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Agenti di intelligenza artificiale

Gli agenti di intelligenza artificiale sono sistemi software che utilizzano ragionamento, pianificazione e strumenti per assistere o automatizzare compiti complessi. Confrontiamo i migliori agenti open source e commerciali.

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Yapay Zeka Ajanları Oluşturma + 18 Ajan Platformu ve Aracı

Agenti di intelligenza artificialeGiu 3

We spent the two days experimenting with real-world demos and tools to build personal AI assistants that can handle your tasks, such as scheduling meetings, managing notes, or sorting through emails. We will dive into three main approaches to building and using personal AI assistants, with real-world examples for each: 1.

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Agenti di intelligenza artificialeGiu 3

Strumenti CLI Agentic: Codex vs Claude Code

Agentic CLI tools are AI coding tools that can create and delete files, run commands, plan, and execute the coding of the entire project.

Agenti di intelligenza artificialeGiu 2

Trappole degli Agenti AI: 20 Incidenti Reali

AI agent adoption has outpaced AI agent security: 82% of enterprises now deploy agents, but only 44% have policies to secure them, and one in five organizations has already experienced an agent-related breach.

Agenti di intelligenza artificialeGiu 2

15 Minacce alla Sicurezza degli Agenti AI

Even a few years ago, the unpredictability of large language models (LLMs) would have posed serious challenges. One notable early case involved ChatGPT’s search tool: researchers found that webpages designed with hidden instructions (e.g., embedded prompt-injection text) could reliably cause the tool to produce biased, misleading outputs, despite the presence of contrary information.

Agenti di intelligenza artificialeMag 30

Strumenti Low/No-Code per Agenti AI: n8n, make, Zapier

Low- and no-code AI agent builders let users create automated, AI-driven workflows without writing complex code, making agent development faster and accessible to non-technical teams.

Agenti di intelligenza artificialeMag 30

Agenti AI locali: Goose, Observer AI, AnythingLLM

Local AI agents are often described as offline, on-device, or fully local. We spent three days mapping the ecosystem of local AI agents that run autonomously on personal hardware without depending on external APIs or cloud services.

Agenti di intelligenza artificialeMag 27

Confronta i Migliori Agenti AI nel Servizio Clienti

AI agents powered by large language models (LLMs) can respond to customer queries in natural language, interpret context, and generate human-like responses. These agents can process and synthesize large volumes of information from sources such as knowledge bases. We compiled four customer service AI agents: Tidio Lyro, Microsoft Azure AI Chatbot, IBM Watsonx Assistant, and Intercom Fin.

Agenti di intelligenza artificialeMag 26

Büyük Eylem Modelleri: Abartı mı Gerçek mi?

Following the launch of Rabbit, an AI device that can use mobile apps, the term large action models (LAMs) is getting popular. These models move beyond conversation by turning LLMs into “agents” that can connect the siloed, app-driven world without requiring users to click on apps or integrate APIs.

Agenti di intelligenza artificialeMag 25

Top 30+ Panorama di Agenti AI Industriali da Tenere d'Occhio

Industrial AI agents address the limitations of siloed data by autonomously integrating and deriving actionable insights from IoT, controls systems (e.g. SCADA), and connected assets.

Agenti di intelligenza artificialeMag 22

Agentic LLM Benchmark: Confronto dei Modelli Leader

We benchmarked the top LLMs across 10 software development tasks by using an agentic CLI tool. We executed ~3,500 automated validation steps per model across both API and UI layers. Agentic LLM benchmark results Success rate comparison Each alias ran 3 times across 10 tasks (30 samples per alias, 230 cells per iteration).

Agenti di intelligenza artificialeMag 22

Prestazioni degli Agenti AI: Tassi di Successo & ROI

Recent research reveals that AI performance follows predictable exponential decay patterns, enabling businesses to forecast capabilities and differentiate between costly failures and successful ROI-generating implementations. I oversaw 12 AIMultiple benchmarks, including nearly 70 AI agents across more than 1,000 tasks.