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Podcasts are just the best! As I’m sure you already know, there’s some good podcasts and ones that just leave you like… “What did I just listen to?” Thankfully the information in this post will be focusing on the good ones! Yes, you’re welcome. :) Podcasts are so great for a number of reasons You can learn from other people while still doing another activity like driving, exercising, working, etc. I usually turn on a podcast when I’m running, exercising, or driving. Learning is so important. Learners are leaders. Leaders are learners. If you’re not constantly learning you’re losing out on achieving your goals. I’ve identified my favorite podcasts for and equipping myself with the information I need to succeed in branding, business, , and entrepreneurship. learning marketing Are you ready to grab hold of this information? Let’s jump right into the list. :) Entrepreneurs on Fire (John Lee Dumas) is truly awesome! His show is one of my favorites. His show is an award winning podcast where he interviews Entrepreneurs who he likes to say, The show has over 2000 episodes! He’s definitely a powerhouse in the podcasting world. JLD likes to say that he helps Entrepreneurs IGNITE their dream life. John Lee Dumas (JLD) from Entrepreneurs on Fire (EOFire) “are truly ON FIRE.” The Tim Ferriss Show (Tim Ferriss) the author of the uber successful 4 Hour Workweek, has a very successful podcast called the Tim Ferriss show. Tim likes to say he’s a bestselling author and human guinea pig. Newsweek calls him “the world’s best human guinea pig,” and The New York Times calls him “a cross between Jack Welch and a Buddhist monk.” Tim likes to say he deconstructs world-class performers from eclectic areas (investing, chess, pro sports, etc.), digging deep to find the tools, tactics, and tricks that listeners can use. Tim Ferriss, Smart Passive Income (Pat Flynn) The one and only ). He reveals all of his online business and blogging strategies, income sources and killer marketing tips and tricks so you can be ahead of the curve with your online business or blog. Pat has been supporting his family 100% with passive income generated online, easily earning a six-figure salary while working only a few hours a week. Automation, outsourcing, crowdsourcing, search engine optimization, building authority and trust, niche sites, social media, Facebook, Twitter, YouTube, Podcasting, eBooks, online courses, affiliate marketing, getting things done and everything that works (and doesn’t work) to help you better understand how to crush it with your online business. Pat Flynn is so awesome and so is his show Smart Passive Income (SPI How I Built This (Guy Raz) If you’re interested in learning how successful companies got to where they are today, then you need to check out by Guy Raz. Guy Raz dives into the stories behind some of the world’s best known companies. As Guy likes to say, “the show weaves a narrative journey about innovators, entrepreneurs and idealists — and the movements they built.” How I Built This Masters of Scale (Reid Hoffman) The famous man behind LinkedIn, Greylock, and so many other famous startups, Reid Hoffman, has his own podcast called the . The purpose of the show is to determine how companies grow from zero to a gazillion. Reid Hoffman interviews famous founders, and shares some of their insights. Guests include Facebook’s Mark Zuckerberg & Sheryl Sandberg, Netflix’s Reed Hastings, Google’s Eric Schmidt, Spanx’s Sara Blakely. I highly recommend checking it out. Masters of Scale Online Marketing Made Easy (Amy Porterfield) How do I start an online business? Grow my email list to thousands of subscribers? Sell more and grow faster? These are just some of the big questions that leading online marketing strategist, Amy Porterfield, digs into on the top-ranked . Amy Porterfield helps people to generate more profits and to make sense of the online marketing space, implement the strategies that really get results, and turn that side hustle into a business that lasts. I first heard about her podcast when she was a guest on Pat Flynn’s Smart Passive Income show. Online Marketing Made Easy Podcast EntreLeadership (Ken Coleman & Dave Ramsey) This is a really awesome show! I love the host Ken Coleman. The features lively discussions and tips on leadership and business by some of the top minds in the business, like Mark Cuban, Seth Godin, Jim Collins and Simon Sinek. EntreLeadership Podcast Rich Dad Radio Show (Robert Kiyosaki) The one and only Robert Kiyosaki, the auther of the ultra successful book Rich Dad Poor Dad, has his own show, the . The show helps you beat conventional advice on personal finance, investing, and business. Robert Kiyosaki sits down with professionals from the world of money, investing, business, and personal development. Listeners will be provided various viewpoints on how to set themselves up for financial success. Definitely recommend checking it out. Rich Dad Radio Show Marketing School (Neil Patel & Eric Siu) show is great for really short, but amazing actionable content. Neil Patel and Eric Siu bring you daily ACTIONABLE digital marketing lessons that they’ve learned through years of being in the