Here's what we shared at #GoogleIO: 👉 Vertex AI for Firebase 👉 Firebase Data Connect 👉 Gemini in Firebase is GA 👉 Firebase App Hosting See the details. 👀 ↓
Nice banner, but I prefer non-relational db 😄
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Here's what we shared at #GoogleIO: 👉 Vertex AI for Firebase 👉 Firebase Data Connect 👉 Gemini in Firebase is GA 👉 Firebase App Hosting See the details. 👀 ↓
Nice banner, but I prefer non-relational db 😄
👍
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Engineering and Product Executive focusing on making Google’s 3P application developers successful. Twitter: @sgnagnarella
What started 8 months ago as a humble pitch, is now out for developers around the world to try out: Introducing Firebase Genkit: an open source framework for building and deploying GenAI Apps. https://lnkd.in/ddjUbWjT What makes Genkit so special? 1- Intuitive for developers 2- AI focused local development 3- Open and extensible 4- Ready for serverless 5- Built for apps in production
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Genkit is definitely worth checking out, especially if you're already a TS/JS dev. If you're a GoLang dev wait a bit for the Go release. The team has done a good job not simply building API connectors, but building a local development playground and toolkit which does trace and evals well. If you've worked in the Gen AI space you likely realize how important observability tooling is to getting your app to a high enough quality that it can launch. I love that Genkit builds that in from the start (not an add on) and I'm hopeful we can continue to provide a guided path for Gen AI app & agent development. On the topic, Vertex AI Eval Service has some great Eval models for (batch or real-time "rapid" API) and returning a "pointwise" score or an automatic side-by-side.
Engineering and Product Executive focusing on making Google’s 3P application developers successful. Twitter: @sgnagnarella
What started 8 months ago as a humble pitch, is now out for developers around the world to try out: Introducing Firebase Genkit: an open source framework for building and deploying GenAI Apps. https://lnkd.in/ddjUbWjT What makes Genkit so special? 1- Intuitive for developers 2- AI focused local development 3- Open and extensible 4- Ready for serverless 5- Built for apps in production
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Announced during Google I/O this year were three features I am excited about - PaLM API, OR queries in Firestore and upgrades to Flutter web. PaLM API is a new AI tool for developing extensions and services on Firebase. It is still still in its infancy and you have to join the waitlist, but it reveals the future ability for adding AI capabilities to Firebase. OR queries... about time! Its crazy that you cannot do an OR query in a database, but you couldn't before this change. In the past we had to workaround this with operations on the client side or elsewhere that makes filtering a hassle and takes up resources. There are so many constraints in the filtering, but I am glad the team is taking steps to add more capabilities like this. In my opinion Flutter web is competing with established web application frameworks like React and Vue. There are some libraries and packages missing from Flutter web that I need which is why I still use React to deploy my web applications, even though my app is ready on Flutter. This could change soon with more off-the-shelf packages. Here is one big one - "Using sign-in with Apple, Google Sign-In, GitHub, and other sign-in providers". This was one of the hurdles when converting my mobile app to a web app. Hoping to only maintain one code base for my app soon. Read more on the other upgrades here: https://lnkd.in/gFcyQrU7 #firebase #flutter #flutterdeveloper #mobileappdeveloper #mobileappdevelopment
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🔥 Firebase app hosting got announced at Google I/O You can use it to host your Angular and Next.js apps using SSG, SSR, and CSR with zero-config! It has been great pairing with the Firebase team to improve deployment for web developers https://lnkd.in/gkZzdh9s #angular #react #firebase #deployment #javascript #typescript #webdev
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How to create a chatbot with Firebase Firestore and PaLM on Android
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Thrilled to have contributed to Microsoft Learn! My recent PR aims to assist developers in saving time while implementing App Insights with Spring Boot. Now, finding the necessary code snippets for App Insights integration will be a breeze. Check out the documentation here: https://lnkd.in/gcmtqkr3 #azure #microsoft #microsoftazure #MicrosoftDocs #Contribution #AppInsights #SpringBoot #DeveloperProductivity
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computer science engineer | java developer | Python programmer | Web developer | Flutter cross platform application developer
Tired of backend battles slowing your Flutter flow? Firebase swoops in, your coding companion! Authentication: Logins become a breeze, social or good ol' email/password. Real-time Database: Your app updates live, like a superhero team chat! Cloud Firestore: Flexible data storage, perfect for villain profiles (weaknesses included ). Cloud Functions: Your app reacts like a trusty sidekick, triggered by events. Firebase + Flutter = Dream Team! Build stunning, cross-platform apps that conquer complexity. It's mobile dev, supercharged! #snsinstitutions #application #firebase #flutter #snsdesignthinkers #snsdesignthinking
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Introducing Firebase Extensions with the Gemini API 🔥 Quickly and easily add AI features to your Firebase apps using the Gemini API. #BuildWithGemini #firebase
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Great initiative, Swami! Sharing your summary of the day's announcements from AWSreInvent is an excellent way to keep the community informed and engaged. Peter Desantis' keynote always offers valuable insights, and his deep dive into serverless technologies must have been fascinating. I'm sure many of us are looking forward to reading your notes and gaining a better understanding of the key takeaways. Keep up the great work!
Trying something new this year. Throughout #AWSreInvent, I’m going to share my summary of the day’s announcements—straight from my notes app. I love Peter Desantis' keynote because of the deep dive he does in a few specific areas, and this year he focused a lot on serverless technologies. Here’s what you need to know about Peter’s keynote:
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Let's continue with the overview of what the Lookout for Equipment app we open sourced last week (see here: https://lnkd.in/dvqbYyiT) lets you do! Expanding on what we have in the AWS console for the service, you will be able to train your own model, but with much more visual feedbacks. With this application, you will be able to visualize your time series signals while selecting the training range of interest, have a direct feedback when you select your signals or labels or even configure your the off time detection with a drag and drop interface. Want to test by yourself? Feel free to check out this GitHub repo and deploy the app in your AWS account: https://lnkd.in/d9W2wxvC #anomalydetection #predictivemaintenance #conditionmonitoring
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2wThe query seems like sql🫡