Sam Altman discusses the imminent arrival of digital superintelligence, its potential impacts on society, and the future of technological progress. He highlights the rapid advancements in AI, the economic and scientific benefits, and the challenges of ensuring safety and equitable access.
LLM 0.26 introduces tool support, allowing LLMs to access and utilize Python functions as tools. The article details how to install, configure, and use these tools with various LLMs like OpenAI, Anthropic, Gemini, and Ollama models, including examples with plugins and ad-hoc functions. It also discusses the implications for building 'agents' and future development plans.
PaperCoder is a multi-agent LLM system that transforms scientific papers into code repositories through a three-stage pipeline: planning, analysis, and code generation. It aims to create faithful, high-quality implementations.
This article details new prompting techniques for ChatGPT-4.1, emphasizing structured prompts, precise delimiting, agent creation, long context handling, and chain-of-thought prompting to achieve better results.
Notte is an open-source browser using an agent, designed to improve speed, cost, and reliability in web agent tasks through a perception layer that structures webpages for LLM consumption. It offers a full stack framework with customizable browser infrastructure, web scripting, and scraping endpoints.
Spammers leveraged OpenAI's GPT-4o-mini to generate unique messages, bypassing spam filters and successfully delivering unwanted messages to over 80,000 websites over a four-month period. The framework, named AkiraBot, used the LLM to personalize messages, making detection more difficult.
This article details the partnership between OpenAI and Notion to integrate generative AI directly into the Notion workspace, enhancing writing, brainstorming, summarization, and more through OpenAI's GPT models.
This article details the Model Context Protocol (MCP), a new approach to integrating Large Language Models (LLMs) like Azure OpenAI with tools. MCP focuses on structured data exchange to improve reliability, observability, and functionality, moving beyond simple text-in, text-out interactions. It aims to standardize how LLMs interact with tools, enhancing their ability to utilize those tools effectively.
A terminal-based platform to experiment with the AI Software Engineer. It allows users to specify software in natural language, watch as an AI writes and executes the code, and implement improvements. Supports various models and customization options.
The article discusses four open-source AI research agents that serve as cost-effective alternatives to OpenAI’s Deep Research AI Agent. These alternatives offer robust search capabilities, AI-powered extraction, and reasoning features, allowing researchers to automate and optimize their workflows without incurring high costs.
