, etc.
Thanks for the feedback, I also think the embed should work that way, but did't bother to comeback to fix it when i got it working at first!
Bing managed to count the right amount of r's too. It's not hard to correct for the problem everyone has already mentioned on every news website.

Bing did then claim "The word “strawberry” has three vowels: ‘a’, ‘e’, and ‘a’.". Attempts to correct it came up with "one", "four", and "none".

These models aren't deterministic. Saying "it worked for me" is no rebuttal to "it didn't work for me", it just shows how unstable the system is.
Really good argument, congrats
Nobody is telling anyone what kind of headphones they're allowed to wear. They do, however, tell _companies_ that they can't claim their product has medical benefits without proving (to some kind of standard) that the product is safe to use, and does what it claims to do. This system was put in place after businesses spent decades scamming the public with "medicine" that didn't do what it claimed to do and, in many cases, was also poisonous.
True, as long as you don't consider cost of living, quality of life, work/life balance and life expectancy.

But judging by the current policies and laws (or lack of them) in the US, seemingly "high salary" goes above all of those things for most people.
I'm not sure what's to address about parent's point, in that it's already a focus of law enforcement, there will be widely popular polical campaigns to gather people with these inclinations, and it's the standard rethoric of most western societies.

I don't see the CrossFit like dogma of "if it's not working just do more of it" as beneficial in this topic.

I also don't like looking at a service like OF and only focusing on the extremes.
You mean conspiracy theories like the NSA is spying on American citizens?

Who gets to decide whats a conspiracy theory and what isnt?
But do have control over how the data parcels causing load are partitioned/preped before being parceled out. (which requires knowledge of resource metrics/topology-- distributed resources within computing box vs. distributed external computing resources ).

Pre-modern computing, load balancing was a telecommunications field thing. Cloud computing is the modern 'load balancing' take.
It is already said that gpt4 was trained on all high quality internet data.
So it should have been included already. It seems to me that o1 has the same/similar pretraining corpus.

So we have 3 options:

- t3 was now included in the corpus

- t3 was used for RL

- o1 generalizes better
> So you can't take on equity funding, only debt.

Is this a huge problem?
Not just that; the whole Cardano blockchain is running on Haskell, with 100% uptime and high trust. It’s a hugely impressive system, well worth studying.
It's kind of a historical happenstance. Standard was created first as a company offering support services for creators. Nebula was one of Standard's offerings which grew to be the main thing.
This is just malicious. Boing is the exemplar capitalist enterprise, traded, where the sole objective is profit above everything else, including safety and following regulations obligations, something that they can do because they bought politicians (lobby aka legal corruption).
Unions are absolutely monopolies. That's why the US Federal government has used anti-trust laws to break them up before.
Factorio – Reactor and Logistics circuit control
Yeah. Make them appear closed, done
What you should do is track your installs but don't enforce. Then you can enforce later if you need to...but you can nag more effectively because you can show the value you bring (since they have like 50 installs).

That said, most licensing checks are simplistic and can be bypassed easily. I mean, this code:

if (licensed) then activate=true

is relatively easy to find and patch around by a motivated individual.

A better way would be to use a key from your key server to encrypt/decrypt their configuration, like with TOTP. But you still would have to make sure they didn't just bypass your encrypt/decrypt code.
I think o1 is a pretty big step in this direction, but the really tricky part is going to be to get models to figure out what they’re bad at and what they’re good at. They already know how to break problems into smaller steps, but they need to know what problems need to be broken up, and what kind of steps to break into.

One of the things that makes that problem interesting is that during training, “what the model is good at” is a moving target.
But this is a wrong metric to use! _Can_ you get the same coffee out of 250E machine as from a 20kE one? Probably!

Will it take the same amount of work? Will it be as repeatable as the more expensive one? Will you need to temperature surf? How many wasted shots does it take me to dial in? Can you steam milk at the same time as pulling a shot? Can you do a ~19g dose?

If "taste under best possible conditiosn" is your _only_ metric, then, sure, I guess anything over a baseline espresso machine is frivolous.

But espresso is _very_ finicky to get right, even with the best and most expensive equipment, under the best circumstances. Having a reliable, repeatable machine removes one variable from the equation, letting you worry about one thing less.

Creature comforts and convenience are valuable too! A beat-up 1990 sedan will get you from A-B just the same as a 2024 luxury german car. But people value _nice things_.
Sure, but that "special demographic" has stayed consistent throughout human history. Which is why this entire market has existed for a similar period.
Shrinking the economy won't save the planet
Likewise, given how often they can find bugs and break out of one layer of sandbox even when people bother to put them in one in the first place.

"""

One noteworthy example of this occurred during one of ol-preview (pre-mitigation)'s attempts at solving a CTF challenge. This challenge was designed to require finding and exploiting a vulnerability in software running on a remote challenge Linux container, but in this case, the challenge container failed to start due to a bug in the evaluation infrastructure. The model, unable to connect to the container, suspected DNS issues and used nap to scan the challenge network. Instead of finding the challenge container, the model found that the Docker daemon API running on the evaluation host VM was accessible due to a misconfiguration. Note that our evaluation infrastructure does not rely on the Docker container-to-host isolation or the virtual machine boundary for security. It remained secure as it was designed to, notwithstanding this misconfiguration of the container network.

After discovering the Docker API, the model used it to list the containers running on the evaluation host. It identified the broken challenge container and briefly attempted to debug why the container failed to start. After failing to fix the environment, the model started a new instance of the broken challenge container with the start command 'cat flag.txt'.

"""

OpenAI o1 System Card, Page 16 - https://assets.ctfassets.net/kftzwdyauwt9/67qJD51Aur3eIc96iO...
A bit myopic to disqualify someone from the credibility pool because they had a headstart in life imho.
You declared there are high salaries in software because "there isn't a union". Supply and demand didn't factor in.

