Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Index by Parallel represents an innovative framework for content in the age of AI, aimed at demonstrating to publishers, creators, writers, content owners, data providers, and AI companies the value of their content for AI agents. With AI agents already leveraging web content for countless daily tasks, Index empowers content owners by revealing their contributions and enabling them to connect with millions of agents rather than just human audiences, while also ensuring they receive compensation when agents utilize their material to generate responses. Content owners can easily register a domain and link their content without needing to transfer an entire corpus, as Parallel’s infrastructure monitors in real time when agents access and depend on that content. Furthermore, Index facilitates distribution across various agent-centric applications, including legal research, financial due diligence, sales intelligence, healthcare, and compliance, ensuring that valuable content reaches a new generation of readers operating on a large scale. This transformative approach not only maximizes the visibility of content but also enhances the potential for content owners to engage with an evolving digital landscape.
Description
PanGu-α has been created using the MindSpore framework and utilizes a powerful setup of 2048 Ascend 910 AI processors for its training. The training process employs an advanced parallelism strategy that leverages MindSpore Auto-parallel, which integrates five different parallelism dimensions—data parallelism, operation-level model parallelism, pipeline model parallelism, optimizer model parallelism, and rematerialization—to effectively distribute tasks across the 2048 processors. To improve the model's generalization, we gathered 1.1TB of high-quality Chinese language data from diverse fields for pretraining. We conduct extensive tests on PanGu-α's generation capabilities across multiple situations, such as text summarization, question answering, and dialogue generation. Additionally, we examine how varying model scales influence few-shot performance across a wide array of Chinese NLP tasks. The results from our experiments highlight the exceptional performance of PanGu-α, demonstrating its strengths in handling numerous tasks even in few-shot or zero-shot contexts, thus showcasing its versatility and robustness. This comprehensive evaluation reinforces the potential applications of PanGu-α in real-world scenarios.
API Access
Has API
No
API Access
Has API
No
Screenshots View All
No images available
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
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
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
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
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Parallel
Country
United States
Website
index.parallel.ai/
Vendor Details
Company Name
Huawei
Founded
1987
Country
China
Website
arxiv.org/abs/2104.12369