Justine Moore spent 6 months doing an experiment, communicating with ChatGPT every day, constantly sharing personal thoughts and emotions, trying to create an "AI brain" that truly understands herself. As a result, the ability of AI completely exceeded expectations. She listed the following scenarios:
1. Communicate with others: By using a large language model (LLM), we can help us convey complex ideas more clearly and greatly improve communication skills.
I am using this myself. At present, the strongest ability of AI that I use is, I think, the ability to summarize and communicate. If your ability to summarize is relatively lacking, especially when you need to explain a thing or a project to others, using AI to learn summary and communication skills is really powerful.
2. Self-understanding: AI brains can "psychologically analyze" you well, helping you to more clearly understand your strengths and weaknesses and correct cognitive biases.
3. Interaction with applications: AI brains can be brought into other applications to unlock truly personalized experiences, such as a writing assistant that fully understands your style, or work or social tools tailored for you.
So, what are the key factors in building an AI brain of your own?
1. Integrity and quality of user data
For the AI brain to truly understand you, you first need a large amount of high-quality personal data. This includes your historical conversations, behavioral records, emotional tendencies, preferences, and decisions. The richer and more complete the data, the more perfectly the AI brain can capture your thinking patterns and personality.
2. Privacy and security of data
The privacy protection of personal data is crucial because it has learned a lot of your living habits, personality preferences, and even weaknesses and defects. When building an "AI brain", users need to have full control over the data to ensure that the data will not be abused or leaked. After all, it is best not to let others invade your AI brain.
3. Transparent model training and data usage mechanism
For an AI brain that truly understands itself, transparency is the key. Users should know how their data is used and how AI models are trained, which can also be understood as a kind of security.
Solution: decentralized architecture and data ownership?
In Justine's philosophy, and based on the above 3 points, the AI brain should be completely in the hands of users to avoid the monopoly and use of data by big technology companies.
Therefore, a decentralized architecture may become a channel that can ensure that users maintain control and interest in their contributions throughout the life cycle of data and AI models by making them the actual owners of data and AI models.
Vana DataDAO Solution
The core concept of this solution is - giving users full sovereignty over their data, which is basically in line with the concept of "AI brain".
Vana introduces the concept of "non-custodial data" to ensure that data is only used for user-authorized operations. Users always have control over their own data and it will not be hosted by the platform or a third party.
The way to achieve this is that the data will be encrypted before contributing to the server. Each user encrypts his or her own data with the server's public key to ensure that even when the data is transmitted to a collective server or used for AI training, the data itself remains confidential, and only participants with the decryption key can decrypt and access the data.
This not only solves the data sovereignty and privacy of users, but also lays the foundation for data quality, which is also very important, because privacy is guaranteed, users can provide real data without worries, and cooperate with the Proof-of-Contribution mechanism of the Vana blockchain, adding the token incentive model that has been deeply rooted in Crypto, which can make users more motivated to provide high-quality data.
In general, Vana DataDAO mainly solves the problem of data sovereignty, of course including data privacy and security. In fact, it is not difficult to train an AI assistant. Many APIs for training language models can provide such an environment, but will our needs in the future only be satisfied with an "assistant"? AI is like a Pandora's box. The magic released after opening it may be more and more difficult to refuse. If human needs rise to the level of AI brain and AI super brain, the issue of data sovereignty is inevitable.
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