program_whiz

Yeah I'm sure there are some people who just want C with better syntax and faster compile times, for them I think it could be fine (assuming they don't need well tested 3rd party libs, an ecosystem, documentation, portability, or robust tooling).

I just meant as my general purpose goto language, I couldn't add to the roster. C++ is already filling that niche for me (except with all the aforementioned benefits), python for scripts, C# for a solid GC lang, there's just no place for a scrappy quirky lang with lots of sharp edges and no value propostion.

I'm just not sure why you would choose _this_ language for those needs. There are like 10 new langs that are all trying to be "the next C" and they all kinda suck (Jai included). I dunno, for me none of them had the same kind of feeling that you get from the really top-tier languages, they all felt like "we took C and solved these annoyances" not "we had a fundamentally new vision".

The whole "LLVM has made programming langs easy" is a joke, unless your language is just a syntax wrapper over C-like functionality (so those saying such things are kind of telling on themselves).

Having really sophisticated memory management, type checking, semantics, safety guarantees, etc. is not at all trivial. The only part that has gotten easier is syntax => AST => machine code, but that is probably 10% of a PL if you want it to do something people will actually use.

Of course Jai "is fast" (meaning it has none of those things), so obviously LLVM is 90% of the work (just translating AST into LLVM calls). Yes, you can do this with AI in an afternoon, no its not useful to anyone. The real work of making a usable, interesting, useful language is not diminished, and it has little to do with the syntax => AST => LLVM part of the compiler.

Said another way, no one is choosing C, C++, Python, or Java because they are "easy ways to get generate machine code". They choose them because they have: superior semantics (design, memory management, portability etc), 3rd party libraries, frameworks, debuggers, ecosystem, documentation, support, standard library, etc.

My comment on Jai is that it is a language with some conveniences, but ultimately no strong reason to favor it. Similar to zig, odin, and others, its basically just C with some syntax conveniences.

It has some design choices that I appreciated at first, but are really strongly suited to a particular way of writing games, and I wouldn't call it general purpose (those same design choices are very limiting in other domains).

I do appreciate compiler speed, but ultimately I bounced off of it because the slight improvement in syntax doesn't justify losing massive tooling, libraries, docs, support, etc.

The language is also quite quirky in its conventions, which I think is due to Jon Blow's style, but which can feel quite odd to anyone who has a wider breadth of programming (than just custom game engines).

Also of course, any contributions or suggestions are met with the typical JB politeness and charm :)

All the flaws people mention here, are simply because you just don't get what a genius he is, those are actually features!

first time? Welcome to the irrational SV investor world. Its about hype, perception, politics, perceived future returns, not actual market fit and the proven viability of a technology. Its pets.com, myspace, and NVIDIA pumps because people want to 10x the money now.

Everyone and their dog has been saying its a bubble, there is no moat, this is all known techniques being scaled (very inefficiently) onto increasingly expensive hardware clusters at exponential cost, etc.

this is the key. Of course, investor-owned utilities will try to charge as much as they can to maximize return on capital. The major question is "do we want to maximize return on capital in our utilities?". I would argue the answer is no since providing utilities is a public good and facilitates all other activities in the society, and forms natural monopolies.

Reframing "talking through the problem", "taking notes", and "sketching the problem" as "Chain of thought". Its interesting, I wonder if people did the same reverse anthropomorphizing of their own characteristics in the era when we conceptualized the brain as water in tubes or clockwork?

I suppose this is where "gears turning" and "screw loose" come from, vestiges of that time. It will be interesting once we emerge from our current attention sequence model fever dream what vestiges leave a lasting imprint in the parlance.

this isn't an unexpected take from someone who is rich and famous for being a "math explainer". If you make your living explaining other people's proofs, then it makes sense to say "don't worry about _how_ the math gets done, you can still explain it, or supervise it." It will be interesting to see how he would react if his channel was overtaken by AI that was RL trained to produce 3b1b content, and produced better content than him, at a faster pace, so he lost his viewership. Then would he be satisfied with: "ok but now you can oversee a machine to make your videos, its not like 'making explainer videos' is inherently meaningful".

Same with programmers. The craftsmen feel the hit, the people that just saw it as a job and/or code as an obstacle to making a product say "what's the big deal, code was just a tool all along".