trenches. Whether you have a new website or an established business, learn the latest SEO, content marketing, social media, email marketing, conversion optimization and general online marketing tactics that work today. The Marketing School Grow Like a Pro (Adam Bankhurst & Jason Fleagle) Yes, this is my where I’m one of the hosts! I love podcasts so much I decided to create my own! It’s been an amazing experience so far. Adam Bankhurst and I host the show together. We pull out the tips, tools, and techniques from other successful people so you can grow like a pro. The goal of the show is to help you achieve your goals and dreams as an entrepreneur and/or business owner. podcast Learn growth tips and hear success stories from many entrepreneurs from all walks of life as they teach YOU how to grow like a pro. We’ve interviewed people like , and so many others. Darshan Vyas from Loud Capital, JD Bergman from inTeam, Ron Greenbaum from the Basement Doctor Shows are released weekly There’s a new show released every Thursday at 6AM! You can check it out by clicking here. You can listen to our episodes and subscribe to hear more tips, tools, and techniques to help you grow like a pro. If you want to submit questions, comments, or want to be on the show please send an email to hello@growlikeaproshow.com. We’re always looking for great entrepreneurs doing incredible things. Are there other shows you think should be on this list? Do you have any favorite podcasts you like to listen to? Tell me in the comment section below. I’d love to hear about them. Thank you so much, and remember to keep moving forward! , is a Business Success Catalyst, Digital Marketer, Web Developer, Speaker, and Writer. Jason has empowered brands like The John Maxwell Company, Ziglar Inc., Kevin Harrington from Shark Tank, and many others. is the Founder of , and the Business Growth Strategist of . You can connect with Jason at Jason Fleagle Jason Fleagle Converge , Catalyst Growth Group Jenesis Marketing Group TheJasonFleagle.com . _In this episode Trent Lapinski and Julian Moncada discuss emerging technologies such as blockchain, augmented reality…_podcast.hackernoon.com Hacker Noon Podcast

The 10 Best Podcasts of 2018 for Branding, Startup, Marketing, and Self-Improvement.

The Evolution of Blockchain Layer 2 Networks: Scaling Solutions for a Decentralized Future

Image by Geralt on Pixabay The trading realm is evolving unprecedentedly, with at the helm of this transformation. The ubiquitous integration of AI in trading is hard to ignore, given that the global AI market is projected to reach a staggering . This growth underscores the increasing importance of AI technologies and the new opportunities and challenges they introduce. AI $407 billion by 2027 As we navigate the pros and cons of AI in trading, it's essential to understand that it's a double-edged sword. On the one hand, AI presents groundbreaking efficiencies and potential profits, but on the other hand, it brings significant cybersecurity concerns in finance. This article offers a balanced, insightful examination of these contrasting aspects. Understanding AI in Trading AI trading strategies represent an innovative leap in the financial sector, blending high-tech algorithms with data analysis to maximize profitability. This enticing fusion of tech and finance paves the way for unprecedented market insights and investment opportunities. Let's delve into AI trading strategies, illuminating the past, present, and potential future. Definition and scope of AI in trading Trading using AI refers to the use of complex algorithms to make trading decisions. These systems analyze vast amounts of data and execute trades at lightning speeds. Automated trading systems have revolutionized modern finance, enabling high-frequency trading and reducing the likelihood of human errors. They offer the potential for greater efficiency and profitability, but their use also raises essential ethical and security questions. Historical context and the evolution of AI in finance The genesis of AI in finance began in the 1980s with rudimentary algorithmic trading. With advancements in technology, AI swiftly progressed. From simple predictive models, it evolved into complex neural networks by the 1990s. The advent of machine learning in the 2000s further propelled AI's capabilities. Today, are integral to finance, encapsulating trading, risk management, and financial planning. sophisticated AI trading strategies Pros and Cons of AI in Trading AI presents a fascinating blend of benefits and challenges. Its impact on the trading industry is transformative, reshaping the landscape in unprecedented ways. Let's uncover AI's intricate pros and cons in trading technology, shedding light on its potential to revolutionize trading as we know it. Pros of AI in trading Here are the pros of using AI trading strategies: Enhanced marketing efficiency AI trading strategies streamline and expedite the trading marketing process. They decipher complex market data, identify patterns, and accurately predict trends. This leads to informed decisions and targeted marketing strategies. Further, automated trading systems reduce costs and increase response times, boosting overall marketing