Live
Bring state-of-the-art agentic skills to the edge with Gemma 4●Supporting Google Account username change in your app●Developer’s Guide to Building ADK Agents with Skills●ADK 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 Java●Closing the knowledge gap with agent skills●Jump to play: Building with Gemini & MediaPipe●Build a smart financial assistant with LlamaParse and Gemini 3.1●Developer’s Guide to AI Agent Protocols●Announcing the Colab MCP Server: Connect Any AI Agent to Google Colab●Plan mode is now available in Gemini CLI●Introducing Finish Changes and Outlines, now available in Gemini Code Assist extensions on...●Unleash Your Development Superpowers: Refining the Core Coding Experience●Introducing Wednesday Build Hour●What's new in TensorFlow 2.21●You can't stream the energy: A developer's guide to Google Cloud Next '26 in Vegas●How we built the Google I/O 2026 Save the Date experience●Supercharge your AI agents: The New ADK Integrations Ecosystem●On-Device Function Calling in Google AI Edge Gallery●TorchTPU: Running PyTorch Natively on TPUs at Google Scale●Get ready for Google I/O: Livestream schedule revealed●New enhancements for merchant initiated transactions with the Google Pay API●Build Better AI Agents: 5 Developer Tips from the Agent Bake-Off●Building with Gemini Embedding 2: Agentic multimodal RAG and beyond●Production-Ready AI Agents: 5 Lessons from Refactoring a Monolith●Subagents have arrived in Gemini CLI●Build Long-running AI agents that pause, resume, and never lose context with ADK●MaxText Expands Post-Training Capabilities: Introducing SFT and RL on Single-Host TPUs●Agents CLI in Agent Platform: create to production in one CLI●Bring state-of-the-art agentic skills to the edge with Gemma 4●Supporting Google Account username change in your app●Developer’s Guide to Building ADK Agents with Skills●ADK 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 Java●Closing the knowledge gap with agent skills●Jump to play: Building with Gemini & MediaPipe●Build a smart financial assistant with LlamaParse and Gemini 3.1●Developer’s Guide to AI Agent Protocols●Announcing the Colab MCP Server: Connect Any AI Agent to Google Colab●Plan mode is now available in Gemini CLI●Introducing Finish Changes and Outlines, now available in Gemini Code Assist extensions on...●Unleash Your Development Superpowers: Refining the Core Coding Experience●Introducing Wednesday Build Hour●What's new in TensorFlow 2.21●You can't stream the energy: A developer's guide to Google Cloud Next '26 in Vegas●How we built the Google I/O 2026 Save the Date experience●Supercharge your AI agents: The New ADK Integrations Ecosystem●On-Device Function Calling in Google AI Edge Gallery●TorchTPU: Running PyTorch Natively on TPUs at Google Scale●Get ready for Google I/O: Livestream schedule revealed●New enhancements for merchant initiated transactions with the Google Pay API●Build Better AI Agents: 5 Developer Tips from the Agent Bake-Off●Building with Gemini Embedding 2: Agentic multimodal RAG and beyond●Production-Ready AI Agents: 5 Lessons from Refactoring a Monolith●Subagents have arrived in Gemini CLI●Build Long-running AI agents that pause, resume, and never lose context with ADK●MaxText Expands Post-Training Capabilities: Introducing SFT and RL on Single-Host TPUs●Agents CLI in Agent Platform: create to production in one CLI●

KI Force — Die deutsche KI-Wissensreferenz

18 Anbieter · 123+ Quellen · 101090+ 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 — 22. Oktober 2026 715 Artikel, 44 relevant
KI-Tagesüberblick 2026-10-22

### Highlights

1. Anthropic startet Claude Duet als Agenten-Konkurrenz — [Anthropic präsentiert Claude Duet](https://www.theverge.com/ai-artificial-intelligence/1015843/anthropic-claude-duet-ai-agent), einen KI-Agenten für Profis und kleine Unternehmen als Research Preview. Das Produkt konkurriert direkt mit Meta Muse und OpenAI Dots.

