I read the book years ago, and while I think it's interesting, today I think it's better to learn lambda calculus directly, without the Lisp "gimmick".

"[It's better to] learn type theory, category theory, lambda calculus, logic, etc." I have heard a similar notion for years. And I tried. Oh boy, I tried. Grokking Haskell felt like a Sisyphean grind. And then I tried Lisp. I dunno what happened to my brain, but the sheer pragmatism and plain simplicity of it suddenly made all the things that before felt so difficult to grok clearer than Lego-set instructions. Recursion, with its small intricacies that confused me for years, made me realize how simple it actually was, I just wasn't seeing it the way it actually is. Y Combinators, Folds, Monads, Applicatives, Laziness, and many other things.

I wish I had found Lisp many years sooner. That simplified Haskell, Rust and Idris for me. The downside is that it turned out to be vastly pragmatic, and for personal stuff I'm on Lisp. Even though most things at work are not.

So, maybe you should honestly self-reflect: had that book not happened in your life before, would you even consider understanding LC today, unadulterated by "gimmicks"?

I think you're making a good point, perhaps it was necessary in my path (which was roughly C++ -> Python -> Common Lisp -> Forth -> Haskell -> soon Lean).

But perhaps we're teaching lambda calculus wrong. Let and lambda are essential building blocks of it, and Lisp is a sort of special case.

I don't think it has to be hard - To Mock a Mockingbird is just as enjoyable as LoL. It's just difficult to see significance of LC for programming, I think, because people do not think of lambda calculi as programming languages.

> I think it's better to learn lambda calculus directly, without the Lisp "gimmick".

The book isn't about teaching lambda calculus, though. It's covering things you can do in Common Lisp, specifically around macros.

And around lexical binding with functions as first class values. That to me is the lesson that is possible in other non-CL environments. E.g. JavaScript.

I agree but the reality is most authors want to use their OSS creations at work, which usually means they will make a compromise with capitalists who reject copyleft licenses.

Many human problems could be solved if humans were less willing to compromise with greedy people, but unfortunately authors are too nice in general to do that.

I predict the opposite: Humans will collectively create something like an LLM, but curated. That will be next level for Wikipedia-like project.

Think about it - LLM is just a computer program that predicts a next word. So it has a very detailed, formal description of each concept it can represent in its residual vector.

I think humans will understand (perhaps with AI help) these formal descriptions and put them into a giant database.

You say, building ontologies with a specific intent will actually lead to intelligence at a similar level of current AI?

This would be a severe blow to the bitter lesson, and generally vindicate the AI researchers of the 80s that put a bet on symbolic processing

Well, the ontologies are there inside LLMs, humans just don't know them. There is nothing that contradicts with bitter lesson to what I said.

Companies that let SW engineers go because of productivity improvements are being stupid. These people will go and build new products, and will compete with your company.

If your company is a big corporation, I don't think they need to worry about the file and rank SWEs. I know that I'm going to compete with Google, Meta or Microsoft. But stupid or not, that's what they're doing at the moment.

Yeah they don't need to worry about them, they will just probably join some startup that the bigco can eventually buy, instead of innovating internally, it's just bad management as usual. Bigcos might not see smaller companies as a competition, but they do compete with them for SW engineers.

Why is it so surprising? Humans can make compilers that are better coders than they themselves are.

Humans cannot teach another person calculus via manual brain surgery, though.

Not yet. Maybe I'll still be alive when we figure that one out. For now, the most advanced brain surgery I'm aware of is to cure drug addicts of their addiction by scanning their brains while showing them images of drugs and paraphernalia to find where it's located, and the using ultrasound to operate on that region.

Like a refusal abliteration. You need to run the model to locate the refusal though, you can't just stare at it

Humans do something more impressive: we indirectly figure out what the wrong weights are and correct them - just by talking and/or drawing. Theory of mind is our unreplicated super-power.

And you can teach another person to make herpes virus.

LLM is just a computer program, we have binary code for it. The human brain is not. It would be unethical to even attempt that.

> It would be unethical to even attempt that.

Then pick a smaller organic brain which doesn't have the ethical problem.

The closest we would know about how to teach a honey bee calculus, is to train an LLM, then stick around a billion tiny electrodes into the honey bee and do Hebbian learning to rewire it completely to match the LLM, which would likely completely erase anything the honey bee had learned, or it might not because we are missing something fundamental with Hebbian theory and (AFAICT, I'm not a neuroscientist) we don't all agree on what.

> Obviously this doesn't work on the internet

Not obvious to me. I am generally a fan of Cyberspace manifesto and the free Internet, I think it's great people can reach outside their ingroup and talk to strangers and ostensible enemies.

But, that doesn't mean we should give up physical security, the guarantee that the connecting party comes from a certain physical location (state, company). I think allowing connections from anywhere by default is fundamentally flawed security architecture, for certain things.

I don’t think North Korean hackers are attacking things from their North Korean IPs. They just buy a residential proxy. How would you prevent that?

I don't really feel like an expert on this, but perhaps residential proxy shouldn't be allowed to connect to critical infrastructure without additional authorization?

The point about a residential proxy is that you can’t tell it from a normal residential user. If a user is supposed to access the banks website, how would you filter out the North Korean? Or if a regular user is supposed to be able to do an interview with someone working at binance, how would you filter out the North Korean?

You can't tell it today, because the thing is legal. But maybe you shouldn't be allowed to misrepresent your identity when connecting to a bank. And if you have to, then there would be an additional check or the operation would be delayed.

If you're running a proxy, it's your responsibility to keep NKans out.

I am not saying close down all the Internet. But I do believe there should be tiers.

Big vs little endian are equivalent up to rotation, which includes permutations.

But it's actually much weaker condition than it looks, because, for example, lot of representations of boolean circuits are equivalent up to linear transformations over Z_2^n.

Anyway, if they truly proven such a theorem you won't find "incompatible" representations of the same thing.

When you get a dollar bill, you can actually tell whether it's from oil or not? I can't..

What's really amazing are the lengths by which people justify they cannot have a nice society. It's easy to see, mathematically, the willingness to share has no relation to absolute GDP or where it comes from.

It's public money. I assume the government keeps track.

Way to miss the point. Any government can take any share from economy and redistribute it more fairly. There is nothing specific to oil that makes society more equal.

The argument "but Norway has oil" is so tiring. So what, US has a big tech with huge profits. Why can't you have a UBI from ads? Of course you can.

I thought we have learnt from Microsoft, and my father thought we learnt from IBM, my grandfather thought we learnt from AT&T, my grandgrandfather thought we learnt from Standard Oil..

IME the models know some basic information about all the popular games, including some basic strategy, but they don't know/remember the details to be even a moderately familiar player. And usually if you ask a question they will google it.