architecture
architecture
architecture
The top layer of the current operating systems is the Application Layer - that's why the answer to all our computing problems is building an app, whether it's ordering food, booking a cab, or shopping - applications that work in isolation.
Light is an AI-Native Operating System layer on top of Android (Open Source) that integrates the Connected Data Architecture or CDA (discussed later) with an AI App Store. This ensures your device can perform simple to complex tasks based on multimodal inputs.
The CDA is the layer that connects any application, whether a website, an app, or a piece of software, ensuring secure, on-device orchestration of multi-application tasks without dependency on 1000s of APIs.
The top layer of the current operating systems is the Application Layer - that's why the answer to all our computing problems is building an app, whether it's ordering food, booking a cab, or shopping - applications that work in isolation.
Light is an AI-Native Operating System layer on top of Android (Open Source) that integrates the Connected Data Architecture or CDA (discussed later) with an AI App Store. This ensures your device can perform simple to complex tasks based on multimodal inputs.
The CDA is the layer that connects any application, whether a website, an app, or a piece of software, ensuring secure, on-device orchestration of multi-application tasks without dependency on 1000s of APIs.
The top layer of the current operating systems is the Application Layer - that's why the answer to all our computing problems is building an app, whether it's ordering food, booking a cab, or shopping - applications that work in isolation.
Light is an AI-Native Operating System layer on top of Android (Open Source) that integrates the Connected Data Architecture or CDA (discussed later) with an AI App Store. This ensures your device can perform simple to complex tasks based on multimodal inputs.
The CDA is the layer that connects any application, whether a website, an app, or a piece of software, ensuring secure, on-device orchestration of multi-application tasks without dependency on 1000s of APIs.
Hardware and Kernel
Hardware and Kernel
Hardware and Kernel
This OS layer leverages ARM-based CPUs, GPUs, and optional NPUs/DSPs for on-device AI inference, featuring ephemeral caching of AI models and local data in an encrypted partition. User Applications and Sensors (like cameras, GPS, and accelerometers) feed contextual data into the system (with user consent). The AOSP-derived Linux Kernel is customized with a modified HAL to provide AI acceleration hooks and integrated memory management for large language models, while enhanced security modules (like SELinux) enforce authentication policies. Specialized I/O scheduling further prioritizes AI inference workloads to ensure optimal performance.
This OS layer leverages ARM-based CPUs, GPUs, and optional NPUs/DSPs for on-device AI inference, featuring ephemeral caching of AI models and local data in an encrypted partition. User Applications and Sensors (like cameras, GPS, and accelerometers) feed contextual data into the system (with user consent). The AOSP-derived Linux Kernel is customized with a modified HAL to provide AI acceleration hooks and integrated memory management for large language models, while enhanced security modules (like SELinux) enforce authentication policies. Specialized I/O scheduling further prioritizes AI inference workloads to ensure optimal performance.
This OS layer leverages ARM-based CPUs, GPUs, and optional NPUs/DSPs for on-device AI inference, featuring ephemeral caching of AI models and local data in an encrypted partition. User Applications and Sensors (like cameras, GPS, and accelerometers) feed contextual data into the system (with user consent). The AOSP-derived Linux Kernel is customized with a modified HAL to provide AI acceleration hooks and integrated memory management for large language models, while enhanced security modules (like SELinux) enforce authentication policies. Specialized I/O scheduling further prioritizes AI inference workloads to ensure optimal performance.
Connected Data Architecture (CDA)
Connected Data Architecture (CDA)
Connected Data Architecture (CDA)
CDA is the foundation for how apps, services, and user contexts interact within the LightOS environment. It ensures that data is unified, orchestrated, and shared responsibly, without direct app-to-app communication. Instead, all communications are brokered by a central intelligence (the CIL) and executed by agentic action models (AAM), using a defined connected data protocol (CDP).
CDA is the foundation for how apps, services, and user contexts interact within the LightOS environment. It ensures that data is unified, orchestrated, and shared responsibly, without direct app-to-app communication. Instead, all communications are brokered by a central intelligence (the CIL) and executed by agentic action models (AAM), using a defined connected data protocol (CDP).
