Flock meets OpenClaw: Enterprise-Ready Agentic AI with First-Class Agent Integration Contents The AI That Does Things, Now with Enterprise Orchestration What's New in Flock v0.5.400 Architecture: Engine-Level Integration Getting Started What You Can Build Error Handling Running Agentic AI in a Secured Environment Flock's declarative type contracts and blackboard [...]
Deklarative Agenten und Blackboard-Orchestierung – Flock 0.5 ist da! Inhalt Highlights auf einen Blick Deklarative Agenten - Typed Contracts statt Prompt-Prosa Blackboard-Orchestrierung - Pub/Sub mit Persistenz und Sichtbarkeit Weitere Highlights von Flock 0.5 Weitere neue Features & Getting Started Viele KI-Projekte starten mit Begeisterung und enden im Prompt-Chaos. [...]
Token Control 4.0 - Release Notes Mehr Transparenz, mehr Kontrolle, mehr Modelle: Mit Token Control 4.0 heben wir KI-Governance und FinOps auf das nächste Level – von einer noch detaillierteren Kostenberechnung über eine überarbeitete Oberfläche bis hin zur Unterstützung neuer Modelle und Azure AI Foundry. TL;DR Neue Modelle: text-embedding-3-large, GPT-4.1-nano, GPT-4o, vollständige GPT‑5‑Familie, image-1 [...]
Schluss mit Kostenblindflug: Wie Token Control KI-Kosten zähmt und Governance vereinfacht KI-Use-Cases nehmen zu, Agenten werden komplexer – doch Budgets, Limits und Sicherheit halten oft nicht Schritt. Token Control hilft Ihnen, FinOps und Governance für KI praxistauglich umzusetzen. Anhand konkreter Beispiele aus dem Unternehmensalltag zeigen wir, wo typische Kostenfallen [...]
Flock - Our new open-source AI Agent Framework Flock is a framework for orchestrating LLM-powered agents. It leverages a declarative approach where you simply specify what each agent needs as input and what it produces as output—without having to write lengthy, brittle prompts. Under the hood, Flock transforms these declarations into [...]
What's all the hype with Transformers? Part 3: Enter the Transformer Model In our previous posts "What’s all the Hype with Transformers? The Trouble with Natural Language Processing" and "What’s all the hype with Transformers? Part 2: Memory for RNNs", we highlighted some of the issues of natural language [...]
What's all the hype with Transformers? Part 2: Memory for RNNs Contents Introduction Recurrent Neural Networks Towards a Solution: Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) Introduction In the previous post, we highlighted some of the issues we are faced with when attempting to process natural language [...]
What's all the Hype with Transformers? The Trouble with Natural Language Processing Contents Introduction The Troubles with Natural Language Processing Traditional Neural Networks Recurrent Neural Networks Outlook Introduction This post tries to highlight the practical differences between traditional RNNs and the new Transformer Architecture. We are not going to [...]
Personalizing AI – How to Build Apps Based on Your Own Data Generative AI is on everyone's lips. Both software providers and companies with in-house developers have started to implement intelligent applications and functions based on generative AI models, such as those from OpenAI. One of the best ways [...]
Erweiterung unseres Portfolios um AI und weitere Microsoft Zertifizierung für AI. Neue Angebote zur Steigerung der Developer Productivity mit GitHub Copilot und der Entwicklung von intelligenten Anwendungen mit Azure OpenAI.