Rami's Readings #97 - AI Summits in Paris & China

Welcome to Rami’s Readings #97 - a weekly digest of interesting articles, papers, videos, and X threads from my various sources across the Internet. Expect a list of reads covering AI, technology, business, culture, fashion, travel, and more. Learn about what I do at ramisayar.com/about.

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🤖 AI Reads

LM2: Large Memory Models

Notes: Interesting idea to add memory without modifying the vanilla Transformers architecture. You can find the code here.

MiniMax-01: Scaling Foundation Models with Lightning Attention

Notes: New model with MoE with 32 experts and can handle context windows of 4 million tokens from MiniMax. Code here.

Titans: Learning to Memorize at Test Time

Notes: New family of architectures from Google.

Foundations of Large Language Models

Notes: New book from Northeastern University about LLMs. Yet another book on my reading list.

Marker-Inc-Korea / AutoRAG

Notes: An open source framework for RAG evaluation and optimization from South Korea.

💼 Business Reads

Macron Unveils $112B AI Investment

Notes: Vive la France!

Great Summary of AI Action Summit Conference

Notes: I really need to go Paris again…

🔀 Other Reads

MongoDB’s Moat Breaking?

Notes: I still instinctively reach for MongoDB on my personal projects, but FerretDB is interesting.

Undergraduate Upends a 40-Year-Old Data Science Conjecture

Notes: Hash tables are critical data structures! Any improvement will have profound downstream performance effects.

That’s all for this week. Signing off from Redmond.