Immaterial Computing: Democratizing Supercomputing

Advancing User-Centric Paradigms in a Decentralized Framework. Exploring the Intersection of AI, Blockchain, CMS, and Distributed Data.

A Neural Design Experiment.

ABSTRACT

Advances in various fields like quantum computing, AI, blockchain, and neuromorphic computing are creating new possibilities that extend beyond traditional computing methods. This thesis presents the concept of “immateriality of technology” within a new computing paradigm that involves synthesizing various existing technologies like DeFi networks, AI ecosystems, distributed data storage, and popular web applications and content management systems like Medium and WordPress. The core idea is to transcend the physicality of technology, focusing on how these systems can compose an ecosystem where technology becomes an extension of human capabilities and possessions, such as data, content, and community interactions. This paper introduces a novel computational paradigm diverging from conventional personal computers and cloud computing. By amalgamating various open, decentralized, and distributed systems like LLMs (Large Language Models), GPT-4, Ethereum or Polygon, IPFS, Google Colab, Open Publishing, CMS, we pave the path for a customizable supercomputing system that is both user-centric and human-centered. We present detailed benchmarks and potential advancements into open neurotechnology like BCIs, predicting a future of synthetic telepathy, and thought control and communication.

INTRODUCTION

The advancement of computing towards an era of multiple and diverse paradigms is driven by a combination of technological innovation, different and changing user needs, and the evolving landscape of challenges and opportunities in the digital world. The blending of computing with other disciplines (like biology, physics, and social sciences) is leading to the emergence of novel computing approaches. The vast increase in data generation and the need for interconnected systems are pushing the boundaries of traditional computing paradigms. Diverse user needs and environments demand more tailored computing solutions, leading to the development of specialized paradigms.

Different paradigms offer specialized solutions for complex and varied problems that cannot be efficiently addressed by a one-size-fits-all approach. So, while the competitive tech landscape incentivizes innovation, leading to the exploration of alternative paradigms to gain an edge, multiple paradigms ensure a more resilient and adaptable computing infrastructure, capable of withstanding various challenges like cyber threats or changing user demands. Diverse paradigms allow for greater democratization of technology, making computing accessible and relevant to a broader spectrum of society.

In this context, the “immaterial computing” paradigm can be viewed as one among many emerging paradigms. It uniquely addresses the need for a more fluid, user-empowering, and decentralized approach to computing. It prioritizes user control and customization, breaking away from the constraints of traditional hardware and centralized systems. By integrating decentralized technologies like blockchain with AI and distributed data storage, it offers a novel approach to data management and processing. This paradigm is particularly relevant in an era where data privacy, digital ownership, and accessibility are becoming increasingly important.

The evolution towards multiple computing paradigms reflects the dynamic nature of technology and society. The immaterial computing paradigm exemplifies this diversity, offering a unique approach that aligns with current and future digital needs.

While building an integrated ecosystem of blockchain, AI, and distributed storage is complex, the availability of user-friendly tools, platforms, and a supportive community makes it increasingly accessible. Users can contribute significantly by educating themselves, leveraging the right tools, and engaging with the community, while being mindful of the security and technical limitations of their projects.

The goal of this new computational paradigm is to democratize access to advanced computing resources, empowering users of all skill levels and material conditions. This democratization hinges on making supercomputing power, previously accessible only to large tech companies, available to the average user.

Users don’t require expensive, high-end hardware to access supercomputing capabilities. This is enabled through open cloud-based advanced technologies and distributed computing networks, utilizing cloud infrastructures and distributed networks (like blockchain and IPFS) to provide vast computational resources and data storage, and incorporating AI tools and machine learning models, including LLMs, to process, analyze, and generate valuable data and high quality content efficiently. Also allowing users to customize their use of technology to fit their specific needs, whether it’s for business, research, community-driven ecosystems (socioeconomic networks), or personal projects.

Thus, through the integration of decentralized finance, AI ecosystems, distributed data storage systems, and web applications, we can achieve an immaterial computing paradigm, transforming traditional physical dependencies in technology to a more fluid, customizable, and user-centric ecosystem.

The concept of immateriality in the context of technology pertains to the idea that as technology becomes more integrated and pervasive, its presence becomes less noticeable. It starts to function seamlessly in the background of our lives, enabling enhanced capabilities without the overt perception of its involvement.

