Refefer

This is a tough sell. Yes, those languages (with some small nits about Ada) can accomplish the same safety guarantees, but they're nowhere performant enough in practice or memory efficient compared to Rust. A big part of the original mission of Rust was safety without performance compromises which for the most part its accomplished, though the price is paid during compilation. Further, their runtimes and limitations make it difficult to work directly with operating systems or low level system hardware. And I say this as someone who has written Haskell code in production.

That said, I would love for Idris to continue to develop. I'm a big believer in dependently typed languages and would actually improve correctness, assuming there are reasonable ways to avoid the other trappings of the language.

One of the big learnings from 3.8 27b is adding reasoning budget really hurts the model. you need to let it spin for as many thinking tokens as it wants to to get it out. Another big takeaway is reasoning effort set to low doesn't save you tokens: low is pretty uncertain about things so it ends up thinking more (you can find some tests from folks on youtube). The final question, as always, is what quant are you running it at? KLD matters _a lot_ when it comes to its performance and it especially manifests with MTP/DFlash acceptance rate which makes those long thinking traces take a long time.

Pragmatically, cost and ease of access is especially important in suppressed countries or ones with unstable infrastructure. While the devices you're talking about has lots of conveniences, distribution and price dominate in lower income regions.

For a side project, sure. But in first world countries, the odds of infrastructure breakdown or suppression of Internet is incredibly rare. In Iran's case, suppression is a weapon so phone only makes a lot of sense.

Systems Languages are considered niche these days?

Menlo Park, Ca - Full time - Onsite - Frontend, AI Systems, Dev Ops

Blackbird is an artificial intelligence technology company focused on solving important challenges faced in today's ecommerce space. Our stack is primarily in functional style Scala (we are heavy functional programming users) and a polyglot AI stack written in everything from Python to Scala to Haskell. Our team has worked on everything from search at Google, distributed systems at Twitter, and self driving cars at Stanford. We work on and implement the state of the art in machine learning.

We're currently looking to add some great engineers to our team. Want to write highly scalable software with the architects who scaled Twitter and Google? Want to run ops for software designed to handle hundreds of millions of API calls? Want to design next generation user interfaces? Want to scale the state of the art in machine learning systems? jobs at blackbird.am

Feel free to ask any questions directly or in thread!

Implicit is basically just an implementation detail. The idea of only allowing one typeclass instance per data is generally referred as confluence and you're correct in that scala doesn't attempt to enforce it.

I understand the Haskell communities desire for coherent typeclasses, but I still find the newtype work around cludge to allow multiple implementation of, say, Monoid to be quasi hacky. What's worse, you can still fairly easily define multiple instances of the same typeclass accidentally (orphan instances) and the compiler won't catch it.

Menlo Park, Ca - Full time - Onsite - Frontend, AI Systems, Dev Ops

Blackbird is a ventured backed, artificial intelligence technology company focused on solving some important challenges created by the shift from desktop to mobile. Our stack is primarily in functional style Scala (we are heavy functional programming users) and a polyglot AI stack written in everything from Python to Scala to Haskell.

We're currently looking to add some great engineers to our team. Want to write highly scalable software with the architects who scaled Twitter and Google? Want to run ops for software designed to handle hundreds of millions of API calls? Want to design next generation user interfaces? Want to scale the state of the art in machine learning systems? jobs at blackbird.am

Clearly a chatroom with half a million individuals is unusable from pretty much every perspective. That said, a chat server with N chatrooms and a total population of 500k users sounds like a good day on IRC and well within the realm of what something like this could potentially handle.

Menlo Park, Ca - Full time - Onsite - Frontend, Backend, Dev Ops, ML/AI

Blackbird is a stealth, ventured backed, artificial intelligence technology company focused on solving some important challenges created by the shift from desktop to mobile. Our stack is primarily in functional style Scala (we are heavy functional programming users) with most of our AI stack in Python and C++.

We're one of a few startups that do AI research above and beyond product development. We host regular talks on multiple disciplines ranging from systems to functional programming to deep learning.

The team was founded by former Stanford CS graduates that built self driving cars, search at Google and Yahoo Research, co-authored the google file system and scaled Twitter to 200 million users. Our open source code powers Snapchat, Tumblr, Wikipedia in production today.

We're currently looking to add some great engineers to our team. Want to write highly scalable software with the architects who scaled Twitter and Google? Want to run ops for software which is designed for fault tolerance? Want to design next generation user interfaces? jobs at blackbird.am

Menlo Park, Ca - Full time - Onsite - Frontend, Backend, Dev Ops, ML/AI

Blackbird is a stealth, ventured backed, artificial intelligence technology company focused on solving some important challenges created by the shift from desktop to mobile. Our stack is primarily in functional style Scala (we are heavy functional programming users) with most of our AI stack in Python and C++.

We're one of a few startups that do AI research above and beyond product development. We host regular talks on multiple disciplines ranging from systems to functional programming to deep learning.

The team was founded by former Stanford CS graduates that built self driving cars, search at Google and Yahoo Research, co-authored the google file system and scaled Twitter to 200 million users. Our open source code powers Snapchat, Tumblr, Wikipedia in production today.

We're currently looking to add some great engineers to our team. Want to write highly scalable software with the architects who scaled Twitter and Google? Want to run ops for software which is designed for fault tolerance? Want to design next generation user interfaces? jobs at blackbird.am

Fiefdoms make money for the lord of the manor

Currently Ops, Systems, and UI are our big needs. Great ML folks are always welcome as well!

Menlo Park, Ca - Full time - Frontend, Backend, Dev Ops, ML/AI

Blackbird is a stealth, ventured backed, artificial intelligence technology company focused on solving some important challenges created by the shift from desktop to mobile. Our stack is primarily in functional style Scala (we are heavy functional programming users) with most of our AI stack in Python and C++.

We're one of a few startups that do AI research above and beyond product development. We host regular talks on multiple disciplines ranging from systems to functional programming to deep learning.

The team was founded by former Stanford CS graduates that built self driving cars, search at Google and Yahoo Research, co-authored the google file system and scaled Twitter to 200 million users. Our open source code powers Snapchat, Tumblr, Wikipedia in production today.

We're currently looking to add some great engineers to our team. Want to write highly scalable software with the architects who scaled Twitter and Google? Want to run ops for software which is designed for fault tolerance? Want to design next generation user interfaces? jobs at blackbird.am

That's not really true. Erlang's VM is fantastic at GC with thousands upon thousands of green processes multiplexed onto the system threads, allowing soft realtime performance. Similarly, Haskell's Parallel Strategies library works well with the Parallel GC. Immutability makes this a whole lot easier.

Or were you referring to OCaml in particular?