Crypto Basics

Role of AI in Crypto Industry - Benefits, Risks and Uses

Learn everything about the role of artificial intelligence (AI) in the crypto industry and its uses in this descriptive guide.
Token Metrics Team
8 Minutes
MIN

Artificial intelligence (AI) has become a buzzword in various industries, and the crypto industry is not an exception. AI is playing a vital role in the crypto industry by enhancing the efficiency, security, and transparency of various processes.

The crypto industry is experiencing a paradigm shift in the way it operates due to AI's advancements. To begin, it's essential to comprehend the significance of Artificial Intelligence (AI) in the world of cryptocurrencies. So let's start..

Importance of AI in Crypto Industry

In order to understand the importance of AI, we need to explore the various applications of AI in the crypto industry, including trading, fraud detection, security, and governance. We will also examine the impact of AI on the crypto industry and how it is transforming the future of finance.

Artificial intelligence in Trading

AI is revolutionizing the way trading is done in the crypto industry. With its advanced algorithms, AI can analyze vast amounts of data, identify trends, and predict market movements. This capability is crucial in a fast-paced market like the crypto industry, where timing is everything.

Moreover, AI can execute trades automatically based on predefined criteria, which can save traders a significant amount of time and effort. This automation eliminates human error, increases trading efficiency, and reduces the risk of losses.

Artificial intelligence in Fraud Detection

The crypto industry has faced several fraud cases in the past, which have raised concerns about its security. However, AI can help detect and prevent fraud in the industry. AI can analyze data from various sources, including social media, to identify fraudulent activities and alert the relevant authorities.

Additionally, AI can help prevent money laundering by tracking the movement of funds across the blockchain network. This capability can enhance the industry's transparency and make it more attractive to investors.

Artificial intelligence in Security

AI can also play a vital role in the security of the crypto industry. With its advanced algorithms, AI can identify and prevent cyber attacks, which have become increasingly common in the industry. AI can also detect vulnerabilities in the blockchain network and suggest ways to fix them.

Moreover, AI can help prevent hacking attempts by analyzing user behavior and identifying suspicious activities. This capability can enhance the security of the industry and protect investors' funds.

Artificial intelligence in Governance

AI can also improve the governance of the crypto industry. With its ability to analyze data and identify patterns, AI can help regulators identify potential risks and take necessary actions. AI can also help regulators develop policies and regulations that are more effective and efficient.

Moreover, AI can enhance the transparency of the industry by analyzing data on blockchain networks and providing insights into how they operate. This transparency can increase trust in the industry and attract more investors.

Benefits of Using AI in Crypto Trading

The use of AI in cryptocurrency trading has been increasing over the years due to its ability to analyze vast amounts of data, detect patterns, and make predictions. Let's explore some of the benefits of using AI in cryptocurrency trading.

1. Improved Efficiency‍

One of the most significant benefits of using AI in cryptocurrency trading is improved efficiency. AI can analyze large amounts of data from various sources in real-time, making it easier to identify profitable trades.

This capability saves traders a significant amount of time and effort by automating the trading process. Traders can also set specific criteria for trading, and the AI can execute trades automatically based on those criteria.

2. Accurate Market Predictions

AI has the ability to analyze vast amounts of data and detect patterns that are difficult for humans to see. This capability enables AI to make accurate price predictions about the future movement of cryptocurrencies. With its advanced algorithms, AI can analyze market trends and historical data to identify potential price movements.

3. Reduced Risk of Losses

By using AI, traders can reduce the risk of losses. AI can detect potential risks and help traders make informed decisions about when to buy or sell cryptocurrencies. AI can also execute trades automatically based on predefined criteria, which eliminates human error and reduces the risk of losses.

4. Improved Security

AI can also improve the security of cryptocurrency trading. With its advanced algorithms, AI can detect potential cyber attacks and protect traders' funds from being stolen. AI can also identify vulnerabilities in the blockchain network and suggest ways to fix them.

5. Increased Transparency

AI can increase transparency in cryptocurrency trading by analyzing data on the blockchain network. This capability enables traders to see how cryptocurrencies are moving and who is trading them. Increased transparency can enhance trust in the industry and attract more investors.

