paip-lisp VS Graal

PAIP by Peter Norvig, Chapter 23, Compiling Lisp

https://github.com/norvig/paip-lisp/blob/main/docs/chapter23...

Emacs is so much more than a text editor! But I need to stay on topic...

I believe your assessment of LISP (and therefore of MacArthy)'s impact on AI to be unfair. Just a few days ago https://github.com/norvig/paip-lisp was discussed on this site, for example.

Sounds like a great project idea to make a toy demo of this direction you'd like to see. Maybe comparable to https://github.com/norvig/paip-lisp/blob/main/docs/chapter15... and https://github.com/norvig/paip-lisp/blob/main/docs/chapter8.... which are a few hundred lines of Lisp each, but do enough to be interesting.

You could look into Paradigms of AI Programming by Peter Norvig which might interest you regardless of Lisp content.

Lisp has great power, examine PAIP, part II chapters 7 and 8.

A computer running Prolog reasons, and that only requires a couple of pages of code. So it seems feasible that the network could have learned some ability to reason within its network.

IMHO it's because lisp shines to manipulate symbols whereas the current AI trend is crunching matrices.

When AI was about building grammars, trees, developing expert systems builds rules etc. symbol manipulation was king. Look at PAIP for some examples: https://github.com/norvig/paip-lisp

This paradigm has changed.

Origen: Conversación con Bing, 4/4/2023(1) gigamonkey/monkeylib-binary-data - GitHub. https://github.com/gigamonkey/monkeylib-binary-data Con acceso 4/4/2023. (2) paip-lisp/chapter4.md at main · norvig/paip-lisp · GitHub. https://github.com/norvig/paip-lisp/blob/main/docs/chapter4.md Con acceso 4/4/2023. (3) bibliography.md · GitHub. https://gist.github.com/gigamonkey/6151820 Con acceso 4/4/2023.

If anyone is interested PAIP is downloadable at https://github.com/norvig/paip-lisp

Contrary to what vocal Kotlin advocates might believe, Kotlin only matters on Android, and that is thanks to Google pushing it no matter what.

https://spectrum.ieee.org/the-top-programming-languages-2023

https://snyk.io/reports/jvm-ecosystem-report-2021/

And even so, they had to conceed Android and Kotlin on their own, without the Java ecosystem aren't really much useful, thus ART is now updatable via Play Store, and currently supports OpenJDK 17 LTS on Android 12 and later devices.

As for your question regarding numbers, mostly Java 74.6%, C++ 13.7%, on the OpenJDK, other JVM implementations differ, e.g. GraalVM is mostly Java 91.8%, C 3.6%.

https://github.com/openjdk/jdk

https://github.com/oracle/graal

Two examples from many others, https://en.wikipedia.org/wiki/List_of_Java_virtual_machines

Pkl was built using the GraalVM Truffle framework. So it supports runtime compilation using Futurama Projections. We have been working with Apple on this for a while, and I am quite happy that we can finally read the sources!

https://github.com/oracle/graal/tree/master/truffle

Disclaimer: graalvm dev here.

That's pretty interesting. It's not as aggressive as Bee sounds, but the Espresso JVM is somewhat similar in concept. It's a full blown JVM written in Java with all the mod cons, which can either be compiled ahead of time down to memory-efficient native code giving something similar to a JVM written in C++, or run itself as a Java application on top of another JVM. In the latter mode it obviously doesn't achieve top-tier performance, but the advantage is you can easily hack on it using all the regular Java tools, including hotswapping using the debugger.

When run like this, the bytecode interpreter, runtime system and JIT compiler are all regular Java that can be debugged, edited, explored in the IDE, recompiled quickly and so on. Only the GC is provided by the host system. If you compile it to native code, the GC is also written in Java (with some special conventions to allow for convenient direct memory access).

What's most interesting is that Espresso isn't a direct translation of what a classical C++ VM would look like. It's built on the Truffle framework, so the code is extremely high level compared to traditional VM code. Details like how exactly transitions between the interpreter/compiled code happen, how you communicate pointer maps to the GC and so on are all abstracted away. You don't even have to invoke the JIT compiler manually, that's done for you too. The only code Espresso really needs is that which defines the semantics of the Java bytecode language and associated tools like the JDWP debugger protocol.

https://github.com/oracle/graal/tree/master/espresso

This design makes it easy to experiment with new VM features that would be too difficult or expensive to implement otherwise. For example it implements full hotswap capability that lets you arbitrarily redefine code and data on the fly. Espresso can also fully self-host recursively without limit, meaning you can achieve something like what's described in the paper by running Espresso on top of Espresso.

I'm also using GraalVM if that's of any help.

Quarkus is one of Java frameworks for microservices development and cloud-native deployment. It is developed as container-first stack and working with GraalVM and HotSpot virtual machines (VM).

Apologies, I didn't mean to imply DCEVM went poof, just that I was sad it didn't make it into OpenJDK so one need not do JDK silliness between the production one and the "debugging one" since my experience is that's an absolutely stellar way to produce Heisenbugs

And I'll be straight: Graal scares me 'cause Oracle but I just checked and it looks to the casual observer that it's straight-up GPLv2 now so maybe my fears need revisiting: https://github.com/oracle/graal/blob/vm-23.1.0/LICENSE

> to be compiled to a single executable is a strength that Java does not have

I think this is very outdated claim: https://www.graalvm.org/

https://github.com/oracle/graal/issues/7182