flatline

I’m not sure that it’s masculinity per se that is a sticking point on the Left, it’s the other thing you pointed to, the culture around how we address these things. So-called “cancel culture” is actually a very masculine and conservative activity, specifically by way of established dominance and social hierarchy, and reinforcing in-group norms.

It can be about toxic masculinity, racism, misogyny, homophobia, whatever. I think that these are all real things and important to address, but participating in make-wrong and alienating fellow leftists, while completely dismissing non-leftists as inhuman, is self-defeating.

I like the idea of “call-in” vs “call-out” culture. By inviting other people to the table in a private setting and opening a dialogue to discuss the experiences of marginalized people - or any individual’s need for accommodation - rather than scolding people in public for not adhering to in-group norms that may be completely opaque to outsiders, you change the dynamic. And just by relating to people as people, in more intimate and personal settings than online anonymous forums or a standoffish workplace culture, we take down some of the walls that seem to separate us.

I don’t even know what AGI is, and neither does anyone else as far as I can tell. In the parts of the video I watched, he cites several things missing which all have to do with autonomy: continual automated updates of internal state, fully autonomous agentic behavior, etc.

I feel like GPT 3 was AGI, personally. It crossed some threshold that was both real and magical, and future improvements are relying on that basic set of features at their core. Can we confidently say this is not a form of general intelligence? Just because it’s more a Chinese Room than a fully autonomous robot? We can keep moving the goalposts indefinitely, but machine intelligence will never exactly match that of humans.

The content was good for me up till “The Operation.” Typical of AI output in my experience - some solid parts then verbose, monotonous text that fits one of a handful of genai patterns. “Sloppified” is a good term, once I realize I’m in the middle of this type of content it pulls me out of the narrative and makes me question the authenticity of the whole piece, which is too bad. Thanks for your transparency here and the prompt, I think this approach will prove beneficial as we barrel ahead with widespread AI content.

The narrative around AI taking all the jobs, causing layoffs, etc. is certainly about power. The stock prices are about sentiment. When that sentiment evaporates because AI cannot in fact replace the workforce, the stock prices will fall, maybe precipitously. Ironically, if AI fulfills its promise, I suspect the same will happen due to a lack of confidence in the consumer economy from mass unemployment.

This bubble will pop either way, but it could continue like this for years.

The normal simulator is the negative space in this game. The people on the party committee. The networking event. Your mom who has called three times. Just imagine those activities boosting all of your stats.

To pile on to the litany of complaints, I think PRs are a rather poor abstraction. It’s not a good way to review code. If I’m doing an actual review of anything complex, I’ll check out the branch, step through the code, jump around in the IDE: this is how we work with code, not through a fairly unreadable git diff.

PRs have no scope and no way to designate scope. What do I want from each reviewer? At some point, the PR becomes superfluous to adequate code review and communication around said review.

Ultimately they can be used to micromanage and gatekeep merges to main. This is the PR at its worst.

Overall I’m not a big fan, it feels like a necessary evil to meet the demands of Big Agile.

It’s pretty typical of corporations, the cult surrounding its leader notwithstanding. Not even just US corporations - the VW emissions scandal was huge, and today they are doing as well as ever. That was a big shakeup; the kind of stuff we are seeing from Tesla feels like business as usual.

Acetaminophen is not an anti-inflammatory.

How much of the code do you review in a third party package installed through npm, pip, etc.? How many eyes other than the author’s have ever even looked at that code? I bet the answers have been “none” and “zero” for many HN readers at some point. I’m certainly not saying this is a great practice or the only way to productively use LLMs, just pointing out that we treat many things as a black box that “just works” till it doesn’t, and life somehow continues. LLM output doesn’t need to be an exception.

If it passes the unit tests I make it write and works for my sample manual cases I absolutely will not spend time reading the implementation details unless and until something comes up. Sometimes garbage makes its way into git but working code is better than no code and the mess can be cleaned up later. If you have correctness at the interface and function level you can get a lot done quickly. Technical debt is going to come out somewhere no matter what you do.

I certainly didn’t mean to imply otherwise. I do think that hiring solely or even principally based on superficial status indicators can lead to systemic problems, especially when those indicators may not be good reciprocal proxies for relevant skills.

I’d make an even broader generalization, which is that all of these attributes are proxies for status. Graduated from a top school? Live in the Bay Area or NYC? Did well in High School (I guess?) These are all status indicators in the mind of someone higher up, and deserving of better pay. If you live in a low cost of living area it’s correspondingly lower status and deserving of lower pay. Other common status indicators include things like age, gender, and race…

Crypto moves the problem from payment providers like Visa to central exchanges like Coinbase. Until you have a completely decentralized ecosystem built around crypto, you run into trouble when offramping to fiat. If I recall, backpage accepted bitcoin when Visa dropped them, but it was way too much hassle to be useful. If you could pay rent and utilities and buy food using some sufficiently decentralized token, crypto may become a viable alternative.

Note that pornography is not banned here in Texas at least. You just have to provide age verification, and PH elected not to participate in that process. It doesn’t seem like that wild a thing at face value.