6. Enhanced Trading Strategies

AI can also enhance trading strategies by providing insights into market trends and identifying profitable trades. Traders can use this information to adjust their trading strategies and make more informed decisions. AI can also analyze the trading behavior of other traders and provide insights into how they are trading.

Risks associated with using AI in crypto

While using artificial intelligence (AI) in cryptocurrency trading has numerous benefits, it is not without risks. Lets see some of the risks associated with using AI in the crypto industry.

1. Over-reliance on AI

One of the most significant risks associated with using AI in cryptocurrency trading is over-reliance on AI. While AI can help traders make informed decisions, it is not infallible. Traders who rely solely on AI may miss critical market movements and make poor trading decisions. It is essential to use AI as a tool to aid in trading decisions, rather than relying entirely on it.

2. Limited Training Data

AI requires vast amounts of data to train its algorithms and make accurate predictions. However, the cryptocurrency industry is relatively new, and there is limited historical data available. This limitation can lead to inaccuracies in AI predictions, which can result in significant losses for traders.

3. Black Box Problem

Another risk associated with using AI in cryptocurrency trading is the black box problem. AI algorithms are often complex, and it can be challenging to understand how they arrive at their predictions. This lack of transparency can make it difficult for traders to trust AI decisions and make informed decisions about their trades.

4. Cybersecurity Risks

AI technology is still new and some systems are vulnerable to cyber attacks, which can compromise the security of traders' funds. Hackers can exploit vulnerabilities in AI algorithms to manipulate trades or steal funds. It is essential to implement robust cybersecurity measures to protect against these risks.

5. Bias in Algorithms

AI algorithms can be biased based on the data they are trained on. If the data is biased, the AI algorithm will make biased predictions, which can result in significant losses for traders. It is crucial to ensure that AI algorithms are trained on unbiased data to avoid this risk.

6. Regulatory Risks

The use of AI in cryptocurrency trading is a relatively new concept, and there is limited regulation surrounding its use. Traders who use AI may be subject to regulatory risks if they violate laws or regulations. It is essential to stay up to date on regulatory developments and ensure that AI systems comply with relevant laws and regulations.

Uses of AI in Crypto Space

Artificial intelligence (AI) has numerous uses in the field of cryptocurrency industry. The most significant use of AI in cryptocurrency space is for research and analysis. AI is used by many investors and traders for predicting market trends and making informed investment decisions. 

Machine learning algorithms can analyze vast amounts of data, including historical crypto price, market cap, trends, volume and many more data points to identify patterns and correlations that may indicate future price movements.

These are few common uses of AI in the crypto space - 

  • Cryptocurrency Market Analysis
  • Accurate Crypto Market Predictions
  • Crypto Market Sentiment Analysis 
  • Automated Crypto Trading Strategies
  • Monetizing Crypto Insights

One best example is Token Metrics itself, We utilize AI's capabilities to deliver high-performance analytics and precise data solutions to users. At Token Metrics, we integrate AI technology and human expertise into our products to provide accurate and reliable market analysis to our users. 

By leveraging AI algorithms, we can process and analyze vast amounts of data efficiently, allowing us to deliver insights and price predictions that aid users in making informed investment decisions. To learn more about the Token Metrics platform, head over to app.tokenmetrics.com and register now. 

The future of AI in Crypto Space

The future of AI in the crypto space is incredibly promising, as the technology continues to evolve and become more sophisticated. One area where AI is expected to make significant strides is in predicting market trends and analyzing large amounts of data quickly and accurately. 

As the crypto market becomes increasingly complex, AI will play a crucial role in identifying trends and patterns that human analysts may miss. AI-powered chatbots and virtual assistants will also become more prevalent, providing data backed suggestions on investment and support to traders and investors. 

Overall, the future of AI in the crypto space is exciting, and it is expected to revolutionize the way investors and traders approach the market.

Conclusion

In conclusion, AI is playing a vital role in the crypto industry by enhancing its efficiency, security, and transparency. AI is transforming the way trading is done, detecting and preventing fraud, improving security, and enhancing governance. The crypto industry is experiencing a paradigm shift in the way it operates due to AI's advancements, and the future looks bright.

Disclaimer

The information provided on this website does not constitute investment advice, financial advice, trading advice, or any other sort of advice and you should not treat any of the website's content as such.

