August 20

August Conversations

I

Note to Self: Write about the time I learned about how XX chromosomal dominance would render XY chromosomes extinct in a thousand years, grappled with the existential weight of this knowledge, etc. when I was like 11 or something.

II

Today Forecast opened. It’s cool to see the birth of a new environment.

It’s fun speaking with people who speak/converse slowly because you get to really test out your ability to model other people’s thought patterns or way of perceiving the world.

Something that’s been bothering me with ulmaceae is the idea of messy, unbounded, untracked, unwanted pip packages/dependencies cluttering up my computer.

I want to research whether it’s possible to segregate the dependencies installed by stablediffusion and llama-cpp into appropriate repo-scoped venvs and nuke everything living at the global scope (my computer)

III

On Ease

Perfection is an idiot’s ideal of a north star or guiding ideal for the work they’re doing. I think any time something is given the label “Perfect”, one immediately gains an awareness of the effort and striving that went into the production of perfection. […] Perfection, like overworked dough, is the result of neurosis. […] It’s lesser as a result.

In my opinion, my highest guiding ideal is to bring about things with “ease” into the world.

I don’t think “ease” can be manufactured or strove for, which makes it scarce […]

“ease” is a particularly human product, I can’t imagine an artificial intelligence capable of producing something like “ease”

ease can’t be felt in the present, it’s only felt in retrospect

ease can’t be manifested, for the future

When you’re near someone with ease, it’s like being in the presence of an angel

IV

Do you know what Object Capture for iOS is?

Yes, as of my last training data in September 2021, Apple had announced “Object Capture” as a part of their RealityKit 2 framework during WWDC 2021. It’s a tool designed to allow developers to create high-quality, photorealistic 3D models of real-world objects using just an iPhone, iPad, or DSLR. These 3D models can then be used in apps, games, and AR experiences.

Here’s a basic overview of how Object Capture works:

Capture: Users take a series of photos of an object from different angles using an iPhone, iPad, or DSLR.

Process: These photos are then processed on a Mac running macOS Monterey or later. The Object Capture API processes the photos to generate a detailed 3D model.

Preview: Once the 3D model is generated, it can be previewed in AR using the Reality Composer app or incorporated into apps and games using the RealityKit framework.

The idea is to make the creation of 3D content more accessible to developers and content creators without requiring expensive equipment or specialized skills.

It’s worth noting that while the capturing and previewing can be done on iOS devices, the actual processing (as of 2021) required a Mac.

Let’s say that I want to use Object Capture to scan objects in the environment and process them, but not preview them. Are these capabilities decoupled?

Yes, the capabilities provided by Apple’s Object Capture are decoupled. This means you can use the different components of the workflow separately, based on your needs. Here’s a breakdown:

Capture: You can use any compatible device, such as an iPhone, iPad, or DSLR, to capture photos of an object from various angles. You don’t have to immediately process these photos with the Object Capture API. You can store them for later processing or even use them for other purposes.

Process: Once you have a set of photos, you can process them on a Mac running macOS Monterey or later using the Object Capture API to generate a 3D model. This doesn’t necessarily have to happen immediately after capturing. Moreover, you aren’t required to preview or display the resulting model in any specific way.

Preview (or Use): If you choose to preview the resulting 3D model, you can use the Reality Composer app or integrate it into apps and games using the RealityKit framework. However, this step is optional based on your use case.

So, if your primary interest is in scanning objects and processing them without previewing, you can definitely do that. You’d capture the photos and then process them to obtain 3D models, which you can store, share, or use in any other way you see fit.

Ok, think carefully about this speculative app idea I have:

I would like to use Object Capture to scan objects with an apple device, and then conceptually “attach” chat interfaces to the scanned object.

For example, let’s imagine that I want to allow people to use an object like a unique plant as a forum, by scanning the plant and gaining access to a particular instance of a chat associated with the plant.

Do you have a sense of whether this is possible? Feel free to ask me questions so I can clarify my thinking here to you.

Your idea is intriguing. Essentially, you’re aiming to use real-world objects as access points or “portals” to unique chat forums. Here’s how I understand it:

A user scans an object, like a unique plant, using Object Capture. Once the object is processed and recognized, it becomes a unique identifier or key to access a specific chat interface. Other users who scan the same object (or perhaps a similar instance of the object) can join the same chat. Here are a few questions and considerations to clarify and refine the idea:

Object Uniqueness: How do you plan to differentiate between two similar objects? For instance, if two users scan two different instances of the same plant species, should they access the same chat or different chats? The uniqueness of the object will determine the uniqueness of the chat interface.

