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Description
ALBERT is a self-supervised Transformer architecture that undergoes pretraining on a vast dataset of English text, eliminating the need for manual annotations by employing an automated method to create inputs and corresponding labels from unprocessed text. This model is designed with two primary training objectives in mind. The first objective, known as Masked Language Modeling (MLM), involves randomly obscuring 15% of the words in a given sentence and challenging the model to accurately predict those masked words. This approach sets it apart from recurrent neural networks (RNNs) and autoregressive models such as GPT, as it enables ALBERT to capture bidirectional representations of sentences. The second training objective is Sentence Ordering Prediction (SOP), which focuses on the task of determining the correct sequence of two adjacent text segments during the pretraining phase. By incorporating these dual objectives, ALBERT enhances its understanding of language structure and contextual relationships. This innovative design contributes to its effectiveness in various natural language processing tasks.
Description
Odyssey-3 represents an advanced foundational world model and dynamic system that forecasts the movement and interaction of objects across space while tracking the evolution of various situations over time. Utilizing an autoregressive diffusion transformer, it captures representations related to physics, dynamics, and the principles of cause-and-effect from an extensive collection of visual data, enabling it to simulate environments effectively and develop strategies for managing physical systems. Additionally, Odyssey-3 is capable of creating immersive environments based on user prompts and can instantly predict how these environments shift in response to actions taken by individuals or agents, featuring both first-person and third-person navigation along with flexible camera controls. The extensive world knowledge it acquires can be tailored to various systems by retraining an action decoder or policy using paired data of observations and corresponding actions. Even with limited amounts of task-specific data, Odyssey-3 has demonstrated its utility in controlling robotic arms, powering humanoid robots, operating vehicles, and producing synchronized multi-sensory observations. Furthermore, it is capable of facilitating interactive experiences that enhance user engagement and understanding.
API Access
Has API
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API Access
Has API
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Integrations
Spark NLP
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Pricing Details
No price information available.
Free Trial
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Free Version
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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
No
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
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Founded
1998
Country
United States
Website
github.com/google-research/albert
Vendor Details
Company Name
Odyssey
Founded
2023
Country
United States
Website
odyssey.systems/meet-odyssey-3
Product Features
Product Features
Alternatives
Alternatives
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