Token Metrics does not recommend that any cryptocurrency should be bought, sold, or held by you. Do conduct your own due diligence and consult your financial advisor before making any investment decisions.

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Token Metrics Team
Token Metrics Team

Recent Posts

Research

From Beginner to Advanced: Building Your First Python Crypto Trading Bot

Token Metrics Team
6
MIN

Automated trading is reshaping the way traders interact with the crypto markets. For beginners and advanced users alike, building a Python-powered crypto trading bot opens up incredible possibilities—from automating strategies to conducting rapid backtests and executing trades 24/7. But how do you go from a basic script to a robust trading algorithm? This guide walks you through the process, addresses key technical considerations, and illustrates how AI and analytics platforms can make your journey more efficient and insightful.

Why Use Python for Crypto Trading Bots?

Python has become the top choice for quantitative finance and crypto automation. Its rich ecosystem of libraries (like ccxt for exchange APIs, pandas for data analysis, and TA-Lib for technical indicators) allows even beginners to build powerful bots.


     

     

     

     


Core Components of a Crypto Trading Bot

Every effective crypto bot has several essential building blocks:


     

     

     

     

     


Organizing these parts within clean Python classes or modules makes your bot scalable and easier to maintain as your strategy evolves.

Step-By-Step: How to Build a Simple Python Crypto Bot

Let’s walk through the foundational process of building your first crypto bot with Python. This approach is equally valuable whether you’re a coding newcomer or migrating from manual trading.


     

     

     

     

     

     

     


This modular workflow sets the groundwork for more advanced automation and risk controls as you gain confidence.

From Basic to Advanced: Expanding Your Bot’s Capabilities

Once you’ve mastered a basic bot, you can enhance its effectiveness dramatically through both software engineering and strategic sophistication:


     

     

     

     

     

     


Successful automation relies on continuous monitoring and refinement. For many, using analytical tools and platforms like Token Metrics can support data-driven hypothesis generation and rapid backtesting.

Security Best Practices and Compliance Considerations

Operating a crypto trading bot safely involves attention to both cybersecurity fundamentals and regulatory factors:


     

     

     

     

     


Consider open-source libraries with active support, or opt for trusted SaaS tools for additional layers of safety and monitoring.

Build Smarter Crypto Apps & AI Agents with Token Metrics

Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key

Frequently Asked Questions

What is a crypto trading bot?

A crypto trading bot is a software application that executes predefined trading strategies automatically, buying or selling cryptocurrencies on your behalf using real-time market data.

How much Python do I need to know to build a bot?

Basic Python programming—data types, functions, loops, modules—is sufficient for creating simple bots. For advanced features (e.g., machine learning, concurrency), deeper knowledge is helpful but not mandatory at the outset.

Is it safe to use Python for crypto bot development?

Python is widely used and considered secure if best practices are followed, especially regarding API key management and keeping dependencies up to date.

Which exchanges support Python crypto bots?

Most major centralized exchanges (like Binance, Coinbase Pro, Kraken, KuCoin) support API-based trading compatible with Python libraries such as ccxt or exchange-specific SDKs.

Can I integrate AI or machine learning in my crypto bot?

Yes. You can utilize libraries such as scikit-learn or PyTorch to add AI models for signal detection, predictive analytics, or anomaly detection, enhancing your strategy’s adaptability.

Disclaimer

This article is for educational and informational purposes only and does not constitute financial, investment, or trading advice. Always conduct your own research and comply with applicable regulations and best practices when developing or using automated trading bots.

Research

Comparing the Top Crypto Trading Bots of 2025: Open Source and Paid

Token Metrics Team
6
MIN

The landscape of crypto trading is rapidly evolving, and as we move into 2025, automation through trading bots remains one of the most transformative trends. Both newcomers and experienced traders are turning to crypto trading bots to streamline processes, manage risk, and take advantage of around-the-clock markets. But with the explosion of open source and paid options, how do you identify which bots merit your attention? In this deep dive, we’ll compare the leading crypto trading bots of 2025—balancing tech, usability, and transparency—so you can navigate this essential toolkit with confidence.

What Are Crypto Trading Bots and How Do They Work?

