agentic ai

Auto Added by WPeMatico

7 sessions worth starting with at SAS Innovate 2026

With SAS Innovate 2026 approaching, it’s a good time to step back and look at what this year’s agenda says about the state of data and AI. As in any year, speakers and presenters will cover a wide range of topics, from platform fundamentals to emerging ideas just entering production. […] The post 7 sessions […]

7 sessions worth starting with at SAS Innovate 2026 Read More »

Agoda Open Sources APIAgent to Convert Any REST pr GraphQL API into an MCP Server with Zero Code

Building AI agents is the new gold rush. But every developer knows the biggest bottleneck: getting the AI to actually communicate to your data. Today, travel giant Agoda is tackling this problem head-on. They have officially launched APIAgent, an open-source tool designed to turn any REST or GraphQL API into a Model Context Protocol (MCP)

Agoda Open Sources APIAgent to Convert Any REST pr GraphQL API into an MCP Server with Zero Code Read More »

How to Build Human-in-the-Loop Plan-and-Execute AI Agents with Explicit User Approval Using LangGraph and Streamlit

In this tutorial, we build a human-in-the-loop travel booking agent that treats the user as a teammate rather than a passive observer. We design the system so the agent first reasons openly by drafting a structured travel plan, then deliberately pauses before taking any action. We expose this proposed plan in a live interface where

How to Build Human-in-the-Loop Plan-and-Execute AI Agents with Explicit User Approval Using LangGraph and Streamlit Read More »

Alibaba Qwen Team Releases Qwen3.5-397B MoE Model with 17B Active Parameters and 1M Token Context for AI agents

Alibaba Cloud just updated the open-source landscape. Today, the Qwen team released Qwen3.5, the newest generation of their large language model (LLM) family. The most powerful version is Qwen3.5-397B-A17B. This model is a sparse Mixture-of-Experts (MoE) system. It combines massive reasoning power with high efficiency. Qwen3.5 is a native vision-language model. It is designed specifically

Alibaba Qwen Team Releases Qwen3.5-397B MoE Model with 17B Active Parameters and 1M Token Context for AI agents Read More »

Debenhams pilots agentic AI commerce via PayPal integration

Debenhams is piloting agentic AI commerce via PayPal integration to reduce mobile friction and help solve a familiar problem for retailers. Mobile checkout abandonment remains a persistent revenue leak for digital retailers. Debenhams Group is attempting to close this gap by deploying an agentic AI interface within the PayPal app. The pilot makes Debenhams the

Debenhams pilots agentic AI commerce via PayPal integration Read More »

URBN tests agentic AI to automate retail reporting

Retail decisions often depend on weekly performance reports, but compiling those reports can take hours of manual work. Urban Outfitters Inc. (URBN) is testing a new approach by using agentic AI systems to generate those reports automatically, changing routine analysis from staff to software. The retailer runs brands like Urban Outfitters, Anthropologie, and Free People,

URBN tests agentic AI to automate retail reporting Read More »

Google DeepMind Proposes New Framework for Intelligent AI Delegation to Secure the Emerging Agentic Web for Future Economies

The AI industry is currently obsessed with ‘agents’—autonomous programs that do more than just chat. However, most current multi-agent systems rely on brittle, hard-coded heuristics that fail when the environment changes. Google DeepMind researchers have proposed a new solution. The research team argued that for the ‘agentic web’ to scale, agents must move beyond simple

Google DeepMind Proposes New Framework for Intelligent AI Delegation to Secure the Emerging Agentic Web for Future Economies Read More »

A Coding Implementation to Design a Stateful Tutor Agent with Long-Term Memory, Semantic Recall, and Adaptive Practice Generation

In this tutorial, we build a fully stateful personal tutor agent that moves beyond short-lived chat interactions and learns continuously over time. We design the system to persist user preferences, track weak learning areas, and selectively recall only relevant past context when responding. By combining durable storage, semantic retrieval, and adaptive prompting, we demonstrate how

A Coding Implementation to Design a Stateful Tutor Agent with Long-Term Memory, Semantic Recall, and Adaptive Practice Generation Read More »

Moonshot AI Launches Kimi Claw: Native OpenClaw on Kimi.com with 5,000 Community Skills and 40GB Cloud Storage Now

Moonshot AI has officially brought the power of OpenClaw framework directly to the browser. The newly rebranded Kimi Claw is now native to kimi.com, providing developers and data scientists with a persistent, 24/7 AI agent environment. This update moves the project from a local setup to a cloud-native powerhouse. This means the infrastructure for complex

Moonshot AI Launches Kimi Claw: Native OpenClaw on Kimi.com with 5,000 Community Skills and 40GB Cloud Storage Now Read More »

Meet ‘Kani-TTS-2’: A 400M Param Open Source Text-to-Speech Model that Runs in 3GB VRAM with Voice Cloning Support

The landscape of generative audio is shifting toward efficiency. A new open-source contender, Kani-TTS-2, has been released by the team at nineninesix.ai. This model marks a departure from heavy, compute-expensive TTS systems. Instead, it treats audio as a language, delivering high-fidelity speech synthesis with a remarkably small footprint. Kani-TTS-2 offers a lean, high-performance alternative to

Meet ‘Kani-TTS-2’: A 400M Param Open Source Text-to-Speech Model that Runs in 3GB VRAM with Voice Cloning Support Read More »