voyager demo

• The Contents
• The Making of
• Where Are They Now
• Frequently Asked Questions
• Q & A with Ed Stone

golden record

Where are they now.

• frequently asked questions
• Q&A with Ed Stone

Mission Status

Instrument status.

Where are the Voyagers now?

To learn more about Voyager, zoom in and give the spacecraft a spin. View the full interactive experience at Eyes on the Solar System . Credit: NASA/JPL-Caltech

View Voyager

Space Flight Operations Schedule (SFOS)

SFOS files showing Voyager activity on Deep Space Network (DSN)

2024 Tracking Schedule

2023 tracking schedule, 2022 tracking schedule, 2021 tracking schedule, 2020 tracking schedule, 2019 tracking schedule, 2018 tracking schedule, 2017 tracking schedule, 2016 tracking schedule, 2015 tracking schedule, 2014 tracking schedule, 2013 tracking schedule, 2012 tracking schedule, 2011 tracking schedule, 2010 tracking schedule, 2009 tracking schedule, 2008 tracking schedule, 2007 tracking schedule, 2006 tracking schedule, 2005 tracking schedule, 2004 tracking schedule, 2003 tracking schedule, 2002 tracking schedule, 2001 tracking schedule, 2000 tracking schedule, 1999 tracking schedule, 1998 tracking schedule, 1997 tracking schedule, 1996 tracking schedule, 1995 tracking schedule, 1994 tracking schedule.

Getting started with Voyager Laravel [Tutorial]

May 22, 2023

Voyager Laravel is a popular open-source package that provides an easy-to-use admin panel and CRUD functionality for Laravel applications. Voyager Laravel is built on top of the Laravel framework. It is designed to simplify building and managing Laravel applications by providing a user-friendly interface for managing data, media, users, and permissions.

With Voyager, you can easily create and manage content for your applications without writing complex code or building custom admin panels from scratch. Laravel Voyager also offers a range of customization options, making it easy to tailor it to your specific needs and requirements.

Whether building a simple blog or a complex web application, Voyager Laravel can help you streamline the development and management process and get your application up and running quickly.

Installing Voyager Laravel

In this section, we will install Voyager and configure it to use a new Laravel application. Here are the steps.

Install Laravel

Voyager is built on top of the Laravel framework. So, the first step is to install Laravel if you haven't already.

This will create a new Laravel project in a directory called voyager_laravel .

Install Voyager

Next, install Voyager using Composer.

This will install the latest version of Voyager and all of its dependencies.

Publish Voyager's assets

After installing Voyager, you need to publish its assets to your application.

This command will publish Voyager's configuration files, views, assets, and other files to your application. The --with-dummy option will also install some dummy data to help you get started. It creates for your application a user with the following login credentials:

email: [email protected] password: password

Alternatively, you can assign admin privileges to an existing user

or create a new admin user with the --create flag.

Configure your database

Voyager uses your application's database to store data. You need to configure your database settings in your .env file. Update the DB_HOST , DB_PORT , DB_DATABASE , DB_USERNAME , and DB_PASSWORD variables to match your database settings.

Run the migration and start the application

Finally, run the migration to create the necessary tables in your database.

This will create the necessary tables in your database.

Now you can start the application.

and log in at http://127.0.0.1:8000/admin .

Using Voyager Laravel

After logging in to Voyager admin, there are unlimited things you can do at a click of a button. For example, you can manage your application's data through the Admin panel.

At a glance, you can see we have 1 user, 4 dummy posts and 1 page. The left panel exposes you to all settings, customizations and management of your application.

You can do CRUD (create, read, update, delete) functionality without writing custom code. For example, if you click on View all posts , Voyager takes you to an interface with all the posts. You create a new post or update, delete, and read the existing ones on the same interface.

Besides, you can use media manager, BREAD builder, user role management and customization options through the dashboard.

Media manager : Voyager includes a media manager that allows you to upload and manage media files, such as images and videos. You can use the media manager to add images to your application's pages or to create image galleries.

BREAD builder : Voyager includes a BREAD (browse, read, edit, add, delete) builder that allows you to create CRUD functionality for your application's data quickly. The BREAD builder can create custom data types and manage their fields.

User and role management : Voyager provides a user and role management system that allows you to manage your application's users and their roles and permissions. You can create new users, assign roles to them, and define their permissions.

Customization options : Voyager provides a range of customization options, such as the ability to create custom views, layouts, and data types. You can use these customization options to tailor Voyager to your specific needs and requirements.

Voyager Laravel is a powerful open-source package that provides an easy-to-use admin panel and CRUD functionality for Laravel applications. It simplifies the process of building and managing Laravel applications by providing a user-friendly interface for managing data, media, users, and permissions.

With Voyager, you can easily create and manage content for your applications without writing complex code or building custom admin panels from scratch. Voyager also offers a range of customization options, making it easy to tailor it to your specific needs and requirements.

If you are a Laravel developer looking to simplify the development and management process of your Laravel application, then Voyager Laravel is worth considering. With its powerful features and customization options, Voyager can help you save time and effort while building and managing your application.

So why not try Voyager and see how it can benefit your Laravel project? Start by following the installation steps and exploring its features to see how it can make your development journey more efficient and enjoyable.

Steve Alila

He specializes in web design, WordPress development, and data analysis, with proficiency in Python, JavaScript, and data extraction tools. Additionally, he excels in web API development, AI integration, and data presentation using Matplotlib and Plotly. You can connect with him on his LinkedIn profile.

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Introduction

Quickstart guide, how to: install and build voyager, how to: host a prebuilt voyager release, demo assets.

