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3 yr. ago

  • Introduction

    I’ve written quite a lot of free software in my life. Most of it was from scratch: projects I started myself. So I get to choose where to host them – or rather, I have to choose where to host them.

    These days, all my projects are held in Git. And mostly, I put them in ‘bare’ git repositories on my personal website.

    I don’t use any git ‘forge’ system layered on top of Git, like Gitlab or Github, which automatically makes a bug tracking database for each project, and provides a convenient button for a user to open a merge request / pull request. I just use plain Git. People can ‘git clone’ my code, and there’s a web-based browsing interface (the basic gitweb) for looking around without having to clone it at all. But that’s all the automated facilities you get.

    Occasionally this confuses people, so I thought I should write something about it.

    Discussion with the author @ https://hachyderm.io/@simontatham/114111520633445984

  • That's not an affiliate link that's an anonymous tracking link.

  • These suggestions are essentially the same as other privacy and libre focused recommendations.

  • I'm talking about posting on their website a link to alternative social media accounts.

  • You're right. I got lazy.

  • That doesn't explain why they don't start a transition by posting to both the new platform and the old. And not including links to their new account on their websites.

  • There are free alternatives that they provide links to.

  • From the article:

    DeepSeek-R1 release leaves open several questions about:

    • Data collection: How were the reasoning-specific datasets curated?
    • Model training: No training code was released by DeepSeek, so it is unknown which hyperparameters work best and how they differ across different model families and scales.
    • Scaling laws: What are the compute and data trade-offs in training reasoning models?

    These questions prompted us to launch the Open-R1 project, an initiative to systematically reconstruct DeepSeek-R1’s data and training pipeline, validate its claims, and push the boundaries of open reasoning models. By building Open-R1, we aim to provide transparency on how reinforcement learning can enhance reasoning, share reproducible insights with the open-source community, and create a foundation for future models to leverage these techniques.

    In this blog post we take a look at key ingredients behind DeepSeek-R1, which parts we plan to replicate, and how to contribute to the Open-R1 project

  • I didn't read your post correctly. Yeah, that's harassment at the very least. No better than someone screaming at a retail worker because of some corporate policies.

  • It's all about your organization's size and if the organization makes use of the Anaconda controlled defaults channel. I'm not a lawyer, but your company may be liable for some licensing fee if your company is using Anaconda's repository of binaries. You'd need to consult with an actual lawyer for more reliable assessment of your potential liability.

    Switch to using miniforge and the conda-forge channel when installing and using Conda.

  • Conda itself is outside of Anaconda, Inc's control.

  • It's better that you don't use resume driven decisions. Just do whatever you are interested in.

  • Embedded software development has dramatically advanced over the past decade. What does that mean for bare-metal programming?

    At a Glance

    • Bare-metal programming is an essential skill as it enables you to understand what your system is doing at the lowest levels.
    • Even if you spend your days working with abstraction layers, bare-metal programming will guide you should abstractions fail.
    • And bare-metal skills can provide a solid foundation for troubleshooting and debugging.
  • These two are my favorite balance of fundamentals and getting to purposeful application as quickly as possible (the first link is definitely not enough, but combined with the second she should be comfortable with the syntax and able to get basic things working):
    https://www.kaggle.com/learn/intro-to-programming
    https://www.kaggle.com/learn/python

    This one takes its time with fundamentals and includes some projects to put them in context of building something. It's presented on Google Colab and Jupyter notebooks: https://allendowney.github.io/ThinkPython/

    Working with GIS data means cleaning data. This one covers that and a lot of common analysis tools and techniques. But it assumes a bit of programming knowledge (Good to follow up after one of the options above): https://wesmckinney.com/book/

  • Debian - The universal operating system @lemmy.zip

    Orphaning bcachefs-tools in Debian – Jonathan Carter | 29 August 2024

    Machine Learning @programming.dev

    Learn PyTorch for Deep Learning: Zero to Mastery | Free Online Book | Daniel Bourke

    Machine Learning @programming.dev

    What’s Really Going On in Machine Learning? Some Minimal Models | Stephen Wolfram | August 22, 2024

    Web Development @programming.dev

    Deno's Standard Library for JavaScript Finally Stabilized at v1 | 3min 5sec Video | Aug 8, 2024

    Machine Learning @programming.dev

    Data Science Handbook | Curated resources (Free & Paid) to help data scientists learn, grow, and break into the field of data science | Andres Vourakis | Last update Jul 23, 2024

    OCaml @programming.dev

    How OCaml type checker works -- or what polymorphism and garbage collection have in common | okmij.org | original February 2013 | updated January 9, 2022

    Gleam @programming.dev

    A look at the Gleam programming language, through the lens of a Rust developer | Code to the Moon | Video 10m32s | Jun 27, 2024

    C Programming Language @programming.dev

    Writing a C Compiler | Build a Real Programming Language from Scratch | Nora Sandler | July 2024 | No Starch Press | 792 pages | ISBN-13: 9781718500426

    Rust @programming.dev

    A table of publicly available Arena crates and their features

    Rust @programming.dev

    Understanding Rust's Trait Objects: Vtables, Dynamic Dispatch, and Memory Deallocation

    Gleam @programming.dev

    First impressions of Gleam: lots of joys and some rough edges

    Machine Learning @programming.dev

    Elements of Data Science | Allen B. Downey | July 17, 2024

    MICROCONTROLLERS @lemux.minnix.dev

    Why you should fall in love with the RP2350 | Dmitry Grinberg | Aug 8, 2024

    Pop!_OS (Linux) @lemmy.world

    COSMIC ALPHA 1 Released (Desktop Environment Written In Rust From System76)

    Data Engineering @programming.dev

    Dremio is offering free pdf copies of "Apache Iceberg: The Definitive Guide: Data Lakehouse Functionality, Performance and Scalability on the Data Lake"

    Neovim @programming.dev

    Using and setting up Neovim in Windows 11 (not WSL)

    Pop!_OS (Linux) @lemmy.world

    System76 with Jeremy Soller | Rust in Production Podcast S02 E07 by corrode Rust Consulting | 2024-07-25

    Rust @programming.dev

    System76 with Jeremy Soller | Rust in Production Podcast S02 E07 by corrode Rust Consulting | 2024-07-25

    Redox OS @lemmy.world

    System76 with Jeremy Soller | Rust in Production Podcast S02 E07 by corrode Rust Consulting | 2024-07-25

    System76 @lemmy.world

    System76 with Jeremy Soller | Rust in Production Podcast S02 E07 by corrode Rust Consulting | 2024-07-25