🌁#85: Curiosity, Open Source, and Timing: The Formula Behind DeepSeek’s Phenomenal Success
How an open-source mindset, relentless curiosity, and strategic calculation are rewriting the rules in AI and challenging Western companies, plus an excellent reading list and curated research collection
we discuss François Chollet's combinatorial approach to reaching AGI, plus offer you a collection of interesting articles, relevant news, and must-read research papers. Dive in!
Topic 23: What is LLM Inference, it's challenges and solutions for it
LLM inference is how trained models deliver real-world value. Learn what it is, why latency matters, and how to optimize inference for production AI systems.
Guest post: Enhancing RAG with RA-DIT: A Fine-Tuning Approach to Minimize LLM Hallucinations*
RA-DIT, or Retrieval-Augmented Dual Instruction Tuning, is a method for fine-tuning both the LLM and the retriever in a RAG setup to enhance overall response quality
we’re revisiting classics. Are GANs still worthy of their title as one of the most captivating ideas in ML? plus collection of interesting articles, relevant news and must-read research papers. Dive in!
Three RAG upgrades explained: HtmlRAG preserves HTML structure, Multimodal RAG retrieves images, and Agentic RAG reformulates queries for better results