Tag Archives: Project IDX

Gemini 1.5: Our next-generation model, now available for Private Preview in Google AI Studio

Posted by Jaclyn Konzelmann and Wiktor Gworek – Google Labs

Last week, we released Gemini 1.0 Ultra in Gemini Advanced. You can try it out now by signing up for a Gemini Advanced subscription. The 1.0 Ultra model, accessible via the Gemini API, has seen a lot of interest and continues to roll out to select developers and partners in Google AI Studio.

Today, we’re also excited to introduce our next-generation Gemini 1.5 model, which uses a new Mixture-of-Experts (MoE) approach to improve efficiency. It routes your request to a group of smaller "expert” neural networks so responses are faster and higher quality.

Developers can sign up for our Private Preview of Gemini 1.5 Pro, our mid-sized multimodal model optimized for scaling across a wide-range of tasks. The model features a new, experimental 1 million token context window, and will be available to try out in Google AI Studio. Google AI Studio is the fastest way to build with Gemini models and enables developers to easily integrate the Gemini API in their applications. It’s available in 38 languages across 180+ countries and territories.


1,000,000 tokens: Unlocking new use cases for developers

Before today, the largest context window in the world for a publicly available large language model was 200,000 tokens. We’ve been able to significantly increase this — running up to 1 million tokens consistently, achieving the longest context window of any large-scale foundation model. Gemini 1.5 Pro will come with a 128,000 token context window by default, but today’s Private Preview will have access to the experimental 1 million token context window.

We’re excited about the new possibilities that larger context windows enable. You can directly upload large PDFs, code repositories, or even lengthy videos as prompts in Google AI Studio. Gemini 1.5 Pro will then reason across modalities and output text.

  1. Upload multiple files and ask questions
  2. We’ve added the ability for developers to upload multiple files, like PDFs, and ask questions in Google AI Studio. The larger context window allows the model to take in more information — making the output more consistent, relevant and useful. With this 1 million token context window, we’ve been able to load in over 700,000 words of text in one go.

    moving image illustrating how Gemini 1.5 Pro can find and reason from particular quotes across the Apollo 11 PDF transcript.
    Gemini 1.5 Pro can find and reason from particular quotes across the Apollo 11 PDF transcript. 
    [Video sped up for demo purposes]

  3. Query an entire code repository
  4. The large context window also enables a deep analysis of an entire codebase, helping Gemini models grasp complex relationships, patterns, and understanding of code. A developer could upload a new codebase directly from their computer or via Google Drive, and use the model to onboard quickly and gain an understanding of the code.

    moving image illustrating how Gemini 1.5 Pro can help developers boost productivity when learning a new codebase.
    Gemini 1.5 Pro can help developers boost productivity when learning a new codebase.  
    [Video sped up for demo purposes]

  5. Add a full length video
  6. Gemini 1.5 Pro can also reason across up to 1 hour of video. When you attach a video, Google AI Studio breaks it down into thousands of frames (without audio), and then you can perform highly sophisticated reasoning and problem-solving tasks since the Gemini models are multimodal.

    moving image illustrating how Gemini 1.5 Pro can perform reasoning and problem-solving tasks across video and other visual inputs.
    Gemini 1.5 Pro can perform reasoning and problem-solving tasks across video and other visual inputs.  
    [Video sped up for demo purposes]

More ways for developers to build with Gemini models

In addition to bringing you the latest model innovations, we’re also making it easier for you to build with Gemini:

  • Easy tuning. Provide a set of examples, and you can customize Gemini for your specific needs in minutes from inside Google AI Studio. This feature rolls out in the next few days. 
  • New developer surfaces. Integrate the Gemini API to build new AI-powered features today with new Firebase Extensions, across your development workspace in Project IDX, or with our newly released Google AI Dart SDK
  • Lower pricing for Gemini 1.0 Pro. We’re also updating the 1.0 Pro model, which offers a good balance of cost and performance for many AI tasks. Today’s stable version is priced 50% less for text inputs and 25% less for outputs than previously announced. The upcoming pay-as-you-go plans for AI Studio are coming soon.

