FutureAI unveils new architecture to enable the creation of personalized AI apps

Introducing FutureAI’s Masterpiece: A revolutionary architecture for AI-native applications: FutureAI has unveiled Masterpiece, a cutting-edge architecture designed to enable developers to build AI-native applications with built-in generative personalization capabilities.

Core features and capabilities: Masterpiece offers a suite of powerful tools and functionalities to enhance AI-driven application development.

• The architecture utilizes a contextualization-specialized version of Llama 70B, Leo 1, and incorporates an LDA model for topic modeling trained on hundreds of thousands of emails.
• Masterpiece integrates Vertex AI’s multimodal embedding library and provides two datasets (Gmail and Plaid) for inference.
• The platform ensures user data sovereignty, offering controls, consents, and privacy choices for users regarding their data usage in generative personalization and inference graph building.

Generative personalization and inference graphs: At the heart of Masterpiece are five inference graphs that power its generative personalization capabilities.

• The Interests graph allows developers to pull user interests, either independently or paired with existing datasets, enabling personalized content recommendations.
• The Relationships graph provides insights into user connections, including relationship taxonomies and the ability to pair relationships with interests.
• The Knowledge graph extracts and clusters information about a user’s expertise in various subject matters.
• The Persona graph mimics a user’s tonality and linguistic style, enabling AI-powered communication that reflects the user’s unique voice.
• The Preferences graph offers insights into users’ modality preferences, including preferred engagement formats and languages.

Technical specifications and infrastructure: Masterpiece is built on robust technical foundations to ensure high performance and scalability.

• The architecture is based on Leo 1, a fine-tuned version of Llama 3.1 70B, and operates on NVIDIA H100s infrastructure.
• It offers SDK support for JavaScript and TypeScript, with data sources including Gmail and Plaid.
• The platform maintains a p95 response time of 5,000ms and imposes rate limits to ensure system stability.

Pricing and accessibility: FutureAI offers a flexible pricing model to accommodate various development needs.

• Developers can start building with Masterpiece using a Pay Per MTok model, with separate pricing for input and output MTok.
• Enterprise-level tiers are available for larger-scale implementations.

Broader implications: Masterpiece represents a significant step forward in AI-native application development, offering developers powerful tools to create highly personalized user experiences.

• The platform’s focus on user data sovereignty and privacy controls addresses growing concerns about data protection in AI applications.
• By providing ready-to-use inference graphs and personalization capabilities, Masterpiece has the potential to accelerate the development of sophisticated AI-driven applications across various industries.
• However, the reliance on user data for personalization may raise questions about data privacy and the ethical use of AI, highlighting the need for ongoing discussions about responsible AI development and deployment.