AI Trader, what is It? Discover the goals and characteristics of this ecosystem as well as direct access to its website.
AI Trader was built with a strong design philosophy built on five main pillars: Simplicity, Pragmatism, Sustainability and Intelligent AI Trading.
One of the fields impacted by the DeFi is trading, decentralization offers many advantages, we already talked about it in the article dedicated to this decentralized trading platform, here is a new project related to trading and which this time also integrates AI.
AI trader, Design Philosophy
AI Trader was built with a strong design philosophy built on five main pillars: Simplicity, Pragmatism, Sustainability and Intelligent AI Trading.
Simplicity
This project aims to keep the feature set it offers as simple as possible. Ideally, this ecosystem should contain the minimum number of moving parts required for a secure, scalable and flexible system. This simplicity gives AI Trader’s design a number of significant advantages over other, more complex structures.
This platform prefers to use existing battle-tested Ethereum code and BSC code wherever possible. The clearest example of this philosophy in practice is the choice to use AITRADER as the client software for AI Trader. When dealing with critical infrastructure, simplicity is also security.
Every line of code we write is an opportunity to introduce unintentional bugs. A clean and minimal code base is also easier for external contributors and auditors to access. All of these help to maximize the security and correctness of the AI Trader protocol.
This will only become more apparent as the protocol solidifies and existing resources can be redirected to core Ethereum infrastructure.
Pragmatism
AI Trader’s design philosophy puts the needs of users and developers above theoretical perfection. This ecosystem was also founded on the understanding that any core team would have limited areas of expertise.
This project is developed iteratively and strives to continuously gain user feedback. Many of today’s core AI Trader features, such as EVM equivalence (opens new window), were only possible through this iterative approach to protocol development.
Sustainability
AI Trader has been involved for a long time. Application developers need to ensure that the platforms they are building can not only keep running, but remain competitive in the long run.
AI Trader’s design process was built around the idea of long-term sustainability, rather than taking shortcuts for scalability. At the end of the day, a scalable system is meaningless without the ecosystem that supports it.
The more complex the codebase, the harder it is for people outside the core development team to actively contribute to it. By keeping our codebase simple, we are able to build a larger community of contributors who can help maintain the protocol over the long term.
AI Trader has more advantages
Although AI Trader appears to be an independent blockchain, it is ultimately designed as an artificial intelligence transaction, and all transaction scenarios will be applicable to AI Trader.
Automation: this platform can automate workflows and processes, or work independently of human teams. For example, artificial intelligence can help automate various aspects of information security by continuously monitoring and analyzing network traffic; quickly avoid risks through data analysis and market trend data, and make automatic decisions thousands of times faster than humans.
Reduce human error: AI Trader can eliminate human error in data processing, analysis, making decision recommendations, and other tasks through optimal automation of functions and algorithms.
Fast and accurate: Compared with humans, this ecosystem can process more information faster, so as to find patterns and discover data relationships that humans may miss. For example, when trading opportunities arise, AI Trader can buy and sell 10,000 times faster than humans. Data will be easily captured and used in AI Trader.
Unlimited availability: this platform is not limited by time of day, rest needs, or other human burdens. When running in the cloud, AI Trader and machine learning can be « always on », so that the assigned tasks can be continuously processed, and the benefits of decision-making can be obtained at any time, this ecosystem is the first.