ralusek

We used to not know, but now because open source models are being hosted and served by people whose only incentive is making profit on directly running inference, we have a ballpark idea.

If my grandmother were to find out that housekeepers occasionally do actually take things, it would set us back decades.

It can also do that for any picture of a man.

The human mind is capable of the same thing, you know? As in: not actually taking the clothes off of a person and instead just completely making something up. I hereby give permission to all AI, and human minds, to completely make up what I look like naked.

What's puzzling or schizophrenic about that? Those seem like two very natural factors that would be in tension with one another and have to be balanced.

PaymentMethods = a specific credit card, debit card, etc. Payment Method is basically a term of art so ubiquitous that it's user-facing in UIs and has nothing to do with Stripe.

PaymentIntents is definitely a Stripe abstraction, however, but that's one that I like. It's been a while since I used it, but I remember liking that it allowed me to bundle up everything related to the payment, i.e. the amount, the payment method, etc, and pass it around between server, client, and different views in the client, such that you could really build the exact payment flow you want without touching PCI data.

The Stripe abstractions I have always felt are much clunkier are the distinctions between Products/Prices/Subscriptions/SubscriptionSchedules, etc. A lot of "what lives where?" with those; very clunky to work with.

That feels like it wouldn't provide a useful comparison, because the people who were going to bet on sports when LV was the legal place to do it, would go to LV to do it. Their delinquency rates wouldn't necessarily be reflected in LV, though, since they've come from elsewhere to do it.

I'm a software engineer that, like the vast majority of you, uses AI/agents in my workflow every day. That being said, I have to admit that it feels a little weird to hear someone who does not write code say that they built something, without even mentioning that they had an agent build it (unless I missed that).

Maybe I'm just naive but I don't really understand discontinuing things like this. Like, unless there are like 100 people using this, how can it not be possible to just leave this running at like 0.5% of its former capacity. Just leave up like 1 server, collapse all of the DBs into one, and let these few autists have their stuff.

What is the most reliable place for ROMs these days? Is there any sort of checksum that can accompany them to ensure safety? While I trust Dolphin, I don't trust most ROMs.

I tinkered with an alternative to stream interfaces:

https://github.com/ralusek/streamie

allows you to do things like

    infiniteRecords
    .map(item => doSomeAsyncThing(item), { concurrency: 5 });

And then because I found that I often want to switch between batching items vs dealing with single items:

    infiniteRecords
    .map(item => doSomeAsyncSingularThing(item), { concurrency: 5 })
    .map(groupOf10 => doSomeBatchThing(groupsOf10), { batchSize: 10 })
    // Can flatten back to single items
    .map(item => backToSingleItem(item), { flatten: true });

Has AI transformed the economy radically? Yes.

Will it continue to transform the economy radically? Yes.

Will that translate to the model-makers somehow capturing the entire value of the transformed economy? No.

There were a few key moments that revealed this. When OpenAI initially declared "there is no moat," I wasn't sure whether to believe them. GPT 3.5 and 4 were so much better than the competition, it felt like them saying that they had no moat was some sort of attempt to avoid regulation or scrutiny. But then, lo and behold, Claude and Gemini caught up; there really was no moat.

But up until then, while it was clear that there was no moat around OpenAI, it was unclear if there was a moat around big tech. Mistral was meh. Even Meta's were meh. We also had no idea how much these models actually cost to run. It wasn't until the "DeepSeek moment," and especially once these open source models actually started being hosted on third party services, that it became clear that this was actually a competitive landscape.

And as has already been demonstrated, because the interface for all of these models is just plain language, the cost of switching models is basically non-existent.

Please find me an American, or other human being, that looks like Abraham Lincoln.

mono no aware

Disagree completely. Judgement of the sort you're describing should be done at the legislative phase (i.e. writing code).

Inconsistent execution/application of the law is how bias happens. If a judgement done to the letter of the law feels unjust to you, change the letter of the law.

What’s updog?

I think Gemini is an excellent model, it's just not a particularly great agent. One of the reasons is that its code output is often structured in a way that looks like it's answering a question, rather than generating production code. It leaves comments everywhere, which are often numbered (which not only is annoying, but also only makes sense if the numbering starts within the frame of reference of the "question" it's "answering").

