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What is Gemma 3?
Gemma 3, introduced by Google, is a state-of-the-art AI model built on the Gemini 2.0 architecture, specifically engineered to provide enhanced efficiency and flexibility. This groundbreaking model is capable of functioning effectively on either a single GPU or TPU, which broadens access for a wide array of developers and researchers. By prioritizing improvements in natural language understanding, generation, and various AI capabilities, Gemma 3 aims to advance the performance of artificial intelligence systems significantly. With its scalable and durable design, Gemma 3 seeks to drive the progression of AI technologies across multiple fields and applications, ultimately holding the potential to revolutionize the technology landscape. As such, it stands as a pivotal development in the continuous integration of AI into everyday life and industry practices.
What is ESMFold?
ESMFold exemplifies how artificial intelligence can provide us with groundbreaking tools to investigate the natural world, similar to how the microscope transformed our ability to see the intricate details of life. By leveraging AI, we can achieve new insights into the rich tapestry of biological diversity, thus deepening our understanding of life sciences. A considerable amount of AI research focuses on teaching machines to perceive the world in ways that parallel human cognition. However, the intricate language of proteins remains difficult for humans to interpret and has posed challenges for even the most sophisticated computational models. Despite these hurdles, AI has the potential to decode this complex language, thereby enhancing our understanding of biological mechanisms. Investigating AI's role in biology not only broadens our comprehension of life sciences but also illuminates the wider implications of artificial intelligence as a whole. Our research underscores the interconnected nature of various disciplines: the large language models that drive advancements in machine translation, natural language processing, speech recognition, and image generation also have the potential to uncover valuable insights into biological systems. This interdisciplinary strategy may lead to groundbreaking discoveries in both the fields of AI and biology, fostering collaboration that could yield transformative advancements. As we continue to explore these synergies, the future holds great promise for expanding our knowledge and capabilities in understanding life itself.
Integrations Supported
BLACKBOX AI
C
C++
CSS
Clearview Elite
EmbeddingGemma
F#
FriendliAI
Gemini
Gemini 2.0
Integrations Supported
BLACKBOX AI
C
C++
CSS
Clearview Elite
EmbeddingGemma
F#
FriendliAI
Gemini
Gemini 2.0
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Free Trial Offered?
Free Version
Pricing Information
Free
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Date Founded
1998
Company Location
United States
Company Website
ai.google.dev/gemma
Company Facts
Organization Name
Meta
Date Founded
2004
Company Location
United States
Company Website
github.com/facebookresearch/esm
