How ML developers are saving moms in India
Abbiramy Kumar from Savemom explains how she uses her Machine Learning role to create a healthcare app for doctors and expecting moms.
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How student developers are using Vertex AI for healthcare
Savemom is comprised of software engineers and computer science students who delivered a market ready AI powered healthcare app in no time using Google Vertex AI.
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Using Vertex AI for healthcare
Meet Savemom Founder & Engineer Senthil Kumar in India. Senthil is leveraging multimodal AI in Vertex AI studio to digitize, analyze, and process healthcare paperwork.
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How Google AI helps with safer pregnancies
In India, expectant mothers often face lengthy wait times and paper based record keeping for their pregnancy care. Savemom is changing that with the help of Google AI.
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Google Cloud Compute Engine: Provisioning options
gcloud compute instances create → goo.gle/4iBDqdM Take control of your cloud infrastructure with this guide to provisioning Google Cloud Compute Engine (GCP) instances.
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Get started with JAX using NNX 🦾🧠
NNX makes building and training machine learning models a breeze with its intuitive, Pythonic approach.
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NNX the neural network for Flax explained
Tutorial (NNX Basics) → goo.gle/3BMV6St Tutorial (MNIST) → goo.gle/4f472ON Tutorial (NNX vs JAX Transformations) → goo.gle/4h81iEZ Discover NNX, a powerful neural network
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AI powered security for your team
Gemini in Google SecOps → goo.gle/40tDZhu Create and edit a playbook with Gemini → goo.gle/40C2Fo6 Explore how Gemini in Security Operations is an artificial intelligence-powered
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Translating baby sounds using Google AI
Get started with Vertex AI → goo.gle/3DcrC1b Build with Gemini → goo.gle/4fl9YWp Create document processors → goo.gle/4gaPG39 Extract insights from images, documents, and
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Introduction to JAX with Pallas
Unlock the power of custom JAX kernels with Pallas.
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How to use custom JAX kernels with Pallas
Pallas quickstart → goo.gle/48bjFEN Pallas design overview → goo.gle/408hpw4 Dive into the world of custom kernel programming in JAX with Pallas.
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How to build interactive Gen AI applications with Vertex AI
RAG vs Model tuning vs Large prompt window → goo.gle/405POu7 GitHub → goo.gle/CymbalToys Want to create more engaging and effective AI applications?
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Securing your AI inference pipeline
Check out part 1 of this video → goo.gle/4gpPXzc Google SAIF → goo.gle/3Dbfg9s Google AI Supply Chain Security Whitepaper → goo.gle/3ZRZf15 Are you leaving the door open for
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Why use GKE for AI/ML workloads?
Learn more → goo.gle/AIMLonGKE With Google Kubernetes Engine (GKE), you can implement a robust, production-ready AI/ML platform with all the benefits of managed Kubernetes.
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Skip versions when upgrading clusters on GDC
Learn more → goo.gle/skip_version_upgrade Google Distributed Cloud (GDC) supports skip-version upgrades so your GDC clusters stay on a supported window for a longer time.
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Chatting with Gemini as a developer 🤖
Watch along as Googler Tanya Dixit uses Google AI Studio to build a voice-first chatbot.
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How to use Gemini function calling with Cloud Run
Explore the power of Gemini function calling and learn how to integrate external APIs into your AI applications.
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Protect against vulnerabilities in your app with Red teaming
Watch along as Tanya Dixit, Gen AI Solutions Architect at Google, discusses how to use Gemini to design prompts to expose vulnerabilities in your app and create solutions to protect your app before
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Google Cloud Tech
The Google Cloud Tech YouTube channel is your all-access pass to Google Cloud expertise.
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Securing your AI model development pipeline
Vertex AI Pipelines → goo.gle/41IIBSZ Binary Authorization → goo.gle/3VOTAGL Vertex AI Pipeline demo → goo.gle/4ghaHJE Are you concerned about AI models going rogue?
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How to deploy a Gemini powered Mesop app to Cloud Run
Cloud Run docs → goo.gle/3D6PYcB Enabling Vertex AI APIs → goo.gle/41l5z2q Watch along and learn how to deploy a Gemini powered application to Google Cloud using Mesop to Cloud Run.
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Gemini APIs for advanced developers
Unlock new possibilities with advanced techniques for the Gemini APIs. Join Paige Bailey on our channel to learn about advanced techniques like long context, context caching, and code execution.
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How to use the Gemini APIs: Advanced techniques
Context caching → goo.gle/3YdU1eh Code execution → goo.gle/3NtMaEb Long context → goo.gle/3BYdrMp Dive into the world of advanced Gemini API techniques for developers.
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Text to image with Google Cloud’s Vertex AI on Cloud Run
Code lab → goo.gle/4iLL2KK Unleash your creativity and build an image generation app using Vertex AI on Google Cloud.
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How to use customer-managed keys (CMEK)
Cloud services that have a CMEK integration → goo.gle/4iKELPm Protection levels → goo.gle/49PFyur Learn how Google Cloud's Customer-Managed Encryption Keys (CMEK) simplify data
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How to build a Gemini powered Mesop app
Mesop docs → goo.gle/4fevNas Gemini docs → goo.gle/3Zv3LB9 Join Googler Remigiusz Samborski in this hands-on video tutorial that demonstrates how to deploy a Gemini powered
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What is Low-Rank Adaptation (LoRA) for Gemma?
Level up your machine learning skills with Low-Rank Adaptation (LoRA) for fine tuning your AI model.
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Fine tuning Gemma with LoRA in Google Colab
Fine-tune Gemma models in Keras using LoRA → goo.gle/407Kise Learn how to optimize large language models using LoRA (Low-Rank Adaptation) with a model from Google AI, Gemma.
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Evaluate any generative AI model with Vertex AI
Colab Notebook: Evaluate Gemma 2 with the Gen AI evaluation service on Vertex AI → goo.gle/4iIAZpI Docs: Gen AI evaluation service on Vertex AI → goo.gle/3VOThvJ Reference
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Gemini Code Assist tools: Stay in the flow while coding
Tools for Gemini Code Assist → goo.gle/4fvbvZT Gemini Code Assist → goo.gle/3BfYUvU Stay in your workflow and never leave your IDE again.
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