• How To: Embed a model on your site
• How To: Create a scene file
• How To: Use the component offline
• How To: Customize Voyager branding
• API Overview
• API Examples
• API Example: Annotations
• API Example: Articles
• API Example: Background Properties
• API Example: Camera Offset
• API Example: Camera Orbit
• API Example: Get Content
• API Example: Set Language
• API Example: Toggle Displays
• API Example: Tours
• API Example: UI Configuration
• How To: Launch the app
• How To: Use the app
• Capture Task
• Derivatives Task
• Settings Task
• Annotations Task
• Articles Task
• Multilingual Support
• Scene Title

SVX Document Format

Unsure where to start with Voyager? Try the Quickstart Guide!

Installation and configuration

Hosting a release package

Installation of the provided Voyager demo assets

Voyager is free and open source, licensed under the Apache 2.0 license.

Fast, Simple, In-Memory Nearest Neighbor Search

Voyager provides approximate nearest-neighbor search in Python and Java. It's up to 10 times faster than Annoy, while using 4 times less memory and providing more features.

Tuned for lighting-fast production use at Spotify, Voyager provides near-instantaneous nearest-neighbor lookups on in-memory collections of embeddings — without requiring GPUs — so you can power millions of requests per day at millisecond latencies.

Well-Documented

Need an example to get started? Voyager includes documentation for every method, and a comprehensive guide for common use cases. With a strongly-typed API in both Python or Java, you can have your IDE guide you with autocomplete every step of the way — or check out Voyager's documentation.

Easy to Integrate

Add Voyager to your existing application with just one line of code. No dependencies or setup required. Voyager works with all popular Python and Java versions, on macOS, Linux, and Windows. Just import voyager in Python or import com.spotify.voyager; in Java and go!

Lightweight

Voyager is built to minimize resource usage. There's no server to start, no resources to keep running in the background, and no operational overhead. Add Voyager to your application code and you can search through millions of embeddings while only using gigabytes of memory.

Check out a demo of how to use Voyager in both Python and Java in 5 minutes:

You can hear more from the Voyager team on the NerdOut@Spotify podcast:

• Open Source @ Spotify
• @SpotifyEng
• Spotify R&D on LinkedIn
• NerdOut@Spotify Podcast
• Spotify R&D Engineering
• Spotify R&D Research
• Spotify R&D Design
• Life at Spotify

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• Start Monitoring for Free

Exploring the best GraphQL data visualization tools

GraphQL is a popular, powerful query tool for APIs. It provides developers with an efficient and flexible way to access and manipulate data in our databases.

With its increasing popularity, many developers are seeking new ways to better understand and visualize their GraphQL data. There are a number of visualization tools that satisfy this need efficiently.

In this article, we will discuss using GraphQL Voyager, GraphiQL, and Altair for data visualization, exploring how you can use these tools to enhance your workflow and gain deeper insights into your data. We will cover:

• Use cases for GraphQL data visualizer

Exploring data with GraphQL Voyager

Graphql voyager caveats to consider, using powerful graphiql features to construct queries, important considerations while using graphiql, using graphql altair to work with apis, considerations to keep in mind for graphql altair, use cases for graphql data visualizers.

GraphQL data visualizers are useful tools for various scenarios, including:

• Debugging GraphQL APIs
• Collaborating with teams
• Optimizing performance
• Understanding API dependencies
• Testing GraphQL APIs

Let’s explore each of these use cases in more detail now.

GraphQL data visualizers can help developers debug their GraphQL APIs by giving them visual representations of the data they fetch from their servers. These data visualization tools show you how your queries work and which data they call so you can easily identify any mistakes or errors in your query.

You can also use GraphQL data visualizers to highlight performance issues in your queries and show you how you can optimize said queries. With GraphQL data visualization tools, it’s easy to debug your APIs and ensure that your app works as expected.

In a team setting, different members bring various skills from different areas of focus. A GraphQL data visualizer can help team members communicate better and leverage the team’s collective expertise more efficiently by allowing them to visualize the API and its components.

By visualizing a GraphQL API, developers can identify performance bottlenecks and inefficiencies in query execution. They can then optimize queries to improve response times and overall application performance.

In complex systems with multiple APIs and microservices, a GraphQL visualizer can help developers visualize dependencies between different services, making it easier to identify and resolve issues or bottlenecks.

Data visualization tools also help in testing GraphQL Apis by providing a good view of expected responses and identifying issues with queries.

One of the most popular and open source data visualization tools for GraphQL is GraphQL Voyager .

GraphQL Voyager provides an interactive visual representation of your GraphQL schema and allows you to look through your API by visually browsing its object types, fields, and relationships.

With its simple and user-friendly interface, you can zoom into and out of your schema easily, search for particular fields, and see data types.

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GraphQL Voyager demo

GraphQL Voyager works by parsing a GraphQL schema and generating a visual representation of its types and fields.

The tool uses the GraphQL introspection query to obtain the schema, making it compatible with any GraphQL server that supports this query. Once the schema is obtained, GraphQL Voyager generates the interactive graph that visualizes the schema.

Let’s explore an example of GraphQL Voyager in action.

Navigate to the live demo of GraphQL Voyager on GitHub to see APIs represented as interactive graphs. For this example, we’ll analyze the Star Wars API.

Click on the “Change Schema” button on the top left side of the screen and select Star Wars:

You’ll see a graphical representation of the schema in the center of the screen. Familiarize yourself with the interface.

The pane on the left side of the screen lists all the object types in the Star Wars schema. The pane on the right side of the screen shows information about the currently selected type or field.

This schema is based on the Star Wars universe and includes object types for characters, films, planets, and other entities from the Star Wars saga. Each type is depicted as a node in the graph.

You can click on a node to view the type details, which include the type name, description, and the fields it contains. The lines you see on the interface represent the relationships between different types and fields in the schema.

In GraphQL, types are connected to each other through their fields, and these connections are represented as edges in the visualization. The edges are directed, meaning that they point from the type that declares the field to the type that the field returns:

Select a type to explore

To explore a type in your schema, you can click on its name in the left pane. This will highlight the type in the graphical representation and display its information in the right pane.

As an example, select Film . The Film object type represents a film in the Star Wars universe. It has fields like title , episodeID , openingCrawl , characters , etc.