Crypto trading bots are software programs designed to automate buying, selling, and portfolio rebalancing in cryptocurrency markets. Leveraging predefined rules, technical indicators, or advanced machine learning, these bots execute trades faster and without the emotional bias that can affect manual trading. Bots can operate 24/7, responding instantly to market changes and often employing sophisticated strategies that would be challenging to replicate manually.

In 2025, the variety of bots available spans from simple rule-based systems to complex AI-driven agents. They connect to crypto exchanges—such as Binance, Coinbase, or Kraken—through API integrations. Most bots allow users to customize strategies, set risk parameters, and monitor performance through intuitive dashboards.

Open Source vs. Paid Trading Bots: Key Differences

The difference between open source and paid crypto trading bots often comes down to transparency, control, and ease of use.

  • Open Source Bots: These bots offer transparency and community collaboration. Users can audit the code, ensure no hidden functionality exists, and even tweak algorithms to better suit their needs. Popular examples include Freqtrade and Gekko. While these bots are typically free, they require more technical expertise to set up and maintain, especially when connecting APIs or deploying custom strategies.
  • Paid (Commercial) Bots: Premium bots bundle user-friendly interfaces, customer support, and often proprietary algorithms. Services like 3Commas, Cryptohopper, and Bitsgap lead this category by offering plug-and-play features, cloud hosting, and advanced automation. While they have subscription fees, they cater to users who prefer convenience, security, and ongoing updates over full source code access.

Choosing between open source or paid options in 2025 depends on your technical skill, needs for customizability, trust level, and budget allocation for trading infrastructure.

As AI integrates deeper into crypto trading, both open source and paid bots have seen an upgrade in intelligence and adaptability:

  • Natural Language Strategy Creation: Some advanced bots allow users to describe trading strategies in plain language, which the AI then translates into executable code.
  • Reinforcement Learning Algorithms: AI-driven bots in 2025 commonly use reinforcement learning, optimizing their strategies based on real-time outcomes and historical market data.
  • On-Chain Data Integration: The best bots can process on-chain metrics—such as wallet movements and DeFi protocol activity—adding fresh market context to traditional technical indicators.
  • Risk-Aware Trade Execution: Automated position sizing, stop-loss rules, and volatility analysis are standard, reducing exposure in turbulent conditions without constant user intervention.
  • Multi-Exchange and Cross-Asset Support: Top bots can manage portfolios across several trading platforms, balancing trades among Bitcoin, Ethereum, altcoins, and even tokenized real-world assets.

This evolution assists users at all experience levels, turning AI-powered bots into leading research and automation companions rather than just passive trading engines.

Top Open Source and Paid Crypto Trading Bots in 2025

Let’s spotlight a few prominent options, emphasizing their core features without bias:

  1. Freqtrade (Open Source): Known for its robust backtesting engine, extensive strategy customization, and active GitHub community. Ideal for tech-savvy users who value flexibility and transparency.
  2. Gekko (Open Source): A lightweight bot that runs on Node.js and connects to multiple exchanges. Supports plugin architecture but may lack advanced AI integrations found in newer bots.
  3. Hummingbot (Open Source): Specializes in liquidity mining and market making, enabling users to deploy custom bots with cloud or local hosting. Actively maintained with built-in analytics.
  4. 3Commas (Paid): Offers smart trading terminals, grid bots, trailing features, and AI-powered portfolio management. Designed for accessibility, cloud-based operation, and mobile controls.
  5. Cryptohopper (Paid): Boasts AI strategy creation (“Hopper AI”), paper trading, and a marketplace for community-generated strategies. Focuses on low-latency, round-the-clock trade automation.
  6. Bitsgap (Paid): Supports arbitrage, futures, and spot trading across several exchanges. Known for quick setup, portfolio analytics dashboards, and dynamic grid bots suitable for volatile markets.

Each of these solutions appeals to different user profiles and ambitions. Some prioritize full-stack transparency and algorithmic control (the open source camp), while others seek set-and-forget usability, support, and feature-rich tools (the paid category).