efficiency. Superior data processing and analysis AI in trading revolutionizes , making financial decisions faster and more efficient. Automated trading systems can handle vast amounts of market data in real-time. data processing and analysis They identify subtle patterns and trends that humans could miss. These systems excel at predictive analysis, providing traders with insightful forecasts. This superior analysis capability translates to more precise, data-driven trading decisions, enhancing profitability. Automated decision-making and speed AI-powered trading systems ensure speedy and automated decision-making. They analyze and act on market data at an unrivaled pace, offering a competitive edge. This lightning-fast decision-making ability eliminates the lag associated with human intervention. It enables traders to capitalize on fleeting trading opportunities, which are commonplace in volatile markets. By eliminating human error and emotional trading decisions, AI ensures more strategic, efficient, and profitable trading. Cons of AI in trading Here are the cons of AI in trading: Ethical considerations and biases AI trading systems can inadvertently perpetuate biases, skewing trading decisions based on flawed algorithms or biased data. Ethical considerations arise when these systems prioritize profitability over fairness or transparency. Furthermore, such biases could lead to discriminatory trading practices, amplifying market disparities. This highlights the need for rigorous bias and ethics checks in AI trading strategies. Risk of over-reliance and loss of human oversight An over-reliance on AI in trading could result in a lack of human oversight. This absence of human judgment might exacerbate market risks. AI systems, while efficient, lack the intuition and adaptability inherent in human traders. This makes them susceptible to unexpected market changes. Moreover, an over-reliance could lead to complacency, with traders not fully understanding the underlying trading strategies. A balanced approach between AI and human oversight is crucial for sustainable and responsible trading. Cybersecurity threats and data privacy concerns While highly efficient, AI trading platforms expose financial markets to an increased risk of cyber-attacks. Cybercriminals can exploit weak security measures to manipulate trading algorithms and compromise sensitive data. Additionally, data privacy concerns arise as AI systems process large quantities of personal and financial information. Therefore, implementing in finance is paramount in AI trading to protect the integrity of trading strategies and the privacy of trader's data. robust cybersecurity The Impact of AI on Trading Strategies and Performance AI has revolutionized trading strategies with its accuracy and speed, fostering a new era of automated trading systems. These sophisticated systems are transforming traditional trading, offering innovative strategies and improved performance. Innovative trading strategies enabled by AI harness the power of artificial intelligence to analyze vast data sets, identify trading opportunities, and execute trades at lightning-fast speeds. These strategies can learn from market patterns and trends and adapt their tactics accordingly. AI trading strategies AI's ability to process high volumes of data and make real-time data-driven decisions significantly enhances trading operations' efficiency and profitability. Incorporating AI in trading strategies has ushered in a new era of precision, speed, and effectiveness in financial markets. Performance Analytics Automated trading systems provide robust performance analytics, furnishing traders with critical insights. These systems analyze market data, assessing trade performance with pinpoint precision. The analytics highlight effective strategies and potential areas for improvement. This data-driven method leads to more informed decision-making and improved trading outcomes. Risk management in AI trading AI significantly bolsters risk management in trading. It delivers predictive analytics, enabling traders to foresee potential market downturns and adjust strategies proactively. Enhanced cybersecurity measures in AI trading systems also ensure data integrity and privacy. Due to AI's ability to detect anomalies, cybersecurity threats are identified and mitigated promptly, safeguarding financial transactions and confidential data. AI's role in cybersecurity in finance is crucial, ensuring safe and secure trading operations. AI's Impact on Employment in the Trading Sector AI's integration into the trading sector isn't just transforming strategies—it's revolutionizing the job landscape. As we delve into its impact on employment, we'll explore the delicate balance between job displacement and creation. We'll also discuss the changing skill requirements in this rapidly evolving industry. This exploration will shed light on the increasingly vital role of human expertise amidst the rise of machines. Job displacement vs. job creation AI has led to job displacement in the trading sector. Due to automated trading systems, traditional roles, such as floor traders and stock analysts, are becoming redundant. These systems can execute trades faster and more