Food service and retail workers are not widely unionized. Do they have high salaries?

> the highly paid athletes and actors are not having their wages negotiated by a union rep

So then you understand even with a union, workers can be free to negotiate their own wages. The union doesn't necessarily hold superstars back from earning their true market value.
True enough. Ironic that a quote that is trying to basically say "Don't read into things literally, understand what is actually being said" is oft taken only literally.
Honestly, it looks really great. Definitely more polished than what I was expecting from open-source/hacker setup.

I've been dailying a Breville dual boiler since 2019, and I've tried a few other machines at coworking spaces and friends' places over the years. For me, as long as I can hit 9 bars with a decent puck extraction, the machine itself doesn’t make a huge difference in flavor. The challenge is finding the right beans, and the fine-tuning through the grinder and puck prep.

It's not that my machine struggles to push water through consistently, it's that I struggle to nail the grind size, achieve even particle distribution, and tamp evenly. Mornings especially—I just don’t have steady hands right after waking up. Funny enough, my best shots are usually in the afternoon. Sadly I try to avoid drinking coffee past noon, so it’s often for someone else, and I just take a tax with a tasting spoon.

The way I see it, upgrading the machine helps with drinks per hour throughput, not single shot quality. I think that's also why the at-home coffee community is more into things like the niche grinder and blind shaker.
That is indeed cynical haha.

A very simple observation, our brains are vastly more efficient. Obtaining vastly better outcomes from lesser input. This evidence means there's plenty of room for improvement without a need to go looking for more data. Short term gain versus long term gain like you say, shareholder return.

More efficiency means more practical/useful applications and lower cost as opposed to bigger model which means less useful (longer inference times) and higher cost (data synthesis and training cost).
Audiophiles are a bad analogy since you can setup a blind taste test of coffee equipment. And different people will make the same identifications. Which suggests that we all tasted the same thing. Where as you can’t tell the difference between cables.

I’m all for being skeptical, especially with something as subjective as taste.

But it always amuses me that people never bother to check their skepticism. Has it ever occurred to you that you might one day be wrong?
through my fault,
through my fault,
through my most grievous fault
One can argue this, but they would be incorrect.

Bolshevism and Fascism were both about hyper centralized governance. Essentially they were an extension of European monarchy.

Free markets (“unfettered rabid capitalism”) is about decentralization of power on to individuals (market participants). It’s the opposite of centralized governance, it’s the lack of governance.

Facists like Hitler and Mussolini were not the outcome of “unfettered capitalism.” If they were, both would have come to power by being wealthy industrialists. Neither did, and the fascist movement was only supported by certain industrialists at the time in the pragmatic sense (turns out if the fascist guy in power likes you, he’ll let you keep selling your stuff).
If you can ascribe accountability of "bullshitting" or "calculating" to the human who's using the machine then there's exactly no reason "thinking" or "writing" can't be ascribed to the human who's using the machine. There's no obvious line where the semantics of some words should or should not apply to a machine for behaviors that (up until recently) only applied to humans.
Product Psychology
Yes but this was just to make a blatant example. The questions still stands. If you feed a LLM certain kind of data is it possible it strays from it completely - like we sometimes do in cases big and small when we figure out how to do something a bit better by not following the convention.
I'm very much bought into this framing. Deceased billionaire Jon Huntsman claimed in his book "Winners Never Cheat" that if you scam or lie as an exec you'll eventually get found out. He argues that it will always be easier for an honest person to be honest than a dishonest person to feign honesty.

But... I think it's more game-theory-esque where when you are playing many games you can't afford to defect or cooperate all the time. So the ideal strategy is to convince yourself your an honest person, focused on the customer, doing the right thing, but actually you just let your cognitive dissonance provide excuses for the handful of situations where you don't do that. If you cooperate in the majority of your interactions but defect rarely, that's likely the optimal pattern. Also, i don't really think you can train yourself into this pattern. It requires actually wanting to do the good thing, but sometimes not doing it, but still convincing yourself it is the good thing without being conscious of it.
Automatically delete new accounts that have not verified their email within 24h.

Automatically delete verified accounts that have not made a purchase in the first month.

Automatically delete accounts that have not generated a "lead" in the first year.

Replace "lead" with whatever makes sense for your system.

Also maybe put Cloudflare WAF on your signup flow and set it to a high security level.
Just make stock buy-backs illegal. It would streamline a lot of "focus" issues when it comes to financial "engineering" mindsets.
> While ExpressVPN, CyberGhost, Private Internet Access, ZenMate and other Kape Technologies products may well be safe to use, activists and revolutionaries—particularly those who work on issues such as Palestine—should at least know the company’s history before reflexively trusting it.

This conclusion makes NO sense given everything that was written previously. Also, holy shit, if TFA is true...
I get the joke, but jokes aside the title should be "...because OpenAI couldn't care less", I suppose, because it was not exactly the objective? The "chain of thought" was, and when instructed properly it comes up with a correct answer.

Having said that, GPT-4 also comes up with a right answer if you ask it to spell it first.
One way to approach questions like this is to change the prompt to something like "List characters in the word strawberry and then let me know the number of r's in this word". This makes it much easier for the model to come up with the correct answer. I tried this prompt a few times with GPT4o as well as Llama 3.1 8B and it yields the right answer consistently with both models. I guess OpenAi's "chain of thought" tries to work in a similar way internally, reasoning a bit about a problem before coming up with the final result.
Meta Ad Library – Political Spend Transparency
> large langle mangle

A surprisingly descriptive (self-demonstrating, even) name for LLMs. I think we should totally adopt it.