In GraphQL Voyager, fields are used to define the data that can be queried for a given type. You can explore the fields in Film by clicking on them in the left-side pane.

Once you have selected a field to explore, you can view its details, which include the field name, description, and the arguments it takes. You can also view the type of data returned by the field. Also, it highlights the fields in the right pane.

View relationships between types

You can explore relationships between types by clicking on the links between types in the graphical representation. This will highlight the related types and display information about the relationship in the right pane.

Search for types and fields

If you have a large schema with many types and fields, you can use the search box at the top of the screen to search for specific types and fields. Just type in a few letters of the name of the type or field you’re looking for, and GraphQL Voyager will filter the list of types and fields accordingly:

Filtering your search

GraphQL Voyager offers various options to help you refine your search further:

The “Sort by Alphabet” setting allows you to sort the nodes — i.e., types — in the schema alphabetically. By default, the nodes are sorted by the order in which they appear in the schema, but using this option can make it easier to find a specific node in a large schema.

Relay is a framework developed by Facebook for building data-driven React applications. If your schema includes Relay-specific types and fields, you can use the “Skip Relay” setting to exclude them from the visualization. This can be useful if you are not using Relay in your application and want to simplify the visualization.

The “Skip deprecated” setting allows you to exclude deprecated fields and types from the visualization. Deprecated fields and types are marked with a strikethrough in the visualization, but excluding them entirely can make the visualization easier to read.

By default, GraphQL Voyager only shows the top-level fields of each type in the visualization. Enabling the “Show leaf fields” setting will also show any “leaf” fields, which are fields that do not have any subfields. This can make it easier to see all the fields available on a type at a glance.

It’s important to consider compatibility when working with GraphQL Voyager. This data visualization tool relies on introspection queries to generate its visual representation of the schema. If the GraphQL server doesn’t support introspection, Voyager won’t work.

When it comes to performance, Voyager generates a visual representation of the entire schema, which can be a challenge for large and complex schemas. Make sure you monitor performance metrics and optimize queries as needed.

GraphiQL is an interactive web-based IDE that provides a user-friendly interface for writing and executing GraphQL queries.

The GraphiQL IDE is widely used by developers, as it allows you to explore and visualize your GraphQL schema by displaying the useable types and fields, as well as their documentation. With its built-in support explorer, you can easily view the information you need to write your queries.

One of the most useful features of GraphiQL is its power to provide real-time feedback on the GraphQL queries that are constructed.

As a user types a query into GraphiQL, it will immediately highlight any syntax errors and provide autocomplete suggestions for fields and arguments. This makes it easy to quickly write complex queries without having to remember the right syntax for each field.

Let’s go ahead and explore the GraphiQL interface with the Star Wars API (SWAPI) as an example.

SWAPI is a public API that provides data about Star Wars movies, characters, planets, and more. We will use GraphiQL to explore SWAPI and demonstrate some of the key features of the GraphiQL interface.

The GraphiQL interface has two main sections — the query editor and the results pane:

The query editor section is where we construct our GraphQL queries. The results pane displays the results of our queries in real-time. In the results pane, we can find the data that is returned by the API. Errors or warnings that are generated by our queries appear there as well.

Now let’s start with a simple query that retrieves information about all Star Wars films. To construct this, we will use the allFilms field and retrieve three fields under it. Run the query below in the editor:

Click the “play” button after pasting. This will transport the query to the SWAPI API, and display the results in the results pane. As you can see, the results pane displays the data that is returned by the API:

Using autocomplete in GraphiQL

One of the most powerful features of GraphiQL is its autocomplete functionality. As you type a query into the query editor, GraphiQL will provide autocomplete suggestions for fields and arguments. This way, you can create queries quickly without needing to remember the precise syntax for each field.

You can try creating a query that retrieves information about Luke Skywalker to test how autocomplete operates. As you start to type, GraphiQL will display autocomplete suggestions for available fields and arguments:

The GraphiQL interface includes a number of buttons, features, and settings that allow you to customize GraphQL queries and view the data that is returned by the API. Here are some of the features you’ll find on the GraphiQL interface:

The query editor is the main text editor in the GraphiQL interface where you can write and edit your GraphQL queries. The editor program provides syntax highlighting, autocompletion, and error highlighting, making it easy to construct and debug complex queries.

The “play” button is one of the most important features on the GraphiQL interface, this button executes the GraphQL query that is currently in the query editor. When the Play button is clicked, your query is sent to the API and the results are displayed in the results pane.

The query variables panel allows you to define variables that can be used in your GraphQL queries. Variables can be defined with different data types and can be either required or optional.

As previously mentioned, the results panel displays the information that is returned by the GraphQL API in response to the query. The results are displayed in JSON format and can be expanded or collapsed to view nested data.

The query history feature allows you to save and manage your GraphQL queries. Saved queries can be easily retrieved and executed with a single click.

The settings panel allows you to customize the behavior of GraphiQL. The settings include options for enabling or disabling query validation, enabling or disabling schema introspection, and changing the theme of the interface:

Finally, the documentation explorer feature provides support for the GraphQL API, including descriptions of types, fields, and arguments. This feature allows users to quickly and easily search for information about the API and its model.

Security is important in modern development. GraphiQL is a tool for debugging and exploring GraphQL APIs, but it’s not intended for production use. Ensure that proper security measures are in place when you’re interacting with sensitive data.

Additionally, like GraphQL Voyager, GraphiQL also relies on introspection queries to generate its interface. If the GraphQL server doesn’t support introspection, GraphiQL won’t work.

GraphQL Altair is a powerful GraphQL client that provides a user-friendly interface for working with GraphQL APIs. It’s an open source project that allows developers to easily interact with GraphQL APIs, making it easier to test, debug, and optimize queries.

Altair’s interface is divided into several panels that allow you to perform various tasks. Here are the key features of the Altair interface:

The endpoint panel allows you to enter the endpoint URL of the GraphQL API you want to connect to. Once you enter the URL, you can click the “Send Request” button to connect to the API and start working with its schema.