accurately than human traders, enhancing efficiency and performance. Moreover, AI can analyze vast amounts of financial data in real-time, eliminating the need for human analysis. On the flip side, AI has also stimulated job creation. are emerging. For instance, AI trading strategists analyze AI trading outcomes and refine AI algorithms. There's also a surge in demand for AI compliance officers who ensure AI trading systems adhere to regulatory standards. New roles that require expertise in AI and machine learning AI developers and cybersecurity specialists are also in high demand to build and protect these systems. This indicates that while AI may replace specific jobs, it's also creating new roles for those with specialized skills. Changing skill requirements The shift towards AI trading mandates traders to adapt their skill sets. A strong understanding of AI algorithms, data analysis, and financial modeling becomes crucial. Expertise in programming languages like Python that aid in developing AI strategies is beneficial. Lastly, skills in risk management, understanding AI ethical considerations, and regulatory compliance are indispensable in this increasingly AI-driven trading environment. The Human Element in AI Trading While AI has disrupted trading with its speed, efficiency, and data-crunching prowess, human insight remains essential. This intersection of AI and human expertise creates a dynamic, transformative landscape in trading. The nuanced balance between these two elements unfolds as we delve further, revealing their collective impact on AI trading strategies. Let's explore the enduring relevance of the human element in this AI-dominant environment. Importance of human intuition and management Human intuition in trading continues to hold ground amidst advanced automated trading systems. Experienced traders, with their intuitive understanding, can discern patterns in market behavior that AI might overlook. Furthermore, they can make adaptive decisions based on fluctuating market contexts, something that AI systems may struggle with given the limited predefined parametrics. Therefore, while automated trading systems provide significant benefits, human oversight often brings balance, propelling successful trading strategies. Balancing AI and human decision-making Striking a balance between AI and human decision-making in trading has its unique set of challenges. AI tools excel in processing vast data, making quick decisions, and reducing human errors. On the other hand, they lack the intuitive understanding humans have of market subtleties. Humans excel at making flexible judgments based on experience and context. However, they can be slow and prone to errors. The ideal scenario is a symbiosis—AI offering efficiency and speed, humans providing oversight, nuance, and intuition. Training for tomorrow's AI-enhanced workforce Preparing for an AI-enhanced workforce entails comprehensive training and upskilling initiatives. Companies must foster a continuous learning culture, encouraging employees to embrace AI tools. Training should focus on understanding AI's capabilities, application in their respective roles, and ethical considerations. This readiness will help businesses adapt swiftly to AI's influence, particularly in dynamic sectors like marketing, where data-driven strategies are gaining prominence. Exploring Cybersecurity in Finance Evolving technology comes with increased cybersecurity risks, particularly in finance. While financial institutions harness AI's immense power, they must simultaneously address cybersecurity concerns. The following sections dive deeper into this critical interplay, highlighting the importance of robust security measures in our increasingly digital world. Emerging threats in AI systems AI systems in finance are facing emerging cybersecurity threats. Hackers are exploiting AI's intricate algorithms to launch sophisticated attacks. These threats can compromise data integrity, disrupt trading operations, and tarnish a company's reputation. Additionally, deepfakes, powered by AI, pose a significant identity verification challenge. Consequently, the industry must invest heavily in advanced cybersecurity measures to counter these risks. Strategies for securing AI in trading Here are practical yet helpful strategies to secure your trading journey: Employing multi-factor authentication is crucial to secure AI in trading. This strategy enhances access control, reducing unauthorized entry. Regular audits can help detect anomalies early. Encrypted communication protocols bolster data security during transmission. Continuously updating AI algorithms increases resilience against emerging cyber threats. Privacy Concerns in AI-Driven Trading Privacy concerns occupy a pivotal role in the rapidly evolving realm of AI-driven trading. As financial institutions leverage AI's prowess, they grapple with an unseen adversary—privacy breaches. These intrusions are detrimental to their reputation and potentially risk their financial stability. Now, let's explore this further and see how the finance sector can navigate this precarious cyber landscape. Data collection and usage In AI-driven trading, vast amounts of data are collected relentlessly. This