Best Practices for Choosing Crypto Trading Bots

Whether you gravitate toward open source innovation or streamlined paid solutions, consider the following best practices:

  • Security First: Audit the bot’s access permissions. Use secure API keys, track data privacy, and avoid sharing credentials.
  • Community and Support: Evaluate the strength of the bot’s user community or customer support. Active development and transparent documentation are critical for troubleshooting and growth.
  • Strategy Flexibility: Choose bots that support the indicators and logic you require, whether it’s AI-driven strategies or manual rules.
  • Backtesting Capability: Review bots’ simulation features, allowing you to test algorithms on historical data before live implementation.
  • Integration and Scalability: Ensure compatibility with your desired exchanges, assets, and portfolio size. Consider future-proofing with multi-exchange and cross-asset support.

The right research, careful strategy testing, and a responsible approach to automation ensure bots enhance your trading—not replace foundational knowledge or risk management.

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FAQ: Crypto Trading Bots in 2025

Using crypto trading bots is legal in most jurisdictions. However, exchanges may have their own rules, so always review the terms of service for the platforms you use. Compliance with local laws regarding crypto assets is also important.

Can I use trading bots with any crypto exchange?

Most major exchanges provide APIs that allow trading bots to connect and execute trades. However, the level of support and functionalities may vary. Always verify the bot’s compatibility with your chosen exchange.

Do I need to know coding to use crypto trading bots?

Not necessarily. Many paid trading bots offer user-friendly interfaces requiring no coding skills. Open source bots often need technical setup and strategy tweaks, so basic programming knowledge can be helpful for those options.

Are AI-based bots better than rule-based bots?

AI-based bots can adapt to changing market conditions and process complex data in real time, offering advantages in dynamic environments. However, success depends on the implementation, underlying data, and usage. Rule-based bots can be more predictable and transparent.

What are the main risks of using crypto trading bots?

Risks include technical failures, API connection issues, untested algorithms, security breaches, and unpredictable market behavior. It’s important to use secure practices, monitor performance, and regularly audit bot activities.

Disclaimer

This article is intended for informational and educational purposes only. It does not constitute investment advice or recommendations of any kind. Always conduct your own research and consult with financial professionals before engaging in any cryptocurrency trading or investment activities.

Research

Unlocking the Potential of Cryptocurrency APIs for Developers and Analysts

Token Metrics Team
5
MIN

The evolving world of digital assets runs on data. For developers, analysts, and organizations navigating this landscape, harnessing accurate, timely, and actionable crypto data is fundamental to success. But how can you efficiently access vast ledgers, prices, and on-chain analytics from thousands of cryptocurrencies? Enter cryptocurrency APIs—the engines quietly fueling innovation and insight across the blockchain sector.

What Is a Cryptocurrency API?

An API (Application Programming Interface) is a standardized way for software to communicate and exchange information. A cryptocurrency API specifically facilitates seamless access to crypto-related data and functions. Whether dealing with historical prices, blockchain transactions, token metadata, or real-time market feeds, these APIs offer a programmatic gateway into complex digital asset ecosystems. Instead of manual research across multiple platforms, users can automate data collection, run analytics, or even build trading infrastructure—all with efficient, secure calls to an API endpoint.

The emergence of APIs has democratized access to blockchain data, benefiting projects of all sizes. Whether launching a DeFi dashboard, researching token analytics, or simply syncing exchange prices into spreadsheets, APIs are the backbone of digital asset research and development.

Types of Cryptocurrency APIs and Their Use Cases

Not all crypto APIs are created equal. Various categories reflect the diverse needs of the blockchain community:

  • Market Data APIs: Provide real-time and historical price feeds, trading volume, order books, and metadata for thousands of cryptocurrencies across exchanges. Use cases include price tracking apps, research dashboards, and price alerts.
  • Blockchain APIs: Serve raw blockchain data such as transaction histories, wallet balances, gas fees, and block explorers for networks like Bitcoin, Ethereum, and Solana. Essential for wallet apps, compliance tools, and NFT platforms.
  • Trading APIs: Enable users and bots to execute trades, manage orders, and monitor account activity directly on supported exchanges. Vital for algo-trading platforms, portfolio balancers, and market-making bots.
  • On-chain Analytics APIs: Provide deeper analytics, wallet clustering, smart contract activity, and DeFi/NFT insights to inform risk management, due diligence, or automated research.

The right API opens myriad doors—automating research, developing robust applications, and reducing manual overhead.

