人工智能（AI）和加密貨幣代表了我們這個(gè)時(shí)代最具顛覆性的兩項(xiàng)技術(shù)。

一種是讓個(gè)人自己做他們需要金融機(jī)構(gòu)做的事情；

另一個(gè)讓機(jī)器做他們需要人類做的事情。

隨著人工智能繼續(xù)影響全球各行各業(yè)，它也進(jìn)軍加密貨幣領(lǐng)域，誕生了一種集成人工智能技術(shù)的新型貨幣。

與人工智能相關(guān)的加密貨幣旨在將人工智能的能力帶入數(shù)字貨幣和區(qū)塊鏈網(wǎng)絡(luò)。

但人工智能加密貨幣到底是什么？它們是如何運(yùn)作的？

AI加密貨幣使用人工智能進(jìn)行操作，承諾改善風(fēng)險(xiǎn)管理、無情緒決策和不間斷交易。

然而，它們通常容易受到安全漏洞、技術(shù)故障和價(jià)格波動(dòng)的影響——就像其他加密貨幣一樣。

AI幣是利用人工智能技術(shù)進(jìn)行運(yùn)營的代幣——從為人工智能研究人員建立平臺(tái)到使用人工智能交易加密貨幣并做出市場預(yù)測。

本文概述了人工智能加密貨幣、它們的功能、排名前五的人工智能加密項(xiàng)目以及與這些資產(chǎn)相關(guān)的收益和風(fēng)險(xiǎn)。

什么是人工智能？

人工智能是指能夠執(zhí)行通常需要人類智能的任務(wù)的計(jì)算機(jī)系統(tǒng)和機(jī)器。

這包括視覺感知、語音識(shí)別、決策、語言翻譯等等。

人工智能旨在創(chuàng)造能夠以類似于人類思維的方式運(yùn)行、反應(yīng)和學(xué)習(xí)的智能機(jī)器。

然而，人工智能在準(zhǔn)確建模金融市場等極其復(fù)雜的系統(tǒng)方面仍然存在局限性。

人工智能加密系統(tǒng)中仍然存在偏見、錯(cuò)誤和不可預(yù)見的差距的風(fēng)險(xiǎn)。

隨著技術(shù)的不斷進(jìn)步，可能需要進(jìn)一步的創(chuàng)新和監(jiān)督，以充分發(fā)揮人工智能在加密領(lǐng)域的潛力。

什么是人工智能加密貨幣？

人工智能加密貨幣是指利用人工智能技術(shù)進(jìn)行操作的加密貨幣和代幣。

根據(jù)項(xiàng)目的目標(biāo)，集成可以通過多種方式進(jìn)行。

一些人工智能加密貨幣專注于為人工智能計(jì)算平臺(tái)和機(jī)器學(xué)習(xí)模型提供動(dòng)力，而另一些則強(qiáng)調(diào)支持去中心化的人工智能市場。

然而，最常見的應(yīng)用是利用人工智能/機(jī)器學(xué)習(xí)進(jìn)行自動(dòng)化加密貨幣交易策略，其中人工智能用于預(yù)測加密貨幣波動(dòng)。

例如，人工智能加密基金可能會(huì)創(chuàng)建一種代幣，允許持有者分享其自動(dòng)量化交易算法性能的利潤。

代幣經(jīng)濟(jì)將通過智能合約將基金回報(bào)的一定比例分配給代幣持有者。

In another example, an AI crypto project building a decentralized supercomputing network for machine learning models may reward participants contributing computing resources with native tokens. Users would pay the same tokens to access the network’s processing power for running their models.

The token integrates within the ecosystem to enable value exchange between network participants. These examples highlight that the mechanisms for deriving and accruing value vary across AI crypto coins based on the offering. But artificial intelligence capabilities provide the common thread.

Best AI cryptos making waves

The crypto industry has witnessed multiple high-profile AI crypto launches. Many focused on finance and trading. Below is a list of some of the best artificial intelligence crypto projects in terms of valuations.

Fetch.AI (FET). ThisEthereum-based token powers an open machine-learning network for building AI solutions. Fetch.AI provides the infrastructure for creating intelligent autonomous software agents and running them securely and scalably. Despite declines from its peak, FET retains a market cap of over $760.5 million per CoinGecko.

SingularityNET (AGIX). With a market cap of around $415.9 million, AGIX is the native token of SingularityNET, a decentralized AI services marketplace. Participants can buy and sell various AI algorithms and services using AGIX.

Numeraire (NMR). NMR is the utility token powering the Numerai platform focused on AI for quantitative hedge fund modeling and data science competitions. NMR has a market cap of nearly $104.6 million.

Matrix AI Network (MAN). MAN is the native token for Matrix AI Network, an open-source blockchain project focused on AI capabilities. The network enables miners to run AI applications in a decentralized manner. MAN has a relatively modest market cap compared to others on this list, netting $9.7 million.

DeepBrain Chain (DBC). DBC is the native token behind DeepBrain Chain, a distributed computing network for lower-cost AI processing and machine learning. Despite immense hype earlier on, DBC has a market cap of $6.8 million.

These projects showcase how AI crypto coins aim to merge artificial intelligence and blockchain technology for innovative models. However, the integration is still in the early stages and comes with substantial risk.

The promise and perils of AI cryptocurrencies

AI crypto coins offer immense potential but also uncertainties typical of emerging technologies.

Potential Benefits

• Increased efficiency via faster-automated analysis and transactions.

• Improved risk analytics for better decisions.

• 24/7 high-frequency trading and portfolio management.

• Emotionless non-stop monitoring powered by algorithms.

• Democratization of advanced AI for finance.

Associated risks

• Coding errors leading to incorrect outputs or system failures.

• Cybersecurity vulnerabilities that increase the risk of theft or manipulation.

• Lack of regulation around AI automation in finance and crypto.

• Job losses in traditional finance sectors.

• Extreme price volatility synergistic across AI and crypto.

Conclusion

Although both artificial intelligence and AI crypto coins are relatively in their infancy, there is insight into the benefits they provide, enabling automation, predictive analytics, and efficiency improvements.

Rather than relying solely on human analysis, AI crypto projects incorporate algorithms that can analyze data, identify patterns, make AI crypto forecasts, execute trades, and adapt as market conditions change. This allows for applications such as automated high-frequency trading, portfolio balancing, and risk management without constant human oversight.

However, it’s important to remember that AI crypto coins ulitmately represent speculative assets with rewarding upside and commensurate downside dangers. As the tech matures, AI may emerge as a defining force in fintech and crypto. However, regulatory uncertainty and technology risks imply investing in AI blockchain projects demands thorough due diligence.

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