Live
Bring state-of-the-art agentic skills to the edge with Gemma 4Supporting Google Account username change in your appDeveloper’s Guide to Building ADK Agents with SkillsADK Go 1.0 Arrives!Boost Training Goodput: How Continuous Checkpointing Optimizes Reliability in Orbax and Ma...Announcing ADK for Java 1.0.0: Building the Future of AI Agents in JavaClosing the knowledge gap with agent skillsJump to play: Building with Gemini & MediaPipeBuild a smart financial assistant with LlamaParse and Gemini 3.1Developer’s Guide to AI Agent ProtocolsAnnouncing the Colab MCP Server: Connect Any AI Agent to Google ColabPlan mode is now available in Gemini CLIIntroducing Finish Changes and Outlines, now available in Gemini Code Assist extensions on...Unleash Your Development Superpowers: Refining the Core Coding ExperienceIntroducing Wednesday Build HourWhat's new in TensorFlow 2.21You can't stream the energy: A developer's guide to Google Cloud Next '26 in VegasHow we built the Google I/O 2026 Save the Date experienceSupercharge your AI agents: The New ADK Integrations EcosystemOn-Device Function Calling in Google AI Edge GalleryTorchTPU: Running PyTorch Natively on TPUs at Google ScaleGet ready for Google I/O: Livestream schedule revealedNew enhancements for merchant initiated transactions with the Google Pay APIBuild Better AI Agents: 5 Developer Tips from the Agent Bake-OffBuilding with Gemini Embedding 2: Agentic multimodal RAG and beyondProduction-Ready AI Agents: 5 Lessons from Refactoring a MonolithSubagents have arrived in Gemini CLIBuild Long-running AI agents that pause, resume, and never lose context with ADKMaxText Expands Post-Training Capabilities: Introducing SFT and RL on Single-Host TPUsAgents CLI in Agent Platform: create to production in one CLIBring state-of-the-art agentic skills to the edge with Gemma 4Supporting Google Account username change in your appDeveloper’s Guide to Building ADK Agents with SkillsADK Go 1.0 Arrives!Boost Training Goodput: How Continuous Checkpointing Optimizes Reliability in Orbax and Ma...Announcing ADK for Java 1.0.0: Building the Future of AI Agents in JavaClosing the knowledge gap with agent skillsJump to play: Building with Gemini & MediaPipeBuild a smart financial assistant with LlamaParse and Gemini 3.1Developer’s Guide to AI Agent ProtocolsAnnouncing the Colab MCP Server: Connect Any AI Agent to Google ColabPlan mode is now available in Gemini CLIIntroducing Finish Changes and Outlines, now available in Gemini Code Assist extensions on...Unleash Your Development Superpowers: Refining the Core Coding ExperienceIntroducing Wednesday Build HourWhat's new in TensorFlow 2.21You can't stream the energy: A developer's guide to Google Cloud Next '26 in VegasHow we built the Google I/O 2026 Save the Date experienceSupercharge your AI agents: The New ADK Integrations EcosystemOn-Device Function Calling in Google AI Edge GalleryTorchTPU: Running PyTorch Natively on TPUs at Google ScaleGet ready for Google I/O: Livestream schedule revealedNew enhancements for merchant initiated transactions with the Google Pay APIBuild Better AI Agents: 5 Developer Tips from the Agent Bake-OffBuilding with Gemini Embedding 2: Agentic multimodal RAG and beyondProduction-Ready AI Agents: 5 Lessons from Refactoring a MonolithSubagents have arrived in Gemini CLIBuild Long-running AI agents that pause, resume, and never lose context with ADKMaxText Expands Post-Training Capabilities: Introducing SFT and RL on Single-Host TPUsAgents CLI in Agent Platform: create to production in one CLI

KI Force — Die deutsche KI-Wissensreferenz

18 Anbieter · 123+ Quellen · 47688+ Artikel

★ Aktuell Alle News →

Bring state-of-the-art agentic skills to the edge with Gemma 4

Google DeepMind has launched Gemma 4, a family of state-of-the-art open models designed to enable multi-step planning and autonomous agentic workflows directly on-device. The release includes the Google AI Edge Gallery for experimenting with "Agent Skills" and the LiteRT-LM libra...

Neueste Artikel Mehr ansehen →
• developers

ADK Go 1.0 Arrives!

The launch of Agent Development Kit (ADK) for Go 1.0 marks a significant shift from experimental AI scripts to productio...

