A script utilizing OpenAI's Llama models to interact within a terminal environment, allowing the models to execute Python code and communicate based on predefined prompts.
ServiceNow releases AgentLab, an open-source Python package for developing and evaluating web agents, addressing challenges in agent development such as poor scalability and difficulty in conducting reproducible experiments.
The article discusses the use of AI agents for automating and optimizing tasks in the networking industry, including network deployment, configuration, and monitoring. It outlines a workflow with four agents that collectively achieve the setup and verification of network connectivity within a Linux and SR Linux container environment.
The author demonstrates a workflow involving four AI agents designed to deploy, configure, and monitor a network:
Document Specialist Agent: This agent extracts installation, topology deployment, and node connection instructions from a specified website.
- Linux Configuration Agent: Executes the installation and configuration commands on a Debian 12 UTM VM, checks the health of the VM, and verifies the successful deployment of network containers.
- Network Configuration Specialist Agent: Configures network IP allocation, interfaces, and routing based on the network topology, including detailed BGP configurations for different network nodes.
- Senior Network Administrator Agent: Applies the generated configurations to the network nodes, checks BGP peering, and verifies end-to-end connectivity through ping tests.
The author demonstrates a workflow involving four AI agents designed to deploy, configure, and monitor a network:
Document Specialist Agent: This agent extracts installation, topology deployment, and node connection instructions from a specified website.
- Linux Configuration Agent: Executes the installation and configuration commands on a Debian 12 UTM VM, checks the health of the VM, and verifies the successful deployment of network containers.
- Network Configuration Specialist Agent: Configures network IP allocation, interfaces, and routing based on the network topology, including detailed BGP configurations for different network nodes.
- Senior Network Administrator Agent: Applies the generated configurations to the network nodes, checks BGP peering, and verifies end-to-end connectivity through ping tests.
The article discusses the emerging role of AI agents as distinct users, requiring designers to adapt their practices to account for the needs and capabilities of these intelligent systems.
- Agents are becoming active users in systems, requiring designers to extend UX principles to include both humans and A and agents.
- The future of UX lies in understanding and designing for Agent-Computer Interaction.
- Agents are becoming active users in systems, requiring designers to extend UX principles to include both humans and A and agents.
- The future of UX lies in understanding and designing for Agent-Computer Interaction.
The article discusses the role of AI agents in generative AI, focusing on tool calling and reasoning abilities, and how they can be evaluated using benchmarks like BFCL and Nexus Function Calling Benchmark.
This article provides a comprehensive overview of AI agents, discussing their core traits, technical aspects, and practical applications. It covers topics like autonomy, reasoning, alignment, and the role of AI agents in daily life.
1. **Emerging Prominence of AI Agents**: Agents are increasingly popular for day-to-day tasks but come with confusion about their definition and effective use.
2. **Core Traits and Autonomy**: Julia Winn explores the nuances of AI agents' autonomy and proposes a spectrum of agentic behavior to assess their suitability.
3. **AI Alignment and Safety**: Tarik Dzekman discusses the challenges of aligning AI agents with creators' goals, particularly focusing on safety and unintended consequences.
4. **Tool Calling and Reasoning**: Tula Masterman examines how AI agents bridge tool use with reasoning and the challenges they face in tool calling.
5. **Proprietary vs. Open-Source AI**: Gadi Singer compares the advantages and limitations of proprietary and open-source AI products for implementing agents.
1. **Emerging Prominence of AI Agents**: Agents are increasingly popular for day-to-day tasks but come with confusion about their definition and effective use.
2. **Core Traits and Autonomy**: Julia Winn explores the nuances of AI agents' autonomy and proposes a spectrum of agentic behavior to assess their suitability.
3. **AI Alignment and Safety**: Tarik Dzekman discusses the challenges of aligning AI agents with creators' goals, particularly focusing on safety and unintended consequences.
4. **Tool Calling and Reasoning**: Tula Masterman examines how AI agents bridge tool use with reasoning and the challenges they face in tool calling.
5. **Proprietary vs. Open-Source AI**: Gadi Singer compares the advantages and limitations of proprietary and open-source AI products for implementing agents.
Composio equip's your AI agents & LLMs with 100+ high-quality integrations via function calling
NVIDIA introduces NIM Agent Blueprints, a collection of pre-trained, customizable AI workflows for common use cases like customer service avatars, PDF extraction, and drug discovery, aiming to simplify generative AI development for businesses.
Learn about AI Agents, their benefits, and how to create a complete system from scratch using Python.
Raoul Pal predicts that AI agents will use cryptocurrency for transactions, bypassing traditional finance systems.
