Sure! Here’s the translation into American English:
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Organizations are increasingly interested in the potential of artificial intelligence (AI) agents, although many find themselves in what is known as the “proof-of-concept purgatory.” This expression describes the situation where promising prototypes of agents fail to advance toward effective deployment in production environments. Through various conversations with clients, several common challenges have been identified that hinder this transition from experimentation to business implementation.
One of the main obstacles is the variety of frameworks and models that developers wish to employ for different use cases. The pressure to standardize often stifles innovation. Additionally, the stochastic nature of the agents complicates security aspects, requiring greater separation between user sessions. Identity management and access control issues also arise for agents that need to operate on behalf of users or access sensitive systems. Moreover, challenges come from handling different types of input, such as text, images, and documents, which frequently exceed computing limits in serverless environments.
Uncertainty regarding the computational resources required for each agent can lead to excessive spending if they are overprovisioned to respond to demand spikes. Furthermore, managing the infrastructure for agents that may be short- or long-lived requires specialization, diverting attention from the agent’s core functionality.
To address these challenges, Amazon has introduced the AgentCore Runtime, a secure, serverless hosting environment specifically designed for AI agents and tools. This service aims to eliminate the complexity of the infrastructure that has prevented promising prototypes from becoming production-ready, handling aspects like container orchestration, session management, scalability, and security, allowing developers to focus on creating intelligent experiences.
With AgentCore, developers can utilize different frameworks and agent models, as well as deploy, scale, and stream responses with just four lines of code. Agent execution is ensured by session isolation and integrated identity management. Additionally, state persistence is provided for agents that need to retain information between interactions, processing various modalities and large payloads.
This innovative approach of the AgentCore Runtime promises to simplify both the deployment and management of AI agents, addressing critical challenges that have hindered their large-scale adoption. Developers can quickly and easily start using AgentCore Runtime, pushing the boundaries of what is possible in the field of artificial intelligence.
via: MiMub in Spanish
