🌸 Agents

🌼 MindSearch: A Multi-Agent AI Framework Processing 300+ Web Pages in Under 3 Minutes

MindSearch is an open-source AI Search Engine Framework with Perplexity.ai Pro performance. You can simply deploy it with your own perplexity.ai style search engine with either close-source LLMs (GPT, Claude) or open-source LLMs (InternLM2.5-7b-chat). It owns following features:

• 🤔 Ask everything you want to know: MindSearch is designed to solve any question in your life and use web knowledge.

• 📚 In-depth Knowledge Discovery: MindSearch browses hundreds of web pages to answer your question, providing deeper and wider knowledge base answer.

• 🔍 Detailed Solution Path: MindSearch exposes all details, allowing users to check everything they want. This greatly improves the credibility of its final response as well as usability.

• 💻 Optimized UI Experimence: Providing all kinds of interfaces for users, including React, Gradio, Streamlit and Terminal. Choose any type based on your need.

• 🧠 Dynamic Graph Construction Process: MindSearch decomposes the user query into atomic sub-questions as nodes in the graph and progressively extends the graph based on the search result from WebSearcher.

• Github

🌸 BioTech

🌼 ACEGEN: A TorchRL-based toolkit for reinforcement learning in generative chemistry.

ACEGEN is a comprehensive toolkit designed to leverage reinforcement learning (RL) techniques for generative chemistry tasks, particularly in drug design. ACEGEN harnesses the capabilities of TorchRL, a modern library for general decision-making tasks, to provide a flexible and integrated solution for generative drug design challenges.

• 📚 Github

🌼  Structure prediction of protein-ligand complexes from sequence information with Umol

Protein-ligand docking is an established tool in drug discovery and development to narrow down potential therapeutics for experimental testing. However, a high-quality protein structure is required and often the protein is treated as fully or partially rigid. Here they develop an AI system that can predict the fully flexible all-atom structure of protein-ligand complexes directly from sequence information

• 📚 Github

🌸 Funding

🌼 Groq Raises $640M To Meet Soaring Demand for Fast AI Inference.

🌸 Engineering

🌼 Must Read - How Meta Trained the 405 Billion Parameter Model?

🌼 Netflix Open Sources Maestro, a Next-Gen Data Workflow Engine

Maestro is a general-purpose workflow orchestrator that provides a fully managed workflow-as-a-service (WAAS) to the data platform users at Netflix.

It serves thousands of users, including data scientists, data engineers, machine learning engineers, software engineers, content producers, and business analysts, for various use cases. It schedules hundreds of thousands of workflows, millions of jobs every day and operate with a strict SLO even when there are spikes in the traffic. Maestro is highly scalable and extensible to support existing and new use cases and offers enhanced usability to end users.

• 📚 Github

Thank you for reading Musings on AI. This post is public so feel free to share it.

🌸 Miscellaneous

🌼 Do you want to learn Quantization?

•  A Visual Guide to Quantization. 

• Introduction to Quantization cooked in 🤗 with 💗🧑‍🍳

• Quantization Fundamentals with Hugging Face

• How Fireworks evaluates quantization precisely and interpretably

Love MusingsOnAI? Tell your friends and get rewards!

Share your referral link below with friends!

📮Want to Advertise with us?

If your company is interested in reaching an audience of AI professionals and decision makers, reach us.

If you have any comments or feedback, just respond to this email!Thanks for reading,Raahul