AI Briefing#dspy
The latest AI and developer news about #dspy, with the original source and a short summary.
The latest AI and developer news about #dspy, with the original source and a short summary.
Imp brings DSPy's declarative, self-improving language-model programming paradigm to Elixir, leveraging OTP for reliable, concurrent agent execution.
DSPy's Flex leverages GEPA to automatically optimize not just prompts but also program code.
Dropbox leveraged DSPy to refine its LLM-based evaluation model, thereby improving both the response quality and efficiency of the Dash Chat agent.
Using GEPA, a genetic-algorithm-based approach, prompt tuning work that used to take days has been reduced to just one hour.
DSPy made Dropbox Dash's relevance judge cheaper and more accurate.
After calibrating an LLM with a small amount of human labels, it automatically generates relevance labels at scale.
Dropbox Dash reduces tokens and latency through index, knowledge graph, and MCP optimization.
It covers how to program foundation models by leveraging DSPy and ColBERT's multi-vector semantic search.