anko

We're talking past each other a bit. I was just trying to give examples of where observability on the jvm isn't that great, because you were were stating it's where AI needs the most help.

The parent was saying these new features don't matter as much post-AI and i think I agree with them. The AI can just write in rust if you need to optimise a hot loop, but if you need observability, you could do worse than the BEAM.

> GC pauses in the JVM have been optional for a few years now. ZGC doesn't have GC pauses.

yeah that's a fair comment, zgc is a lot better for pauses. I'd still say that it pulls along a fair bit of incidental complexity - it encourages you to allocate a fair amount of memory to your heap, which isn't ideal in this world of kubernetes and microservices. If you leave on uncommit (returning memory to he OS periodically) you get extra latency penalties which are just as painful as garbage collection stalls IMHO.

I now manage a team writing languages on the jvm. I have found the jvm ecosystem terrible for observability. Examples;

- junit parallelisation - how are shards handled? how do you balance the tasks across forked processes? What is the bottleneck? Options are 1) pay someone for better tooling or 2) write your own

- long pauses in garbage collection - how do you know which objects are causing the pauses? the options; 1) profiling 2) analysing heap dumps that you periodically capture 3) add metrics or gc logging

- what is the performance bottleneck? options 1) profiling

Sure AI can do this stuff, but it's painful and time consuming

Contrast it to Elixir on the BEAM;

- exunit parallelization - basically free and because you don't have coupling due to OOP. mocks are basically an antipattern

- long pauses due to gc? They just don't happen - everything is isolated and can be cleaned up in parallel.

- performance bottleneck? Open inspector and see what is doing all the reductions, and if any of the inbox queues are backlogged. You don't have to profile, you can just look in production - memory? Open inspector and sort processes by size descending. Again no profiling needed

I would be interested to know what speeds you can get from gemma4 26b + 31b from this machine. also how rocm compares to triton.

100% this, i've been finding metal is getting very compelling against aws. For example latitude has 4 real cores and 32 GB of ram for $92/month.

https://www.latitude.sh/pricing/c2-small-x86?gen=gen-2

hetzner doesn't even have specs this low from what i can tell!

https://www.hetzner.com/dedicated-rootserver/#cores_threads_...

I have been thinking along these lines myself. Most of the time, if we need to calculate things, we'd use a calculator or some code. We wouldn't do it in our head, unless it's rough or small enough. But that's what we ask LLMs to do!

I believe we juggle 7 (plus or minus 2) things in our short term memory. Maybe short term memory could be a tool!

We also don't have the knowledge of the entire internet in our heads, but meanwhile we can still be more effective at strategy/reasoning/planning. Maybe a much smaller model could be used if the only thing it had to do is use tools and have a basic grasp on a language.

I would love if tantivy had a single file format, eg. .tantivy extension so you could drag it into a notebook like you can with .sqllite files.

my demo ran out of time before it did anything :(

> The cost of computing decreases over time. No one will pay $100 Billion to train GPT-6. That is absurd. The current top supercomputer in the world (Frontier) cost $600M.

Just wanted to ask the question - do you think frontier has provided more or less value to the world than gpt-4?

> The real issue is running out of the input window.

isn't this what abstractions are for? you summarise the key concepts into a new input window?

I wonder if AMD would adopt this too?

> Gross. Python is a million times better than ruby to read and write

why do you think that?

which one is elixir liveview?

I agree 100% and I'd add, static typing helps when you inherit a poorly written codebase. This unfortunately is probably 99% of codebases in the wild. It has happened so many times when i've seen a lack of test coverage, a lack of understanding of the codebase but the business requirement to make changes.

Having a type system in place makes minor refactoring possible in this nightmare scenario.

I have been in the situation of poorly written ruby codebases and I can tell you 100% that I would prefer to have a poorly written java codebase with its static types. I prefer ruby as a language but man when it's bad, it's terrible. Just trying to work out the intent of a function when multiple types are passed in as the same argument over the codebase is pure hell.

aussies are doing a similar thing although they install by pulling via tractor and the panels concertina out see https://suncable.energy/

they are doing an underwater cable to supply energy to singapore

server side computing is probably my take - it does handle more than that, eg. nerves but server side computing is the big win.

I'm not too sure - scala really has a crazy number of language features, which makes the scope of it way bigger. I'd say kotlin : Java is closer :)

Care to elaborate? I myself feel this way, but when i break it down I can't give good examples.

2022 m1 macbook pro here - and i have one from work too. never had either crash, haven't plugged this one in for literally days, and right now i have an ide, vscode, ableton, slack, chrome with like 400 tabs in multiple windows and it's cool to the touch.

I think you'd like apple silicon macs.

why do you say that? genuinely curious.

i'd love to know the operations they were doing and what they used the sorted sets for. I find for this type of thing, if the ids of the users are integers you can often use a bitset and optimise the crap out of it via SIMD. If memory is a huge concern, or if the data is super sparse you can use a roaring bitset.

I have solved a similar problem, in a similar way and i've found polars <https://www.pola.rs/> to solve this quite well without needing clickhouse. It has a python library but does most processing in rust, across multiple cores. I've used it for data sets up to about 20GB no worries, but my computer's ram became the issue, not polars itself.

it's compulsory to vote. If people start rocking up and it says they have already voted, it will be caught pretty quickly.

Australians are also fairly trustworthy

> Go's M:N scheduler is an incredible piece of technology that is (IMO) unmatched by any other mainstream language.

I guess it depends how you define mainstream, but in Rust, Rayon has a work stealing scheduler too.

On the other hand, it has existed in Erlang for decades, and Elixir takes full advantage of it.

As for my 2c, I would say Rust is a better choice than Go in terms of the first language to learn. The main reason for this, is it is easy to embed in other languages. When I get to a problem that is too slow in a higher level language, eg. Python or Elixir, Rust is a great way to solve this problem. Just have a look at polars (https://www.pola.rs/).

yep.. i even just miss the google reader days. why don't sites use rss/atom anymore? it drives me nuts

This is a really good comment, and I hadn't really thought of it in those terms. So it's insightful to me. It encapsulates a lot of things I hadn't really directly tried to answer before.

My previous answer is that good code makes it easy to discover intent.

But I think the semantics are important too - for example in scala we use monad transformers to treat futures (async code) much like lists. But the problem with this approach is it's not clear without inspecting the type signature if you're doing something that has a high algorithmic complexity eg. spawning threads or not.

I think the best language i've ever read for semantics is elixir.

But i think the lack of static typing makes it harder to code review, especially on github. Maybe Gleam is the answer?

What language do you like?

cool stuff! I was trying to do something similar on Arm Neon (m1 pro) with the CNT instruction https://developer.arm.com/documentation/ddi0596/2020-12/SIMD...

I believe it does 128 bits per instruction, but I'm still struggling with rust w/ asm.

Along my journeys, however, I found this repo https://github.com/WojciechMula/sse-popcount/ which has tons of competing simd implementations for both intel and arm.

life eg. cellular growth

Really interesting article! so does this mean you could use an eex Engine to render liquid? (https://shopify.github.io/liquid/)

I think the problem is a bit more nuanced, but i don't have a perfect answer.

This is fine but relying on an IDE for code reviews really sucks. I'd much prefer to be able to do it on github. And it sucks for any language which infers types :( Scala is in particular awful for reviewing on github

appreciate the tip on Zod :) It looks like what i've been looking for!