Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
MuSES achieves unparalleled accuracy in electro-optic and infrared renderings through a systematic process that starts with the identification of heat sources like engines, exhaust systems, bearings, and electronic components, followed by a comprehensive in-band diffuse radiosity solution. After establishing your sensor at a specified range, you can render multi-bounce radiance values that have been spectrally summed, utilizing DeltaT-RSS contrast metrics for detailed analysis. If you have a sensor response curve available, simply import it to uncover insights you may have overlooked. With MuSES, you can explore reality in unprecedented detail. The software’s capability extends to comprehensively address physics from heat sources to environmental influences, enabling you to effectively manage thermal signature contrasts and assess control kits essential for low observable design in any geographical context. You can rigorously evaluate heat shields, cooling methods, and camouflage surface treatments for in-band radiance while accounting for atmospheric attenuation along the sensor’s line-of-sight. By prioritizing engineering tasks with MuSES early in your project development cycle, you empower your team to make informed decisions that enhance overall design effectiveness. This foresight can significantly streamline the development process and improve project outcomes.
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
API Access
Has API
Integrations
Microsoft Azure
OpenAI
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
ThermoAnalytics
Founded
1996
Country
United States
Website
www.thermoanalytics.com/muses
Vendor Details
Company Name
OpenAI
Founded
2015
Country
United States
Website
openai.com/blog/musenet/
Product Features
Simulation
1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Continuous Modeling
Design Analysis
Direct Manipulation
Discrete Event Modeling
Dynamic Modeling
Graphical Modeling
Industry Specific Database
Monte Carlo Simulation
Motion Modeling
Presentation Tools
Stochastic Modeling
Turbulence Modeling