As the pressure on Google to reveal its AI monetization strategy grows, the tech giant is releasing what it calls its most powerful AI model on Wednesday. Its biggest and most powerful category, Gemini Ultra, will be part of the huge language model in Gemini’s suite of sizes. Gemini Pro will be scalable over a broad variety of jobs, while Gemini Nano will be used for particular tasks and mobile devices.
For the time being, the business intends to license Gemini to clients via Google Cloud so that they may include it in their own apps.
Overview:
- Gemini Ultra, the latest addition to Google’s AI suite
Includes different sizes like Gemini Pro and Gemini Nano
Gemini Pro scalable for various tasks; Gemini Nano is for specific functions; and mobile devices
Licensing and Integration: - Google plans to license Gemini to clients via Google Cloud
Integration into applications is possible
Release of Gemini API in Google AI Studio and Google Cloud Vertex AI on December 13
Applications Across Industries: - Powers Google’s chatbot Bard and Search Generative Experience (SGE)
Enhances customer care interactions, product recommendations, and advertising trend analysis
Useful for content production, marketing campaigns, blog posts, and productivity tools
Notable Features: - Analyzes extensive research documents, captures charts, and updates graphics
Evaluates complex assignments, identifies correct answers, and points out errors
Milestone Achievement: - Gemini Ultra surpasses human experts on Massive Multitask Language Understanding (MMLU) test
Covers 57 subjects, including math, physics, history, law, medicine, and ethics
Bard’s Evolution: - Bard, Google’s chatbot, now uses Gemini Pro for advanced capabilities
“Bard Advanced,” powered by Gemini Ultra, is set to launch early next year
Comparison with GPT-4: - Gemini Ultra outperforms GPT-4 in various benchmarks
Detailed in a white paper published on Wednesday
Subscription Model: - No information on subscription fees for “Bard Advanced” yet
Focus on delivering a positive user experience
Gemini’s Additional Skills: - Likely possesses additional skills compared to current-generation language models
Specific novel capabilities are still under exploration
Deployment Delay Insights: - Testing more complex models takes time
Gemini has the most comprehensive safety evaluations among Google’s AI models
Cost-Effectiveness: - Gemini Ultra, the largest model, is claimed to be more cost-effective to maintain
More efficient in addition to being more competent
Technical White Paper: - Google to publish a technical white paper with more details about the methodology
Specific parameters to remain undisclosed
Next-Gen Tensor Processing Unit (TPU): - Introduction of TPU v5p processor for AI model training
Claims superior value for money compared to TPU v4, but no details on performance against Nvidia
Industry Trends: - The announcement follows competitors incorporating bespoke silicon to combat AI
Investor inquiries on Google’s plans to convert AI into tangible profits
Search Generative Experience (SGE): - Introduced in August as an early experiment
Reflects a conversational tone but has not gone live to the public
Gemini’s integration into SGE expected in the coming year