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ease 5 out of 5 stars
features 5 out of 5 stars

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Description

Muse Wonder is an advanced AI foundation model developed by Meta to support personal AI agents, professional knowledge work, and software engineering tasks. The model is part of the Muse Wonder series, which includes Muse Wonder and the larger Muse Wonder Full variant. Its Active Memory capability maintains important contextual information across conversations and retrieves relevant details when they become useful for subsequent tasks. Active Focus enables the model to pursue multistep objectives, evaluate alternative approaches, respond to obstacles, and continue working toward completion. Muse Wonder supports applications involving legal document analysis, financial information, health-related questions, and business workflow automation. Its coding capabilities include generating applications, modifying existing codebases, tracking project requirements, and iterating through testing and debugging cycles. The model can operate as part of agentic systems that interact with browsers, external applications, and connected tools to complete user-directed activities. Meta has evaluated Muse Wonder on benchmarks covering personal assistance, professional agent tasks, long-term memory, sustained execution, and software development. Muse Wonder is accessible through the Meta Model API and Muse Code, with plans to incorporate its capabilities into the Muse assistant and additional AI-powered experiences.

Description

We have developed MuseNet, an advanced deep neural network capable of producing 4-minute musical pieces featuring 10 distinct instruments, while seamlessly merging genres ranging from country to the classical compositions of Mozart and even the iconic sounds of the Beatles. Rather than being programmed with musical knowledge, MuseNet identifies and learns patterns of harmony, rhythm, and style through the process of predicting the subsequent token in a vast collection of MIDI files. This innovative model employs the same unsupervised technology as GPT-2, a robust transformer model designed to anticipate the next token in a sequence, whether it pertains to audio or text. Thanks to MuseNet's understanding of diverse musical styles, we are able to create unique blends of musical generations. We eagerly anticipate the creative ways in which both musicians and those without formal training will leverage MuseNet to craft original compositions! Users can select a composer or style and optionally begin with a well-known piece, allowing them to delve into the rich array of musical styles that the model can produce. This opens up exciting possibilities for artistic exploration and experimentation.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

C# Yes 
C++ Yes 
Cursor Yes 
Devin Desktop Yes 
Gray Swan Yes 
JavaScript Yes 
Model Context Protocol (MCP) Yes 
Muse Code Yes 
Muse Spark Yes 
Objective-C Yes 
OpenAI No 
OpenCode Yes 
Oracle Cloud Infrastructure Yes 
PowerShell Yes 
Python Yes 
R Yes 
Rust Yes 
SQL Yes 
Solidity Yes 
Vercel AI Gateway Yes 

Integrations

C# No 
C++ No 
Cursor No 
Devin Desktop No 
Gray Swan No 
JavaScript No 
Model Context Protocol (MCP) No 
Muse Code No 
Muse Spark No 
Objective-C No 
OpenAI Yes 
OpenCode No 
Oracle Cloud Infrastructure No 
PowerShell No 
Python No 
R No 
Rust No 
SQL No 
Solidity No 
Vercel AI Gateway No 

Pricing Details

$4 per 1M tokens (input)
Input: $4 per 1M tokens
Output: $20 per 1M tokens
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

meta.ai/

Vendor Details

Company Name

OpenAI

Founded

2015

Country

United States

Website

openai.com/blog/musenet/

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