The query editor panel allows you to construct your GraphQL queries, mutations, and subscriptions. Altair provides you with syntax highlighting, code auto-completion, and error highlighting to make it easier to write valid GraphQL queries.

The panel labeled “VARIABLES” allows you to define variables that can be used in your GraphQL queries. You can create variables with different data types, and Altair will automatically generate the right input fields in the query editor:

Altair also has a feature for setting headers that allows you to add custom headers to your GraphQL requests. You can define headers for authentication, caching, or other purposes:

The response panel displays the response from the GraphQL API you sent your query. You receive the response in either a JSON or a tree view format.

If you select “Docs” at the top right of your screen, to the left of the “Send Request” button, you should see a panel that provides a graphical representation of the GraphQL schema of the API you are working with. You can use this panel to explore the various types, fields, and relationships in the schema:

The “Settings” panel allows you to customize the appearance and behavior of Altair. You can tinker with settings such as theme, font size, and query timeout.

Altair keeps a history of all the queries you have executed, making it easy to revisit previous queries and results. It also provides real-time validation of your GraphQL queries, helping you to highlight errors and syntax issues as you write your queries.

Finally, Altair also provides an easy way to export your GraphQL queries as code snippets in various programming languages.

Demo of GraphQL Altair features

To see how Altair works, we can use any online demo of GraphQL Altair with the Trevorblades API .

Open the GraphQL Altair demo page . In the “Endpoint” panel on the left-hand side of the page, paste the following endpoint URL:

Next, click on the “Send Request” button to connect to the Trevorblades API endpoint. If everything is set up correctly, you should see the schema of the API displayed in the right-side panel.

To test a query, mutation, or subscription, click on the “Query” button at the top of the page. This will open the query editor, where you can enter your GraphQL query.

Next, enter a GraphQL query for the countries API in the editor. For example, you can try the following query to get information about all the countries in the API:

After you have entered your query, click on the “Send Request” button to execute it. The results of your query will be displayed in the response pane beside the query editor.

Altair has a slightly steeper learning curve than Voyager or GraphiQL, as it offers a greater range of features and customization options. This means you may need to invest time in learning the interface and functionality of Altair before you can fully benefit from it.

Furthermore, Altair requires additional dependencies to be installed, such as the Altair GraphQL client library. Ensure that you have the necessary dependencies installed and configured correctly to avoid any issues or errors.

When it comes to visualizing data for GraphQL, there are several great options available.

GraphQL Voyager offers a visually stunning representation of your GraphQL schema, while GraphiQL provides a straightforward and user-friendly interface. Altair, on the other hand, offers advanced features for debugging and testing your GraphQL queries.

Ultimately, the best data visualizer for GraphQL depends on your specific needs and preferences. Whether you’re looking for a simple and intuitive tool or a more advanced debugging and testing environment, there’s a data visualizer out there that’s right for you.

No matter which tool you choose, it’s important to remember that data visualization is a crucial part of working with GraphQL. By using a high-quality data visualizer, you can gain deeper insights into your data, identify potential issues more easily, and streamline your development process.

Don’t be afraid to try out different options and find the one that works best for you!

Monitor failed and slow GraphQL requests in production

LogRocket is like a DVR for web and mobile apps, recording literally everything that happens on your site. Instead of guessing why problems happen, you can aggregate and report on problematic GraphQL requests to quickly understand the root cause. In addition, you can track Apollo client state and inspect GraphQL queries' key-value pairs.

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Yardi Voyager

About Yardi Voyager

Awards and recognition, yardi voyager pricing.

Contact Yardi Systems directly for pricing information.

Starting price: 

$1,200.00   per month

Free trial: 

Not Available

Free version: 

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Yardi Voyager Reviews

Overall rating, ratings breakdown, secondary ratings.

Ease-of-use

Customer Support

Value for money

Functionality

4.21/5 out of 227 Reviews

Most Helpful Reviews for Yardi Voyager

1 - 5 of 227 Reviews

51-200 employees

Used daily for less than 2 years

OVERALL RATING :

EASE OF USE

VALUE FOR MONEY

CUSTOMER SUPPORT

FUNCTIONALITY

Reviewed October 2018

The onboarding was awful. I wanted to cancel the conrqctnhalfway through and we were actually upgrading from an old Yardi platform, not another software. Once getting through that though it is a truly phenomenal product.

Capabilities are almost limitless. So many options and modules available. It’s expensive but can automate enough workload that administrative staffing can. It really is amazing what it can do.

The onboarding was brutal. Yardi has no subject matter experts on their teams that actually care understand property management and maintenance and that makes it very difficult to speak the same language. Some of their trainers are great and some are awful. The trainers are not Yardi employees they are independent contractors.

Real Estate , 201-500 employees

Used daily for more than 2 years

Reviewed September 2022

Highly recommend

Very great experience. I have used various other software and Yardi is by far my preference.

There isn’t much that Yardi can’t do. Very detailed reporting which is customizable. Excellent costumer service

The initial set up can be tedious but really Yardi supports are very involved to make it as easy as possible

Reasons for switching to Yardi Voyager

Yardi much more detailed and many more useful modules for larger scale operation

Real Estate , 11-50 employees

Reviewed April 2022

Industry Standard PM Software that declined over time

We ceased using Yardi after many years, primarily due to the outrageous costs and at the end horrible customer support. They "a-la-carte" every module and the functions within each module can be limited unless you license everything. The main reason was we could not get customer/technical support. Support emails would go unanswered, phone numbers disconnected or unanswered. Their management team would get involved and still nothing would be responded to or helped.

User interface was easy to understand and use. You could create your own customized reports.

That is a long list. Rent Cafe (tenant portal) never worked right for our tenants. You could never get two different reports to give you the same answer. Not nearly enough automation options for day to day functions. The primary con was little to no customer/technical support. Even the numbers on their "Support" site were either disconnected or unanswered.