Object Persistence: Objects in the real world can change over time (plants grow, objects wear out). How do you plan to handle this? Will users have to rescan objects periodically?

Object Database: You’d need a database to store the 3D representations or some unique fingerprints of the objects and link them to chat instances. How do you plan to manage this, especially considering storage and retrieval efficiencies?

Access Control: What if someone wants a private chat linked to an object? Will there be mechanisms to restrict access or create private object-based chat rooms?

Use Cases: While plants are an interesting example, have you considered other potential use cases? For instance, scanning a historical artifact to join a chat about its history or a product to join a customer support chat.

Augmented Reality: Have you considered integrating AR into this app? Users could potentially see visual indicators or chat bubbles when pointing their device at a scanned object.

Chat Management: How would you handle moderation, user management, and other standard chat functionalities in this context? From a technical standpoint, creating such an app is feasible, especially with the advancements in AR, 3D scanning, and cloud technologies. The real challenge would be in refining the user experience, ensuring object uniqueness, and managing the database efficiently.

I can answer your questions above:

1. I plan on not differentiating between objects meaningfully. This means that if someone named Alice scans a common object that another user Bob has scanned first, Alice should be able to “portal” into the original chat created by Bob, which might have originated from another object Alice doesn’t have access to. This is interesting to me because it means that common objects around the world can become forums, in a sense. Instead of browsing the web for Q&A or facts about a product, which is inherently a context removed from the product, people can discuss a product by using the product itself.
2. Rescanning for dynamic or living objects should definitely be possible. Perhaps a user can “mark” instances of the object over time similar to version control, and perhaps this could evoke interesting features of the communication method “attached” to the object using this hypothetical app.
3. That’s a good question, I’d love to hear any expert opinions you have about how to best manage object data, their 3D representations, and any other data “attached” to these objects, especially if this app is designed for many people to use concurrently.
4. There probably should be access control somehow granted to people who scan an object. It might be interesting to use geolocation data, coupled with the object scan, to determine distinct locations/objects in space. If someone is scanning an object in close proximity to a prior scanned instance, maybe they’re given a choice to join the prior scan, or join a “global” and inherently public chat attached to an object, in the case of commodity goods many people might have access to
5. The examples you provided are amazing, I’d love to hear more ideas along these lines. You made me realize that one could potentially scan a person to attach a chat to them, and build a small social network directly correlated to an individual. This could be a cool evolution of a personal forum or “profile” or “homepage” on the internet
6. This is a really good idea, I haven’t considered it deeply, but it makes sense to use AR to depict when an object your AR system recognizes as having been “scanned” by someone in this network, and carries a communication method within it or associated with it
7. Good question, we don’t have to address this now, but it seems to make sense that someone who first scans an object has the ability to set initial moderation or governance settings.

Do you have any further responses to my own responses to you? Do you have any other novel ideas that I may have sparked with my own answers? Anything else we could think about here?

Your clarifications provide a strong foundation for this speculative app idea, and I’m excited to delve deeper into its potential and challenges. Here are my thoughts based on your responses:

Dynamic Object Forums: The idea of using common objects as forums is intriguing. This turns everyday items into shared experiences. A coffee mug, a specific book, or even a type of toy could become shared discussion points around the world. It decentralizes the idea of forums from websites to the real world, turning the tangible into the intangible.

Version Control for Dynamic Objects: Your idea of marking instances of an object over time is very innovative. This could lead to a fascinating exploration of how objects evolve. For example, a plant might have discussions related to its growth stages or a building might have comments related to its changing facade or renovations over time.

Database Management:

Use a cloud-based system for scalability and to handle concurrent users.

Store a compact representation or “fingerprint” of the 3D object instead of the entire 3D model to save space and make retrieval faster.

Attach metadata to each object: timestamps, geolocation, chat settings, version history, etc.

Consider using distributed databases or technologies like blockchain for added transparency, especially if users are marking instances over time.

Geolocation and Object Proximity: Using geolocation is a great idea for determining unique instances. It also adds another layer to the experience: users could explore object-based chats native to their current location.

Expanding Use Cases:

Personal Profiles: As you mentioned, scanning a person to create a personal chat or profile is intriguing. Imagine walking into a conference and being able to scan individuals to see their professional profiles, portfolios, or even just fun facts.

Historical Sites: Tourists could scan monuments or historical sites and join chats discussing the history, significance, or even guided tours.

