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A new learning curriculum on @ChapterPal: Prep reading for the ad ranking and targeting interview
This curriculum provides a comprehensive foundation for understanding the mechanics and machine learning challenges essential to ad ranking, targeting, and recommendation systems.
A new curriculum on @ChapterPal: Foundational milestone papers in AI
This curriculum is a paper-by-paper path across what was groundbreaking in AI, from the stochastic gradient descent invented in 1951 to DeepSeek R1 in 2025.
Read with an AI tutor: chapterpal.com/curriculum/d8a…
The LoRA paper is now on @ChapterPal: chapterpal.com/s/4y2jj82r/lor…
The LoRA technique from Microsoft made the finetuning of LLMs within reach of an average organization on relatively modest GPUs because it allows training only a small fraction of parameters by keeping the original weights of the LLM being finetuned frozen.
A new learning curriculum on @ChapterPal:
Prep reading for the ranking systems interview
This curriculum provides a comprehensive foundation in modern information retrieval, beginning with classic probabilistic models like BM25 and fundamental evaluation metrics such as
Qwen3.5-Omni Technical Report is now on @ChapterPal if you would like to read it with an AI tutor: t.co/2KA1wvisVT
PDF: t.co/13Ak549T0y
Qwen3.5-Omni is an omnimodal LLM that achieves state-of-the-art performance across 215 audio and audio-visual benchmarks, introduces an innovative Adaptive Rate Interleave Alignment (ARIA) method for stable speech synthesis, and demonstrates emergent audio-visual vibe coding capabilities.
When reading papers, stop switching between PDF, NotebookLM, and ChatGPT. Use @ChapterPal, where reading, asking questions, and taking notes are in a single flow.
A new learning curriculum on @ChapterPal: Prep reading for the search and retrieval systems interview
This curriculum provides a comprehensive foundation for understanding and building modern search and retrieval systems, bridging the gap between classical information retrieval
A new curriculum on @ChapterPal : **Prep reading for the LLM finetuning and alignment techniques interview**
Curated by Andriy Burkov
This curriculum provides a comprehensive progression through the theoretical foundations and practical methodologies of large language model
A new curriculum on @ChapterPal:
**Prep reading for the embeddings and vector systems interview**
This curriculum provides a comprehensive foundation for understanding modern vector systems, beginning with the evolution of word representations from early static embedding
A new learning curriculum on @ChapterPal: Prep reading for the AI platform and MLOps interview
This curriculum provides a foundation for MLOps and the engineering of production-grade AI platforms by bridging the gap between theoretical machine learning research and scalable
New feature on @ChapterPal: the reader can now add a quiz on demand and choose what content it should cover.
Previously, quizzes could only be created for the entire chapter by asking a multi-agent system to identify the topic to test and the places to put the quizzes.
Some
A new curriculum on @ChapterPal: Prep reading for the ML monitoring and observability interview
This curriculum offers a comprehensive technical foundation for monitoring, evaluating, and maintaining production-level machine learning systems.
It begins by framing the challenges
Several @ChapterPal users mentioned to me that they use Obsidian for notes, and they asked how to move their highlights, annotations, and Q&As from ChapterPal to Obsidian.
Unfortunately, Obsidian doesn't have an API, so I showed a couple of screenshots to Codex today, and now
A new curriculum on @ChapterPal:
Prep reading for the model serving and inference interview
This curriculum provides a comprehensive technical foundation for understanding the architecture and deployment of modern machine learning models, specifically focusing on the lifecycle
If you are an author or just write regularly and Markdown is your system of choice, try my @ChapterPal platform in the Editor mode.
It's a WYSIWYG Markdown editor that I've built for myself, and I've added lots of cool AI features that simplify writing and achieve high writing
A new curriculum on @ChapterPal:
Prep reading for the model training infrastructure interview
This curriculum equips learners with a deep understanding of fundamental and cutting-edge techniques in model training infrastructure.
Covering optimization, distributed training
A new curriculum on @ChapterPal:
Prep reading for the streaming and event-driven ML system design interview
This curriculum provides a deep dive into the foundational theories and cutting-edge practices of streaming and event-driven machine learning system design. Learners will
25 Followers 409 FollowingCrafting web-sites for 20+ years, and plan to do so in future. In love with Coldfusion, Python, PHP, databases. Occasionally trying to teach. #SaveUkraine
323 Followers 840 Followingresearch assistant professor @northwestern working on gun violence, policing, NLP. phd @umichsph. former @UChicago #CrimeLab.
244 Followers 3K FollowingI love art and animals, and people that make things with their brains and their hands, and ridiculous humor that makes me laugh out loud. Math, CompSci, Music.
1K Followers 7K FollowingEpistemic forager. Tweeting about AI, science, philosophy, business and other interests. A disciple of Charlie Munger and Yogi Berra.
57K Followers 120 FollowingBooks: https://t.co/0EmPM3De9B & https://t.co/45NGbbXIzC
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PhD in AI, author of 📖 The Hundred-Page LMs Book & The Hundred-Page ML Book
4.7M Followers 458 FollowingCutting-edge research, news, commentary, and visuals from the Science family of journals. Follow @NewsfromScience for stories from our News team.