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Description
The Apple Foundation Models framework enables developers to leverage Apple's on-device model, which excels in language comprehension, organized output, and invoking tools. This framework grants access to the large language model integral to Apple Intelligence, thereby assisting applications in executing intelligent tasks tailored to their specific needs. By recognizing patterns, the text-based on-device model can produce relevant text in response to various prompts and has the capability to call upon developer-written code for targeted functionalities. Developers are empowered to create text content across a multitude of applications, such as summarization, entity extraction, text comprehension, enhancement, game dialogues, creative content crafting, classification, and beyond. Additionally, it offers guided generation features that enable developers to construct complete Swift data structures with robust assurances by utilizing the Generable macro, enhancing the versatility and functionality of the model. Ultimately, this framework significantly streamlines the process of integrating advanced AI capabilities into applications.
Description
Gemini Diffusion represents our cutting-edge research initiative aimed at redefining the concept of diffusion in the realm of language and text generation. Today, large language models serve as the backbone of generative AI technology. By employing a diffusion technique, we are pioneering a new type of language model that enhances user control, fosters creativity, and accelerates the text generation process. Unlike traditional models that predict text in a straightforward manner, diffusion models take a unique approach by generating outputs through a gradual refinement of noise. This iterative process enables them to quickly converge on solutions and make real-time corrections during generation. As a result, they demonstrate superior capabilities in tasks such as editing, particularly in mathematics and coding scenarios. Furthermore, by generating entire blocks of tokens simultaneously, they provide more coherent responses to user prompts compared to autoregressive models. Remarkably, the performance of Gemini Diffusion on external benchmarks rivals that of much larger models, while also delivering enhanced speed, making it a noteworthy advancement in the field. This innovation not only streamlines the generation process but also opens new avenues for creative expression in language-based tasks.
API Access
Has API
API Access
Has API
Pricing Details
Free
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
Apple
Founded
1976
Country
United States
Website
developer.apple.com/documentation/FoundationModels
Vendor Details
Company Name
Google DeepMind
Founded
2010
Country
United Kingdom
Website
deepmind.google/models/gemini-diffusion/