solana VS rust

Solana (9700 GitHub Stars) https://github.com/solana-labs/solana

EIP Core standards: Changes to Solana’s core code go through “feature gates” in the Solana repo. Yes, it’s much less organized than the EIP pages you are used to, and a headache to understand or keep up with. A cost of the speed of development, I’m told.

I visited the project on github (https://github.com/solana-labs/solana), and tried to get an overview of the ~800 open issues and ~100 open PRs.

Solana

With the introduction of new and advanced blockchain platforms in the Web 3.0 scene, the narrative around Ethereum has slowly shifted towards its younger “Ethereum Alternatives”. Solana, Avalanche, and MultiversX (former Elrond) are some of the crypto blockchains that are given this terminology, as they share similar features but are comparatively cheaper and better than Ethereum.

I understand this initiative is connected with Solana network [1] in some way?

[1] https://solana.com/

They do, actually: https://github.com/solana-labs/solana/security/policy

Not sure I understand your question, but if you want the source code you can find it on github (https://github.com/solana-labs/solana)

Some topics that may be discussed in the next call include @ShinobiSystems Timely Vote Credits proposal (https://github.com/solana-labs/solana/blob/master/docs/src/proposals/timely-vote-credits.md), @elusivprivacy new built-in cryptographic operations to accelerate ZK verification (for privacy tech), and feature activation coordination standards.

You can use Tensorflow for Rust to simplify that task and avoid pain with regex. Just have the right mindset.

What is the benefit of this compared to using bindings/a wrapper to Tensorflow, or other ML libraries written in C/C++, such as this community hosted project on tensorflow's github. If it's just for fun that is a valid enough reason imo, just curious since you describe it as a better Tensorflow because of the typing vs using the python wrapper, when there already exist ways to interact with tensorflow with both Rust and other statically typed languages, also including C++ (officially supported), C#, Haskell and Scala, as well as probably having bindings not mentioned on the documentation for more niche languages.

(3) You could use TensorFlow as your executor: https://github.com/tensorflow/rust

TensorFlow has language support for TypeScript well as Rust.

Thank you for the restponse! With tensorflow I am probably better of with something like; [tensorflow rust bindings](https://github.com/tensorflow/rust/tree/master/src). But I believe some useful extensions are still written in python for example; [TFDV](https://github.com/tensorflow/data-validation).. and how about scikit-learn or even something that is simpler like fb-prophet that is entirely written in python?

Tensorflow bindings exist, technically, but they're in a pretty rough state AFAIK.

tensorflow/rust (Rust): Rust language bindings for TensorFlow