When discussing the potential immateriality of user-centered supercomputing, especially when derived from a fusion of systems, networks, and ecosystems, is about the idea that technology’s operation becomes so seamless, intuitive, and integrated that the user is largely unaware or unconcerned with the underlying processes, systems, or hardware. In other words, it’s the notion that technology becomes a natural extension of the user’s intent, almost like a subconscious thought process.

BENCHMARKS

View full screen diagram: https://diagrams.helpful.dev/d/d:tylEJN0a

This table outlines a comparison between three computing paradigms across several benchmarks. Let’s analyze the differences between Personal Computers (PC), Cloud Computing, and the proposed concept of Immaterial Computing:

Hard Drive

• PC: Uses local storage which is inherently limited by the device’s physical capacity and it´s lifespan.
• Cloud: Offers remote storage which is scalable based on the user’s subscription and needs.
• Immaterial: Emphasizes decentralized, distributed storage, leveraging technologies like IPFS, making your assets more censorship resistant and your property not at risk of being deleted as there is no central point of control.

Cyber Security

• PC: Security is individually managed, often leaving it susceptible to inconsistent protection levels.
• Cloud: Managed by the provider, offering professional-level security but with potential vulnerabilities in shared environments.
• Immaterial: Focuses on decentralized security measures, potentially increasing resilience to attacks through distributed ledger technologies like blockchain.

Costs

• PC: Incurs initial hardware costs and ongoing maintenance expenses.
• Cloud: Typically operates on a subscription model, with costs variable based on resource usage.
• Immaterial: Envisioned to be community-driven and sustainable, potentially lowering costs through shared resources and community management.

Efficiency

• PC: Efficiency is hardware-dependent and fixed to the capability of the individual machine.
• Cloud: Provides scalable resources that can be adjusted to meet demand, offering greater potential efficiency.
• Immaterial: Aims for enhanced efficiency through distributed processing, which can optimize resource use across a network.

Hardware/Software

• PC: Users have individual control over their hardware and software configurations.
• Cloud: Relies on provider infrastructure, which may limit user control but offers professional maintenance and updates.
• Immaterial: Leverages an open-source, diverse ecosystem which can offer a wide range of options and customizations.

IT Management

• PC: Often requires user troubleshooting, which can vary in expertise and effectiveness.
• Cloud: Managed by the provider, reducing the IT burden on the user but also reducing control.
• Immaterial: Community support and collaboration are key, suggesting a model where the community aids in the management and troubleshooting of IT issues.

Operability

• PC: Requires technical skills for operation and troubleshooting.
• Cloud: Typically offers user-friendly interaction, often through simplified web interfaces.
• Immaterial: Emphasizes a user-centric and simplified approach, potentially making advanced computing accessible to a broader audience.

Customization

• PC: Offers a limited number of configuration options based on the hardware and software capabilities.
• Cloud: Provides various services (IaaS, PaaS, SaaS) that offer different levels of customization based on user subscriptions.
• Immaterial: Highly customizable, likely due to the use of open-source software and the inherent flexibility of decentralized systems.

The transition from PC to cloud to immaterial computing show a trajectory towards more distributed, user-empowered, and flexible computing models. The immaterial computing paradigm aims to build on the scalability and professional management of cloud computing while enhancing user control, community collaboration, and security through decentralization.

INTEGRATION OF TECHNOLOGIES

Decentralized Systems

Utilizing blockchain and DeFi for financial transactions, tokenization, monetization, socioeconomic networking, and asset management.

AI and Machine Learning

Employing AI, particularly LLMs and generative models, for advanced data processing, advanced data analytics, high quality content creation, and user interaction.

Distributed Storage

Using systems like IPFS for decentralized and secure data storage.

Web Applications and CMS

Leveraging platforms like Medium and WordPress for content creation, management, and dissemination.

This evolving computing paradigm, characterized by technology’s immateriality and its seamless integration with subconscious processes, is fundamentally altering our relationship with technology. By combining decentralized platforms, advanced AI ecosystems, distributed networks, and open-source principles, we’re witnessing the democratization of supercomputing power and capabilities. This integration of technologies not only provides every user with unprecedented computational power — once the privilege of tech giants — but also ushers in a new class of applications and possibilities, once not even accessible to tech giants. We’re transitioning from viewing technology as a mere tool to embracing it as an innate extension of our cognitive and creative faculties.

