Browsing: Agentic

In healthcare and life sciences, AI agents help organizations process clinical data, submit regulatory filings, automate medical coding, and accelerate drug development and commercialization. However, the…

Image by Author   # Introduction  Running a top-performing AI model locally no longer requires a high-end workstation or expensive cloud setup. With lightweight tools and smaller…

Z.AI, the AI platform developed by the team behind the GLM model family, has released GLM-5.1 — its next-generation flagship model developed specifically for agentic engineering.…

import subprocess, sys subprocess.check_call( [sys.executable, “-m”, “pip”, “install”, “-qU”, “google-genai”], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, ) import getpass, json, textwrap, os, time from google import genai from google.genai import…

This post is co-written with Arad Ben Haim and Hannah Danan Moise from Windward. Windward is a leading Maritime AI™ company, delivering mission-grade, multi-source intelligence for…

Agentic tool calling is what makes AI agents useful in production. It’s how they query databases, trigger workflows, retrieve real-time data, and act on a user’s…

print(“\n” + “=” * 70) print(“🤖 SECTION 8: Multi-Tool Agentic Loop”) print(“=” * 70) print(“Build a complete agent that can use multiple tools across turns.\n”) class…

Image by Author   # Introduction  The rise of frameworks like LangChain and CrewAI has made building AI agents easier than ever. However, developing these agents often…

Run Google’s latest omni-capable open models faster on NVIDIA RTX AI PCs, from NVIDIA Jetson Orin Nano, GeForce RTX desktops to the new DGX Spark, to…

DevOps used to be predictable: same input, same output, binary success, static dependencies, concrete metrics. You could control what you could predict, measure what was concrete,…