CDA is the foundation for how apps, services, and user contexts interact within the LightOS environment. It ensures that data is unified, orchestrated, and shared responsibly, without direct app-to-app communication. Instead, all communications are brokered by a central intelligence (the CIL) and executed by agentic action models (AAM), using a defined connected data protocol (CDP).
read more on CDA
Central Intelligence Layer (CIL):
The CIL is the “brain” of the CDA. It receives context (e.g., flight booked, meeting scheduled) from different apps and user activities and runs AI inference (leveraging large language models or specialized AI modules) to figure out what next steps might be valuable.
Agentic Action Models (AAM):
AAM is the “execution engine” for tasks recommended by the CIL. It triggers agent actions in apps (e.g., booking a cab, sending notifications, updating calendars) once the CIL identifies the need.
Translates high-level AI decisions (e.g., “book a ride”) into concrete app actions.
Can handle multi-step or parallel actions across different apps.
Sends results or progress updates back to the CIL, enriching the AI layer’s context and learning.
Ensures each action is within the user’s allowed permissions, factoring in PDC or AVAS constraints.
Connected Data Protocol (CDP):
CDP is the communication protocol apps and agents use to interface with the CIL. It establishes a secure channel for event notifications, data payloads, and action commands.
Event-Driven: Apps “fire events” to the CIL through CDP. CIL broadcasts relevant events or queries via CDP to the appropriate agents or system components.
Secure & Encrypted: All data transfers are encrypted (e.g., TLS-based or OS-level cryptographic channels). Respect AVAS (Anonymous Verified Authentication System) tokens, ensuring no private info is leaked.
Asynchronous: Non-blocking event loops or message queues enable seamless background tasks and real-time responses.
Controlled Access: No direct app-to-app data exchange - all cross-service interactions go through the CIL via CDP, preserving a single point for policy and security enforcement.
Central Intelligence Layer (CIL):
The CIL is the “brain” of the CDA. It receives context (e.g., flight booked, meeting scheduled) from different apps and user activities and runs AI inference (leveraging large language models or specialized AI modules) to figure out what next steps might be valuable.
Agentic Action Models (AAM):
AAM is the “execution engine” for tasks recommended by the CIL. It triggers agent actions in apps (e.g., booking a cab, sending notifications, updating calendars) once the CIL identifies the need.
Translates high-level AI decisions (e.g., “book a ride”) into concrete app actions.
Can handle multi-step or parallel actions across different apps.
Sends results or progress updates back to the CIL, enriching the AI layer’s context and learning.
Ensures each action is within the user’s allowed permissions, factoring in PDC or AVAS constraints.
Connected Data Protocol (CDP):
CDP is the communication protocol apps and agents use to interface with the CIL. It establishes a secure channel for event notifications, data payloads, and action commands.
Event-Driven: Apps “fire events” to the CIL through CDP. CIL broadcasts relevant events or queries via CDP to the appropriate agents or system components.
Secure & Encrypted: All data transfers are encrypted (e.g., TLS-based or OS-level cryptographic channels). Respect AVAS (Anonymous Verified Authentication System) tokens, ensuring no private info is leaked.
Asynchronous: Non-blocking event loops or message queues enable seamless background tasks and real-time responses.
Controlled Access: No direct app-to-app data exchange - all cross-service interactions go through the CIL via CDP, preserving a single point for policy and security enforcement.
Central Intelligence Layer (CIL):
The CIL is the “brain” of the CDA. It receives context (e.g., flight booked, meeting scheduled) from different apps and user activities and runs AI inference (leveraging large language models or specialized AI modules) to figure out what next steps might be valuable.
Agentic Action Models (AAM):
AAM is the “execution engine” for tasks recommended by the CIL. It triggers agent actions in apps (e.g., booking a cab, sending notifications, updating calendars) once the CIL identifies the need.
Translates high-level AI decisions (e.g., “book a ride”) into concrete app actions.
Can handle multi-step or parallel actions across different apps.