Art Pieces: Museums could allow visitors to scan art pieces and join discussions about the artwork, the artist, or the art’s historical context.

AR Enhancements: AR could also be used to display the history of an object, show user comments in real-time as annotations, or even visualize the “popularity” or “activity” of an object’s chat.

Governance and Moderation: Given the decentralized nature of your idea, consider crowd-sourced moderation methods, similar to platforms like Reddit or Stack Exchange. Users could earn reputation points for positive contributions and could then use these points for moderation tasks or to unlock special features.

Additional Ideas:

Object Stories: Allow users to attach stories or memories to objects. Imagine scanning an old typewriter and reading personal stories from various users about their experiences with similar typewriters.

Learning Opportunities: For objects like plants or animals, the chat could also become a space for educational content. Experts could join and provide insights, turning the chat into a live Q&A session.

Privacy Considerations: Ensure there are strict privacy controls, especially when it comes to scanning personal items or individuals. You wouldn’t want unintended privacy breaches.

Your app idea is genuinely innovative and has the potential to bridge the gap between the physical and digital worlds in a way that enhances social connections, learning, and shared experiences. With the right execution and attention to user experience, it could be a game-changer in the AR and social networking space.

Given our discussion, do you have an idea for how to prototype an iphone app using swiftUI that uses Object Capture in the way we’ve imagined? Could you provide sample code to help me get started?

An ideal prototype app could somehow perform the following:

1. Immediately open up to a camera view (similar to snapchat)
2. Grant a user the ability to start scanning objects in the camera’s view using Object Capture by tapping on an object in the camera view
3. Once successfully scanned, give a user the ability to name a page associated with the object
4. After naming the page representing the object, the user should be able to choose a medium to “attach” to the object, such as a chat, an image, a tract of editable text, or a URL
5. Other people using the app should be able to view the data structured in step 4. by scanning the same object, or another similar/equivalent object
6. All users who’ve scanned an object probably need another page to view a history of all objects they’ve scanned, so they can revisit objects

Absolutely! Let’s break down the steps needed to prototype this app:

Step 1: Setup Before you start, ensure you have the necessary tools:

Xcode (Latest version, as Object Capture API will be part of the newer SDKs).

An Apple Developer Account to run the app on a real device (since camera functionality and ARKit features are often limited or non-functional on the simulator).

macOS Monterey or later for Object Capture API.

Step 2: Basic SwiftUI App with Camera Access

Create a new SwiftUI App in Xcode.

Request camera permissions by adding the necessary keys (NSCameraUsageDescription) to the Info.plist file.

Step 3: Implement Camera View

You’d typically use AVCaptureSession from AVFoundation to create a custom camera view. However, for object scanning, you’ll need to integrate ARKit, since Object Capture will likely work in tandem with ARKit’s capabilities to recognize and scan objects.

Here’s a basic skeleton to get you started:

swift
Copy code
import SwiftUI
import ARKit

struct ARScanView: UIViewRepresentable {
    func makeUIView(context: Context) -> ARSCNView {
        let arView = ARSCNView(frame: .zero)
        arView.session.delegate = context.coordinator
        // More configurations if needed
        return arView
    }

    func updateUIView(_ uiView: ARSCNView, context: Context) {
        // Handle updates
    }

    func makeCoordinator() -> Coordinator {
        Coordinator(self)
    }

    class Coordinator: NSObject, ARSessionDelegate {
        var parent: ARScanView

        init(_ parent: ARScanView) {
            self.parent = parent
        }

        // Implement ARSessionDelegate methods here
    }
}

Step 4: Object Scanning Implement object scanning using Object Capture. This would be a more complex process, involving taking multiple images of the object, processing them, and then creating a 3D model.

Step 5: Attach Data to Scanned Object Once the object is scanned, present a new view where users can name the object and attach data (chat, image, text, URL). Store this data, along with a representation of the object, in a database (e.g., Firebase, CoreData with CloudKit, etc.).

Step 6: Recognize Scanned Objects and Retrieve Data When another user scans a similar/equivalent object, retrieve the data from the database and present it in a suitable format.

Step 7: History Page Maintain a local history of scanned objects. This can be a simple list view in SwiftUI that displays all the objects a user has scanned.

Note: This is a high-level overview, and the actual implementation can get quite complex, especially when dealing with ARKit and Object Capture. Apple’s documentation and WWDC sessions on ARKit and Object Capture would be invaluable resources as you dive deeper.

