Ivan Nardini

generative-ai/gemini/tuning/dpo_gemini.ipynb at main · GoogleCloudPlatform/generative-ai Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI - GoogleCloudPlatform/generative-ai

Documentation: docs.cloud.google.com/vertex-ai/g...
Code: github.com/GoogleCloud...

Supervised Fine-Tuning (SFT) adapts pre-trained models with labeled data but often misses aligning with user preferences.

Vertex AI now supports preference tuning (DPO) for Gemini 2.5 Flash and Flash-Lite, allowing you to use response pairs to adjust user preferences.

Code and docs in the 🧵

Agents in Action: Hands-on Workshop with Google Cloud, Meta & Arize AI · Luma Join Google Cloud, Meta, and Arize AI for an advanced hands-on workshop exploring how to build, evaluate, and optimize agents and applications. In this…

I’m skipping this event, but you're in good hands.

Yemi Falokun, a Global AI/ML Partner SA, will lead a workshop on AI agent engineering challenges with Meta and Arize AI.

If you're in the Bay Area, check it out: luma.com/gcpmetaariz...

Many have asked about agent memory and its differences from RAG.

We just released a whitepaper, "Context Engineering: Sessions and Memory," detailing how memory evolves from raw conversations to curated agent knowledge.

You can find the paper here: lnkd.in/euud4BUB

Building AI Agents Visually with Google ADK Visual Agent Builder Google ADK v1.18.0 introduced the Visual Agent Builder — a browser-based interface that lets you design, configure, and test complex…

Release notes: github.com/google/adk-...
Blog: medium.com/@chongcht/b...

TIME to upgrade: ADK introduces Visual Agent Builder 🚀

Last week, in the latest ADK release (v1.18.0), the team introduced a low-code Visual Agent Builder, along with new observability and testing features.

Release notes and a blog from Thomas Chong about the visual builder in the 🧵

Vertex AI Agent Engine adds Memory Revisions!

Trusting an agent's memory is tricky. Is chat info verified? Without history, it's guess. Memory Revisions (preview) helps with version control through snapshots for each change.

Code & doc in 🧵

More ways to build and scale AI agents with Vertex AI Agent Builder | Google Cloud Blog Announcing new capabilities across the entire agent lifecycle to help developers build, scale, and govern AI agents using Vertex AI Agent Builder. Get started today.

Blog: cloud.google.com/blog/product...

🚢 The New Vertex AI Agent Builder is OUT!

Vertex AI launched major updates to Vertex AI Agent Builder for easier deployment and scaling agents in production.

I'm working with the Agent Engine team to release content on our new features, starting today with Memory Bank. Stay tuned!

generative-ai/open-models/benchmarking_eagle_on_vertex_ai.ipynb at main · GoogleCloudPlatform/generative-ai Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI - GoogleCloudPlatform/generative-ai

Notebook: github.com/GoogleCloud...

Spent some time last week benchmarking LLMs on Vertex AI. I couldn't find a tutorial on using the @vllm_project bench library with Vertex, so I made one.

It's a walkthrough that compares Llama 4 (baseline vs. EAGLE) on 8x H100s and includes the code patch needed to make vLLM work.

Hope it helps! 👇

🔥 Benchmarking a new optimization integrated by the Model Garden team for serving LLMs on Vertex AI.

Can't wait to share!

#VertexAI #LLMs #Benchmarking #Optimization #ModelGarden #LLMServing

The Agent Factory Welcome to The Agent Factory, a podcast that goes beyond the hype and dives into building production ready AI agents. Join hosts Shir Meir Lador and Ivan as ...

The Agent Factory Podcast playlist:

www.youtube.com/playlist?li...

Another week, another episode of the Agent Factory podcast!

This time, Amit and I welcomed a special guest: Ravin Kumar from Google DeepMind. He shared insights on building open models with agentic capabilities.

Stay tuned! The episode will soon be on the Google Cloud Tech YouTube channel👇

Choosing the right format for your AI model: A comprehensive guide to AI inference formats By: Ekaterina Sirazitdinova, NVIDIA and Ivan Nardini, Google Cloud TL;DR: A technical guide to AI model formats for AI inference. Learn the trade-offs: use Safetensors for fast, secure serialization (replacing .bin), GGUF for quantized local/CPU inference (e.g., llama.cpp), TensorRT for compiled, high-performance NVIDIA GPU engines, and ONNX for graph-level framework interoperability. For further learning and hands-on experience with foundational inference workloads on Google Cloud, conside...