Reason for choosing Yardi Voyager

We choose AppFolio. Outstanding customer support, great owner/tenant portals, more streamlined and automated processes. They also don't nickel dime you for every function and every module.

Reviewed February 2024

Helps complete task in an organized, timely manner!

Very easy to navigate, beginner friendly and easy to collaborate with others

It alerts you to any tasks due, keeps you on tract

Charges and payments can task can take over night to sync with other programs

Real Estate , 1,001-5,000 employees

Reviewed September 2020

Best Platform

I would recommend Yardi over the other platforms.

I like the reports and how easy it is to find exactly what you are looking for. it is very easy to process POs especially now that vendors can upload invoices directly into Yardi for processing.

some of the reports take a very long time to pull the information.

I like that it interacts well with other platforms like VendorShield and CRM

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Voyager: An Open-Ended Embodied Agent with Large Language Models

We introduce Voyager, the first LLM-powered embodied lifelong learning agent in Minecraft that continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention. Voyager consists of three key components: 1) an automatic curriculum that maximizes exploration, 2) an ever-growing skill library of executable code for storing and retrieving complex behaviors, and 3) a new iterative prompting mechanism that incorporates environment feedback, execution errors, and self-verification for program improvement. Voyager interacts with GPT-4 via blackbox queries, which bypasses the need for model parameter fine-tuning. The skills developed by Voyager are temporally extended, interpretable, and compositional, which compounds the agent's abilities rapidly and alleviates catastrophic forgetting. Empirically, Voyager shows strong in-context lifelong learning capability and exhibits exceptional proficiency in playing Minecraft. It obtains 3.3x more unique items, travels 2.3x longer distances, and unlocks key tech tree milestones up to 15.3x faster than prior SOTA. Voyager is able to utilize the learned skill library in a new Minecraft world to solve novel tasks from scratch, while other techniques struggle to generalize.

Introduction

Voyager components.

Automatic Curriculum

Skill Library

Iterative Prompting Mechanism

Experiments

We systematically evaluate Voyager and baselines on their exploration performance, tech tree mastery, map coverage, and zero-shot generalization capability to novel tasks in a new world.

Significantly Better Exploration

Tech tree mastery.

Extensive Map Traversal

Efficient Zero-Shot Generalization to Unseen Tasks

Ablation Studies

In this work, we introduce Voyager, the first LLM-powered embodied lifelong learning agent, which leverages GPT-4 to explore the world continuously, develop increasingly sophisticated skills, and make new discoveries consistently without human intervention. Voyager exhibits superior performance in discovering novel items, unlocking the Minecraft tech tree, traversing diverse terrains, and applying its learned skill library to unseen tasks in a newly instantiated world. Voyager serves as a starting point to develop powerful generalist agents without tuning the model parameters.

Media Coverage

"They Plugged GPT-4 Into Minecraft—and Unearthed New Potential for AI. The bot plays the video game by tapping the text generator to pick up new skills, suggesting that the tech behind ChatGPT could automate many workplace tasks." - Will Knight, WIRED "The Voyager project shows, however, that by pairing GPT-4’s abilities with agent software that stores sequences that work and remembers what does not, developers can achieve stunning results." - John Koetsier, Forbes "Voyager, the GTP-4 bot that plays Minecraft autonomously and better than anyone else" - Ruetir "This AI used GPT-4 to become an expert Minecraft player" - Devin Coldewey, TechCrunch Coverage Index: [Atmarkit] [Career Engine] [Crast.net] [Daily Top Feeds] [Entrepreneur en Espanol] [Finance Jxyuging] [Forbes] [Forbes Argentina] [Gaming Deputy] [Gearrice] [Haberik] [Head Topics] [InfoQ] [ITmedia News] [Mark Tech Post] [Medium] [MSN] [Note] [Noticias de Hoy] [Ruetir] [Stock HK] [Tech Tribune France] [TechCrunch] [TechBeezer] [Toutiao] [US Times Post] [VN Explorer] [WIRED] [Zaker]

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Title: voyager: an open-ended embodied agent with large language models.

Abstract: We introduce Voyager, the first LLM-powered embodied lifelong learning agent in Minecraft that continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention. Voyager consists of three key components: 1) an automatic curriculum that maximizes exploration, 2) an ever-growing skill library of executable code for storing and retrieving complex behaviors, and 3) a new iterative prompting mechanism that incorporates environment feedback, execution errors, and self-verification for program improvement. Voyager interacts with GPT-4 via blackbox queries, which bypasses the need for model parameter fine-tuning. The skills developed by Voyager are temporally extended, interpretable, and compositional, which compounds the agent's abilities rapidly and alleviates catastrophic forgetting. Empirically, Voyager shows strong in-context lifelong learning capability and exhibits exceptional proficiency in playing Minecraft. It obtains 3.3x more unique items, travels 2.3x longer distances, and unlocks key tech tree milestones up to 15.3x faster than prior SOTA. Voyager is able to utilize the learned skill library in a new Minecraft world to solve novel tasks from scratch, while other techniques struggle to generalize. We open-source our full codebase and prompts at this https URL .

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Rob Gronkowski Settlement of Voyager Crypto Suit Gets Early Nod

By Peter Hayes

A $2.4 million settlement funded primarily by retired NFL star Rob Gronkowski of claims that he and other athletes helped promote failed cryptocurrency exchange Voyager Digital Holdings Inc. received preliminary approval from a federal judge.

Judge Roy K. Altman of the US District Court for the Southern District of Florida also preliminarily certified a class of US customers who enrolled in a Voyager Earn Program Account or bought one of its VGX tokens between Oct. 23, 2019 and June 10, 2024.

The settlement resolves claims against Gronkowski, basketball player Victor Oladipo, who last played for the NBA’s Miami Heat, and ...

