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Security: Trust and liveness assumptionbinance buy bitcoin credit card feess, tolerance for malicious behavior, security and reflexivity of user funds.

The future obitcoin euro coingeckof France has never been so bright!On a personal level, I put Sushi before physical and mental health, relationships, family and friends. In the next month or two, I will slow down. It must be interesting to build on top of Sushi. Unfortunately, I will not post spam on Twitter. Maybe I will de-anonymize it a bit? Write an in-depth book...Who doesn't want a Hollywood-produced Sushi/DeFi version of "Social Network"? Ha ha. I might divide my BAYC ape into several parts for fun, and then airdrop it to everyone in this community.

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After all... We are 0xMaki in some ways, and we have no intention of leaving this space. I have joined the community for a long time, and I am ready to come back when the community needs it. I am a lifetime asset of you.The "two giants" in the game fieldIn the field of "playing and earning" games, the two most famous projects are Axie Infinity and YGG.Axie Infinity created an unprecedented type of game that is "play while earning", just like "Candy Legend" created the dominance of free games in 2012.At this stage, Axie Infinity already has more than 1.5 million daily active players, mainly in the Philippines, Indonesia, Brazil, Venezuela, India and Vietnam. For thousands of users, playing Axie Infinity has become their source of livelihood, and sometimes the revenue provided by this game far exceeds their income from working locally. Although most players are not native users in the crypto industry, through viral word-of-mouth marketing, many people have learned about the Axie Infinity game. The explosive growth, global influence, and extensive revenue generation achieved by the Axie Infinity game is indeed impressive. The reason for this achievement is mainly because they created a new game model of "play while earning". In terms of gameplay, Axie Infinity is similar to Pokémon. Players need to breed and breed Axies, a cartoon character that looks like a salamander, and then participate in the battle. The difference is that instead of winning points, the winner gets the game’s native token-Smooth Love Potion (SLP), which can be immediately transferred to another crypto asset or used as collateral, or Cashed as legal tender. Axies and the digital land of games can be bought and sold between individuals as NFTs, and they even launched a governance token (AXS) that allows holders to determine the future of the game.

Another project is Yield Guild Games (YFF), which is a "guild" aimed at the new "play while earning" economy. This union is managed by a decentralized autonomous organization (DAO) for those who want to professionally play Axie Infinity and Other people who "play and earn" games provide "scholarship" incentives to share part of their income. Therefore, this decentralized autonomous organization holds NFTs from various Metaverse games, making its governance token YGG an index of game earning economy. Although the project is still in its infancy, there are already more than 4,500 "scholars" with weekly transactions exceeding US$1 million.In recent months, some other "play while earning" mode games have become more and more popular, such as CryptoBlades, Zed Run, Cometh, REVV, etc. In fact, in the "play while earning" mode games have obtained orders. After the jaw-dropping success, this game revolution is very meaningful for big-name game developers. This trend cannot be ignored, and the futureThe future may see some mature game industry participants begin to incorporate these ideas into their games and bring this game model to a wider audience.Participants monitor events on the source chain and generate encrypted packaging proofs about past events recorded on the chain. These proofs will be forwarded to the contract on the target chain (such as "light client") along with the block header, and then verify whether an event is recorded, and perform operations after verification. This design mechanism requires some participants to "relay" the block headers and proofs. Although users can "self-relay" transactions, there is indeed an active assumption that the relay will continue to forward data. This is a relatively secure bridging design because it guarantees the effective delivery of trustlessness without trusting intermediate entities. But it is also resource-intensive, because developers must build a new smart contract on each new target chain to parse the source chain's state proof; the verification process itself requires a large amount of gas.

Type 3: Liquidity networksThis is similar to a peer-to-peer network, where each node acts as a "router", holding a "library" of source and target chain assets. These networks usually take advantage of the security of the underlying blockchain; through the use of locking and dispute mechanisms, it can be ensured that routers will not steal users' funds. Because of this, a liquid network like Connext may be a safer choice for users who transfer large amounts of value. In addition, this type of bridge may be most suitable for cross-chain asset transfer, because the assets provided by the router are the original assets of the target chain, rather than derivative assets that cannot be completely replaced by each other.It should be noted that any given bridge above is a two-way communication channel. There may be independent models in each channel, so this classification cannot accurately represent mixed models such as Gravity, Interlay, and tBTC. Because they all have light clients in one direction and validator nodes in the other direction.In addition, the design of a bridge can be roughly evaluated based on the following factors:

Security: Trust and liveness assumptions, tolerance for malicious behavior, security and reflexivity of user funds.Speed: The delay time of transaction completion, and the guarantee of final certainty. There is usually a trade-off between speed and safety.