Join the NVIDIA & Google Cloud community: developers.google.com/community/n...
Course: developers.google.com/learn/pathw...
Blog: discuss.google.dev/t/choosing-...

Since the beginning of the year, I've wanted to dedicate time on some content about LLM inference in a way that was accessible to everyone. Today I'm excited to launch the 1st learning path on LLM inference, built with NVIDIA!

Check out the course and blog in the 🧵 And stay tuned...more is coming!

GitHub - google/adk-python: An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. - google/adk-python

> Release notes: github.com/google/adk-...
> ADK Community call: github.com/google/adk-...

ADK just released v1.17.0!

The team rolled out features focused on secure code execution, stateful debugging, and better DevX.

Check out the full release notes in 🧵. And keep an eye on the repo for the next ADK community call!

generative-ai/agents/agent_engine/tutorial_multi_agent_systems_on_vertexai_with_claude.ipynb at main · GoogleCloudPlatform/generative-ai Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI - GoogleCloudPlatform/generative-ai

> RVSP: cloudonair.withgoogle.com/events/depl...

> Tutorial: github.com/GoogleCloud...

In the upcoming webinar, together with Alex Notov from @AnthropicAI we're building a complete multi-agent system, exploring the key protocols (MCP & A2A) and how to scale agents using Claude on Vertex AI Agent Engine.

RVSP and tutorial in the 🧵

cloud-foundation-fabric/modules/agent-engine/README.md at master · GoogleCloudPlatform/cloud-foundation-fabric End-to-end modular samples and landing zones toolkit for Terraform on GCP. - GoogleCloudPlatform/cloud-foundation-fabric

Agent Engine in CFF: github.com/GoogleCloud...

Vertex AI Agent Engine is in the Cloud Foundation Fabric!

We launched a Terraform module for agent deployment on Vertex AI, initially needing a local Python script and GCS uploads.

The new blueprint automates agent serialization and packaging during the Terraform apply cycle.

Link in the 🧵

This is why I'm excited about Google Cloud's agent builder stack!

Building multi-agent systems using various models and frameworks can be challenging. So today I spent some time on what you can build and deploy with ADK, MCP, A2A, Agent Engine, and Vertex AI.

Full tutorial dropping soon!

Blog: blog.vllm.ai/2025/10/16/...
Docs: cloud.google.com/vertex-ai/g...
Notebook: console.cloud.google.com/vertex-ai/p...;publisherModelVersion=gemma-3-27b-it

🚀 vLLM on TPU just got a massive upgrade!

Google and vLLM announced a new backend uses tpu-inference for efficient PyTorch and JAX models on TPUs.

Check out the full blog and try it on Vertex AI with the new vLLM TPU container!

Vertex AI open models for MaaS  |  Generative AI on Vertex AI  |  Google Cloud Understand Vertex AI's managed open models as a service (MaaS). Discover, deploy, and use serverless open models, including embedding models.

Docs: cloud.google.com/vertex-ai/g...

This morning, I checked out Vertex AI docs and was impressed by the open-source models as APIs.

Model as a Service (MaaS) gives access to large open models via a managed, serverless API, removing the need for your infrastructure.

Check the new documentation in 🧵 to learn more

generative-ai/agents/cloud_run/agents_with_memory/get_started_with_memory_for_adk_in_cloud_run.ipynb at main · GoogleCloudPlatform/generative-ai Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI - GoogleCloudPlatform/generative-ai

GKE & AE: github.com/GoogleCloud...

Cloud Run & AE : github.com/GoogleCloud...

Can you use Agent Engine services on GKE or Cloud Run? Yes! You can combine managed services like memory bank with your preferred runtime.

Check out the two new tutorials in 🧵 on building AI agents using the Agent Development Kit (ADK) + Vertex AI Agent Engine for Sessions & Memory.

Notebook: github.com/GoogleCloud...

Blog: discuss.google.dev/t/deploy-yo...