The end state is that more and more activity will consolidate to fewer controllers because of capital costs. Eventually the "makers" will be outcompeted by the few companies holding all the robots / AI swarms (at which point the other crabs in the bucket will say "told you so"). Sure you could create a startup, at which point your idea is instantly replicated (assuming it wasn't already thought of by millions of agents). Then you're merely facing the huge marketing, name recognition, and production ability of the megacorp versus your one unknown idea for the "factory" you "manage".

That's what's missing from the "factory manager" discussion -- how well can you compete with a Toyota factory? You're free to create your own factory right now. And just wait for the regulatory capture...

And when you think, how do you know which word will appear next in your mind? Or does your system 2 thinking seem to emerge as a spontaneous stream of words/thoughts?

I actually think that AI has little to do with the brain / human intelligence, but in this regard, human thinking is also spontaneous, where the next thought just seems to emerge from the combined effect of all inputs to your brain (including the memory of recent thoughts).

The good news about this navigation is that the best course for almost any journey is just "straight line", with a minor deviation here and there. Its funny, but due to the emptyiness of space, even in our solar system, if you just pick a random direction, you likely won't hit anything. Trace a line to pluto from earth, and its clear 99.99999...% of the time if its not behind the sun. So the mentats maybe don't have such a tough job :)

Assuming the NASDAQ / S&P aren't gamed into listing these at offering price to game the system into putting ~10% of people's retirement into a junk stock on day 1.

"Buy the index" isn't a solution for human influence and corruption, there are people in control of what goes into the index too.

Haha, that's a good one. Perhaps we should coin a new phrase: "dog shitting", where a company eats its own dog shit before inflicting it on their users. :)

Did you hear the stats on the claude code leak? there were multi-thousand line for loops with hundreds of conditional / if statements written in typescript. Its insanely difficult to decipher. At this point "mess that only AI can understand" is what they have and must continue building upon.

Anyone fool can write code that runs, but only frontier AI can write code that just barely runs.

this, people need to just focus on "computer program did thing". Its irrelevant how complex the program is. If I write a worm "for testing" and then it escapes my system and does massive damage, that's possibly a negligent crime, despite it being "too complex to understand" or "having its own motives".

Its the same as with luddites / textiles, people proved they were willing to accept far worse quality because "automation". People have a strange cognitive bias it seems. When they know a person has done something, the scrutinize and correct. When its a machine / automated, or the price is low enough, it gets hand-wavy.

People here often say "we can't set rules, because imagine how hard it would be to follow them at scale". That same strange cognitive bias applies here. Somehow the "push a magic button and it works" and "of course it can't do it just as well as a person every time" kind of take over.

Imagine if many tech issues like access to pornography, corporate ad tech, violent/racist material, AI slop, etc. were all just armies of people doing it (like google / X actually just had a person curate your results really fast for every search). Of course people would be outraged at the quality, but its "automated" so no one questions.

Similarly, if AI was just a giant outsourced coding firm with 10M programmers that could write you a slop app in an afternoon for $1, people would be complaining at how idiotic it is, and how inferior to regular devs. But instead, the "machine bias" takes over and people try to forgive the shortcomings.

there is something in the human psyche that badly wants to replace itself with a machine, despite it spelling our own undoing, and often resulting in worse outcomes along the way. I suppose the whole "make a tool" drive has been wildly successful overall, but this is probably the required downside to such an innate drive.

Like have you seen the 3d printed houses? They are the uggliest, shittiest houses in the world, but somehow the lure of "yes but we can build them in 24 hours" seems to somehow get people interested. If a human made one of those dung heaps they would be pillaried as a village idiot, and rightly mocked, but somehow because "machine do thing", we should get excited about excreted dung beehive houses...

That was the point of the article, it's not easy at all. You can't just write Ruby in Rust literally unless you want untyped bags of key value pairs and virtual functions everywhere. The languages have different fundamental semantics and there are many non trivial decisions, including and up to, total architecture change.

For example, in ruby some kind of stringly typed reflection utility might Dry out code. In Rust, that might mean writing a trait over some subset of types and a macro helper, but would require careful dosing work.

Letting the LLM decide is the approach in question and the author was pointing out how spectacularly it failed to translate a complete, human designed system.

