#GeminiAi

cloud.google.com

Your agentic summer: No-cost lessons from Google experts to build and scale agents

Many in development and IT leadership are seeking practical ways to deploy AI agents into production. The provided information offers a hands-on solution through a comprehensive program designed to guide users from AI concept to fully autonomous agents. This summer, individuals can utilize Google's frameworks and approaches for building and scaling agents at no cost. The Gemini Enterprise Agent Ready (GEAR) program offers labs and courses to equip users with the necessary tools and blueprints. The learning path includes foundational introductions to AI agents and their impact on productivity. Users will delve into agent fundamentals like decision models and execution loops for adaptive agents. The curriculum also covers enterprise agent use cases, mapping agents to KPIs, and utilizing various coding frameworks. Several skill badges are available, validating expertise in creating Gemini Enterprise applications, orchestrating multi-agent workflows, and engineering AI agents with the Agent Development Kit. Additional modules focus on integrating currency tools, managing agent memory and state, creating custom agent skills, and operationalizing agents on Google Cloud. Participants can test their skills in the All Things Agentic Hackathon, competing for significant prizes. The program encourages immediate engagement to build in-demand skills and credentials, with new learning paths available for multi-agent systems and enterprise agent security.

www.techradar.com

The 'poison AI' movement wants to corrupt ChatGPT and Gemini to make them useless — but it comes with a huge risk of collateral damage

www.techradar.com

The 'poison AI' movement wants to corrupt ChatGPT and Gemini to make them useless — but it comes with a huge risk of collateral damage

The movement to sabotage AI through poisoned training data may be aimed at major tech companies, but its damage could spread to ordinary people and smaller organizations.

cloud.google.com

Mirendil taps AI Hypercomputer TPUs and GPUs for pre- and post-training applications

Google Cloud infrastructure is the preferred platform for most major AI labs and high-growth AI startups. These organizations rely on it for training models, inference, and cutting-edge research. Mirendil, a new frontier AI lab, is now also leveraging Google Cloud's AI Hypercomputer. This will involve using a combination of Google's TPU AI accelerators and NVIDIA's AI infrastructure. This specialized setup is designed to support Mirendil's model pre-training and post-training applications. Mirendil aims to develop AI systems that accelerate and democratize AI research and development. Their work involves managing complex training workflows and powering large-scale reinforcement learning. The flexibility to choose both TPUs and NVIDIA's platform on Google Cloud provides Mirendil with rapid access to compute resources. This allows them to match workloads to the most suitable architecture over time. Google Cloud partnered closely with Mirendil on the design and deployment of this integrated infrastructure. They also collaborated on a system using managed training clusters within the Gemini Enterprise Agent Platform. Mirendil is already utilizing TPU v5P chips and will soon integrate NVIDIA accelerated computing systems. This expansion allows Mirendil to scale and enhance their AI systems. They aim to put advanced AI research capabilities into the hands of more scientists and engineers.