It's also just not as good at being self-directed and doing all of the rest of the agent-like behaviors we expect, i.e. breaking down into todolists, determining the appropriate scope of work to accomplish, proper tool calling, etc.

This doesn’t make sense. It’s either written by a person or the AI larping, because it is saying things that would be impossible to know. i.e. that it could reach for poetic language with ease because it was just trained on it; it it’s running on Kimi K2.5 now, it would have no memory or concept of being Claude. The best it could do is read its previous memories and say “Oh I can’t do that anymore.”

I mean at the very least if their clients can read it then they can at least read it through their clients, right? And if their clients can read it’ll be because of some private key stored on the client device that they must be able to access, so they could always get that. And this is just assuming that they’ve been transparent about how it’s built, they could just have backdoors on their end.

Why would you want an LLM to identify plants and animals? Well, they're often better than bespoke image classification models at doing just that. Why would you want a language model to help diagnose a medical condition?

It would not surprise me at all if self-driving models are adopting a lot of the model architecture from LLMs/generative AI, and actually invoke actual LLMs in moments where they would've needed human intervention.

Imagine if there's a decision engine at the core of a self driving model, and it gets a classification result of what to do next. Suddenly it gets 3 options back with 33.33% weight attached to each of them and a very low confidence interval of which is the best choice. Maybe that's the kind of scenario that used to trigger self-driving to refuse to choose and defer to human intervention. If that can then first defer judgement to an LLM which could say "that's just a goat crossing the road, INVOKE: HONK_HORN," you could imagine how that might be useful. LLMs are clearly proving to be universal reasoning agents, and it's getting tiring to hear people continuously try to reduce them to "next word predictors."

Archived: https://archive.is/32SMK

I feel like algorithmic/architectural breakthroughs are still the area that will show the most wins. The thing is that insights/breakthroughs of that sort that tend to be highly portable. As Meta showed, you can just pay people 10 million to come tell you what they're doing over there at that other place.

inb4 "then why do Meta's models still suck?"

> Absolutely nothing about free software requires or even implies any responsibility to “give back”

You're correct about that. The free software itself doesn't confer any responsibility. But the free software exists inside other contexts. Social/moral context. There're also future contexts for you or humanity. For example, if developing free software proves to be a sustainable model for people to do, you might get other projects LIKE the Blender Foundation to crop up in the future. You might benefit from them directly, or benefit from them by enjoying the things people produce with them. Also, if it's a tool that you like to use, maybe you just want that specific tool to continue to improve.

If my quicksave/quickload savescumming is to be observed, I’d be pining for that sperm from before I told the waitress “you too” wrt to her telling me to enjoy my meal.

Yes it does. I never use Claude anymore outside of agentic tasks.

Only thing I use grok for is if there is a current event/meme that I keep seeing referenced and I don't understand, it's good at pulling from tweets

Going to war with AI is pointless. It’s not going anywhere.

Acknowledging that the world has already been turned upside down however, rather than burying our head in the sand (present company excluded), is necessary.

It genuinely makes me see the value in private companies. Public companies must grow. They're accountable to so many different interests. Private companies can be happy sitting at whatever profit level they want. They can take time to tinker on something that they care about. If it doesn't pay off, that's fine.

I think I would say it this way: private companies can be good or bad, but public companies must ultimately become bad.

Comments are kind of embarrassing how many people seem to derive a sense of identity from not using AI. Before LLMs, I didn’t use them to code. Then there were LLMs, and I used them a little to code. Then they got better at code, and now I use them a little more.

Probably 20% of the code I produce is generated by LLMs, but all of the code I produce at this point is sanity checked by them. They’re insanely useful.

Zero of my identity is tied to how much of the code I write involves AI.

It's a bit odd to say, but another big clue identifying something as AI-generated is that it simply looks "too good" for what it is being used for. If I see a little info graphic demonstrating something relatively mundane, and it has nice 3D rendered characters or graphical elements, at this point it's basically guaranteed to be AI, because you just sort of intuitively know when something would've justified the human labor necessary to produce that.

It appears to be a law that is simply adding restrictions to what the state can do (like the first amendment, the best sorts of laws IMO). It’s not granting people limited rights. Any existing rights people had under the fourth or first example, for example, are still in place, this just sounds like further restrictions on the state.