BingX is a number one cryptocurrency exchange, serving over 10 million users worldwide. We got to talk with BingX CPO Vivien Lin about how AI and blockchain are changing the way in which people trade online.
Blockchain is so far more than the technology that underpins cryptocurrencies. Vivien Lin explains how smart contracts and the decentralized nature of blockchain complement the analytical capability of AI.
(Q): How can AI complement cryptocurrencies and the way is it changing the way in which persons are trading it?
(Vivien Lin): “I believe there are three different concepts. Cryptocurrency, blockchain technology, and AI technology, right? Cryptocurrency is more of a certificate. It’s something you hold because you wish to spend money on the worth of the project.
You consider the worth of the project goes to rise and you may profit from that. But AI and blockchain are only technologies.
If you’re trading a stock you need to use AI to do what it is sweet at, which is to research data, to collect together information, like the value, the macro economies, micro-economies, every little thing, like data processing and it helps you see the trend of the market and to do the valuation, etc.
When we’re talking about trading, I believe there’s not much difference. The only difference is you’re trading a stock versus you’re trading a cryptocurrency.
Six or seven years ago, people trading in stocks or Forex, already deployed machine learning models to predict the trend and to make quantitative strategies.
But now the methodology has obviously leveled up with AI, since the AI or the massive language models we at the moment are talking about, they’ve a much greater computation power.
So it’s more efficient for us or for the trader who trades cryptocurrency or whatever asset to make use of a big language model or the newest AI model to make the prediction or to make use of them to auto-adjust the weights of the factor.
So that is how AI is implemented in investment and likewise cryptocurrency investment. One application is in, for instance, stock trading or Forex trading. Much of the trading data is public. It’s centralized, but you discover it’s very easy to get the information because every exchange publishes the trading volume, etc.
But in crypto, a few of the transactions occur in a centralized exchange like ours. Then we’ll publish the quantity or the value data. But rather a lot more transactions occur in a decentralized place.
So you’ve got to have a tool to trace all that data. And sometimes if there may be a transaction across different blockchains or mainnet, you’ll find that for a human, it’s actually quite difficult for average people to trace all this data. So if we are able to use AI technology, then the information tracking and data evaluation can be much easier.
This is one in every of the implementations. And after all, as we operate our exchange, then we are able to use AI technology in the safety space to detect suspicious activities, like within the anti-money laundry evaluation, those sorts of tasks are currently where AI was used.”
(Q): There’s a giant concern about fraud in the case of crypto trading and security measures. How is AI being integrated into these exchanges to make sure those security measures?
(Vivien Lin): “Actually, I even have to say this implementation is sort of on early stage. Because if we’re talking about anti-money laundry or anti-cyber attacks, these are quite mature technologies. Some of them already integrate AI, and a few a part of them haven’t yet, but it surely’s quite mature technology.
Somewhere I believe is more promising is to make use of AI technology to detect fraud, especially trading fraud.
In traditional finance, since it’s highly regulated, you simply have two stock exchanges within the US and one stock exchange within the UK. So those centralized exchanges are strictly regulated by the regulator.
It’s difficult for anyone trading on those exchanges to make a mistake or commit fraud. But in the event you’re taking a look at crypto, there are greater than 200 centralized exchanges and I believe over 1,000 decentralized exchanges.
So it’s almost inconceivable at this moment for any regulator to control the entire exchanges.
So whether or not they can function properly largely relies on two things. One is how those decentralized exchanges or centralized exchanges regulate themselves. If they’ve arrange a better moral standard or higher ethical standard is one thing.
Another thing is to depend on their ability to detect fraudulent transactions. This could vary rather a lot. I might say in the event you’re taking a look at the highest 20 centralized exchanges, I believe they’re ethically excellent.
They don’t really intend to make mistakes or they need to be sure that their business can last ceaselessly. But the thing is, have they got the vital technology or vital knowledge to support them in making the business last ceaselessly?
So before an organization deploys AI technology it is extremely reliant on the chance manager, if his or her knowledge is sufficient to write down down all those cases, how people commit fraud or benefit from the flaw of the trading rules within the exchange.
