appplication

There’s also probably a lot less noise from casual internet conversations. I imagine a nontrivial amount of what LLMs know about certain technologies comes directly from forums like reddit where quality of response isn’t guaranteed.

Do notice he is quite Socratic, the approach works well for LLMs they love to please so you have to be careful in how you lead them.

Nothing to worry about, it turns out it’s just a collection of parquet and some metadata

It may not have started that way but there definitely was some amount of commenters that took it quite literally

Relative to their other compute or other players inference, not as significantly. Though yes, they certainly have some share.

I think there are some really interesting thought there, but I’d challenge some of this:

Models are not free. Downloading them is free. Running them is not. This has manufacturing economics, not software economics; the idea that they are "free" is an economic category error as it relates to their actual use

I think a large part of manufacturing economics is illiquid overhead and the cost of expertise to set up and run your manufacturing line. Compute economics don’t have the same illiquidity nor do they require the same expertise or even specialized infra (current temporary chip shortage aside).

The implications of this are small players (e.g. your uncle running an inference server out of his garage) have comparably efficient marginal costs as big players. Compare this to actual manufacturing where small players have essentially no access to the manufacturing facilities of the big players.

Additionally, big players with a lot of compute who are not meaningfully in inference today (e.g. Amazon) have a fairly straightforward glide path to utilizing that compute to compete.

This is because US labs are leading on cost efficacy of inference ($/task)

It’s possible, but I would need to see better data on this.

A big part of training now is optimizing token efficiency. It's hard to distill token efficiency; that is perhaps why Chinese LLMs are so inefficient.

I think it’s fair to assume this is true, but also token efficiency is not a meaningful competitive moat. It’s not like these are secrets the Chinese will never figure out, it’s a fairly active research space and the outcomes are quantifiable.

That’s fair. What’s the Apple-recommended way to avoid this? I interact with a lot of software and tend not to hit it but I also don’t really interact with downloaded executables

I’ve been developing on MacOS for years and don’t think I’m familiar with what you’re talking about. I’m familiar with the warnings, but hardly ever see them.

There is a somewhat valid argument to be made that aggressively trying to hack these insecure government portals could lead to a real reprioritization towards competence.

What you’re describing is essentially the concept of civic duty and, at least in America, it’s unfortunately become deconstructed and politicized to the point where it’s impossible to exist as a meaningful cultural phenomenon.

It also relies on people putting effort towards often intangible, uncapitalized, and unextractable shared value. So perhaps it makes sense that this is being diminished over time, as the grip of capitalism squeezes tighter and more efficiently. With more economic stress placed on individuals, people have less available time and resources to devote to things other than staying afloat.

Between polarization/politicization of literally everything and the relentless corporate desire to deconstruct society in the name of quarterly growth, I’m not optimistic this is making a comeback. If we want to teach the children anything, it is that The System has failed and is in dire need of replacement.

I’ll defend batterygate. If you know anything about batteries (especially the tendencies of those in that era), the actions taken by Apple were reasonable, though they should have considered the light in which throttling would be taken. The claim against them was valid but I don’t think the actions were ever malicious.

This comment is really strange and reads like disinformation

Did you get lost from the music video thread?

Here's a term for what I think is happening: the human reward function problem. In machine learning, a reward function tells an agent what good looks like. Writing code by hand was never easy, but it was full of small rewards. Solving a problem in your head. Understanding a gnarly bit of logic. Watching the code compile. The feeling of control. LLM-assisted programming has automated much of the work that generated those dopamine hits and replaced it with the cognitive load of review and supervision. The satisfying part shrank. The exhausting part grew. And there are no new rewards to fill the gap.

Say what you will about the Claudisms in this piece, this bit certainly rings true for me. With old school coding, there was always a reward at the end, the harder it was, the more satisfying it felt.

With agentic coding, I really doesn’t feel like that, at least not in the same way. It feels more like continually riding a wave of productivity, where small features or huge features have similar levels of interaction required. And that’s exciting in the beginning but quickly becomes very tiring.

Fair point! Was mostly an intrusive technical thought

I think my silly and unserious naive response would be linear scaling bundled binaries with number of platforms doesn’t seem to be that materially different in terms of total size. But I see your point, didn’t consider the architectures

It seems SQLite could be evolve to solve this by just bundling itself entirely in the data files? After all, the binary is less than 1MB, anywhere you’re putting a database surely has at least that much overhead, for most applications it’s less than a drop in the bucket.

I’d be interested to learn if there are any db implementations that take this approach, or reasons this wouldn’t work.

Well, there’s always woodworking.

Agree, tbh. If I’m doing frontend I’m just using svelte nowadays. It’s quite nice.

Your comment made me laugh but I had a similar experience. It felt almost voyeuristic with how far I am from whoever they’re trying to reach, like I’m reading someone’s private journal.

Could not agree more it makes a ton of sense

Oh funny, my intuition when I was writing that was “there’s probably an xkcd what if about this”, but I imagined it be about surrounding the sun with mirrors. Same idea though in the end

The temperature at the focal point may reach 3,500 °C

I thought this was interesting because it doesn’t really seem like an applicable top level claim, surely this is referring to a specific furnace, not all solar furnaces?

Then this got me thinking if there is some universal upper bound constraint to these temperatures. E.g. if I recall a telescope can’t make a source object brighter than it actually is, and this just seems like a thermal telescope, so I wonder if that principle applies here or not.

Falling sand completely blew my mind

Being spurned is one possible motivation, but so is an outstanding offer, where you go from middle of the pack performer with career stagnation to superstar leading the hot new product.

Honestly yes, that’s most likely a major factor

An acquaintance of mine was accidentally wired about $100k when it was supposed to be $5k. Before it could be reversed, they moved accounts and immediately bought a one way flight out of country. They then changed all socials and handles. They are now ignoring all court documents and are on track to get a default judgement against them.

Their rationale? “It’s mine, they owed me this”. They are 100% convinced that they are in the right, not just that they can keep it but that they actually intended to send them this to begin with. I get it $100k isn’t nothing but they’re also throwing their life away for less than what they used to make a year in salary.

People do weird things when given sudden access to money or power.

FWIW, that was not obvious to me either, and I appreciated the parent comment

Welcome to the world, young robot

LoC isn’t a super helpful metric so I think the better question is why is the headline using it. I can say I’ve personally created about 200k LoC code in the last 5 years and most of that has some value. But it really doesn’t say might about how much value or really anything else meaningful.