Computer-use agents (CUAs) are emerging as practical tools in 2025, driven by progress in multimodal models, open-source frameworks, agentic browsers, and new data efforts. This article broadly explores the landscape for CUAs.
Vector databases provide the speed and scale to enable a model framework to search millions of embeddings in milliseconds to find relevant context.
The International Conference on Machine Learning (ICML) is a leading international academic conference in machine learning.
Computer Use Agents are bringing AI beyond chatbots, transforming software interaction through vision, language, and action to automate complex digital tasks.
RAG systems deliver responses that are fluent, contextually accurate, and verifiable.
The datasets are now also available for querying in the Chakra Data Warehouse.
How decentralized networks, new optimization strategies, and crypto incentives are reshaping the future of AI model training.
The latest interaction patterns between AI and data
Turning the web into a permissionless database.
We’re enabling organizations to move terabyte-level data footprints in near real-time with high performance
All of on-chain data - now queryable directly in DuckDB.
A strategic partnership to leverage Chakra’s open data standard with Flow’s AI agent marketplace.
llms_database.txt as an extension focused specifically on database debugging contexts.
Integrate data natively into chat
A semi-technical overview of how we built our data warehouse
The Chakra Data Warehouse is now available for public preview.
Chakra Labs places at the Solana Radar Hackathon, winning $15,000 in USDC
The first free-to-use, end to end encrypted file storage on Solana
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