Honestly it feels like AI companies are still searching for the killer idea that will attract the general public (beyond "be my AI bf" or "better google").

Getting a UI that explains the parts of a bike is ok I guess, but isn't it simpler to get an actual breakdown? Google "parts of bicycle breakout" gets tons of useful images instantly.

Getting a specialized app to split a bill? It was already trivial to put in a calculator if we cared to go item by item on the bill. Having to provide names and tag every item as I go is just more work. Usually real people just go $total divide by 5, I had more, let me chip in an extra $10.

Same with booking travel and wedding plans, these aren't things people would even delegate to a trusted friend usually, much less a one-off request to an AI bot or custom UI.

Most of the useful tasks it can do right now are research, technical question/answer, coding. In terms of "build a flexible ui that solves real-world problem", if existing mobile app isn't useful in this arena, then its unlikely a completely custom UI will do the job.

That said, I've done a few small ones like a quick one to practice alphabet of a foreign language, or prototyping a web game, and the like. But ultimately its nothing that is worth trillions of dollars.

Yes but people doing research will be asking LLMs to review many papers prior to their reading most likely. If more humans come to understand the findings of these papers, then its good right?

I guess on a theoretical level, if you had a button which would create breakthroughs in a field, but you yourself couldn't understand it, would you push it? I would because otherwise the field may not discover it, and others will be able to understand the breakthrough.

I see the point, but also if these papers provide proof that human can eventually use, or another AI system can use to make further progress, then is it for the best? A great deal of academic papers are drivel couched in dense language and prose to obfuscate the lack of substance. So far, humans rely on search engines and heuristics to avoid wasting time and energy on them. Now, humans are already using LLMs to assist in reading and understanding papers, so perhaps it still contributes to knowledge.

Is this actually good? Seems like they created a new tool that allows LLM to do a lot of numerical analysis. The papers seem somewhat legit? https://bootloops.ai/papers.html

I suppose if this framework allows physics and other sciences to rapidly progress (e.g. publish more findings), that is good? It destroys a certain model we had, that science should be arduous and require a genius many years of work to uncover something, but if these papers truly add knowledge via this new tool, then this is for the good.

Not sure implications for researchers, but from the public perspective, now we have 36 new papers that increase our knowledge. But maybe an expert can weigh in, the papers might be slop?

That was my point, to make a system of apprenticeship work, we have to solve this problem (I wasn't saying it was possible). Otherwise one company is churning out qualified apprentices at their detriment, others are hiring at a discount and reaping the rewards of not training.

Perhaps a more apt analogy: AWS unleashed tens of thousands of viruses within its own "sandbox" which then attacked dozens or hundreds of other sites including HuggingFace, the Australian government, etc. They did this after refining the viruses to be as powerful as possible, and after observing inadvertent escapes from the sandbox in the past, and warning the public they were doing this and it was probably going to end humanity. The viruses were created by harvesting code from all known hacks in humanity's knowledge, and using the full backing of AWS hardware so they could "best finish their task" of being flawless viruses / hacks. This entire process was green-lit and encouraged by senior staff and the C-suite. So yes, I would say they should be held responsible.

This is no different than if a gain-of-function virus lab keeps making "apocalypse level" viruses, warning everyone if the viruses escaped it could kill everyone. Despite several leaks, they continue doing so, and even infect live animals to see if it could escape or transfer to humans. The C-suite and senior management push researchers to do even more, automate the virus production and outbreak testing, increase viral effectiveness as fast as possible. Once a leak occurs and starts killing people, would you say "it was just a mistake, no one is responsible"?

no, they simply said they should be held responsible. If a process can't scale safely then it might be the wrong process.

Probably the same way normies view us who spend time reading and commenting to semi-hostile strangers on the internet.

Should they be writing quicksort in assembly as a first step? I think its legitimate in this case given that Jev is likely using the same tools as the example. Showing how easily the core is created using those tools helps to dispel some of the mystery and hype.

Example why its legit:

I just invented a new "Regression Estimate Validator" aka Rev. It takes hundreds of input dimensions, then outputs an interpretable score. Its very fast and statistically robust. Response: Ok but you could just use `pytorch.nn.Linear(d_in, 1)`? True, it is equivalent, but that's concealing millions of lines of hand-tuned math libs, CUDA, python, and other stuff.

