Understanding a Law Firm through Study — Engram
engram.com · 2,924 words · saved by 1 readers
Training agents to combine knowledge in weights, text memory, and search on realistic legal work.
August 17, 2026 Training agents to combine knowledge in weights, text memory, and search on realistic legal work. Written by Engram, in partnership with Harvey The agents of the future will familiarize themselves with their work in many different ways: learning knowledge and skills into weights, writing notes to themselves, and using tools to efficiently navigate the world. We’re excited to share our first results on what this would look like. In our work, we see these different forms of learning and memory as part of one end-to-end system. Integrating parametric knowledge, notes, and…
saved by
related reading
- PostTrainBenchposttrainbench.com
- Training a State-of-the-Art Legal Agent with Harvey | Applied Computeappliedcompute.com
- LLM Powered Autonomous Agents | Lil'Loglilianweng.github.io
- Machine Studying | Jacob Xiaochen Lijacobxli.com
- karl.pdfdatabricks.com
- Chroma Context-1: Training a Self-Editing Search Agent | Chromatrychroma.com
- The vector database to build knowledgeable AI | Pineconepinecone.io
- Honchohoncho.dev
- Expert Data for Frontier AI - AfterQueryafterquery.com
- AI Model & API Providers Analysis | Artificial Analysisartificialanalysis.ai
- Voyage AI | Homevoyageai.com
- Datacurve | The data engine for frontier AIdatacurve.ai