data, encompassing personal details and transaction histories, fuels the predictive capabilities of AI models. However, such extensive data collection can infringe upon your privacy, as sensitive information could fall into the wrong hands. Moreover, concerns about how this data is stored, processed, and shared persist, warranting stringent data governance protocols. The delicate balance between leveraging data for AI and maintaining privacy is a pressing issue in today's digitalized trading world. Legal implications of privacy breaches When privacy breaches occur, the legal fallout can be severe. Financial institutions may face hefty penalties if found to be non-compliant with data protection laws. Additionally, they may suffer substantial reputational damage. Clients could lose trust and opt for other service providers, leading to a loss of business. Therefore, financial entities must adhere strictly to laws and regulations, taking a proactive stance in ensuring the safety and confidentiality of user data. User consent and data rights Consent and data rights form the bedrock of ethical AI trading. Users must knowingly give consent, understanding the extent of data use. Explicitly stating data rights upholds transparency and builds trust. Informed consent is fundamental to adhere to cybersecurity norms. It fuels the relationship between the finance sector and clients, anchoring it in trust. Redefining Markets With AI: Balancing Risks and Rewards AI is redefining trading markets and unlocking potential while introducing new risks. Emphasizing data privacy and cybersecurity while exploiting AI's capabilities can strike a balance. The benefits are significant: AI can identify trading patterns, automate transactions, and improve decision-making. However, the risks, including data breaches and privacy infringements, are concerning and demand attention. In conclusion, as AI revolutionizes trading markets, it will be crucial to balance its rewards and risks. The future holds promise if we navigate responsibly, ushering in an efficient and secure trading era.

Reflecting on the Pros and Cons of AI in Trading: From Ethics to Cybersecurity Issues

🚩Hidden behind the public view is one of the crypto industry’s biggest secrets, the crypto shadow banking, where cryptos worth billions of dollars are borrowed & lent on an un-collateralized basis, between some of the industry’s biggest names. 🏦Crypto shadow banks engage in bank-like activities such as borrowing & lending but are not licensed banks, hence falling outside of the regulatory requirements. 🏦 engage in bank-like activities such as borrowing & lending but are not licensed banks, hence falling outside of the regulatory requirements, which require capital reserves to cover losses from bad loans or available liquidity in case of a bank run. Crypto shadow banks can be lending platforms (BlockFi, Celsius), exchanges (FTX) when they create credit or lend out clients' deposits to enhance liquidity, or credit networks (Genesis Trading, Hidden Road) that facilitate institutional borrowing & lending. Crypto shadow banks 💡The key player in the crypto shadow banking system is Genesis Trading, namely its highly successful & lucrative lending desk. Genesis Trading lending desk is the world’s leading lending desk in the cryptocurrency markets, facilitating two-way originations between lenders & borrowers, and is considered a trusted counterparty for institutional & professional traders, market makers, hedge funds, & crypto companies with large treasuries. ❗️Genesis was not immune to the stress in the crypto markets in the last month and as of November 16th, it has implemented a withdrawal freeze amid efforts to stave off potential bankruptcy. Genesis cited “unprecedented market turmoil” caused by the collapse of FTX and 3AC, which led to “abnormal” levels of withdrawals that exceeded its liquidity. ❇️Perhaps the most fascinating data on crypto shadow banking comes from Genesis's active loan book, which was until the end of Q3 2022. While Genesis loan origination does not fully cover all the crypto shadow banking activities, it can be considered an excellent proxy, since the lending desk of Genesis Trading was the most significant player in the world’s crypto shadow banking ecosystem. From a peak of almost $15 billion of active loans in Q1 2022 to a collapse of $2.8 billion in Q3 2022, a drop of over 80% over a period of fewer than 6 months. Crypto shadow banking is going through its collapse and the unique & valuable data points from Genesis Trading's quarterly reports confirm this. transparently provided to the public ✅Crypto shadow banking activities were the biggest driver of the spectacular bull market, as well as the ongoing collapse & contagion. World’s regulators are tapping into the dark, trying to understand the causes of the collapse. In the current crisis, crypto industry leaders & experts have an opportunity to provide insights into how the industry really operates & transparently explain crypto #shadow #banking activities. My goal is that my writing creates a platform for open discussion on how to enhance our industry & put a healthy foundation in place, that will support the world's growth in the coming decades.