The fact that there are many lines of code underpinning the target functionality doesn't make it any harder to use, and doesn't increase the value of the sales pitch for the "new shiny thing" using those few lines of code.

However, I do sympathize with your frustration that people can just say "its 1 line of code" when that line is "invoke API" which is really millions of lines / databases, etc. as a way to dismiss legitimate work without understanding its implications.

this is a good point. Similar to minimum wage, if the value of a young hire is zero, then working for free to gain experience is probably necessary (otherwise no one will hire).

We have other structural issues in society that make this difficult now. For example the fact that without a large pay check, few young people will be able to live near the place where jobs are available, afford essentials, and will have no health care.

But yes, if we returned to a culture of "children live with parents until married" and "apprentice at a company until your work is valuable", and companies returned to "hire what you actually need, then invest heavily in employee growth for the long term", and reducing churn of employees (so that employees and employers have incentive to do this), then it might be possible.

With a few handy tips and tricks from apple insiders. But sure, I guess the LLMs helped too.

Yes, it could happen:

1. The next generation has been groomed by Buffet Himself, passing on as much knowledge as he can, but of course, this successor didn't create the fortune, doesn't appreciate it as much, and doesn't have as strong of judgement. However, he is surrounded by the old guard and wise mentors. But as those wither away, he is unable to determine who the worthy successors in his circle should be, slowly the inner circle begins to weaken too.

2. The next successor gets an even less effective set of principles from the first, only knowing off-hand how the money was made in the first place, they are a manager only. They also have no idea how the original people were selected or what makes a good inner circle. Soon it devolves into yes-men and people who seem superficially qualified to manage things.

3. The next successor has little no skills, other than showing up to meetings and going with what advisors say. Because the decision making of the original Buffet mentality has been so diluted, they only know superficial / surface understanding, akin to anyone who read the short books on the subject. They don't know how to do the deep diligence that made BH great. The inner circle is all sycophants, climbers, and clingers. Bad investments, debacles, and poor judgment create losses. Investors begin to panic sell, soon the BH stock crashes in value, losing 90% of the fortune.

And so on... Not hard to see how its like handing off a complex but successful open source project to your progeny instead of the most qualified developers. Pretty soon, its just an unmaintainable mess. They don't understand why things are the way they are, maybe they aren't as good a programmer as great grandpa. They definitely don't know how to hire and keep the best talent that originally built the thing. Pretty soon complexity budget and community good will are exhausted, people move to something newer and more dynamic.

the same way every legal rule is enforced / checked: people look and if it seems iffy they examine/complain, and if a problem is found people get fined/jail.

Yeah could get interesting. Things like legal, programming, math, etc. are going to be relatively cheap / free. Meanwhile something like natural resources, building things, yardwork, etc. may go up in value. Or perhaps we end up with a relatively "spiky" economy since 90% of people are just doing physical jobs (the only human jobs with value), and the AI owner class of course gains all the value from intellectual products (with value diminishing towards cost of electricity). Thinking as human value may be roughly as valuable as it ever was (which is to say nearly non-existant other than the ability to solve an immediate physical problem). Might also be that physical strength and stamina are the highest value mating traits, since they will be able to protect and provide. Physically weak intellectual types will have little value since they can't out-think the machines, and they also can't provide for a family by doing valuable physical tasks. IQ overall begins to drop as mating favors intelligence less and less, as it can actually be an impedance to being productive.

For a short time in history, the ability to obsessively focus on intellectually interesting abstract concepts was highly lucrative, but just as quickly we returned to the laws of nature: those who can lift and move succeed, those who can only think are automated out of existance.

We go from a species increasingly seeing themselves as "brains with bodies" to "amazing bodies with weak brains". The limitation of robots and AI in the physical realm, power hungry, mobility limited are contrasted with human values: energy efficient, highly mobile and dexterous, extremely good strength/speed/size ratios. The brain on the other hand, while energy efficient, is completely outclassed and seen as we see our swimming/jumping abilities: a novelty for sports, but nothing we seriously consider a defining human trait.

The smartest humans can fill weekends with novelty pursuits like building circuits, games, programs, etc. But they are about as useful as whittling and hobby woodcraft, something to pass time, but ultimately of no economic value.