But once the industry deploys more AI or more well-trained models, then even when the one who is answerable for risk management has a flaw of their methodology or flaw within the mechanism, AI will use the huge data to assist us refine the design of the system.
So I believe that is where AI is most helpful in emerging industries like crypto trading, where everybody is trying to achieve more experience throughout the process. Sometimes people make mistakes. AI technology helps people reduce the prospect of constructing mistakes.”
(Q): How is AI changing using trading bots and duplicate trading systems? How is that changing the way in which that users at the moment are shifting away from traditional methods of trading?
(Vivien Lin): “If we’re taking a look at where the industry is at this moment, actually in the event you’re taking a look at the trading bots, they’re quite easy. Just an important bot, right? But there are a couple of more advanced communities who’ve more experienced traders that want to start out to implement AI-driven strategies.
It’s almost inconceivable for those crypto native traders to have the extent of experience and the extent of understanding of the traders in the standard financial markets. So in the event you ask them to collect those greater than 1,000 aspects (indicators), it’s inconceivable for them.
But now they use AI to screen those aspects to auto-adjust the weights of the aspects the technology empowers that group of individuals to find a way to make a technique that is sort of on par with those that come from the skilled trading space.
Another thing is copy trading. In the past, a duplicate trader or master trader, they’re human. So humans make mistakes, right?
When you make a profit, you’re reluctant to take profit. You at all times think that the value of the token could possibly be higher and better, right? But in the event you’re making a loss, you wish to stay there. You don’t need to act on a stop loss.
So there’s at all times bias or human flaw in investment. But now with an AI strategy, it’s grow to be easier for them to make a take profit or a stop loss decision. Or sometimes they should not aware, but their model tells them, it’s time to act in your stop loss or it’s time to take profit.
I might say they use AI tools to help them to research the market and to make a framework for them in order that they’ve more confidence to follow the framework because they think, okay, perhaps this can be a summary of all those traders on the web. So they’ve lower psychological hurdle to implement the foundations strictly.”
(Q) What role is AI playing in helping traders refine their trading strategies when the consider market indicators or aspects?
(Vivien Lin): “I believe it’s nearly market prediction. In the past, in the event you weren’t an expert trader otherwise you begin to form your personal trading philosophy but not there yet, at the moment, you might be taking a look at tens, or a dozen, or several dozen aspects and also you begin to feel that it’s hard to follow, right?
Because a few of the aspects let you know to purchase and a few of the aspects let you know to sell.
You don’t know the right way to read or the right way to translate all those aspects. And now I believe one of the best area for AI to step into the choice is it would enable you to screen out those aspects or those indicators that should not suitable in current market.”
(Q): With data management, how does AI help to categorize and analyze this massive amount of knowledge?
(Vivien Lin): “Data management for me has two layers. One is how people like traders use AI to administer the information. It just boils right down to what AI is best at, to summarize data and make the trend prediction and to screen out layers, those type of things.
Another layer of the information management is in blockchain or in cryptocurrency. If we’re talking about blockchain technology as a substitute of trading cryptocurrency, then a few of the most promising sectors are corresponding to DePIN.
DePIN is like decentralized data management. One of the DePIN sectors is a decentralized data management system. It’s like a protocol which is able to sign the agreement with individual participants.
It could possibly be an organization or could possibly be a person. The protocol or the agreement is to ask you to contribute a part of your computing power of your PC. To contribute a part of computing power to the system when the blockchain technology is proposing blocks and achieving consensus.
This process consumes lots of computing power. So in decentralized data storage or decentralized computing system, it’s at all times been crucial that the protocol can resolve which nodes can be included in current consensus proposing.
This involves a dynamic decision about which nodes to allocate this task to this time. So that is where AI may also help.
AI keeps tracking all that data. Keep tracking, keep predicting, and keep summarizing data. So ideally, AI needs to be very able to measuring the efficiency of every node.
For example, if I even have a consensus task, then what are the nodes I should allocate to? I believe this sort of decision is what AI is absolutely good at.