Since December, developers of all sizes have been building with Gemini models, and we’re excited to turn cutting edge research into early developer products in Google AI Studio. Expect some latency in this preview version due to the experimental nature of the large context window feature, but we’re excited to start a phased rollout as we continue to fine-tune the model and get your feedback. We hope you enjoy experimenting with it early on, like we have.

Introducing Android emulators, iOS simulators, and other product updates from Project IDX

Posted by the IDX team

Six months ago, we launched Project IDX, an experimental, cloud-based workspace for full-stack, multiplatform software development. We built Project IDX to simplify and streamline the developer workflow, aiming to reduce the sea of complexities traditionally associated with app development. It certainly seems like we've piqued your interest, and we love seeing what IDX has helped you build.

For example, we recently learned about Tanaki, an AI-enhanced content creation app built using Project IDX:

Image of content creation app Tanaki on a mobile device in the foreground, with coding in Project IDX on a computer screen in the banckgound.

Pasquale D’Silva one of the developers that built Tanaki, said:

"Using the IDX shared workspace to build Tanaki has been so fun. It allows our remote team of imagineers to build together in one place. It is a magic collaboration portal!"

Developers at Google have also been using IDX internally to help speed up development across various projects. One example is the the Firebase Blog, where the full authoring, development, and deployment of the Astro-powered project is handled using IDX:

Screen grab of The Firebase Blog on a computer

Another interesting project leveraging IDX’s extensibility model is Malloy, a new open-source data language available as a VS Code extension that operates against databases like BigQuery:

Screen grab of Malloy in Project IDX

Lloyd Tabb, a Distinguished Software Engineer at Google, told us:

“I use IDX with the Malloy project. I often have several different data projects going simultaneously and IDX lets me quickly spin up an instance to solve a problem and it is trivial to configure."

If you want to share what IDX has helped you build, use the #ProjectIDX tag on X.


What’s new in IDX?

In addition to seeing how you’re using IDX, a key part of building Project IDX is your feedback, so we’ve continued to roll out features for you to test. We're excited to share the latest updates we've implemented to expedite and streamline multiplatform app development, so you can deliver with speed, ease and quality.


Preview your app directly in IDX with our iOS simulator and Android emulator

We’re bringing the iOS Simulator and Android Emulator to the browser. Whether you’re building a Flutter or web app, Project IDX now allows you to preview your applications without having to leave your workspace. When you use a Flutter or web template, Project IDX intelligently loads the right preview environment for your application — Safari mobile and Chrome for web templates, or Android, iOS, and Chrome for Flutter templates.

Screen grab of an animation project in Project IDX

IDX’s web and Android emulators allow you to develop, test, and debug directly from your workspace, consolidating your multi-step, multiplatform process into one place. With iOS simulation you can spot-check your app's layout and behavior while you work. This feature is still experimental, so be sure to test it out and send us feedback.


Get started fast with a rich library of project templates

Four of our top ten feature requests have been to support more templates, so we’re pleased to share that we’ve added new templates for Astro, Go, Python/Flask, Qwik, Lit, Preact, Solid.js, and Node.js. Use these templates to jump right into your project so you can spend less time setting up and more time creating.

Preview of template gallery in Project IDX
Check out our new and improved template gallery

Of course you can still import your own repo from GitHub, directly from your local files, or you can choose your own setup using a custom Nix environment.


Quickly build and customize your IDX workspace with improvements to Nix

.idx/dev.nix

IDX uses Nix to define the environment configuration for each workspace to give you flexibility and extensibility in IDX – even our templates and previews are configured using Nix to ensure they’re working correctly inside IDX. We’re continuously working on Nix improvements to help boost your productivity, so now you can:

  • Customize IDX starter templates easily by leveraging Nix extensibility.
  • Reduce the likelihood of errors and write code more efficiently with Nix file editing, including support for syntax highlighting, error detection, and suggested code completions.
  • Recover from broken configurations quickly and avoid unnecessary rebuild attempts with major improvements to our environment customization workflow, including seamless environment rebuilds and troubleshooting.

