Smart Contracts Just Got Smarter – Thanks, AI Overlords!

Artificial Intelligence has brought the vision with it for building self-sovereignty through blockchain to give people control over their assets, data, and governance power. This concept extends beyond just financial assets to include important aspects of personal data and their worldview.

Self-sovereignty is crucial, especially in countries with unstable economic conditions, where bank failures and hyperinflation are common experiences. A prominent figure within the blockchain sector, Eric Vorhees points out an irresistible reason for combining AI with blockchain – to prevent the centralization of intelligence. Today we’re taking a look at how AI can help us use and secure smart contracts.

AI in Smart Contracts

When it comes to the achievement of decentralization within blockchain technology, smart contracts are a vital element as they eliminate intermediaries. Their integration with AI makes them not only upgradable but also self-reliant.

Also, smart contracts often have limited storage to reduce transaction fees, but AI models could help. This is where data feeds or ‘oracles’ become vital. Oracles are crucial for smart contracts to interact with external data without congesting the network. An AI model can serve as an oracle, providing smart contracts with real-time data and decision-making abilities.

AI can also be used for identity-based biometric methods such as face and fingerprint recognition, automated trading through bots, lending based on credit scores, and evaluating the price of assets.

AI Providing Solutions in Smart Contract Security

Smart contracts have been host to several security vulnerabilities like reentrancy, over/underflow, and frontrunning. Events like these suggest that security is essential and measures need to be employed.

One way to achieve this is through the integration of AI techniques and machine learning (ML). These advanced techniques stand in a better position when compared with simple processes, which are more rigid and based on programmed rules.

Machine learning excels in identifying patterns in data, making it valuable in analyzing large quantities of smart contracts. It is much more efficient and can recognize patterns that may be undetectable to humans.

AI techniques like audit bots can help identify potential issues in smart contracts more efficiently compared to manual processes. In any case, you could create your own smart contract audit bot with transformer-based models like GPT-3, let’s have a look.

Beware of Using AI to Code

Creating a Smart Contract Audit Bot with GPT

Creating a smart contract audit bot with GPT-3 involves feeding the collected data into the AI model. By instructing GPT-3 to act as a smart contract audit bot, it can learn from the provided data. This includes both the vulnerabilities and the parts of the code where they are present. This process is twofold:

• Stage One: Input the initial labeled data from the created collection into the GPT model.
• Stage Two: Combine all available audit reports into the model to enhance its learning. This helps the AI understand the vulnerabilities present in various contracts and how they were previously addressed.

Key Parameters for Evaluating AI-Based Audit Bots

When evaluating AI-based audit bots, there are three main parameters to consider:

• Vulnerability Detection: This is the bot’s ability to accurately detect vulnerabilities in the smart contract code.
• Code Parsing Capability: This entails evaluating how effectively the bot can understand and interpret the code.
• POC Writing Ability: The bot’s skills in creating proof-of-concept (POC) codes that demonstrate how vulnerabilities can be exploited.

All of these techniques can help coders but can never substitute them, for now that is.

AI in Governance

Crypto-enabled AI also plays a crucial role in governance by improving government services or governance in general. Think at the ‘autonomous’ section of the Decentralized Autonomous Dao branche.

A technology that could perhaps simplify the decision-making process and enhance participation in governance through the collective arrangement of prompts. A report from the World Bank shows that by utilizing AI, governments tend to achieve better citizen engagement, interoperability, and accountability.

Is No-Code the Future?

The no-code movement is gaining traction, but it’s not fully realized yet. While no-code tools offer the promise of tech creation without coding knowledge, it currently can’t do everything, yet.

However, as AI and other technologies evolve, there is a strong possibility that no-code solutions will become more advanced and extensive. This leaves us with a question- will it ever replace developers?

A Future Without Developers

The current trends suggest that we are moving towards a world where everyone can be a creator or developer. However the complete elimination of developers still has a long way to go.

Tools that enable people to create top-down without bottom-up knowledge are becoming more accessible. But the expertise required to execute an idea, and ensure its ongoing operation, security, and scalability, is still crucial.

Perhaps over time, these tasks may become automated, but for now, they remain still in the hands of humans as we are not completely substituted by robots.

The Role of Speculation and Greed

The crypto AI space is not immune to speculation and the lure of quick profits. Projects often gain attention based on the reputation of their supporters rather than the strength of their technology or actual usage.

In a situation like this, projects with high valuations and market capitalization lack a significant user base or practical application. This shifts the focus on speculation and short-term gains rather than on developing a long-term sustainable value. Which is not what we want for the next chapter of the internet.

That being said, you can always speculate or learn more with our expertly curated AI coin selections for this quarter and be ahead of the curve.

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