Key Features to Look for in a Cryptocurrency API

Choosing a crypto API isn’t just about the breadth of assets covered. Making a strategic selection involves assessing several core attributes:

  • Comprehensive Data Coverage: The API should offer support for major blockchains and tokens, with deep historical and real-time data.
  • Latency and Reliability: Low-latency data delivery is crucial for trading and analytics use cases. High uptime and robust SLAs are non-negotiable for mission-critical projects.
  • Granularity: Look for APIs providing granular data—tick charts, historical depth, and address-level on-chain details.
  • Easy Integration: Developer-friendly documentation, SDKs, and sample code reduce integration time and friction.
  • Security: Encryption, authentication, and compliance with regulatory standards protect both data and end users.
  • Advanced Analytics: APIs offering AI-powered signals, token ratings, smart contract analytics, and abnormal trading pattern alerts provide a valuable edge.

Assessing feature sets against your application’s requirements ensures scalability and longevity in rapidly changing markets.

Practical Examples of Cryptocurrency API Integration

How are cryptocurrency APIs shaping real-world workflows? Here are several practical scenarios:

  • Portfolio Trackers: Developers aggregate prices, balances, and transaction histories from exchanges and wallets, offering users a 360° dashboard.
  • Analytics Platforms: Researchers tap APIs to visualize market trends, generate on-chain heatmaps, or compare DeFi activity across protocols.
  • Compliance Tools: Compliance professionals use APIs to track funds, monitor risk, and enforce AML protocols via transaction tracing and wallet analysis.
  • AI-Driven Bots: Algorithmic agents ingest real-time feeds and trading signals via APIs, helping automate research, position sizing, and risk alerts.

APIs save time and reduce errors by replacing manual data collection with automated, scalable solutions accessible to both beginners and professionals.

AI and Advanced Analytics in Crypto APIs

The latest generation of cryptocurrency APIs goes beyond raw data. Powerful platforms leverage artificial intelligence (AI) and machine learning to deliver high-value insights. Examples include:

  • AI-Generated Trading Signals: APIs serving probabilistic buy/sell suggestions based on market sentiment, on-chain behavior, and macro trends.
  • Token Ratings: Algorithms synthesize fundamentals, developer activity, and network metrics to assign token quality scores.
  • Risk Detection: Spotting abnormal trading or potential rug pulls through on-chain analytics and real-time monitoring.
  • Portfolio Optimization: Intelligent portfolio construction—factoring in risk tolerance, correlations, and dynamic volatility—powered by AI within the API itself.

Access to such data is increasingly accessible through well-documented endpoints and SDKs, enabling teams to build smarter, safer crypto tools and gain market context previously reserved for institutional players.

Build Smarter Crypto Apps & AI Agents with Token Metrics

Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key

Frequently Asked Questions About Cryptocurrency APIs

How do I choose the right cryptocurrency API for my project?

Identify your core needs—price data, trading automation, on-chain analysis—and compare leading providers’ data coverage, reliability, security, and ease of integration. Consider documentation quality and the availability of support or SDKs.

Are there free cryptocurrency APIs available?

Yes, many providers offer free tiers with core data endpoints, rate limits, and restricted historical depth. Advanced features and higher call volumes often require a paid plan. Always review usage terms before building mission-critical services on free APIs.

Can I use cryptocurrency APIs for research and analytics?

Absolutely. Cryptocurrency APIs are widely used to source data for research dashboards, quantitative analysis, AI model training, and visualization platforms. Analytical tools like Token Metrics offer API integration for comprehensive analytics.

How secure are cryptocurrency APIs?

Reputable APIs use encryption, token-based authentication, and sometimes allow IP whitelisting. Choose providers with clear security practices, monitor API keys, and avoid sharing them publicly or in client-side code.

What skills are needed to work with cryptocurrency APIs?

Basic knowledge of programming languages like Python or JavaScript, APIs (REST/GraphQL concepts), and JSON/parsing skills are essential. For advanced use cases, familiarity with blockchain concepts and data structures adds value.

Disclaimer

This blog post is for informational and educational purposes only. It does not provide financial, investment, or legal advice. Always conduct your own due diligence before building, integrating, or interacting with cryptocurrency technologies or APIs.

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