Fusion VS go

- Even frequent exchanges like, “Hey, I’m heading to Costco, need anything?” where the follow-up is easier spoken than typed, or may require a brief brainstorming - “Oh, remember our neighbors are visiting us on Sunday?”

That’s how 8 years later (2 years ago) me and my co-founder decided to implement a new chat app.

— Technology —

To make it short, I’ll post just one point here: Actual Chat is based on Fusion (https://github.com/servicetitan/Stl.Fusion) - think MobX / computed observables, but distributed. In Actual Chat, the state it manages spans from our servers to every client app, creating an eventually consistent “state mesh”. The unified state management, where clients and servers use exactly the same abstraction to “observe” the changes happening to any bit of content, is quite a challenge from the technology standpoint. IMO it alone deserves a brief look.

P.S. Thank you for reading up to this point!

P.S. The app is created with Fusion, which is another cool thing for Blazor: https://github.com/servicetitan/Stl.Fusion

So there are different ways how you can do this, there are multiple different protocols for Unity, for example. There is also this more generic state replication framework.

There is this lib: https://github.com/servicetitan/Stl.Fusion

The library benchmarked in the article is Stl.Fusion: https://github.com/servicetitan/Stl.Fusion. I've only learned about it today, and the documentation is a bit messy, but that seems to be a really interesting project. The author describes it as a .Net library to quickly develop efficient, distributed, real-time web applications.

Disagree with every "no" here :) The answer is yes, but you need a fairly fancy "extra": https://github.com/servicetitan/Stl.Fusion/

A Discussion about including this package in Go as encoding/json/v2 has been started on the Go Github project on 2023-10-05. Please provide your feedback there.

I like the Principles section. Very measured and practical approach to releasing new stdlib packages. https://go.dev/blog/randv2#principles

The end of the post they mention that an encoding/json/v2 package is in the works: https://github.com/golang/go/discussions/63397

There used to be the GO FIPS branch :

https://github.com/golang/go/tree/dev.boringcrypto/misc/bori...

But it looks dead.

And it looks like https://github.com/golang-fips/go as well.

I'm not sure what exactly you mean by acknowledgement, but here are some counterexamples:

- A proposal for sum types by a Go team member: https://github.com/golang/go/issues/57644

- The community proposal with some comments from the Go team: https://github.com/golang/go/issues/19412

Here are some excerpts from the latest Go survey [1]:

- "The top responses in the closed-form were learning how to write Go effectively (15%) and the verbosity of error handling (13%)."

- "The most common response mentioned Go’s type system, and often asked specifically for enums, option types, or sum types in Go."

I think the problem is not the lack of will on the part of the Go team, but rather that these issues are not easy to fix in a way that fits the language and doesn't cause too many issues with backwards compatibility.

[1]: https://go.dev/blog/survey2024-h1-results

Now, I’m not going to use C++ again; I left that chapter years ago, and it’s not going to happen. C++ isn’t memory safe and easy to use and would require extended time for developers to adapt. Rust is the new kid on the block, but I’ve heard mixed opinions about its developer experience, and there aren’t many libraries around it yet. LLRD is too new for my taste, but **Go** caught my attention.

Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!

net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements

Make sure you have Go installed https://go.dev/.