Brian Gerami

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@sudox7 Python 3.13+ will just-in-time compile down to a normal int though

something that bothers me every time I think about it: a Python integer takes 28 bytes of memory. a C int takes 4. it's not a Python bug. it's the price of dynamic typing. every Python object carries a reference count, a type pointer, and size metadata. a million integers in Python costs 28MB same in C costs 4MB.

banger articles you should read

It’s over for digital animation. This is too good. Guilds and unions will try to void it in Hollywood but it’s over, amazing full length films will be made by amateurs in weeks. They’ll need a distribution platform. Can anybody set a video to be a rental on YouTube?

@Davidmdrpi @realBigBrainAI en.wikipedia.org/wiki/Boltzmann…

@realBigBrainAI So every time you close your chat session an AI dies?

Stephen Wolfram, founder of Wolfram Research, explains how LLMs are quietly dismantling our deepest assumptions about consciousness: He argues that large language models have done something philosophy and neuroscience couldn't: "In terms of consciousness, I have to say, the idea that there's sort of something magic that goes beyond physics that leads to sort of conscious behavior, I kind of think that LLMs kind of put the final nail in that coffin." His reasoning is that LLMs keep doing things people assumed they couldn't: "There were all these things where it's like, oh, maybe it can't do this, but actually it does. And it's just an artificial neural net." Wolfram then challenges a core assumption about conscious experience: the feeling that we are a single, continuous self moving through time. "I think our notion of consciousness is a lot related to the fact that we believe in the single thread of experience that we have. It's not obvious that we should have a persistent thread of experience." He points out that physics doesn't actually support this intuition: "In our models of physics, we're made of different atoms of space at every successive moment of time. So the fact that we have this belief that we are somehow persistent, we have this thread of experience that extends through time, is not obvious." Then Wolfram offers a striking origin story for consciousness itself. @stephen_wolfram suggests it traces back to a simple evolutionary pressure: the moment animals first needed to move. "I kind of realized that probably when animals first existed in the history of life on Earth, that's when we started needing brains. If you're a thing that doesn't have to move around, the different parts of you can be doing different kinds of things. If you're an animal, then one thing you have to do is decide, are you going to go left or are you going to go right?" That single binary choice, he argues, may be the seed of everything we now call awareness: "I kind of think it's a little disappointing to feel that this whole wanted thing that ends up being what we think of as consciousness might have originated in just that very simple need to decide if you are an animal that can move. You have to take all that sensory input and you have to make a definitive decision about do you go this way or that way." The takeaway is unsettling but clarifying. If LLMs can produce complex behavior from simple rules, then consciousness may not be a mystical add-on to physics. It may just be what happens when a layered enough system has to make a decision.

@amazinggengar @OhioBikeLawyer You seem to believe that humans do not respond to prices. Leave a free bag of candy out on Halloween and test this out.

Water and electricity is so cheap as to be functionally free, why aren't people just leaving all the lights on and the faucets all the time? I've heard that premise before and it's absurd. People want to go places and a car on the road is the best solution for that. People staying home because of expected congestion is a problem. It means they aren't going out, they aren't attending events, they aren't spending money in the economy, they're staying home frustrated because the current traffic capacity is insufficient for existing demand. In California, congestion was why I started riding motorcycles in the first place, to lane split. So state and municipal governments, by keeping lanes restricted, are kneecapping their own economies potential by also limiting possible commerce. Is your assumption that people will drive their cars for hours and hours and hours, every single day, to no destination except to return home, if the roads were open? Going nowhere, just consuming a free slot on the road?

Boom - nailed the N+1 Lane theory

@amazinggengar @OhioBikeLawyer The paradox of induced demand is just the very obvious observation that adding capacity always leads to increased use. Demand is basically infinite for free goods. So if the goal is to allow people to get from A to B in a short amount of time, adding new lanes empirically fails

Doesn't... this just mean there was always more demand, and 1 new lane wasn't enough? Like, let's say you were a 40 waist but you only had a 30 waist pair of pants. Going up to a 32 still wouldn't work. For the size of your waist, there is a correct fit pair of pants, the solution didn't go far enough for the need. When a 3 line freeway is congested, when they decide to only add 1 more lane, what research did they do to determine that only 1 more lane was the solution? And where does the government get off deciding how much of a public utility the people get to have?

“And if a computer can grade a task, it can do that task.” Hey guys, @TIME says P=NP. Time to pack it up.