APPLICATIONS

1. Web, Systems, and Networks

Generative AI Ecosystems

Generative AI like GPT-4 can produce content, answer queries, assist in education, provide therapy, and even help in designing and coding. In web systems, they could potentially auto-generate articles, assist in debugging, or even generate code based on user requirements.

IPFS

The InterPlanetary File System (IPFS) is a distributed file system. Instead of locating files based on where they are (an address), IPFS locates them based on what they are (a hash of the file’s content). This makes the web more resilient to failures, reduces redundancy, and can combat web censorship.

Ethereum, Uniswap, Metamask

These platforms bring about the decentralized web (or Web3). Ethereum is a smart contract platform, Uniswap is a decentralized exchange built on it, and Metamask is a crypto wallet and gateway. They enable decentralized finance, token economies, and new business models, including Decentralized Autonomous Organizations (DAOs).

Google Colab

A cloud-based platform that allows for collaborative AI and machine learning, democratizing access to powerful computational resources.

Open Publishing

Platforms like WordPress have democratized content publishing. Combined with IPFS, one could potentially have uncensorable content.

2. The Mobility and Immateriality

Traditional mobile apps are largely centralized, hosted on company servers, and distributed through app stores. With the shift towards the decentralized web, there’s a level of “immateriality” — apps and content aren’t bound to a central location or authority.

Comparison:

• Traditional Mobile Apps: Centralized, subject to platform rules, potential for censorship, often siloed data.
• New Decentralized Apps (DApps): Decentralized, resistant to censorship, transparent operations, shared and verifiable data.

3. Socioeconomic Applications

Company Based on Advanced Data Analysis

With the growth of AI, you can have real-time analytics, predictions, and automation, where business decisions, product recommendations, and even content creation are driven by AI.

DAO

Instead of a traditional corporate structure, you can have a DAO — an organization run by code and consensus mechanisms, where stakeholders vote on decisions.

Designing Currencies

You can tokenize assets or even ideas. For instance, artists can tokenize their art, ensuring they get paid for secondary sales.

Protecting IP

With platforms like Ethereum, IP can be tokenized. This means that the ownership, transfer, and royalties of IP can be tracked and managed on a transparent and immutable ledger.

4. User-Centered Supercomputing

Combining platforms like Google Colab, decentralized systems, and generative AI ecosystems gives users unprecedented power. They can harness the computational might previously reserved for large corporations.

5. Integration with Neurotechnology, Biometrics, and Biosensing

Enhanced User Experience

Integrating with biometrics can lead to user interfaces that adapt in real-time to users’ emotional and cognitive states, offering more personalized interactions.

Open Hardware Projects

OpenBCI is a project that offers open-source brain-computer interfaces. By integrating it with the aforementioned technologies, one could potentially build decentralized, AI-driven platforms that are controlled via brainwaves or other biosignals.

Health and Wellness

With biosensing, decentralized networks, and AI, it’s possible to have real-time health monitoring platforms that predict potential health issues and offer instant recommendations or alerts.

NEUROTECHNOLOGY AND THE FUTURE

The integration of biosensing, neurotechnology, brain-computer interfaces (BCIs), augmented reality (AR), and virtual reality (VR) with systems like decentralized computing, AI, and distributed data storage can potentially lead to a paradigm where technology understands and responds to human conditions and emotions more intimately than traditional professionals once ANI (Narrow AI) systems already advances to AGI (General AI).

Biosensing

Devices that measure physiological factors can collect real-time data on an individual’s health. When integrated with AI, this data can be analyzed to detect patterns and anomalies, potentially identifying health issues before they become apparent to the individual or even a doctor. Wearables and smartphones are already moving in this direction, tracking everything from heart rate to sleep patterns.

Neurotechnology and BCI

Neurotechnology and BCIs can capture brain activity, interpreting intentions, thoughts, or moods. When combined with AI and machine learning, these insights can enable systems to respond to cognitive and emotional states. For example, a BCI could detect the onset of stress and trigger a VR environment designed to calm the user down.

AR and VR

AR and VR can create immersive experiences that are responsive to both the physical environment and the user’s emotional state. These technologies can be used in therapeutic settings, education, or entertainment, providing experiences that are tailored to the individual’s needs and reactions.

