Ethereum is one of the most innovative blockchain solutions on the market, and more and more businesses are leveraging it to gain cost-effectiveness and scalability benefits. Brands like Mastercard and Visa are approaching Ethereum and Solana blockchains to make user payments faster and more efficient, albeit in a centralized ecosystem.
Still, this is just the beginning of a long-term development phase that introduces and embraces decentralization to increase business transparency, improve decision-making skills, and increase autonomy. The rise in ETH prices also contributed to the widespread adoption of blockchain, as its value grows steadily over time, increasing customer trust.
However, Ethereum has not yet been widely used in networks around the world due to several challenges such as security and efficiency. One of the many solutions to these problems is the use of artificial intelligence. Here's how it helps.
AI can identify vulnerabilities better than any other tool
Ethereum is fairly efficient at keeping users and their finances safe, but the problem is its smart contracts. These technologies provide a fast and automated way to complete a contract once both parties agree to a set of predetermined rules. Therefore, they treat the world based on algorithms and written code.
Across these smart contracts, developers eventually discovered numerous vulnerabilities. For example, smart contracts depend on the data sources used, which are not necessarily reliable. Therefore, it is possible to interact with a compromised price feed. Another common vulnerability in Ethereum occurs when multiple function calls occur at the same time, impeding the efficiency of the code to execute them all in sequence. This phenomenon is called reentrancy and can expose your network to numerous hacks.
Artificial intelligence can identify these invisible vulnerabilities without much effort, especially since one of its most interesting use cases is automated vulnerability scanning. This technology uses patterns to detect any problems in the network and uses machine learning algorithms to analyze large amounts of data.
AI can generate smart contract code to improve security
In addition to the security gained from better vulnerability analysis, smart contract code generation can be a potentially useful use case for ensuring higher levels of network security. Given that humans develop smart contracts, smart contracts are not perfect, leaving room for cracks in the code. Developing a smart contract means planning your project and working with your team to choose important elements such as hosting provider and appropriate blockchain type.
However, developers can harness the power of AI to generate smart contract code. This is an easier way to comply with security standards and requirements. Generative models can create these codes by learning from poor code samples or by focusing attention on good examples.
Machine learning allows AI to learn from developers' mistakes and best examples of how to write smart contracts. Therefore, it is possible to generate the correct code that meets the specific requirements of various blockchains, including Ethereum, which is one of the most developed and expanded on the market.
AI can reduce Ethereum investment risk
Investing in Ethereum is not that different from other cryptocurrencies. After all, by their very nature, prices are volatile, and their prices are influenced by industry performance and investor sentiment. At the same time, Ethereum has a number of competitors, including Cardano, Solana, and Polygon. That makes it a risky investment if its popularity lags behind these blockchains.
Therefore, when investing in Ethereum, users should always take additional precautions, such as adopting certain strategies and staying up to date with the latest crypto news. However, this could change as AI is introduced as a way to evaluate cryptocurrency models by analyzing trading records, social media data, and market performance information through machine learning algorithms.
Such valuation models can efficiently predict the potential risks of cryptocurrencies, allowing investors to better avoid the risk of losing their investments. AI-based models have the potential to establish a healthier and more secure crypto environment in case digital decentralized assets become legal tender around the world.
At this time, investors can adopt several methods to reduce risks and vulnerabilities, including:
We conduct research on all crypto projects to ensure you get safe and productive assets. Diversify your portfolio and evenly spread your potential risks as well as your income. Set realistic goals for your risk tolerance. In other words, know your limits. Avoid emotional decision making. Emotional decision-making often leads to FOMO (fear of missing out).
However, AI integration is not that simple
Artificial intelligence is not a new subject, but it has only recently become more accessible to the general public. At the same time, companies will be able to better deploy it as a tool to analyze data and perform their most time-consuming tasks, which is a major step toward modernization.
However, centralized systems already present many challenges. As a result, some worry that control will be more difficult in a decentralized environment. First, for AI to be truly efficient, developers need to deploy large amounts of data, a significant portion of which may be irrelevant or biased. Therefore, for AI models to be accurate, the community needs access to trusted datasets.
However, AI and cybersecurity remain under scrutiny after experts noticed that AI tends to use sensitive data without being able to filter whether it is ethical. Additionally, a lack of transparency in AI can lead to inaccurate results or injected results.
Finally, AI algorithms are currently quite complex to break down, so we still need time to learn about them and better control them in ways that benefit users. AI is not as easily approachable, which can lead to issues with transparency and interpretability.
What do you think about using AI on Ethereum?
Ethereum is one of the most developed blockchains on the market, leading to partnerships with centralized companies such as Visa and Mastercard. Its capabilities include smart contracts, DAOs, and Daps, but developers can always get creative and design new tools and applications to contribute to the ecosystem. The use of AI will further enhance blockchain capabilities and solve problems by predicting risks and analyzing potential investment strategies.
