New research shows a tuned recommendation engine can boost click‑through rates by 10% while cutting inference cost. The paper dives into model‑serving tricks, optimization for large language models, and deployment efficiency for production AI. Open‑source practitioners will love the practical benchmarks. #RecommendationEngine #InferenceOptimization #ModelServing #ClickThroughRate

🔗 https://aidailypost.com/news/recommendation-engine-lifts-click-through-10-efficiency-needed

Tôi đã phát triển kiến trúc suy luận "Cerebellum" cho LLaMA-3.1 (bản Base), tiết kiệm ~20% tài nguyên tính toán nhờ SLERP & RoPE động, không làm giảm chất lượng. Kiến trúc này dùng cơ chế nhảy lớp (early exit), dự đoán trạng thái ẩn và tái tạo cache bằng nội suy hình cầu (SLERP), duy trì tính nhất quán KV Cache. Đã kiểm thử trên Qwen, Llama, Mistral. Tỷ lệ thoát sớm: 25-30%, không lệch ngữ nghĩa. #AI #LLM #InferenceOptimization #MachineLearning #TríTuệNhânTạo #TốiƯuHóaMôHình #AIResearch

https:/

Luminal raises $5.3 million to build a better GPU code framework

https://fed.brid.gy/r/https://techcrunch.com/2025/11/17/luminal-raises-5-3-million-to-build-a-better-gpu-code-framework/

🤯 Multi-model LLM teams orchestrated by Monte Carlo Tree Search – a paradigm shift in LLM inference!

This means decentralized, adaptable AI is on the horizon.

But what are the biggest unforeseen challenges we'll face in building truly efficient #agentorchestration systems?

Full blog post: https://dougortiz.blogspot.com/2025/07/the-future-of-ai-moving-beyond-single.html

#MultiModelLLMs #InferenceOptimization #DeepTech #DataDrivenAgentOrchestration https://www.blogger.com/blog/post/edit/3045684979747909405/27457725471072296