2. Google Cloud vereint alle großen Modellreihen auf einer Plattform — [Google Cloud bietet erstmals Gemini, Claude und OpenAI-Modelle zusammen an](https://the-decoder.de/google-cloud-bietet-als-erster-anbieter-gemini-claude-und-openai-modelle-auf-einer-plattform-an/). GPT-6 Astra, GPT-6.1 Sol und GPT-6 Luna starten als private Vorschau für Unternehmenskunden.

3. Kritische Sicherheitslücke in Agenten-Memory-Systemen entdeckt — [Prompt Injection über persistente Memory-Features](https://arxiv.org/abs/2610.28810) ermöglicht dauerhafte Kompromittierung von LLM-Agenten, die über Sessions hinweg Kontext bewahren.

4. Stille Informationsverluste bei Document-Ingestion identifiziert — [Formatierungsinformationen gehen bei der Dokumentenkonvertierung verloren](https://arxiv.org/abs/2610.30026), was Agenten zu konfidenten Fehlentscheidungen führt statt zu erkannten Unsicherheiten.

5. Robothik-Agenten-Benchmark zeigt Grenzen der Frontier-Modelle — [LIBERO-10 Manipulation Tasks offenbaren systematische Schwächen](https://arxiv.org/abs/2610.30051) bei der praktischen Roboter-Steuerung, trotz starker visueller Reasoning-Fähigkeiten.

### Forschung

- Monitor-Korrelationsfehler: [Approval-Systeme mit gemeinsamen Basismodellen fallen koordiniert aus](https://arxiv.org/abs/2610.29178) — ein Sicherheitsrisiko für Multi-Monitor-Architekturen.

- Memory-Systeme unter Druck: [MemoryTax-Studie zeigt, dass spezialisierte Memory-Systeme (Mem0, Zep) modernen Modellen unterlegen sind](https://arxiv.org/abs/2610.29823), wenn Modelle stark genug für Self-Search sind.

- Coding-Agent-Evaluation: [UserSWE Benchmark adressiert Multi-Turn Konversationen](https://arxiv.org/abs/2610.29822) und reduziert False Positives/Negatives bei Bug-Fix-Bewertungen.

- Memorization vs. Generalization: [Chess-Testbed trennt Reasoning von Recall](https://arxiv.org/abs/2601.16823) und bietet Methoden zur Unterscheidung echter Fähigkeiten von Trainingsdaten-Reproduktion.

- Diagnostische LLM-Evaluierung: [TIDE-Framework ersetzt einzelne Aggregate Scores durch granulare Fähigkeits-Diagnosen](https://arxiv.org/abs/2610.29985).

### Tool-Releases

- Omnara Open-Source Agent API — [Durable Agents als Open-Source Alternative zu Claude Managed Agents](https://github.com/omnara-ai/omnara). Agenten-State in Postgres, Sandbox-Ausführung, RBAC-Support.

- Claude Code v2.1.307 — [Update mit neuer API-Version 2026-10-21](https://github.com/anthropics/claude-code/releases/tag/v2.1.307), verbesserte OpenTelemetry-Events für Tool-Calls und Safety-Checks.

### Business & Standards

- Suchmaschinen-Manipulation durch LLMs: [Generative Engine Optimization kann Ranking-Reihenfolgen kontrollieren](https://arxiv.org/abs/2602.03608) und benachteiligt kleine Unternehmen systematisch.

- Klinische KI-Evaluation: [Decision Language Models kosten- und zeiteffizienter als LLM-Judges](https://arxiv.org/abs/2610.28826) für Qualitätsbewertungen im Healthcare-Kontext.

---

Datenstand: 715 verarbeitete Quellen (Top 20 nach Relevanz); Stand: 2026-10-22
▶ Top Playbooks Alle Playbooks →
Bereiche