It would take a lot of power to send even a radio signal that could be picked out from the noise at a few light years. Add a requirement for that signal to be more or less continuous over geologic timescales - we’ve only been able to emit and detect these for ~100 years - and my personal surprise diminishes rapidly. Huge distances in time and space with human-level technology make detection highly unlikely.

This was the standard advice 2-3 years ago when the market was hot, I can’t imagine this being feasible for most people right now.

What's up with the typescript rant? Don't we have decades of research about the improvements in productivity and correctness brought by static type checking? It starts out strong but stuff like this really detracts from the overall point the article is trying to make, and it stands out as an incorrect and unjustified (and unjustifiable) point.

Just because they weren’t born into the owner class (or “capital class”) doesn’t mean they didn’t work their way into it. That’s kind of the American dream.

I have not seen a clip of a young Bill Burr in ages! Now that he is bald, he is my doppelgänger.

Viktor Frankl also claimed that staying clean-shaven made you look younger, and attributed it as one factor in his survival of the concentration camps. He used a piece of broken glass to shave.

I agree about the clickbait. As I come up on 50, however, I think there are a number of axes on which we can analyze aging.

Chronological age: there is no getting past getting older, you will age and it will be increasingly apparent with time.

Grooming and style: you can, nonetheless, choose to date yourself with your clothing and overall presentation, or not. This can be overdone and make you stand out “trying too hard” not to be old. But there’s a world of middle ground.

Physical: a mix of genetics, nutrition, exercise, access to medical care, self care, and luck. Some people slow down much more than others. Some people, like the author, simply choose to, having been relived of the expectation that younger folks be very busy.

Mentality: do you want to look at younger generations as an alien species, or do you want to deal with people as people and acknowledge that while we all have different backgrounds, new perspectives have their own value. I find I can still relate well to people of about any age. At some point mental decline may rob me of that, but I won’t stop while it’s in my control.

Interests: do you mostly enjoy media and activities particular to a time when you were younger, or do you have a penchant for novelty despite your age?

Degenerate amateurish quantitative analysis modeling copy-trading on the Solana network.

If you watched the video, you would have the answer. Well, an answer. Which is that there does not need to be a cause! Even in an idealized dome with no air, friction, or external forces.

As it does for you for different reasons, this also matches my lay intuition of physics: sometimes things just spontaneously occur, and a system in dynamic equilibrium simply will not hold still forever.

> It’s like my whole computer is a toddler screaming “LET ME DO IT!” every time I try to create something.

Every autocorrect or auto suggestion ever has felt like this to me, but the volume has been turned up to 11. The otherwise drab Adobe Reader is covered with colorful sparkly buttons and popups suggesting I need not even read the document because it can give me “insights.” First, no you may not ready my proprietary document, nor do I suspect most people using this particular software - I only have it for digital signatures - have permission to share IP with a third party. But mostly, it can sometimes be a useful tool, and the fact everyone is shoving it in my face reeks of desperation.

The tech industry is in real trouble.

The format is the same but not the algorithm or what people are putting on it. I’m not a tok tok user but the few times I’ve been on it they felt surprisingly different. Meta reels are less substantial in content.

We are talking about delivering care, not innovative medical technology. The biggest single target for innovation in care delivery is to get rid of private insurers.

I think the graph at the top of this article really says it all: https://www.economist.com/graphic-detail/2019/05/22/republic...

“Staff engineer” varies by employer but this is generally exactly what I expect it to be.

There are times I do technical work and times my entire job is putting out fires and making sure the wheels stay on the bus as we barrel full speed to a release. Making sure people have work. Making sure they know what it is, and the customer is on board. Tracking deadlines. Managing expectations. Making critical decisions about the architecture and the like.

Any developer can write code. This stuff requires a different set of executive functions, and engineers that can do both are generally promoted.

Hypothesis: an LLM capable of generating a correct proof in a formal language, not through random chance but through whatever passes for “reasoning,” should also be capable of describing the proof in a way meaningful to humans. Because LLMs have a limited context window and are trained on human behavior, they will generate solutions similar to what humans would generate.

We have already accepted some proofs we cannot fully understand, such as the proof of the four color theorem that used computational methods to explore a large solution space and demonstrate that no possible special-case combinations violate the theorem. But that was just one part of the proof.

I wonder what we know about proof space generally, and if we had an ASI that reasoned in a substantially different way than humans, what types of proofs it would be likely to generate. Do most proofs contain structural components that humans find pleasing? Do most devolve into convoluted case analyses? Is there a simplest form that a set of correct proofs could be reduced to?

I like the idea of your optimization, but it will not work as stated. The largest would be something close to MAXINT, the smallest 3999. With a range of 2 billion over 32 bits, the odds of both these being within a list of a million is quite a bit poorer than 99.9%.

Because for things like the Putnam questions, we are trying to get the performance of a smart human. Are LLMs just stochastic parrots or are they capable of drawing new, meaningful inferences? We keep getting more and more evidence of the latter, but things like this throw that into question.

I got a 3.25% loan post-divorce in a part of the country I hated, and ended up selling and relocating. I do not plan on buying again soon, current prices combined with current interest rates make it unappealing. If home prices come off or stagnate long enough, I will once again consider buying. Right now I can set aside $1000/mo renting, which is enough to pay someone else for the hassle of maintaining a house.