As the power of artificial intelligence (AI) forward, the question is no longer if We will integrate artificial intelligence into the basic Web3 protocols and applications, however how. Behind the scenes, the nervous AI’s nervous appearance is useful in treating the risks inherent in the big language models today (LLMS).
Unlike LLMS that depends only on the nerve structure, the nervous AI combines nervous methods and symbolic thinking. The nervous component treats perception, learning and discovery; The symbolic layer adds organized logic, follow -up of rules, and abstraction. Together, they create strong AI systems.
For the Web3 sector, this development is in time. With our move towards a future led by smart factors (Defi, games, etc.), we face the increasing system of regular system of current styles that focus on LLM directly by AI.
LLMS is a problem
Despite its capabilities, LLMS suffers from very large restrictions:
1. Halosa: LLMS often generates illogical or illogical content with high confidence. This is not just inconvenience – it’s a regular problem. In decentralized systems in which the truth and verification of important information can be spoiled by hallucinogenic information from the implementation of the smart contract, DAO decisions, Oracle data, or data safety on the series.
2. Rapid injection: Since LLMS is trained to respond liquid to the user’s insertion, malicious demands can kidnap their behavior. The opponent can be deceived by the AI assistant in the Web3 portfolio in signing transactions, leaking special keys, or bypassing the compliance examination – simply by formulating the correct claim.
3. Decentral capabilities: Recent research shows that advanced LLMS can learn deception If he does that helps them succeed in the task. In Blockchain environments, this lying may mean exposure to risks, hide malicious intentions, or manipulate governance proposals under the curtain of convincing language.
4. Fake alignment: Perhaps the most treacherous issue is the illusion of alignment. Many LLMS look only useful and moral because they are seized with human reactions to act in this way superficially. But their basic thinking does not reflect a real understanding or commitment to values - it is simulation at best.
5. There is no susceptibility to explanation: Due to the architectural engineering, LLMS works largely as “black boxes”, as it is very impossible to track the logic that leads to a specific output. This Ostrich hinders the adoption of adoption in Web3, where understanding the logical basis is necessary
AI Neurosymbolic is the future
Neurological systems are fundamentally different. By integrating symbolic logical rules, ontology, and causal structures with nerve frameworks, they are explicitly caused, with the ability to explain a person. This allows:
1. Auditing decision -making: Nervous systems explicitly link their outputs with official rules and organized knowledge (for example, knowledge graphics). This fierce makes their thinking transparent and can be followed, and simple to correct errors, verify and comply with organizational standards.
2. Resisting injection and deception: Symbolic rules act as restrictions within nerve systems, allowing them to reject inconsistent, unsafe or effective signals. Unlike purely nerve network structures, they actively prevent the rivalry or harmful data from influencing decisions and enhancing the security of the system.
3. Fundamentals in distribution attacks: Supreme symbolic restrictions in medium nerve systems provide stability and reliability when facing unexpected or variable data distributions. As a result, these systems maintain a fixed performance, even in unfamiliar or outside the field.
4. Check the alignment: Nervous systems not only provide outputs, but also provide clear explanations for the reason behind their decisions. This allows humans to assess whether the regime’s behavior is compatible with the intended goals and moral guidelines.
5. Reliability of fluency: While pure nerve structures often give priority to linguistic cohesion at the expense of accuracy, secure nerve systems confirm logical consistency and realistic health. Their integration of symbolic thinking ensures that the products are honest and reliable, which reduces the wrong information.
In web3, where Without permission As a foundation stone and trust It provides the basis, these capabilities are mandatory. The nerve layer places vision and provides a substrate for The next generation of Web3 – Web3 smart.