How the Shady World of Crypto Shadow Banking Collapsed

Blockchain technology was created in by a pseudo-anonymous individual or group going by the name of Satoshi Nakamoto. This innovation gave birth to Bitcoin, the most prominent cryptocurrency to date. Although there are , the real identity of the genius behind this incredible innovation remains a mystery. 2009 speculations as to who Satoshi is A blockchain is a distributed ledger technology (DLT) secured by advanced cryptography methods and consensus algorithms. These distributed ledgers utilize nodes to synchronize, send, and record data over a peer-to-peer network. As an immutable technology, DLTs ensure data integrity and security, providing a database that no single entity owns or controls. The blockchain industry has been growing at an exponential rate since its inception. With Statista forecasting the blockchain technology market to reach , blockchain is a technology that is necessary for everyone to understand. $163 billion by 2027 This article explains the two essential types of blockchain layers: Architecture Layers and Protocol Layers, and will cover the various functions of each layer. The Blockchain Architecture The first type of Blockchain Layer is the Architecture Layer, which is composed of 5 sub-layers: the hardware layer, the data layer, the network layer, the consensus layer, and the application layer. Read more to learn how these layers work. Hardware layer The hardware layer is the first layer of blockchain architecture. As the foundation of blockchain technology, the hardware layer provides the physical infrastructure for the blockchain network. This layer consists of nodes, which are multiple computer servers running the blockchain’s hardware and software for the purpose of processing, verifying, and storing transactions on the blockchain. Each blockchain’s group of nodes forms a to communicate and share information about the blockchain. Nodes also serve as validators for all transactions happening on the network. Because these nodes are generally run from many locations across the globe, they help the blockchain maintain its integrity by ensuring maximum uptime and making it extremely difficult to hack. peer-to-peer network Data layer The data layer is the second layer of the blockchain architecture and is responsible for storing the actual data on the blockchain. The data layer consists of the blocks in a blockchain, which are  collections of transactions that have been verified and confirmed by the nodes running the network. This layer includes the first block of the chain, the genesis block. Data layers are essential because they ensure that the blockchain’s data is accurate and tamper-proof. The data inside these blocks are secured by private keys and public keys that serve as digital signatures to maintain their security and integrity. Network layer The network layer is the third layer of blockchain architecture. Often referred to as the peer-to-peer layer,  the network layer is responsible for managing and maintaining the network infrastructure of the blockchain. It is also called the “propagation layer” because it is where block creation, block addition, and node communication all happen. This propagation layer is where the nodes and miners consistently communicate transactional data over a peer-to-peer network. The nodes and miners use their computing power to solve complex mathematical problems to check the transactions’ validity. Through consistent communication between nodes of transaction data on the network, the network layer ensures the legitimacy of the transactions. Consensus layer As the fourth layer of the blockchain architecture, the consensus layer is responsible for ensuring that all nodes on the network agree on the validity of the transaction data. This layer is vital because it guarantees that all nodes in the network are in agreement on the information stored on the blockchain. This consensus layer consists of the algorithms and protocols for multiple nodes to reach a consensus on new blocks and additions to the blockchain. All nodes validating the transaction must be in agreement to declare that the transaction is valid. can vary across blockchains, such as with Bitcoin’s Proof-of-Work consensus mechanism or Ethereum’s Proof-of-Stake method. Consensus mechanisms It is also worth mentioning that the more node validators are in the consensus mechanism, the more decentralized the