Edge 418: Meet The New DSPy: The Hot Framework to Build LLM Apps You Should Know About
Was this email forwarded to you? Sign up here Edge 418: Meet The New DSPy: The Hot Framework to Build LLM Apps You Should Know AboutCreated by Stanford researchers, the framework provides an interesting alternative to LangChain or LlamaIndex.
The universe of language model programming(LMP) frameworks has been expanding rapidly on the last few months. Frameworks such as LangChain or LlamaIndex have certainly achieved relevant levels of adoption within the LLM community and Microsoft’s Semantic Kernel is boosting an impressive set of capabilities. Recently, a new alternative known as DSPy came into the scene with a unique approach to LMP. DSPy was created by Stanford University researchers with the goal of providing improved abstractions for different LMP tasks. DSPy prioritizes programming over prompting in an attempt to enable the foundation to create more sophisticated LMP apps. Part of the current set of limitations of LLMs is that they are not very effective at tasks such as control logic such as loops or conditional statements, and they also require fundamentally different constructs for tasks such as fine-tuning or knowledge-augmentation. DSPy attempts to tackle these problems with a programming-centric approach... Subscribe to TheSequence to unlock the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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Edge 417: Building Multi Agent Systems
Tuesday, July 30, 2024
Can multiple agents collaborate in a single application? Some research and technologies that might help with that. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
3 vs. 3: The Open vs. Closed Battle for Big AI
Sunday, July 28, 2024
Big model announcements by Meta, Mistral and xAI. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Edge 416: Inside Apple's 4M-21 Model that Could be the Foundation of its On-Device Multimodal Experience
Thursday, July 25, 2024
The model was trained simultaneously across 21 different modalities. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Edge 415: Agents that Remember Actions with Procedural Memory
Tuesday, July 23, 2024
One of the most unique forms of memory in autonomous agents. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
📝 Guest Post: Local Agentic RAG with LangGraph and Llama 3*
Monday, July 22, 2024
In this guest post, Stephen Batifol from Zilliz discusses how to build agents capable of tool-calling using LangGraph with Llama 3 and Milvus. Let's dive in. LLM agents use planning, memory, and
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