LLMs

Pipeline RobustQA Avg. score Avg. response time (secs) Azure Cognitive Search Retriever + GPT4 + Ada 72.36 >1.0s Canopy (Pinecone) 59.61 >1.0s Langchain + Pinecone + OpenAI 61.42 <0.8s Langchain + Pinecone + Cohere 69.02 <0.6s LlamaIndex + Weaviate Vector Store - Hybrid Search 75.89 <1.0s RAG Google Cloud VertexAI-Search + Bison... See more

The xAI PromptIDE is an integrated development environment for prompt engineering and interpretability research. It accelerates prompt engineering through an SDK that allows implementing complex prompting techniques and rich analytics that visualize the network's outputs. We use it heavily in our continuous development of Grok.

The multiple cantilevered AI overhangs:

Compute overhang. We have much more compute than we are using. Scale can go much further.

Idea overhang. There are many obvious research ideas and combinations of ideas that haven’t been tried in earnest yet.

Capability overhang. Even if we stopped all research now, it would take ten years to digest the new... See more

Mem0: The Memory Layer for Personalized AI

Mem0 provides a smart, self-improving memory layer for Large Language Models, enabling personalized AI experiences across applications.

Note: The Mem0 repository now also includes the Embedchain project. We continue to maintain and support Embedchain ❤️. You can find the Embedchain codebase in the embedchai

... See more

I’ve been giving talks and speaking with engineers and non-technical audiences about interpretability since 2022, and I still struggle to explain exactly what a “feature” is. I often use words like “concept” or “style”, or establish metaphors to debugging programs or making fMRI scans of brains. Both metaphors help people outside of the subfield... See more

📦 Service Deployment - Ray Serve (https://lnkd.in/eAV-Y6RN)

🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)

🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)

🗄 Vector Database - Weaviate (https://weaviate.io/)

📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)

📈 LLM Observability - Weights & Biases Traces (https... See more

First of all, I'd say you have a bigger problem where your company is trying to find nails with a hammer. That is where your sentiment comes from, and could be an obstacle for both you and the company. It's the same deal when I see people keep on talking about RAG, and nowadays "modular RAG", when really, you could treat everything as a software... See more

The quality of dataset is 95% of everything. The rest 5% is not to ruin it with bad parameters.