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#reproduction

@FinanceYF5: Zihan co-authoring DeepSeek-V2 and then being first to successfully reproduce DeepSeek-R1's RL agents outside the origi…

X AI KOLs Timeline · 2d ago Cached

Zihan, co-author of DeepSeek-V2 and the first to reproduce DeepSeek-R1's RL agents outside the lab, has been appointed CTO of O2 AI.

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#reproduction

@Ryrenz: Explosive! Hugging Face fully open-sourced and reproduced the entire training pipeline of DeepSeek-R1. GitHub 26.4k stars, from the official Hugging Face team, the most authoritative one. DeepSeek-R1 amazed everyone, but the real training recipe…

X AI KOLs Timeline · 2026-07-03 Cached

The official Hugging Face team fully open-sourced and reproduced the entire training pipeline of DeepSeek-R1 (Open-R1 project), including data, training, and evaluation. It has received 26.4k stars on GitHub, providing a reproducible textbook for training reasoning models for the industry.

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#reproduction

The first early human eggs from stem cells

Hacker News Top · 2026-07-01 Cached

Conception announces a milestone in creating early human eggs from stem cells using lab-grown mini-ovaries, advancing in vitro gametogenesis toward potential fertility treatments.

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#reproduction

@xiaoerzhan: Replica skill release - I used this skill to 1:1 replicate the currently recognized top-notch frontend website, achieving 100% fidelity. See comments. Here I explain the principles. I. Core understanding: Where is the "true source code" of a website? The key is to distinguish two types of websites— A. Server-side rendered / data-driven sites (Taobao, backend systems, most SaaS…

X AI KOLs Timeline · 2026-06-30 Cached

This article explains how to 1:1 replicate a recognized top-notch frontend website (oryzo), including methods for capturing dynamic assets and modifying a small amount of configuration, achieving high fidelity.

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#reproduction

Open Reproduction of DeepSeek-R1

Hacker News Top · 2026-06-11 Cached

Hugging Face's Open R1 project provides a fully open reproduction pipeline for DeepSeek-R1, including distilled datasets, training scripts, and evaluation tools, with the goal of enabling anyone to replicate and build on top of R1's reasoning capabilities.

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