Sends results or progress updates back to the CIL, enriching the AI layer’s context and learning.
Ensures each action is within the user’s allowed permissions, factoring in PDC or AVAS constraints.
Connected Data Protocol (CDP):
CDP is the communication protocol apps and agents use to interface with the CIL. It establishes a secure channel for event notifications, data payloads, and action commands.
Event-Driven: Apps “fire events” to the CIL through CDP. CIL broadcasts relevant events or queries via CDP to the appropriate agents or system components.
Secure & Encrypted: All data transfers are encrypted (e.g., TLS-based or OS-level cryptographic channels). Respect AVAS (Anonymous Verified Authentication System) tokens, ensuring no private info is leaked.
Asynchronous: Non-blocking event loops or message queues enable seamless background tasks and real-time responses.
Controlled Access: No direct app-to-app data exchange - all cross-service interactions go through the CIL via CDP, preserving a single point for policy and security enforcement.
System Services
System Services
System Services
“System Services” is an umbrella term that includes:
Core Android Services (e.g., Activity Manager, Package Manager, Window Manager) inherited from AOSP.
Additional LightOS Services extend Android’s functionality with AI-driven features, privacy controls, and cloud-native capabilities.
“System Services” is an umbrella term that includes:
Core Android Services (e.g., Activity Manager, Package Manager, Window Manager) inherited from AOSP.
Additional LightOS Services extend Android’s functionality with AI-driven features, privacy controls, and cloud-native capabilities.
“System Services” is an umbrella term that includes:
Core Android Services (e.g., Activity Manager, Package Manager, Window Manager) inherited from AOSP.
Additional LightOS Services extend Android’s functionality with AI-driven features, privacy controls, and cloud-native capabilities.
Anonymous Verified Authentication System (AVAS):
AVAS is a core system service in LightOS designed to provide secure, privacy-first user authentication without disclosing personally identifiable information (PII) such as email addresses or phone numbers. Its functionality spans from initial user onboarding to continuous verification for apps and services within the OS.
Anonymity: No direct link between user identity (like phone number, email, or government IDs) and the authentication token used within the OS.
Verified Trust: Even with anonymity, apps and services can verify that the user session is legitimate and belongs to a unique, authenticated individual (or device).
Hardware-Backed Security: Integrated with secure enclaves or Trusted Execution Environments (TEE) to store keys and handle cryptographic operations, mitigating risk from software-level attacks.
Extensibility: Provide clean APIs so third-party apps can utilize AVAS tokens without needing to implement their own identity solutions.
Private Data Cut-off (PDC):
Enables users to define “no AI involvement” zones - parts of their data or apps that remain off-limits to the OS’s central intelligence features. Offers fine-grained control over personal privacy, ensuring certain apps or interactions remain completely private from AI or system analytics.
Cloud Native Platform (CNP):
CNP (Cloud Native Platform) is designed to deliver on-demand applications and services to LightOS devices without requiring traditional installations. Users can instantly stream or execute apps/microservices from the cloud, leveraging serverless or container-based infrastructure for seamless, up-to-date experiences.
Anonymous Verified Authentication System (AVAS):
AVAS is a core system service in LightOS designed to provide secure, privacy-first user authentication without disclosing personally identifiable information (PII) such as email addresses or phone numbers. Its functionality spans from initial user onboarding to continuous verification for apps and services within the OS.
Anonymity: No direct link between user identity (like phone number, email, or government IDs) and the authentication token used within the OS.
Verified Trust: Even with anonymity, apps and services can verify that the user session is legitimate and belongs to a unique, authenticated individual (or device).
Hardware-Backed Security: Integrated with secure enclaves or Trusted Execution Environments (TEE) to store keys and handle cryptographic operations, mitigating risk from software-level attacks.
Extensibility: Provide clean APIs so third-party apps can utilize AVAS tokens without needing to implement their own identity solutions.
Private Data Cut-off (PDC):
Enables users to define “no AI involvement” zones - parts of their data or apps that remain off-limits to the OS’s central intelligence features. Offers fine-grained control over personal privacy, ensuring certain apps or interactions remain completely private from AI or system analytics.