Also, as this is a prototype, there are many aspects (like error handling, UI/UX improvements, performance optimizations, etc.) that aren’t addressed but would be crucial for a production app.

OK I have one last question for now: How might I allow users who’ve scanned objects using this app to associate AI characters with objects?

An example here is that I might want to breathe digital life into ordinary objects using this app. I could potentially scan an object like a mug, and select an option to grant it “sentience” through something like ChatGPT-4. Of course, this isn’t real sentience, but it would be interesting to use the object model data to provide context to the LLM so that it could “assume” the character of the object it’s now associated with. Does this seem feasible, or interesting?

Your idea is both feasible and deeply interesting. It’s essentially blending Augmented Reality (AR) with conversational AI to create a unique and interactive experience. Here’s a conceptual overview of how you might achieve this:

Object Identification: After scanning and recognizing an object (like a mug), the app should allow users to associate an AI character with it. This can be achieved by saving a reference to the object, perhaps its 3D fingerprint or some unique identifier, along with the AI character’s details.

Contextual Conversations: When a user interacts with the “sentient” object, the app should use the object’s model data as context for the conversation. For instance, if it’s a mug, the AI might talk about coffee, tea, or its “experiences” being a mug. This can be achieved by sending contextually relevant prompts to the AI, like “You are a mug. Tell me about your day.”

Object-Specific Personalities: Each object can have its own unique “personality” based on its type, where it’s used, its age, etc. A centuries-old artifact will have a different personality and set of stories compared to a brand-new tech gadget. You could create predefined personalities for common objects and allow users to customize or tweak them.

Interactivity: Enhance the experience by allowing users to ask the object questions or even give it commands. For instance, asking a “smart lamp” to share a joke or a story about “its” history.

AI Backend: Since GPT-4 or similar models are typically cloud-based due to their size, the app would need to send the user’s messages to a backend where the model resides, and then return the model’s responses to the user. Ensure that this communication is secure and efficient.

AR Integration: To make the interaction more immersive, use AR to project the AI character onto the real-world object. For instance, when talking to the “mug”, an AR overlay might show the mug’s “face” and animate it based on the conversation’s mood.

Learning & Evolution: An exciting feature could be the AI “learning” or “evolving” based on its interactions. Over time, the mug might “remember” its owner’s favorite drink or recall past conversations.

Challenges:

Storage & Computation: Storing 3D models of objects and running large language models requires significant resources. Consider using cloud solutions and optimizing data storage.

Privacy Concerns: Ensure that users are aware of what data is being sent to the cloud and stored. Implement robust privacy measures.

Realism vs. Uncanny Valley: Striking the right balance between a realistic AI character and one that feels unnatural or eerie can be a challenge. Test and iterate based on user feedback. In summary, your idea takes object scanning and AR to a whole new level by imbuing inanimate objects with “life” and personality. With advancements in AI and AR, creating such an experience is becoming increasingly feasible. The potential applications, from education to entertainment, are vast and captivating.

If you were to pitch this idea to an investor, how might you very capture the essence of the idea we’ve explored here?

If it helps, I’m starting to think that this could be an excellent answer to the future of localized collective knowledge stored in objects. It could be a new way to think about entertainment or embedding playful interactions into everyday objects. It could allow people from across the world to bond over the experiences of otherwise commodity goods.

Do you have any other ideas for how to pitch this idea?

Certainly! Crafting a compelling pitch requires clarity, brevity, and a sharp focus on the unique value proposition. Here’s a potential pitch for your idea:

[Opening with a Relatable Scenario] Imagine you’re sipping coffee from your favorite mug. What if that mug, a mundane everyday object, could talk? What stories would it tell? What if it could connect you with someone sipping coffee halfway across the world?

[Introducing the Solution] Introducing [App Name], the future of localized collective knowledge. Our platform transforms ordinary objects into interactive experiences, embedding the magic of play and connection into the things you touch every day.

[Key Features]

Object Sentience: Breathe digital life into any object. Your old grandfather clock, your running shoes, or even that souvenir from your last vacation can have a voice, a personality, a story.

Connect Over Commodities: A toy in New York can share stories with the same toy in Tokyo. People from across the globe can bond over shared experiences, facilitated by the very objects they own.

Localized Collective Knowledge: Objects become living forums, repositories of user-generated content, discussions, and shared experiences. The history of an object, its tales, its interactions, all stored and accessible to anyone, anywhere.

