Foundations
Understand language models and choose a learning path.
- Llm Fundamentals (139)
- Courses And Learning Paths (179)
- From Scratch Implementations (1)
- Practitioner Overviews (387)
706 resources · page 16 of 23
Vicki Boykis (@vboykis)
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Vicki Boykis' blog: technical explanations of embeddings, ML engineering and LLM tooling.
VinAI
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VinAI site: Vietnamese company doing AI research and building applied AI products.
Vincent Warmerdam (@fishnets88)
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Vincent Warmerdam's calmcode: short video lessons on Python tools and data science.
DL in NLP (@dlinnlp)
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DL in NLP Telegram channel by Vlad Lialin: Russian-language news and paper reviews on natural language processing.
Vukosi Marivate (@vukosi)
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Vukosi Marivate's site: researcher on African-language NLP and data science, co-founder of Masakhane.
@vukosi (Vukosi Marivate)
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X account of Vukosi Marivate, University of Pretoria and Masakhane co-founder: posts on African language NLP.
WGA: AI provisions of the 2023 MBA
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WGA page on artificial intelligence provisions in the 2023 Minimum Basic Agreement.
Will Brown (@willccbb)
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verifiers GitHub repo (Will Brown, Prime Intellect): library for RL environments and evaluations for LLMs.
Wing Lian (@winglian)
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Axolotl GitHub repo, led by Wing Lian: open-source tool for fine-tuning LLMs with many methods.
X recommendation algorithm
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twitter the-algorithm GitHub repo: source code of the X recommendation algorithm services.
@xai (xAI)
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X account of xAI: official Grok model and company announcements.
XGBoost Documentation
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XGBoost documentation: distributed gradient boosting library, a standard non-neural baseline for tabular data.
ngxson GitHub profile (Xuan-Son Nguyen)
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Xuan-Son Nguyen's GitHub profile: llama.cpp server and multimodal contributions.
@yandex (Яндекс)
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X account of Yandex: Russian-language company news including AI products.
@ylecun (Yann LeCun)
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X account of Yann LeCun, executive chairman of AMI Labs: posts on world models and AI research.
Yann LeCun (@ylecun)
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AMI Labs site associated with Yann LeCun, currently a launch placeholder with an email signup.
Yao Fu (@Francis_YAO_)
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Yao Fu's Notion site with papers and technical notes on LLM reasoning and long context.
sglang
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SGLang GitHub repo, co-led by Ying Sheng: serving framework for large language and vision models.
@yoavgo (Yoav Goldberg)
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X account of Yoav Goldberg, Bar-Ilan professor and author of a neural NLP primer: posts on NLP and LLMs.
Yoshua Bengio (@Yoshua_Bengio)
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Yoshua Bengio's site: Université de Montréal professor and LawZero scientific director, with writing on AI safety.
Matsuo-Iwasawa Lab (University of Tokyo)
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Matsuo-Iwasawa Laboratory (University of Tokyo) Japanese site, led by Yutaka Matsuo, Japan government AI strategy adviser.
Zenn
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Zenn: Japanese platform where engineers publish technical articles and books, including many on LLMs and AI tooling.
Zhihong Shao (DeepSeek)
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DeepSeekMath paper (2024), first-authored by Zhihong Shao, which introduced the GRPO algorithm.
知乎 Zhihu (AI columns)
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Zhihu: Chinese question-and-answer and article platform where Chinese AI engineers publish technical analyses.
Zhu Jun 朱军
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Zhu Jun's Tsinghua homepage: ML professor and co-founder of Shengshu, developer of the Vidu video model.
Zindi (community)
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Zindi Africa: data-science competition platform with AI challenges and a community of African practitioners.
Zvi Mowshowitz (@TheZvi)
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Zvi Mowshowitz's Don't Worry About the Vase: weekly roundups and analysis of AI developments and safety.
3Blue1Brown Neural Networks
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3Blue1Brown neural networks series: visual video lessons explaining neural networks, backpropagation and transformers.
ai.gov.ru: National portal for artificial intelligence
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Russia's national AI portal with the national AI strategy, Code of Ethics and government AI programmes.
AIAAIC Repository
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AIAAIC Repository: independent register of AI incidents and controversies with case entries.
Alex Ziskind (@digitalix)
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Alex Ziskind's YouTube channel: benchmarks of local LLMs on Macs and other consumer hardware.
An Introduction to Statistical Learning
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Author site for An Introduction to Statistical Learning, with free PDF and labs in R and Python.