Cloud Native Platform (CNP):
CNP (Cloud Native Platform) is designed to deliver on-demand applications and services to LightOS devices without requiring traditional installations. Users can instantly stream or execute apps/microservices from the cloud, leveraging serverless or container-based infrastructure for seamless, up-to-date experiences.
Anonymous Verified Authentication System (AVAS):
AVAS is a core system service in LightOS designed to provide secure, privacy-first user authentication without disclosing personally identifiable information (PII) such as email addresses or phone numbers. Its functionality spans from initial user onboarding to continuous verification for apps and services within the OS.
Anonymity: No direct link between user identity (like phone number, email, or government IDs) and the authentication token used within the OS.
Verified Trust: Even with anonymity, apps and services can verify that the user session is legitimate and belongs to a unique, authenticated individual (or device).
Hardware-Backed Security: Integrated with secure enclaves or Trusted Execution Environments (TEE) to store keys and handle cryptographic operations, mitigating risk from software-level attacks.
Extensibility: Provide clean APIs so third-party apps can utilize AVAS tokens without needing to implement their own identity solutions.
Private Data Cut-off (PDC):
Enables users to define “no AI involvement” zones - parts of their data or apps that remain off-limits to the OS’s central intelligence features. Offers fine-grained control over personal privacy, ensuring certain apps or interactions remain completely private from AI or system analytics.
Cloud Native Platform (CNP):
CNP (Cloud Native Platform) is designed to deliver on-demand applications and services to LightOS devices without requiring traditional installations. Users can instantly stream or execute apps/microservices from the cloud, leveraging serverless or container-based infrastructure for seamless, up-to-date experiences.
Rendering Engine
Rendering Engine
Rendering Engine
Intelligent Information Rendering (IIR)
Purpose:
Transform raw system or app data (via the CIL and AAM) into actionable, user-facing UI components.
Mechanism:
Notification: The CIL (through AAM) indicates a recommended user task (e.g., “Book a cab”).
Data Enrichment: IIR queries the CDA for extra info (destination, route, cost) and compiles it into a cohesive “task card.
Rendering: Presents this task card in the system UI or an overlay, providing a streamlined user flow (e.g., a single tap to confirm booking).
Implementation:
Primarily in Kotlin for deep Android integration.
Can leverage Jetpack Compose or a custom declarative UI engine that allows dynamic adaptation to user context and screen size.
Intelligent Information Rendering (IIR)
Purpose:
Transform raw system or app data (via the CIL and AAM) into actionable, user-facing UI components.
Mechanism:
Notification: The CIL (through AAM) indicates a recommended user task (e.g., “Book a cab”).
Data Enrichment: IIR queries the CDA for extra info (destination, route, cost) and compiles it into a cohesive “task card.
Rendering: Presents this task card in the system UI or an overlay, providing a streamlined user flow (e.g., a single tap to confirm booking).
Implementation:
Primarily in Kotlin for deep Android integration.
Can leverage Jetpack Compose or a custom declarative UI engine that allows dynamic adaptation to user context and screen size.
Intelligent Information Rendering (IIR)
Purpose:
Transform raw system or app data (via the CIL and AAM) into actionable, user-facing UI components.
Mechanism:
Notification: The CIL (through AAM) indicates a recommended user task (e.g., “Book a cab”).
Data Enrichment: IIR queries the CDA for extra info (destination, route, cost) and compiles it into a cohesive “task card.
Rendering: Presents this task card in the system UI or an overlay, providing a streamlined user flow (e.g., a single tap to confirm booking).
Implementation:
Primarily in Kotlin for deep Android integration.
Can leverage Jetpack Compose or a custom declarative UI engine that allows dynamic adaptation to user context and screen size.
Single Platform Architecture (SPA)
Goal:
Enable a single codebase to run across multiple devices - phone, laptop, tablet, AR glasses, etc. - without duplicating development.
Key Concept:
Replace Android’s traditional notion of “Activities/Intents” with a higher-level “task flow” concept.
