Navigating the Future of AI in Code Refactoring

📖 TUTORIALS & CASE STUDIES

Mastering Mistral: A Comprehensive Short Course

watch time: 60 minutes
DeepLearning.AI offers a beginner-friendly course on leveraging Mistral AI's open source and commercial models. The course covers effective prompting techniques, function calling, JSON mode, and Retrieval Augmented Generation (RAG). Learn more about the course here.

Building a RAG System with a Self-Querying Retriever in LangChain

Read Time: 10 minutes

This article demonstrates how to build a movie recommendation system using a RAG (Retrieval-Augmented Generation) approach with a self-querying retriever in LangChain. The system allows users to search for movies based on natural language queries, without relying on user data. It utilizes a self-querying retriever to filter movies by metadata before performing a similarity search. The article provides an overview of the data retrieval process, uploading documents to Pinecone, creating the self-querying retriever, and building the chat model. The author also discusses the system's limitations and potential improvements.

Enhancing Vector Search with Graph-Based Metadata Filtering

read time: 18 minutes
Tomaz Bratanic from Neo4j introduces a method for optimizing vector retrieval using advanced graph-based metadata filtering with LangChain and Neo4j. The approach combines metadata filtering and vector similarity search to increase the accuracy and relevance of search results. The full article includes a detailed walkthrough of implementing this method with OpenAI's function-calling agent.

A Beginner's Guide to Hugging Face Transformers

read time: 20 minutes
This article provides a comprehensive introduction to Hugging Face Transformers, aimed at beginners with no prior knowledge. It covers the basics of open-source machine learning, the Hugging Face Hub, and how to run Microsoft’s Phi-2 LLM in a Hugging Face space.

🧰 TOOLS

Explore the Best ML Tools on GitHub

read time: you’ll loose hours exploring these links
Discover a curated list of top machine learning tools on GitHub, ideal for developers looking to enhance their projects. This comprehensive resource includes libraries, frameworks, and more. Dive into the details here.

Top 7 MLOps Platforms to Streamline Your AI Projects in 2024

read time: 10 minutes

Explore the best end-to-end MLOps platforms for 2024, ideal for personal and enterprise projects. These platforms simplify the entire machine learning workflow, including training, deployment, and monitoring. Learn more about each platform's unique features in this detailed guide.

Introducing Mistral-Common: Advanced Tokenization for AI Models

read time: 3 minutes
Mistral-common introduces advanced tokenization capabilities, supporting structured conversations and tool parsing, essential for developers using Mistral models. The toolkit includes multiple tokenizer versions and installation instructions. Explore the features and installation guide on GitHub.

And for those looking to bring GanAI into the development pipeline a work here are a couple great open source options

Agenta: Revolutionizing LLM Application Development

read time: 7 minutes

Agenta is an open-source LLMOps platform designed to streamline the development of AI applications using LLMs. It supports rapid experimentation, prompt management, and collaborative features, enabling developers to deploy applications swiftly and efficiently.

Haystack 2.0: Revolutionizing AI Application Development

read time: 7 minutes

Explore the capabilities of Haystack 2.0, a production-ready, open-source AI framework designed for building customizable AI applications. It supports a wide range of use cases including multimodal AI, conversational AI, and advanced retrieval-augmented generation (RAG), with robust deployment options for various environments.

📰 NEWS & EDITORIALS

🎧Navigating the Future of AI in Code Refactoring

listen time: 37 minutes
Explore the potential and challenges of AI in code refactoring with insights from industry experts in a recent Thoughtworks podcast. The discussion covers AI's current capabilities, its impact on code quality, and future prospects for software development.

Introducing Reka Core: A New Frontier in Multimodal AI Models

read time: 5 minutes

Reka introduces its most advanced model, Reka Core, a multimodal language model that excels in image, video, and language tasks. It competes with top industry models and offers deployment flexibility. Learn more about its capabilities and partnerships in the full article.

Introducing Qwen1.5-110B: A New Benchmark in AI Language Models

read time: 9 minutes

Explore the capabilities of the new Qwen1.5-110B model, which boasts over 100 billion parameters and shows remarkable performance in language and chatbot benchmarks. Learn more about its features and potential applications in this detailed overview.

Why Meta's Llama 3 is Revolutionizing the AI Landscape

read time: 5 minutes
Meta's Llama 3, a new open-source large language model, is setting new benchmarks in AI with its free, open-source nature and ability to run locally on consumer hardware. Explore the full capabilities and future potential of Llama 3 in this detailed article.