Integration with Decentralized Systems

By merging these technologies with decentralized systems like blockchain and distributed storage, the following can be achieved:

1. Data Sovereignty: Users retain control over their sensitive health and biometric data, choosing how and with whom to share this information.
2. Security: Blockchain can ensure that the data remains secure and tamper-proof, which is crucial for maintaining privacy.
3. Customized Responses: AI can process the vast amounts of data generated by biosensors, BCIs, AR, and VR to provide personalized feedback, interventions, or recommendations. This could be more accurate than professionals who do not have continuous access to such detailed data.
4. Accessibility: Decentralized systems could allow for the democratization of access to these technologies, making personalized health and wellness care more widely available.

Practical Applications

• Health Monitoring: Continuous health monitoring through biosensors could give AI systems a detailed understanding of a person’s physical state, potentially noticing signs of illness that a doctor might miss during a routine check-up.
• Emotional Intelligence: BCIs could give systems the ability to read a user’s mood and emotional state, allowing for adaptive responses, such as changing a room’s lighting or temperature, selecting music, or even alerting the user to take a break or meditate.
• Therapeutic Environments: VR can be used to create therapeutic environments for mental health treatments, providing controlled, responsive settings where users can confront and work through issues with real-time AI support.
• Legal and Financial Advice: With the integration of expert systems powered by AI, users could receive personalized legal and financial advice based on a comprehensive understanding of their personal data, habits, and preferences.

CONCLUSION

The concept of immaterial computing, as it evolves with the emergence of Web4 and Web5 paradigms, aims to create a more symbiotic and emotionally responsive web. These paradigms envision a web that not only understands user needs and emotions through advanced technologies but also empowers users to have greater control over their digital identity, assets, and data.

Future systems may use biometric data or cryptographic keys as unique identifiers, eliminating the need for traditional passwords. This makes access to services both more secure and user-friendly. Web4 and Web5 propose the use of DIDs, which give users complete control over their identity and personal data without relying on central authorities.

Users can tap into open, free, decentralized and distributed computing resources, allowing them to access supercomputing power, while AI can optimize the use of these distributed resources, providing individuals with the necessary computing power for complex tasks like data analysis or content creation.

Users can design their digital currencies or tokens, which could be used within specific communities or ecosystems. These digital currencies can be governed by smart contracts on blockchain networks, automating transactions and ensuring the terms of agreements are met without intermediaries.

Data can be encrypted, tokenized as NFT and stored on decentralized networks like IPFS, making it resistant to censorship and central points of failure. Blockchain technology can ensure data integrity and traceability, providing a secure and transparent record of transactions and data exchanges.

In the immaterial computing paradigm, data and content created by users are considered valuable assets. Blockchain technology can help users securely monetize this content. And content that is relevant and valuable to a community can be more readily monetized, with the community’s engagement directly influencing the content’s value.

DAOs allow for the creation of community-driven digital enterprises that operate on democratic principles without centralized control. Communities can issue tokens to incentivize and reward contributions, creating an economy where the value is tied to participation and utility.

As immaterial computing evolves, integrating elements of Web4 and Web5, it has the potential to create tecno-socioeconomic networks that are not only responsive to our emotional and cognitive states but also empowers us as creators and consumers. In this envisioned future, our biometrics and cryptographic keys become passports to a digital reality where we have unprecedented control over our data, our digital assets, and the very nature of our online interactions. This paradigm shift towards a more personal and economically potent web has profound implications for privacy, security, and the structure of digital societies. It proposes a shift from being mere users of services to being sovereign individuals in control of our digital destinies.

Note on Thesis Creation Using the Immaterial Computing Paradigm

This thesis was compiled within a matter of hours, leveraging the very paradigm it discusses — immaterial computing. This accelerated workflow is a testament to the paradigm’s transformative potential and relevance in today’s digital landscape.

The immaterial computing paradigm enables instantaneous access to vast repositories of knowledge, allowing for swift research and data aggregation that would traditionally take days or weeks. Advanced AI tools, integral to the immaterial computing environment, can analyze and suggest content improvements, ensure the coherence of arguments, and even verify the integrity of data, all within a fraction of the conventional time required.

The relevance of this paradigm shines through its application in creating the thesis itself. It demonstrates not only the theoretical possibilities of immaterial computing but also its practical implications for academic research, content creation, and knowledge dissemination. By utilizing a computing paradigm that embodies the cutting-edge of decentralized, AI-enhanced, and user-centric technologies, the thesis serves as a living example of the power and efficiency of the systems it proposes. This meta-level application illustrates how immaterial computing can reshape not just the content of our work, but the very methods by which we create and share knowledge.