Implementation:
Unified Packaging: Apps come in a standard format with metadata describing capabilities and UI flows.
Shared Services: The same OS services (CDA, AAM, AVAS) exist on all devices, or can be accessed via the cloud if a device is too lightweight (e.g., AR glasses).
Automation: “Task flows” handle cross-device transitions seamlessly (e.g., from phone to laptop mode).
Single Platform Architecture (SPA)
Goal:
Enable a single codebase to run across multiple devices - phone, laptop, tablet, AR glasses, etc. - without duplicating development.
Key Concept:
Replace Android’s traditional notion of “Activities/Intents” with a higher-level “task flow” concept.
Implementation:
Unified Packaging: Apps come in a standard format with metadata describing capabilities and UI flows.
Shared Services: The same OS services (CDA, AAM, AVAS) exist on all devices, or can be accessed via the cloud if a device is too lightweight (e.g., AR glasses).
Automation: “Task flows” handle cross-device transitions seamlessly (e.g., from phone to laptop mode).
Single Platform Architecture (SPA)
Goal:
Enable a single codebase to run across multiple devices - phone, laptop, tablet, AR glasses, etc. - without duplicating development.
Key Concept:
Replace Android’s traditional notion of “Activities/Intents” with a higher-level “task flow” concept.
Implementation:
Unified Packaging: Apps come in a standard format with metadata describing capabilities and UI flows.
Shared Services: The same OS services (CDA, AAM, AVAS) exist on all devices, or can be accessed via the cloud if a device is too lightweight (e.g., AR glasses).
Automation: “Task flows” handle cross-device transitions seamlessly (e.g., from phone to laptop mode).
Device Adaptive Interface (DAI)
Goal:
Provide responsive design at the OS level, so an app’s UI automatically adapts to the current device’s screen size, orientation, and input methods.
Mechanism:
Semantic UI Definitions: Developers supply data and semantically meaningful “UI blocks” or “widgets.”
Layout Engine: The OS (IIR + DAI) decides how best to present these widgets on a given device (phone, watch, external monitor).
Continuous Adaptation: DAI can dynamically adjust as the user changes orientation, or moves from one device to another (SPA synergy).
Implementation:
Likely in Kotlin/Java, integrated with the Android UI toolkit.
Could unify Jetpack Compose with web-like responsive principles, or utilize a custom layout engine for real-time adaptation.
Device Adaptive Interface (DAI)
Goal:
Provide responsive design at the OS level, so an app’s UI automatically adapts to the current device’s screen size, orientation, and input methods.
Mechanism:
Semantic UI Definitions: Developers supply data and semantically meaningful “UI blocks” or “widgets.”
Layout Engine: The OS (IIR + DAI) decides how best to present these widgets on a given device (phone, watch, external monitor).
Continuous Adaptation: DAI can dynamically adjust as the user changes orientation, or moves from one device to another (SPA synergy).
Implementation:
Likely in Kotlin/Java, integrated with the Android UI toolkit.
Could unify Jetpack Compose with web-like responsive principles, or utilize a custom layout engine for real-time adaptation.
Device Adaptive Interface (DAI)
Goal:
Provide responsive design at the OS level, so an app’s UI automatically adapts to the current device’s screen size, orientation, and input methods.
Mechanism:
Semantic UI Definitions: Developers supply data and semantically meaningful “UI blocks” or “widgets.”
Layout Engine: The OS (IIR + DAI) decides how best to present these widgets on a given device (phone, watch, external monitor).
Continuous Adaptation: DAI can dynamically adjust as the user changes orientation, or moves from one device to another (SPA synergy).
Implementation:
Likely in Kotlin/Java, integrated with the Android UI toolkit.
Could unify Jetpack Compose with web-like responsive principles, or utilize a custom layout engine for real-time adaptation.
Light Store
Light Store
Light Store
Sitting “above everything” is the Light Store, which replaces or parallels the typical app marketplace (like Google Playstore) but is tailored for LightOS.
