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Description
DriveMod represents Cyngn's comprehensive solution for autonomous driving, seamlessly integrating with commonly available sensing and computing equipment to empower industrial vehicles with the ability to understand their environment, make informed decisions, and execute actions. This innovative system is designed to fit effortlessly into your current operations, allowing for straightforward programming of vehicle routes, loops, and missions. Essentially, anything a human driver can accomplish, DriveMod is capable of achieving as well. You can safely equip any commercially available vehicle with autonomous features through a simple retrofit process. The adaptability of DriveMod guarantees that diverse fleets operate efficiently, regardless of the vehicle's make or model. By leveraging advanced AI software alongside top-tier sensors and computing technology, DriveMod delivers performance that surpasses that of human operators. It can identify thousands of objects and evaluate numerous potential paths, efficiently determining the best route in mere fractions of a second, thereby revolutionizing the way vehicles navigate their surroundings. This remarkable capability positions DriveMod as a leading solution in the realm of autonomous vehicle technology.
Description
NVIDIA Alpamayo 2 Super stands as a pioneering open model tailored for robotaxis and autonomous vehicles, designed to navigate rare and intricate driving scenarios while generating decisions that developers can analyze, verify, and rely upon. Utilizing the foundations of NVIDIA Cosmos 3 Super Reasoner and enhanced through reinforcement learning, it merges commercial accessibility with the ability to handle multiple tasks related to autonomous driving. The model comprehensively analyzes full-surround camera input, integrating perspectives from the front, sides, and rear to adeptly manage lane changes, merges, unprotected turns, and complex intersections. In addressing each driving scenario, it can produce a planned trajectory for the vehicle, a chain-of-causation that elucidates the decision-making process, a meta-action such as yielding or stopping, and reasoning auto-labels for both training and validation purposes, along with visual question-answering outputs anchored in specific image regions. These interconnected outputs facilitate the correlation between the model's observations and the actions it undertakes, thereby enhancing transparency in autonomous decision-making. Additionally, this functionality supports developers in refining and optimizing the model's performance in real-world applications.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
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
Cyngn
Founded
2013
Country
United States
Website
www.cyngn.com/industrial-autonomous-vehicle-solutions
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
nvidia.com