I believe for all those decentralized processes on the consensus layer and the information management layer, data storage layer, AI may also help in making the choice.”
(Q): How does this decentralized nature of blockchain complement the analytical capability of AI?
(Vivien Lin): “I’ll provide you with an example. One of the trending sectors within the blockchain side or technology side is known as zero knowledge proof.
This ZK technology is sort of a leading edge approach to reinforce trust and privacy in various industries. Actually, so far as I do know, this technology has been implemented in national security. In lots of those very confidential and necessary nationalized projects.
But it’s also implemented in normal life cases corresponding to investment or asset management verification.
For example, if an asset manager claims to stick to a selected investment strategy. If you spend money on a quantitative fund or a hedge fund, their manager at all times tells you, ‘I spend money on this sector and never that sector. I’ll allocate my assets not more than 5% in each stock.’
But actually, when their strategy becomes more complicated, it’s very hard for people to trace or to confirm in the event that they really persist with the strategy that they claim to.
Using AI-enhanced ZK proof is a way that allows an investor to confirm that their manager adheres to the strategy they claim without really revealing the strategy’s confidential details.
For example, in the event that they trained a quantitative model, right? Basically, they can not reveal how they put the weights and the way they mechanically adjust the weights.
Especially if the strategy itself can also be designed by certain AI model, there isn’t any likelihood that they may reveal all the main points.
But how can we confirm that they adhere to what they claim? Now we are able to use ZK knowledge and particularly AI-enhanced ZK knowledge.
I believe this sort of application or this sort of use case is somewhere where blockchain technology will be utilized in a large spectrum of cases.”
(Q): How is modular blockchain getting used with AI to reinforce the scalability and efficiency of the way in which these transactions occur?
(Vivien Lin): “Modular blockchain technology was just as I described, you separate the computing power, separate the space for storing, make them decentralized.
This is the best strategy to understand modular technology. And AI algorithm can manage and optimize the sharding process in modular blockchains.
So sharding splits the blockchain into smaller or more manageable pieces. So each module can process in transaction independently. So AI may also help dynamically adjust how transactions are allocated.
And AI can even predict the transaction volume and adjust the system dynamically. For example, in the event you anticipate now could be a high load period an AI system can scale, can proactively scale resources or reallocate transactions across different modules to keep up the performance without the Mainnet really blocking.
So that is something that AI plus modular technology can enhance the general speed of transaction in blockchain transactions. And also AI can assist the optimization of the execution of smart contracts.
This remains to be in an experimental phase, I might say. As far as I do know, not many smart contracts really use AI to predict the trail or outcomes based on the historical data. But this is unquestionably something I do know many individuals need to do.”
(Q): You mentioned a few of the solutions are very experimental in the meanwhile. If you look towards the long run, what potential developments do you see in the combination of AI and blockchain that’s going to vary the trading landscape?
(Vivien Lin): “I believe, one thing is trustless AI service. Blockchain can enhance trust within the AI decision-making process by making it transparent and verifiable.
And smart contracts could possibly be used to validate AI decisions before any transaction or trade is executed. This is, I believe, how smart contracts or how decentralized solutions meet AI technology.
We’re at all times talking about how AI could aid blockchain, but here is how smart contracts or blockchain technology can aid AI decisions.
This is one thing. And one other is cross-chain evaluation. AI could manage and analyze data across multiple chain platforms.
Not many individuals have the required knowledge or required skill to access the information on the chain. Because different mainnet can have different coding language. So AI may also help people to with only one click to get all that information from different mainnet.
And second is when you get all those data, the right way to analyze that. This is how we’re attempting to use AI to detect fraud as well. If we depend on humans to do this, then that’s almost inconceivable, especially with current cyber attacks, the hack technology also improved.
Now it’s almost inconceivable for human to do this. So I believe AI could definitely aid on that space.”
Blockchain and AI are increasingly getting used as complementary technologies to vary how we transact, interact online, and do business.
You can learn more about how modern tools and features are making trading crypto easier by contacting Vivien Lin or heading over to the BingX trading platform.
