How AI is fueling self-custody’s emergence
When we think of self-custody in the context of crypto, we often think of wallets, where we're fully responsible for managing, securing and maintaining our digital assets without third-party platforms. But self-custody goes much deeper. It now influences the way we store and access our own data, and underpins new decentralized applications.
Take CocktailPeanut, for example, which created an open-source project called Dalai where you can run LLaMA and Alpaca on your computer (there's more on LLaMA and Alpaca below). By using open-source code, you're cutting out the middle person and not supplying any of your personal details.
Self-custody is a pillar of decentralization and all the benefits it promises, but what does it look like in practice beyond wallets? And, what role is AI playing in its emergence?
Self-custody is on the rise
Many entities see the benefit of giving their users an open-source platform and eliminating tedious, centralized processes that rely on third parties. As such, self-custody is an emerging concept that allows individuals to control their digital assets and personal data without intermediaries or centralized networks.
Self-custody is not just limited to the realms of digital assets and wallets. The concept can be applied across various AI applications and technology domains, such as data storage, communication, and software development. By embracing self-custody, individuals can regain control of their digital lives, ensuring their personal data remains private and secure.
The rise of self-custody represents a paradigm shift in how we approach technology, and its implications are far-reaching.
What role does AI play?
AI's role in accelerating the adoption of self-custody in its many forms will feel familiar.
Blockchain networks are, naturally, a foundation of self-custody platforms. AI is being used to protect these networks through advanced algorithms that can detect and prevent cyber attacks. Beyond security, AI is also being used to bring greater speed and efficiency to self-custody platforms, again through the algorithmic analysis of processes.
As self-custody has grown more sophisticated, so too has the role of AI within it. The technology is helping to smooth the onboarding process for users to tools that are steadily building self-sovereignty into society.
Let's take a look at a few examples of self-custody and AI in practice. 🤖👇
Umbrel
Umbrel is popular among users who run their own self-hosted Bitcoin and Lightning node, among other decentralized applications. Being open source, it allows users to inspect and verify the platform's code, which promotes transparency and helps build trust.
One tool on the Umbrel platform is chatbot-ui, which allows users to interact with their self-hosted node using natural language commands without requiring them to use a command-line interface or other technical tools. This makes it ideal for users new to self-hosting their own Bitcoin or Lightning node.
Here are some examples of how the AI-powered chatbot helps Umbrel users.
Checking the status of the Umbrel node: Users can ask the chatbot for information about the status of their Umbrel node, such as the amount of available disk space or the current Bitcoin and Lightning Network block height.
Installing new applications: Users can install new applications on their Umbrel node by asking the chatbot to install a specific app, such as the Sphinx Relay or ThunderHub.
Managing Lightning Network channels: Users can use the chatbot to manage their Lightning Network channels, such as opening or closing channels, or adjusting the fees associated with those channels.
Checking Bitcoin transaction status: Users can use the chatbot to check the status of their Bitcoin transactions, such as whether they've been confirmed on the Bitcoin network or are still pending.
GPT4All
Developers at Nomic AI, the world's first information cartography company, released GPT4All on GitHub — an open-source and self-hosted application of chatbots trained on large datasets, including code snippets, stories, and dialogues. The application is based on the GPT-3 language model and leverages its advanced natural language processing capabilities to generate human-like responses to user inputs.
GPT4All aims to provide developers with a flexible and customizable framework for building chatbots that can be trained on various datasets. As such, the possibilities across industries are endless. The project also includes a web-based chatbot application that allows users to interact with pre-trained models, demonstrating the project's capabilities.
Meta LLaMA AI
Meta has also hopped on the AI train with Meta LLaMA AI, designed to understand and generate natural language text. The model is based on the GPT-3 architecture and trained on a massive dataset.
One of the key features of Meta LLaMA AI is the ability to generate multiple languages and transfer knowledge across languages, which can help improve machine translation. The application can analyze and recognize the patterns and similarities across languages, which can help improve the accuracy of translations. Meanwhile, it's an ideal plug-in for a personal assistant or chatbot because it can generate more natural-sounding responses and improve the overall user experience.
Alpaca
Stable Diffusion is an AI that automatically generates an image according to the prompts. To use Stable Diffusion in Photoshop, graphic designers and photographers can use the Alpaca plug-in. When the designer gives a prompt, for example, a "horse in a field," the Alpaca application will generate a high-quality image of a horse as if a human drew it.
The AI algorithms used in Alpaca are trained on a vast dataset of professional-grade images, which enables the plug-in to recognize the patterns and characteristics that define high-quality photography. Alpaca allows designers to explore text-to-image generation, image-to-image variations, outpainting, upscaling, and depth map creation, all within Photoshop.
The plug-in provides users with an intuitive interface that allows them to fine-tune the AI-generated results to match their creative vision with the prompts given by the designer.
The final word
AI has reached mainstream consciousness, and self-custody could soon follow in its footsteps as decentralization continues to influence society in new ways. Conveniently, AI could be a powerful catalyst for self-custody's emergence, accelerating its adoption through greater security, trust, and functionality.
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