blockchain network is. However, as more transaction data needs validating on the network, the higher the transaction fees become, a known blockchain scalability issue for Proof-of-Work systems. Application layer The application layer is the fifth and final layer of the blockchain architecture and is where you can find , decentralized applications (dApps), user interfaces (UIs), and chain code. Essentially, this layer consists of services and application programming interfaces (APIs) that provide other apps with access to the blockchain network. smart contracts One of the most popular concepts of a dApp is DeFi, also known as decentralized finance. Unlike transactions in traditional finance, where central banks are intermediaries, DeFi eliminates those middlemen. Instead, the transactions are peer-to-peer. Both Proof-of-Work (PoW) and Proof-of-Stake (PoS) systems are capable of running dApps, thanks to smart contracts on the application layer. Networks like Ethereum, Polkadot, and Cardano are great examples of platforms that have an application layer that developers use to build their own dApps. The Layers of Blockchain Protocols The second way to understand blockchain technology is by knowing the different layers of blockchain protocols. The blockchain network comprises four layers: Layer 0, Layer 1, Layer 2, and Layer 3. Here is how it works: Layer 0 Layer 0 is the network architecture of blockchain technology. This layer is the foundation of the blockchain protocol. It is responsible for providing the essential infrastructure for the blockchain network. Layer 0s utilize native tokens, also known as cryptocurrencies, to and participation in the network. empower development Examples of layer 0 blockchain protocols that have native tokens include: Bitcoin - $BTC Ethereum - $ETH Polkadot - $DOT Layer 1 Layer 1 is responsible for storing the actual data on the blockchain. This layer consists of the blocks, which are a collection of transactions verified and confirmed by the nodes on the blockchain. New blocks join the blockchain in a linear, chronological order. Layer 1 is vital because it ensures that the blockchain’s data is accurate and tamper-proof. There was a known scalability issue with Proof-of-Work Layer 1s systems like Bitcoin and the Ethereum network before the . As more people join the network, higher computing power is needed in the consensus mechanism, leading to higher gas/transaction fees and longer processing times. However, these scalability issues are mitigated by systems, as they have significantly lower energy requirements. Sharding, part of some PoS systems, helps with scalability as it divides the computing power. Merge Proof-of-Stake (PoS) Layer 2 A layer two protocol sits on top of layer 1. These overlapping networks are also known as Layer 2 solutions or scaling solutions. They make it possible to have cheap transaction fees because layer two transactions can happen off-chain, away from the layer 1 ecosystem. One good example of a Layer 2 solution is the Lightning Network of the Bitcoin blockchain. Another example of Layer 2 solutions is sidechains. The best one that fits this is the Ronin Network, the blockchain used by the biggest NFT game, Axie Infinity. of the Ethereum network, which made it possible to avoid high gas fees associated with ETH’s PoW system before the merge in 2022. Ronin is a sidechain Layer 3 Layer 3 protocols are where you can find decentralized applications or dApps. Layer 3s have user interfaces that allow projects like DeFi applications to have real-world use cases. UIs via Layer 3 enable humans to have a communication line in the blockchain. The Bottom Line Understanding the different layers of blockchain technology is essential for anyone looking to develop a blockchain-based project. Blockchain developers are actively working on the scalability issues that blockchain technology suffers from to make this technology more viable for large-scale use cases. The that addresses security, scalability, and decentralization must then be fixed for this technology to achieve global mass adoption. blockchain trilemma Despite the challenges, blockchain technology remains an incredibly powerful tool with much potential. By understanding how the different layers of blockchain protocols work, you can begin to develop your own applications and services that leverage this game-changing technology.

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