Ahead of AI #12: LLM Businesses and Busyness
pair-preference-model-LLaMA3-8B by RLHFlow: Really strong reward model, trained to take in two inputs at once, which is the top open reward model on RewardBench (beating one of Cohere’s).
DeepSeek-V2 by deepseek-ai (21B active, 236B total param.): Another strong MoE base model from the DeepSeek team. Some people are questioning the very high MMLU sc... See more
DeepSeek-V2 by deepseek-ai (21B active, 236B total param.): Another strong MoE base model from the DeepSeek team. Some people are questioning the very high MMLU sc... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Retrieval can be improved by contextual compression, a technique where retrieved documents are compressed, and irrelevant information is filtered out.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
I’m often asked what problem I’d solve if I were to start another company. I probably won’t do a startup any time soon (because startups are hard), but here are some of the problems I find interesting. If you’re solving any of them, I’d love to chat.
1. Data synthesis: AI has become really good both at generating and annotating data. The challenge n... See more
1. Data synthesis: AI has become really good both at generating and annotating data. The challenge n... See more
Feed | LinkedIn
LlamaIndex focuses on advanced retrieval rather than on the broader aspects of LLM apps.