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NASA Tool Gets Ready to Image Faraway Planets

At JPL on May 17, members of the Roman Coronagraph Instrument team use a crane to lift the top portion of the shipping container that the instrument was stored in for its journey to NASA’s Goddard Space Flight Center.

Team members at JPL said farewell to the Roman Coronagraph Instrument on May 17 by signing their names to a flag (featuring the mission logo) on the outside of the shipping container that carried the instrument to NASA’s Goddard Space Flight Center.

A technology demo on the Nancy Grace Roman Space Telescope will help increase the variety of distant planets scientists can directly image.

The Roman Coronagraph Instrument on NASA’s Nancy Grace Roman Space Telescope will help pave the way in the search for habitable worlds outside our solar system by testing new tools that block starlight, revealing planets hidden by the glare of their parent stars. The technology demonstration recently shipped from NASA’s Jet Propulsion Laboratory in Southern California to the agency’s Goddard Space Flight Center in Greenbelt, Maryland, where it has joined the rest of the space observatory in preparation for launch by May 2027.

Before its cross-country journey, the Roman Coronagraph underwent the most complete test of its starlight-blocking abilities yet — what engineers call “digging the dark hole.” In space, this process will enable astronomers to observe light directly from planets around other stars, or exoplanets . Once demonstrated on Roman, similar technologies on a future mission could enable astronomers to use that light to identify chemicals in an exoplanet’s atmosphere, including ones that potentially indicate the presence of life.

The Roman Coronagraph Instrument aboard NASA’s Nancy Grace Roman Space Telescope will improve scientists’ ability to directly image planets around other stars. As the most powerful coronagraph to ever fly in space, it will demonstrate new technologies that might be used by future missions like NASA’s proposed Habitable Worlds Observatory.

Let the Testing Begin

For the dark hole test, the team placed the coronagraph in a sealed chamber designed to simulate the cold, dark vacuum of space. Using lasers and special optics, they replicated the light from a star as it would look when observed by the Roman telescope. When the light reaches the coronagraph, the instrument uses small circular obscurations called masks to effectively block out the star, like a car visor blocking the Sun or the Moon blocking the Sun during a total solar eclipse. This makes fainter objects near the star easier to see.

Coronagraphs with masks are already flying in space, but they can’t detect an Earth-like exoplanet. From another star system, our home planet would appear approximately 10 billion times dimmer than the Sun, and the two are relatively close to one another. So trying to directly image Earth would be like trying to see a speck of bioluminescent algae next to a lighthouse from 3,000 miles (about 5,000 kilometers) away. With previous coronagraphic technologies, even a masked star’s glare overwhelms an Earth-like planet.

The Roman Coronagraph will demonstrate techniques that can remove more unwanted starlight than past space coronagraphs by using several movable components. These moving parts will make it the first “active” coronagraph to fly in space. Its main tools are two deformable mirrors, each only 2 inches (5 centimeters) in diameter and backed by more than 2,000 tiny pistons that move up and down. The pistons work together to change the shape of the deformable mirrors so that they can compensate for the unwanted stray light that spills around the edges of the masks.

How does the Roman Coronagraph Instrument work? This video shows how it removes unwanted starlight to reveal planets around other stars.

The deformable mirrors also help correct for imperfections in the Roman telescope’s other optics. Although they are too small to affect Roman’s other highly precise measurements, the imperfections can send stray starlight into the dark hole. Precise changes made to each deformable mirror’s shape, imperceptible to the naked eye, compensate for these imperfections.

“The flaws are so small and have such a minor effect that we had to do over 100 iterations to get it right,” said Feng Zhao, deputy project manager for the Roman Coronagraph at JPL. “It’s kind of like when you go to see an optometrist and they put different lenses up and ask you, ‘Is this one better? How about this one?’ And the coronagraph performed even better than we’d hoped.”

During the test, the readouts from the coronagraph’s camera show a doughnut-shaped region around the central star that slowly gets darker as the team directs more starlight away from it — hence the nickname “digging the dark hole.” In space, an exoplanet lurking in this dark region would slowly appear as the instrument does its work with its deformable mirrors.

This graphic shows a test of the Roman Coronagraph Instrument that engineers call “digging the dark hole.” At left, starlight leaks into the field of view when only fixed components are used. The middle and right images show more starlight being removed as the instrument’s moveable components are engaged.

Habitable Worlds

More than 5,000 planets have been discovered and confirmed around other stars in the last 30 years, but most have been detected indirectly, meaning their presence is inferred based on how they affect their parent star. Detecting these relative changes in the parent star is far easier than seeing the signal of the much fainter planet. In fact, fewer than 70 exoplanets have been directly imaged .

The planets that have been directly imaged to date aren’t like Earth: Most are much bigger, hotter, and typically farther from their stars. These features make them easier to detect but also less hospitable to life as we know it.

To look for potentially habitable worlds, scientists need to image planets that are not only billions of times dimmer than their stars, but also orbit them at the right distance for liquid water to exist on the planet’s surface — a precursor for the kind of life found on Earth.

Never Miss a Discovery

Developing the capabilities to directly image Earth-like planets will require intermediate steps like the Roman Coronagraph. At its maximum capability, it could image an exoplanet similar to Jupiter around a star like our Sun: a large, cool planet just outside the star’s habitable zone.

What NASA learns from the Roman Coronagraph will help blaze a path for future missions designed to directly image Earth-size planets orbiting in the habitable zones of Sun-like stars. The agency’s concept for a future telescope called the Habitable Worlds Observatory aims to image at least 25 planets similar to Earth using an instrument that will build on what the Roman Coronagraph Instrument demonstrates in space.

“The active components, like deformable mirrors, are essential if you want to achieve the goals of a mission like the Habitable Worlds Observatory,” said JPL’s Ilya Poberezhskiy, the project systems engineer for the Roman Coronagraph. “The active nature of the Roman Coronagraph Instrument allows you to take ordinary optics to a different level. It makes the whole system more complex, but we couldn’t do these incredible things without it.”