Easily build, test, and deploy apps with additional new IDX features and resources

image showing backend ports and workspace tasks in IDX
  • Auto-detect network ports needed for applications or services and adjust the firewall settings to permit ingress and egress without any additional configuration on your end.
  • Instantly run command-line tools, scripts, and utilities directly within workspace without the need to install them locally on your machine.
  • Simplify the process of working with Docker containers and images directly from the development environment by enabling Docker in your dev.nix file.

AI launched in 15 new regions

image showing backend ports and workspace tasks in IDX

We’ve launched our AI capabilities in the following 15 countries: India, Australia, Israel, Brazil, Mexico, Colombia, Argentina, Peru, Chile, Singapore, Bangladesh, Pakistan, Canada, Japan, and South Korea. More countries will be enabled with AI access soon – indicate your interest for AI expansion in this feature tracking post and stay tuned for more AI updates.


Improving together

We're constantly working on adding new capabilities to help you do higher quality work, more efficiently, with less friction. We’ve addressed dozens of your feature requests and fixed a multitude of bugs you flagged for us, so thank you for your continued support and engagement – please keep the feedback coming by filing bugs and feature requests.

For walkthroughs and more information on all the features mentioned above, check out our documentation page. If you haven’t already, visit our website to sign up to try Project IDX and join us on our journey. Also, be sure to check out our new Project IDX Blog for the latest product announcements and updates from the team.

We can’t wait to see what you create with Project IDX!

Global developers use Google tools to build solutions in recruiting, mentorship and more

Posted by Lyanne Alfaro, DevRel Program Manager, Google Developer Studio

Developer Journey is a monthly series highlighting diverse and global developers sharing relatable challenges, opportunities, and wins in their journey. Every month, we will spotlight developers around the world, the Google tools they leverage, and the kinds of products they are building.

This month we speak with global developers across Google Developer Experts, and Women Techmakers, to learn more about their favorite Google tools, the applications they’ve built to serve diverse communities and the role of inclusive design in their process.


Miguel Ángel Durán Garcí

Headshot of Miguel Ángel Durán Garcí, smiling
Barcelona, Spain
Google Developer Expert, Web Technologies
Content Creator & Software Engineer

What Google tools have you used to build?

I've been using Firebase, Google Cloud Platform, CrUX Dashboard, and Chrome DevTools for years. As a web developer, I'm always excited about the new features that DevTools brings to us to improve our productivity and the performance of our applications.


Which tool has been your favorite to use? Why?

Lately, I've been trying Project IDX, an entirely web-based workspace for full-stack application development, and I'm really excited about the future of this project. I love the idea of being able to develop and deploy applications from the browser, without having to install anything on my computer.


Please share with us about something you’ve built in the past using Google tools.

Most recently, I've deployed AdventJS, a holiday calendar for developers. For optimizing the images, I've used Squoosh from the GoogleChromeLabs team. To ensure the website was accessible and to tweak performance, I've used Lighthouse from Chrome DevTools. Also, I used Google Bard to translate the content of the website into English and Portuguese.


What will you create with Google Bard?

I'm planning to expand a website I've created for the Spanish-speaking community to teach JavaScript from scratch. With Google Bard, I can check the content, create some code, and make it help me create challenges for the students.


What advice would you give someone starting in their developer journey?

I would tell them to be patient and to enjoy the process. It's a long journey, but it's worth it. Also, I would tell them to be curious and avoid sticking to only a few technologies. And finally, I would tell them to share their knowledge with the community, because it's the best way to learn and meet new people. You don't need to be an expert to share your knowledge; you just need to be one step ahead of the people you're teaching.


Marian Villa

Headshot of Marian Villa, smiling
Medellín, Colombia
Google Developer Expert, Web Technologies
Co-founder / Director Pionerasdev

What Google tools have you used to build?

Development and Creativity:

  • Google Chrome DevTools
  • Bard
  • TensorflowJS

Productivity and Communication:

  • Gmail
  • Google Calendar
  • Google Drive
  • Google Docs
  • Google Sheets
  • Google Slides
  • Google Meet

Marketing and Business:

  • Google Ads
  • Google Analytics
  • Google My Business
  • Google Workspace
  • Google Cloud Platform
  • Google Marketing Platform

Education and Learning:

  • Google Classroom
  • Google Forms
  • Google Sites
  • YouTube

Which tool has been your favorite to use? Why?