App & Agent Distribution:
Developers upload apps (and their respective Agents) to the Light Store.
Each app can implement CDA-friendly communication (through the CDP protocol) and potentially support advanced OS features (AAM, AVAS, etc.).
Optional System Apps & Services:
System-level add-ons, plugin-style utilities, or advanced AI modules are distributed here.
Users can customize their LightOS experience by downloading additional functionalities not included by default.
Security & Privacy Integration:
Tied into the OS’s AVAS (Anonymous Verified Authentication System), ensuring secure sign-ins or purchases without revealing personal identifiers.
Ensures each uploaded app meets LightOS standards (e.g., no direct app-to-app data exchange, compliance with PDC).
Ephemeral/Cloud-Native Apps:
For CNP (Cloud Native Platform) scenarios, users can discover and launch ephemeral apps that run directly from the cloud.
Payment, subscriptions, or usage metrics are managed in a single place via the Light Store but remain linked to the user’s AVAS identity.
Cross-Device Compatibility:
Because of SPA, a single app listing can describe how the app adapts to different device form factors, enabling one-click installation across phones, laptops, or VR glasses.
In essence, the Light Store is the primary gateway for distributing and updating any software that integrates with LightOS, unifying security, AI orchestration, and user privacy protections.
Sitting “above everything” is the Light Store, which replaces or parallels the typical app marketplace (like Google Playstore) but is tailored for LightOS.
App & Agent Distribution:
Developers upload apps (and their respective Agents) to the Light Store.
Each app can implement CDA-friendly communication (through the CDP protocol) and potentially support advanced OS features (AAM, AVAS, etc.).
Optional System Apps & Services:
System-level add-ons, plugin-style utilities, or advanced AI modules are distributed here.
Users can customize their LightOS experience by downloading additional functionalities not included by default.
Security & Privacy Integration:
Tied into the OS’s AVAS (Anonymous Verified Authentication System), ensuring secure sign-ins or purchases without revealing personal identifiers.
Ensures each uploaded app meets LightOS standards (e.g., no direct app-to-app data exchange, compliance with PDC).
Ephemeral/Cloud-Native Apps:
For CNP (Cloud Native Platform) scenarios, users can discover and launch ephemeral apps that run directly from the cloud.
Payment, subscriptions, or usage metrics are managed in a single place via the Light Store but remain linked to the user’s AVAS identity.
Cross-Device Compatibility:
Because of SPA, a single app listing can describe how the app adapts to different device form factors, enabling one-click installation across phones, laptops, or VR glasses.
In essence, the Light Store is the primary gateway for distributing and updating any software that integrates with LightOS, unifying security, AI orchestration, and user privacy protections.
Sitting “above everything” is the Light Store, which replaces or parallels the typical app marketplace (like Google Playstore) but is tailored for LightOS.
App & Agent Distribution:
Developers upload apps (and their respective Agents) to the Light Store.
Each app can implement CDA-friendly communication (through the CDP protocol) and potentially support advanced OS features (AAM, AVAS, etc.).
Optional System Apps & Services:
System-level add-ons, plugin-style utilities, or advanced AI modules are distributed here.
Users can customize their LightOS experience by downloading additional functionalities not included by default.
Security & Privacy Integration:
Tied into the OS’s AVAS (Anonymous Verified Authentication System), ensuring secure sign-ins or purchases without revealing personal identifiers.
Ensures each uploaded app meets LightOS standards (e.g., no direct app-to-app data exchange, compliance with PDC).
Ephemeral/Cloud-Native Apps:
For CNP (Cloud Native Platform) scenarios, users can discover and launch ephemeral apps that run directly from the cloud.
Payment, subscriptions, or usage metrics are managed in a single place via the Light Store but remain linked to the user’s AVAS identity.
Cross-Device Compatibility:
Because of SPA, a single app listing can describe how the app adapts to different device form factors, enabling one-click installation across phones, laptops, or VR glasses.
In essence, the Light Store is the primary gateway for distributing and updating any software that integrates with LightOS, unifying security, AI orchestration, and user privacy protections.
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