▶ Tages-Digest — 18. Juni 2026 540 Artikel, 26 relevant
# KI-Tagesüberblick 2026-06-18

Highlights

1. GLM-5.2: Mächtiges Open-Source Sprachmodell veröffentlicht — Das chinesische AI-Lab Z.ai hat [GLM-5.2](https://simonwillison.net/2026/Jun/17/glm-52/#atom-everything), ein 753B-Parameter-Modell mit 40 aktiven Parametern (Mixture of Experts), unter MIT-Lizenz freigegeben. Es gilt derzeit als eines der leistungsfähigsten vollständig open-source Sprachmodelle.

2. Agent-Sicherheit im Fokus: Mehrere kritische Benchmarks vorgestellt — Neue Evaluationsrahmen zeigen erhebliche Sicherheitslücken bei KI-Agenten auf: [LivePI](https://arxiv.org/abs/2605.17986) untersucht Indirect Prompt Injection, [SafeClawBench](https://arxiv.org/abs/2606.18356) differenziert zwischen semantischen und praktischen Schäden bei Tool-Use-Agenten.

3. Intent-Execution Gap als fundamentales Problem identifiziert — [Forschung von Anthropic, OpenAI und Google](https://arxiv.org/abs/2606.17454) zeigt, dass KI-Agent-Performance nicht nur ein Modellproblem ist, sondern ein Systemintegrations-Problem. Lücken zwischen Modellintention und tatsächlicher Agent-Ausführung verhindern volle Capability-Realisierung.

4. Agenten für spezialisierte Domänen evaluiert — [TxBench-PP](https://arxiv.org/abs/2606.19245) benchmarkt KI-Agenten in Pharmazie, [ResearchClawBench](https://arxiv.org/abs/2606.07591) testet autonome Forschung über 40 Tasks in 10 wissenschaftlichen Domänen.

5. Praktische Agent-Deployments in Produktion — Cloudflare bringt [Cloudflare One Stack mit Agent-Powered Deployment](https://blog.cloudflare.com/cloudflare-one-stack/), während [Adam (YC W25)](https://github.com/Adam-CAD/CADAM) Open-Source AI-Agenten für mechanisches CAD-Design entwickelt.

## Modell-Updates

- GLM-5.2: 753B-Parameter Open-Weights Modell von Z.ai, nur Text-Input, unter MIT-Lizenz verfügbar

## Tool-Releases

- [Mira](https://github.com/miracodeai/mira) — Open-source, selbstgehosteter KI-Code-Reviewer mit durchschnittlicher Review-Zeit von 77 Sekunden (vs. 5 Minuten bei Konkurrenten)
- [Adam CADAM](https://github.com/Adam-CAD/CADAM) — Open-Source Text-to-CAD Platform für mechanische Designgenerierung
- [Claude Code v2.1.181](https://github.com/anthropics/claude-code/releases/tag/v2.1.181) — Neue Config-Syntax, macOS Apple Events Support

## Forschung

- Agent-Verhalten-Analyse: [Dissecting Model Behavior Through Agent Trajectories](https://arxiv.org/abs/2606.17454) untersucht die Lücke zwischen Modellintention und praktischer Harness-Ausführung
- Sicherheit Tool-Use-Agenten: [SafeClawBench](https://arxiv.org/abs/2606.18356) differenziert zwischen semantischen, Audit- und Sandbox-Schäden
- Domain-Camouflaged Attacks: [Evaluierung von Prompting-basierten Defenses](https://arxiv.org/abs/2606.18530) gegen Injektionsangriffe
- Long-Horizon Agent-Fähigkeiten: [CEO-Bench](https://arxiv.org/abs/2606.18543) testet Agenten auf komplexen, langfristigen Aufgaben
- Menschenähnliches Verhalten: [Multi-dimensionale Analyse](https://arxiv.org/abs/2606.18258) von LLM-Verhaltensweisen und System-Prompts
- Code-Sicherheit durch Agenten: [Code-Augur](https://arxiv.org/abs/2606.18619) beschreibt agentic vulnerability detection durch Spezifikations-Inferenz
- Kontekt-Engineering: [Praktischer Guide für Python-Projekte](https://realpython.com/python-context-engineering-ai/) zur Optimierung von Agent-Context-Windows

## Business & Infrastruktur

- Cloudflare One Stack: Agent-basierte Deployment-Lösung für Zero-Trust-Architektur-Migration
- Curriculum für Agenten-Feedback: [CAPRA](https://arxiv.org/abs/2606.18976) automatisiert Bewertung von Software-Architecture-Deliverables in der Ausbildung
▶ Top Playbooks Alle Playbooks →
Bereiche