Choosing a favorite tool is quite a task given the unique strengths of Bard, TensorflowJS and Google Chrome DevTools, but I'd have to say that Google Chrome DevTools stands out for me. Its versatility in inspecting and debugging web pages, testing code variations, and providing insights into JavaScript behavior has been crucial in my web development endeavors. That being said, both Bard and TensorFlow.js have incredible capabilities. Bard plays a vital role in generating creative content, answering queries, and even composing code. TensorFlow.js, on the other hand, is a game-changer, enabling machine learning in JavaScript, and making it accessible for a wide range of applications. Each tool has its unique appeal, and the choice will depend on the context and specific requirements of the task at hand.


Please share with us about something you’ve built in the past using Google tools.

On our latest website, we use all the Google technologies at hand to enhance our image as an NGO. Find it here.


What will you create with Google Bard?

We are once again resuming a winning mentorship project to advance our career as developers, so Bard and Duet AI are great allies to inspect our code and once again create an MVP of this product for our community.


What advice would you give someone starting in their developer journey?

First, think about the problem you want to solve, or what you want to contribute to the world, then create and make it come true. This is easier if you rely on communities, and people who help you as mentors, sponsors and guides.


Rubens de Almeida Zimbres

Headshot of Rubens Zimbres, smiling
São Paulo - Brazil
Google Developer Expert, Machine Learning and Google Cloud
ML Engineer

What Google tools have you used to build?

I’ve been using the full stack of Google Products. I use Google Workspace daily in my life, my personal website is made on Google Sites, and Google Cloud; I started with Compute Engine and Jupyter Notebooks, customized to my needs.

As I acquired more knowledge through practical experience, Coursera and Google Cloud Skills Boost, I started building end to-end solutions using BigQuery, SQL, lots of Vertex AI (Generative AI Studio, Matching Engine, Speech-to-text, Pipelines, AutoML, Model Fine-Tuning), Cloud Run (and a little GKE - Kubernetes), Cloud Functions, Dialogflow and Document AI.

As the requirements of clients change according to the industry, like recruiting (Virtual Career Center) and contact center (Contact Center AI), I was able to test and deploy in production different Google products to solve the clients’ needs.


Which tool has been your favorite to use? Why?

Vertex AI is my favorite, as it is pure ML and Deep Learning optimized. Using AutoML with NAS (Neural Architecture Search) was a very interesting experience with awesome results. Developing Machine Learning pipelines with Kubeflow is a special pleasure, as this is going into production and the whole MLOps is involved.


Please share with us about something you’ve built in the past using Google tools.

I’ve built a recruiting solution that was implemented in six countries of Latin America, benefiting more than 365,000 people. This solution automatically analyzes resumes using OCR via Document AI.

I delivered a revenue prediction for a hotel chain using Tensorflow, where we increased the accuracy of the client’s model by 0.95%. I also built a Contact Center solution which uses Google Speech-to-Text and analytics to make management easier and also to generate strategic insights.

Lately, I was part of the team that delivered an end-to-end Virtual Career Center solution that matches job candidates to job vacancies using Vertex AI Matching Engine via text embeddings and SCANN. Both the recruiting solution and the contact center solution generated patents in Brazil, in the field of NLP (Natural Language Processing).


What will you create with Google Bard?

Google Bard is part of my daily routine. It helps me while coding, it helps me to plan trips, get to the right public transportation, visit interesting places around the world and it also helps by retrieving the Google search in an organized way, with updated content. My idea is to use Bard along with LangChain to perform optimizations in the finance industry.


What advice would you give someone starting in their developer journey?

Learn the basics first.

The temptation of learning this magnificent field as Machine Learning is gigantic, but coding is a great part of the solution. Learn to code properly, in whatever language you want. This brings efficiency and security if your solution needs to scale, decreasing infrastructure costs and improving user experience.

The same applies to Machine Learning: learn basic disciplines such as Calculus, Computer Science fundamentals and you will understand most of the content is shared today online. Only after learning ML you should dive into Deep Learning and the disciplines associated. Don’t fake it. Make it.