Agents
Obligatory plug for static embeddings. Are you using static embeddings in your projects? Would love to hear how people are leveraging them, …
Obligatory plug for static embeddings. Are you using static embeddings in your projects? Would love to hear how people are leveraging them, whether for retrieval and beyond. Static embeddings offer un
Obligatory plug for static embeddings. Are you using static embeddings in your projects? Would love to hear how people are leveraging them, whether for retrieval and beyond. Static embeddings offer unmatched throughput, but they also suffer from accuracy loss compared to traditional embedding models. Can we make them better for retrieval? We tried several things: ✅️ raw maxsim scoring on the per-token embeddings ✅️ training a small adapter model ✅️ c…
Related
- Static embeddings offer unmatched throughput, but they also suffer from accuracy loss compared to traditional embedding models. Can we make …
- static embeddings are extremely fast/cheap compared to dense embeddings, and still quite powerful. one issue is that they lose accuracy over…
- We're excited to introduce the Retrieval Harness in LlamaParse - which is the 2026 version of RAG over documents Generalized agents need the…
Source: Jerry Liu (X) | 2026-08-28