@BobMurphyEcon Are you saying that the apparent (but artificial) “consciousness” of LLMs are a counter argument to the evolutionary argument for self-awareness? I think i agree

The reason I'm giving a qualified defense of Dawkins against all the dunking, is that you guys are focusing on the wrong thing. One of the best critiques of materialism I've encountered goes like this: If all we need to explain human behavior are the laws of physics operating on the atoms in our bodies, then what extra reproductive fitness does "subjective experience" add? Dawkins was being pushed into that realization from the other end.

@lemire I agree but I’m genuinely curious: why is this post so long? LLMs seem to correlate with the death of microblogging

As an engineer, you should have some depth. AI will probably help you if you let it. Here is how the story of progress goes in people’s minds. Our ancestors coded in machine language, then in assembler, then in C, then in C#, then in JavaScript. And now we prompt Claude. Each time, we drop the previous layer. This is another instance of linear thinking about how progress works. We have seen this linear thinking applied to industrial policies: we no longer need to make steel, we can just order it online. If you view technology as a sequence of new layers where only the last layer matters, you are shallow. You could say, “Why would Elon Musk need to know how rockets work? He can just outsource these details to people he pays.” It amounts to saying that once you have the abstraction, you no longer need access to grounded reality. The problem with abstractions is that they are leaky. Here is Spolsky’s law: Non-trivial abstractions are leaky to some degree. Abstractions fail. Sometimes a little, sometimes a lot. There is leakage. Things go wrong. It happens all over the place when you have abstractions. By the way, people working for you are abstractions too, they are social abstractions. If you don't realize that abstractions are leaky, they you will be mislead constantly. The same applies to your own work when you build the architecture of your system. You are pushed in one direction only: more and more abstraction. But your abstractions are leaky. Things go wrong, and you often cannot understand from the highest level what is happening. We see the effect at the political level. Much of the West today is infected by technocratic thinking. A few smart people sitting in offices believe they can run the world because they have models running on Excel spreadsheets. I have this same problem as a professor teaching computer science. Why would anyone learn to write a for loop? ChatGPT can do for loops just fine. As a result, we have an increasing number of students who finish our introduction to programming course without any actual practical knowledge. We fail them and they don't understand why we do so. Why can't they just prompt their AI, isn't it the same as a coding? Here is what I think a good engineer ought to be able to do: work at different levels. It does not mean that everyone ought to regularly read machine language or understand the layouts of transistors on the CPU, but you should have some depth as an engineer. I am reading a lot more assembly today than I did 20 years ago, by a wide margin. In part because it is much easier. The same is true at different levels. I can much more easily explore how the microarchitecture of my CPU impacts my code. The information is more accessible. AI can more easily index this information for you. What this tells us about AI is that it will make the job of programmers more challenging when it is applied, not less. You will need better trained people, not less sophisticated people. Because, at some point, the abstractions will leak. And you'll need a good engineer. Trust me, you will.

@TheAhmadOsman Nah software engineers with enough experience know to not trust software

If you’re a “Software Engineer” and you don’t know how to bypass this then please pivot to being a Starbucks Barista because you’re ngmi

More people would be pro datacenter if every one had a beautiful open-to-the-public heated pool.

> *opens twitter* > red button vs blue button > "bet your wife doesn't have these cannons" > more red button vs blue button > "top 1% of all vaginas"

@AutismCapital They already did youtu.be/cRujf-pPCCU?si…

HBO please greenlight this for three seasons immediately.

It needs to pass its O.W.L. exam

@lthlnkso You should also put these thoughts into a substack so anyone searching the topic can discover your response

I’m skeptical of the 68,000 number. I think it’s based on motivated reasoning because it’s an unusually high estimate from a relatively small sample when better estimates exist.

perfect analogy of what it's like to work in consumer software for the past ten years

Easily the coolest frame for me even though the camera hadn’t focused yet. So many of the shots were taken with the camera pressed up against the glass, which makes sense. But seeing the window frame and the scale of the entire moon & earth in the shot really made me stop in my tracks.

@twibuznewss The fix for gen 2 was to allow the opponent to attack when the fire spin (or bind or wrap) was done

They say that when a data center comes to town, the crows begin to sing a strange atonal tune, the grass no longer reflects the moonlight and stays pitch black, and the children begin to whisper secrets instead of singing songs