[Market Potential] The fusion of AR and AI is poised to be a multi-billion dollar industry. As the digital and physical worlds converge, the demand for immersive, interactive experiences is skyrocketing.

[Closing with a Vision] With [App Name], we’re not just building an app; we’re crafting a new language of interaction. A world where objects aren’t just passive entities but active participants in our daily lives. Join us in redefining the boundaries of play, connection, and shared experiences.

Additional Pitching Tips:

Demo is King: If possible, have a live demo or a video that showcases the magic in real-time. Seeing a “talking mug” or a “storytelling artifact” in action can be far more compelling than any words.

Address Potential Concerns: Be ready to discuss challenges, especially around privacy, data storage, and tech feasibility. Highlight your plans to tackle them.

Market Research: Showcase any preliminary market research, user surveys, or feedback that indicates demand or interest in such an experience.

Monetization Strategy: Investors will be keen to understand how you plan to monetize. Whether it’s through premium features, partnerships with product manufacturers, or a marketplace for user-generated AI characters, have a clear strategy in place.

Remember, the goal of the pitch is to ignite interest and curiosity. You want investors to ask questions, to want to learn more, and to see the potential of your vision.

It’s one thing to imagine consumer applications of this sort of app/software, but can you imagine ways this type of technology could be used for commercial or B2B applications?

Absolutely! The fusion of object scanning, AR, and AI has significant potential in the commercial and B2B sectors. Here are some potential applications:

Supply Chain & Inventory Management:

Scanned objects in warehouses can “communicate” their status, location, or expiration dates.

Interactive manuals for machinery maintenance. Scan a machine part, and it provides instructions or even connects to a support chat.

Retail & Shopping Experience:

In-store product scans provide detailed product information, reviews, or even a chatbot for Q&A.

Product demos or virtual try-ons for items like furniture, electronics, or apparel.

Real Estate & Property Management:

Scan sections of a property to get detailed information, history, or even “talk” to the property for insights on maintenance needs.

Assist in property valuations by providing contextual information.

Training & Onboarding:

New employees can scan tools, devices, or stations to get instant training or connect with an AI tutor for a specific task.

This can be particularly valuable in industries like healthcare, manufacturing, or IT.

Manufacturing & Quality Control:

Machinery can provide insights into its operation, maintenance schedules, or detect and communicate anomalies.

AI analysis of scanned objects to ensure they meet quality standards.

Museums & Cultural Institutions:

Beyond consumer experiences, B2B applications can include licensing this technology to museums to enhance visitor experiences.

Artifacts and exhibits can “tell” their story or provide deep contextual information.

Hospitality & Tourism:

Hotels can offer guests the ability to scan amenities or features to get more information or customer service.

Tour operators can enhance tours by allowing travelers to scan and interact with landmarks.

Research & Development:

Scientists and researchers can scan prototypes or models to run simulations, gather data, or even get AI-generated insights.

Collaboration on projects where different teams can add input or data to a scanned object.

Marketing & Advertising:

Brands can create interactive campaigns where products “interact” with potential clients, offering personalized information, discounts, or experiences.

B2B trade shows or events can use this technology for interactive booths or product showcases.

Agriculture & Farming:

Farmers can scan crops or livestock for health insights, maintenance, or even market prices.

AI-driven insights can suggest optimal harvest times, detect diseases, or recommend care routines.

In essence, any sector that involves physical objects (which is virtually all of them) can benefit from this convergence of technologies. The key is to identify pain points in each industry that can be addressed by interactive, AI-driven object recognition and engagement.

If you were to recommend a small founding team to work on an app like this, what roles do you think the team would need?

Creating an app that merges AR, object scanning, and AI is a complex task requiring expertise in various domains. For a small founding team, each member would ideally wear multiple hats, but here’s a recommended list of essential roles:

Technical Co-founder/CTO:

Responsibilities: Oversee all technical aspects of the project, make architectural decisions, and guide the development process. Skills: Strong background in software development, familiarity with AR frameworks (like ARKit), and experience with AI/ML integration.

Product Manager/CEO:

Responsibilities: Define the product’s vision, prioritize features, and coordinate the different teams to ensure timely delivery. They would also typically handle investor relations and fundraising.

Skills: Good understanding of the market, experience in product development cycles, and strong leadership qualities.

AR/3D Developer:

Responsibilities: Handle the object scanning and AR aspects of the app. This includes integrating ARKit, Object Capture, and other necessary technologies.