More About the Mission

The Nancy Grace Roman Space Telescope is managed at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, with participation by JPL and Caltech/IPAC in Southern California, the Space Telescope Science Institute in Baltimore, and a science team comprising scientists from various research institutions. The primary industrial partners are BAE Space and Mission Systems in Boulder, Colorado; L3Harris Technologies in Melbourne, Florida; and Teledyne Scientific & Imaging in Thousand Oaks, California.

The Roman Coronagraph Instrument was designed and built at JPL, which manages the instrument for NASA. Contributions were made by ESA (the European Space Agency), JAXA (the Japanese Aerospace Exploration Agency), the French space agency CNES (Centre National d’Études Spatiales), and the Max Planck Institute for Astronomy in Germany. Caltech, in Pasadena, California, manages JPL for NASA. The Roman Science Support Center at Caltech/IPAC partners with JPL on data management for the Coronagraph and generating the instrument’s commands.

For more information about the Roman telescope, visit:

https://roman.gsfc.nasa.gov/

News Media Contact

Calla Cofield

Jet Propulsion Laboratory, Pasadena, Calif.

626-808-2469

[email protected]

Claire Andreoli

NASA's Goddard Space Flight Center, Greenbelt, Md.

301-286-1940

[email protected]

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Avi Loeb (left) and Merav Opher used computer models to track the sun’s path back to a potential collision.

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More than a planetary fender-bender

New study finds Earth collided with dense interstellar cloud, possibly affecting life on planet

Alvin Powell

Harvard Staff Writer

Call it the Milky Way mystery.

Evidence of a long-ago collision involving the Earth was there in the form of specific radioactive isotopes deposited across the Earth and Moon. There were, however, skeptics.

But now researchers have tracked the sun’s path through the Milky Way back to a crash 2 to 3 million years ago with a dense interstellar cloud. The event was so violent it appears to have collapsed the sun’s protective bubble around the solar system and possibly even affected life on Earth.

Merav Opher, a Boston University astronomy professor and director of BU’s SHIELD NASA DRIVE Center, made the discovery in work conducted during a 2021-22 fellowship at the Radcliffe Institute for Advanced Study and published recently in Nature Astronomy.

Her project explored whether the Earth might have come in contact with the interstellar medium outside of the heliosphere, the protective bubble around the solar system created by the sun’s magnetic field and the solar wind.

Though the Earth is often thought of as a planet circling a stationary star, the sun is constantly in motion. In fact, it travels through the galaxy at about 56,000 miles per hour — bringing with it the planets, asteroids, comets, and other bodies of the solar system.

Researchers believe that during those travels a collision may have happened between 2 million and 3 million years ago, and another around 7 million years ago. The evidence exists in the form of noticeable peaks in the deposition of two radioactive isotopes: iron 60 and plutonium 244. Both are very rare, created when massive stars explode in supernova. Those isotopes are thought to be more plentiful in the interstellar medium.

“It is everywhere, in the deep ocean, on the moon, on ice in Antarctica,” Opher said. “These papers describe a global phenomenon. Something happened. And iron 60 is not produced on Earth. So I knew that somehow this iron 60 got trapped in dust, and somehow, 2 to 3 million years ago, we had more dust delivered to us.”

For the interstellar medium (ISM) to be the source of the deposition spikes, however, something unusual must have happened, because today the ISM is nowhere near Earth. The heliosphere’s outer fringe — where the interstellar medium begins — is 11 billion miles away, well beyond the orbits of the outer planets.

Opher started her exploration of potential Earth-ISM contact by reviewing research on the sun’s galactic neighborhood, the “nearby” space out to 65 light-years away.

She initially found mostly empty space. But when she factored in the sun’s own movement, she realized that the solar system exits its interstellar neighborhood after about 1 million years.

And, as she looked farther down the path that the sun and its planets might have taken, her gaze settled on a string of dense clouds of interstellar dust and hydrogen atoms, called the Local Ribbon of Cold Clouds, 2 to 3 million years away as the sun flies.

“I got so excited,” Opher said. “This will collapse the heliosphere and then the Earth is in interstellar medium, collecting more dust, and that can explain this peak that I’ve seen in iron 60.”

Opher got in touch with Avi Loeb, the Frank B. Baird Jr. Professor of Science, who directs Harvard’s Institute for Theory and Computation, where Opher spent a sabbatical year from 2017 to 2018. The two used computer models to examine the movement of both the solar system and the interstellar dust clouds themselves, which are also in motion.

They tracked the sun’s path back to a potential collision with the densest cloud in the ribbon, called the Local Lynx of Cold Clouds, holding more than half of the ribbon’s total mass.  

“We don’t often discuss the impact of astrophysics on Earth because the astronomical timescales are very long, and the human species emerged on Earth just a few million years ago,” Loeb said. “But a few million years ago there was the potential for us to be passing through a very dense cloud. We didn’t work out the biological implications, but it’s clear that if you shrink the heliosphere to within the orbit of the Earth around the sun, we are not protected anymore. It could have significant implications for life on Earth.”

For confirmation, they turned to Joshua Peek, an astronomer at the Space Telescope Science Institute, which runs the Webb and Hubble telescopes. Peek, who had published research on the Local Ribbon of Cold Clouds, cast a dubious eye on their work.

The relative movements of the bodies involved were complex, the statistics required to understand them advanced, and, he thought, the chances were vanishingly small that the sun passed through that Lynx cloud at the same time that the isotope depositions happened on Earth.

“It’s a pretty complicated thing to study,” Peek said. “So I thought, ‘I’m just not going to pay attention to this. This is some crackpot nonsense.’”

But Opher didn’t give up. She repeatedly reached out until Peek, on a pandemic-era trip to California, found himself with time on his hands. He had tested positive for COVID and, though he felt OK, was in self-imposed quarantine, far from home and the daily demands there.

So Peek decided to take a closer look at Opher’s idea. And the more he looked, the more plausible it became.