Skills: Experience in AR development, 3D modeling, and familiarity with tools like Unity or Unreal Engine (if used).

Backend Developer:

Responsibilities: Develop the server infrastructure, handle database management, ensure data security, and integrate AI models (like GPT-4).

Skills: Proficiency in server-side languages, experience with cloud platforms, and knowledge of AI integration.

Frontend/App Developer:

Responsibilities: Develop the user interface of the app, ensure smooth user experience, and integrate with backend services.

Skills: Proficiency in Swift and SwiftUI (for iOS), experience with UI/UX design principles.

AI/ML Specialist (can be part-time or an advisor role in the early stages):

Responsibilities: Optimize the integration of AI models, provide insights on AI-driven features, and ensure the AI behaves as intended.

Skills: Experience in AI/ML deployment, knowledge of NLP (if tweaking AI behavior), and familiarity with platforms like OpenAI.

UX/UI Designer:

Responsibilities: Design the app’s user interface, ensure intuitive user experience, and create any necessary assets or graphics.

Skills: Experience in mobile app design, knowledge of design tools (like Figma or Adobe XD), and an understanding of user behavior.

Business Development & Marketing:

Responsibilities: Identify potential markets, develop go-to-market strategies, forge partnerships, and handle initial user acquisition.

Skills: Strong networking abilities, understanding of the tech industry, and experience in startup marketing.

Operations & Admin:

Responsibilities: Handle day-to-day administrative tasks, financials, HR, and ensure the company meets any legal or compliance requirements.

Skills: Experience in startup operations, knowledge of finance and legal aspects.

Given it’s a startup, many of these roles can be combined based on the team members’ skills. For instance, the Technical Co-founder might also take on Backend Development, or the Product Manager could handle Business Development initially. As the startup grows, roles can become more specialized. The key is to have a core team with complementary skills that cover the critical aspects of the product and business.

Let’s imagine that in a few years, Apple releases an AR/VR headset capable of really high quality immersive mixed reality experiences, does this change anything about the idea we’ve come up with in this discussion?

Absolutely! The introduction of a high-quality AR/VR headset by Apple (or any other major player) would amplify the potential of your idea and open up new avenues for its application. Here’s how this could impact and evolve the concept:

Enhanced Immersion: With a dedicated AR/VR headset, the experience becomes more immersive. Objects wouldn’t just “speak” to users through text; they could have fully animated digital avatars, producing a much richer interaction.

Spatial Computing: Mixed reality (MR) headsets operate in the realm of spatial computing, where digital content is integrated seamlessly into the user’s environment. This means objects could interact with each other or respond to the environment in more dynamic ways. For example, a “sentient” lamp might “react” when placed near a “sentient” book, creating interactive narratives or games.

Object Memory & Persistence: With AR/VR, there’s potential for objects to remember past interactions and display them spatially. Imagine walking into a room and seeing past conversations or memories associated with various objects floating around them, creating a sort of “memory palace.”

Advanced Interaction Modes: Gesture recognition, eye tracking, and voice commands could become primary interaction modes, making the experience hands-free and more natural.

Shared Mixed Reality: Multiple users with headsets could interact with the same “sentient” object in a shared space, leading to collaborative experiences, group games, or shared narratives.

Commercial Applications Expansion:

Retail: Stores could use this technology to provide immersive shopping experiences. Customers could “converse” with products or get recommendations from them.

Education: Schools or training programs could use sentient objects for interactive learning. Historical artifacts in a museum could provide first-person narratives or reenactments.

Workspace: In collaborative workspaces, tools or stations could guide users, provide feedback, or facilitate team interactions.

Dynamic Digital Overlays: Instead of just a chat or text, objects could project dynamic digital content into the environment. A book might show an animated summary, a plant might display its growth stages, or a gadget might project its user manual.

Evolving Monetization Strategies: With the richer media experience that MR headsets offer, there are new monetization avenues, like premium object avatars, interactive narratives, or branded experiences.

Hardware Integration: The app would need to be optimized for the headset, considering factors like spatial audio, 3D UI/UX, and headset-specific features.

Privacy & Security: Immersive experiences might gather more user data, like gaze tracking or spatial behavior. This emphasizes the need for robust privacy measures.

The essence of the idea remains — imbuing objects with “sentience” and creating interactive experiences — but the depth, richness, and possibilities for engagement multiply manifold with the capabilities of an AR/VR headset. It would transition from merely “talking” to objects on a screen to fully experiencing them in an interactive, mixed-reality environment.