“It’ll be so easy,” Peek described his thinking. “I’ll just do a quick analysis — in one day — prove that this is impossible, and we can all move on with our lives. But after the very quick analysis, I thought, this is actually possible. I was just flabbergasted. I wrote back and said, ‘I thought I was proving you wrong, but it turned out I proved you right.’”

Interstellar space beyond the solar system is very heterogenous, Peek and Opher said.

In some places, like just outside the heliosphere, it is nearly a vacuum, averaging just 0.1 particles per cubic centimeter. By contrast, inside the heliosphere, near Earth, there are between three and 10 particles per cubic centimeter, 30 to 100 times denser. Inside a cold cloud, according to Peek’s prior research, particle density could reach 3,000 particles per cubic centimeter.

A collision with a cloud that dense would have collapsed the heliosphere to about 0.2 astronomical units, or about one-fifth of the distance between the Earth and the sun, Opher said. That would leave the Earth outside the sun’s protective influence as the solar system traversed the cloud.

Recent measurements by Voyager 1 and 2, the only crafts to have crossed from the heliosphere into the ISM, showed that the Earth would have likely experienced a spike in galactic cosmic radiation.

It also would have experienced a rain of particles — some interstellar dust, but mainly hydrogen atoms — through the atmosphere.

The particles would likely have changed the chemistry of Earth’s atmosphere, possibly affecting cloud formation, depleting ozone in the middle atmosphere, and cooling the climate.

Though outside the scope of their study, the three authors said the impact on life on Earth might have been substantial and recommended further exploration.

“Our work should trigger more studies into this question,” Loeb said. “It draws attention to our cosmic neighborhood as having potential influence on life on Earth. We usually tend to just look at it and enjoy it, but we are actually moving through interstellar space, and there could be risks along the way.”

Opher’s work is supported by the NASA DRIVE program.

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Voyager 2 is a data exploration tool that blends manual and automated chart specification. Voyager 2 combines PoleStar, a traditional chart specification tool inspired by Tableau and Polaris (research project that led to the birth of Tableau), with two partial chart specification interfaces: (1) wildcards let users specify multiple charts in parallel,(2) related views suggest visualizations relevant to the currently specified chart. With Voyager 2, we aim to help analysts engage in both breadth-oriented exploration and depth-oriented question answering.

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Voyager 2 can be used from JupyterLab via the JupyterLab extension for Voyager . The DataVoyager.jl package integrates Voyager 2 into the Julia programming language .

This repository now hosts an alpha version of the migration of Voyager 2 to a React/Redux application. Older versions of Voyager built in AngularJS at the following URL.

• The Voyager 2 visualization tool, which blends manual and automated chart specification – demo at http://vega.github.io/voyager2 and source code at https://github.com/vega/voyager2
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For basic setup for local development or installation, we use yarn for package management. Installing dependencies can be done with:

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Please see our contributing documentation for more info about setup and coding conventions if you are interested in contributing to this project.

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• Stand alone version of voyager in dist/ . This distribution can be hosted on a web server to deploy Voyager.
• Compiled Javscript and .d.js declaration files for a subset of the Voyager source code in build/src/ . These declarations and sources can be included in other packages that use Voyager as a dependency. See voyager-server for an example.
• Embeddable Voyager build in build/ . See below for more details on embedding Voyager in other applications.

Embed Voyager ( datavoyager library)

Voyager can be embedded in another web application. The following sections document how to use it.

Installation

Using npm or yarn? Add the following to your package.json then run npm install datavoyager or yarn add datavoyager .

If you want to use the latest development version, you may want to clone and link Voyager.

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CreateVoyager(container, config, data)

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To get this running in a local development environment, first clone and install the dependencies of the voyager-server project.

In voyager-server directory, yarn start will start the server running on port 3000 .

With voyager-server now running, we can start voyager in server mode by running:

This will run Voyager in "server-mode" sending requests to voyager-server, which it expects, by default, to be at http://localhost:3000 .

The server url is controlled by the SERVER environment variable.

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by Erin Brown-John

If you’ve visited the Trottier Observatory or tuned in to its livestream, you may recognize SFU Physics alumnus Indira Janzen as a frequent host of Starry Nights.

“I remember when I was in grade two, looking at a book that had pictures that Voyager had taken of our solar system and being amazed at the fact that we were not the only planet out there,” she says.

Janzen doesn’t recall having many friends in high school, but she connected with her physics teacher, Mr. Dueck, because she found his enthusiasm for astronomy inspiring. “He is a huge space and physics nerd,” she says, “but instead of shying away from that he leaned into it and owned it as a part of who he is.”

Through Mr. Dueck she became involved with the Royal Astronomical Society of Canada, which meets regularly at SFU. While still in high school, she was able to get involved with an astrophysics project at the Trottier Observatory with SFU Physics professor Howard Trottier.

“Howard inspired me a lot during my experience at SFU because of his approachability, amazing teaching skills and seemingly endless knowledge of physics,” says Janzen. “I want to be like Howard and inspire the community like he did.” She has been working at the observatory ever since, as a host for public outreach events.

“I feel more comfortable being myself within the astronomy community because of the diversity it has,” she says. “I feel it is the most welcoming community because I am able to geek out, ask questions, and get things wrong sometimes but still feel accepted.”

At Trottier Observatory events and through leading Science in Action workshops she’s made it her mission to inspire more women and girls to consider STEM. “Women and women of colour are still massively under-represented in physics,” she says. “Even in my last year of schooling, I was either the only woman in my class or one of two women.”

“I started to grow curious about astrophysics when I was in elementary school. I believe that starting at that age is a great way to make an impression on girls and maybe inspire them or even just drive their curiosity as to what the field of physics is all about!”

Janzen is the first woman from her family to complete a university degree and is cheered on by her nani-ji (maternal grandmother), who didn’t have the opportunity to go to school. “I hope to make my family proud,” she says.