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Connectivity: The choice of target chains for users and developers, and the different difficulty levels of integrating additional target chains.Capital efficiency: economic mechanism, which sets the transaction cost of capital and asset transfer required to ensure the security of the system.Statefulness: The ability to transfer specific assets, more complex states, and/or perform cross-chain contract calls.In summary, the trade-offs of these three design mechanisms can be evaluated from the perspective of the following figure:

In addition, security is a scope, we can roughly divide it into the following categories:Trust-less: The security of the bridge is bound to the underlying blockchain it bridges. Unless the underlying blockchain is attacked by consensus-level attacks, users' funds will not be lost or stolen. In other words, this is not complete trustlessness, because all the economic, engineering, and cryptographic components of these systems contain trust assumptions (for example, there are no loopholes in the code).Insured (Insured): Attackers can steal user funds, but they may be unprofitable in doing so. Because they need to provide collateral to participate in the network, and they will be punished for wrongdoing and malicious behavior. If the user's funds are lost, the agreement will compensate the user by confiscation of the attacker's collateral.Bonded (Bonded): Similar to the insurance model (for example, the economic benefits of participants are closely related to their behavior), except that the user's collateral is forfeited due to his mistakes and malicious behavior. The type of collateral is important for both the insurance and the mortgage model; endogenous collateral (protocol tokens as collateral) is more risky, because if the bridge fails, the value of the token is also likely to collapse, which further reduces Security guarantee for bridging.

Trusted: Participants do not need to mortgage assets, and users cannot retrieve assets when the system fails or commits malicious behavior. Therefore, security mainly depends on the reputation of the bridge operator."External validators and federalism" are generally better in terms of state and connectivity because they can trigger transactions, store data, and allow data to interact with any number of target chains. However, this comes at the cost of security, because by definition, users rely on the security of the bridge rather than the source or target chain. Although most of the current external validator mechanisms are based on trust models, some require collateralized assets, and a subset of assets is used to insure end users. Unfortunately, their insurance mechanisms are usually reflexive. If the agreement token is used as collateral, it is assumed that the value of the token is sufficient to compensate the user's loss. In addition, if the mortgage asset is different from the insurance asset, it will also depend on the price flow of the oracle, so the security of the bridge will be downgraded to that of the oracle. If a trust model is not required, these bridges are also the least capital efficient, because they promote economic throughput and also need to scale up the scale of collateral.

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"Light client and relay" is also better in terms of state, because the block header relay system can transmit any type of data. Although there are liveness assumptions due to the need for repeaters to transmit information, they are also very safe because they do not require additional trust assumptions. At the same time, they are the most capital efficient bridges because there is no need to lock any assets. However, these advantages come at the expense of connectivity. Every time a pair of chains is connected, the developer must deploy a new light client smart contract on the source chain and the target chain. The complexity of the contract is between O(LogN) and O(N) (the reason is between this The scope is because it is relatively easy to add chain support using the same consensus algorithm). There is also a significant speed flaw in the optimistic model that relies on fraud proofs, which may increase the delay to 4 hours."Liquidity networks" are strong in terms of security and speed because they are locally verified systems (that is, global consensus is not required). They are also more capital efficient than the external validator mechanism of the mortgage/insurance mechanism, because capital efficiency is related to transaction flow/volume, rather than security. For example, assuming that the transaction flows of the two chains are equal, and given a built-in rebalancing mechanism, the liquidity network can contribute to an arbitrarily large economic throughput.

The trade-off lies in the state, because although the call data can be transmitted, its function is limited. For example, they can interact with data across chains, where the receiver has the right to interact based on the provided data (for example, using the signature information from the sender to call a smart contract), but there is no "owner" of the data for the transmission or the transmission belongs to Generalized state data (such as minting representative tokens) is not helpful.Building a strong cross-chain bridge is a difficult problem in distributed systems. Although there have been many attempts in this field, there are still some problems to be solved:Finality & rollbacks: In a chain with probabilistic finality, how does bridging deal with block reorganization and time thief attacks? For example, if any chain has experienced a state rollback, what will happen to users who send themselves from Polkadot to Ethereum?NFT transfers & provenance: How can bridges trace the provenance of NFT across multiple chains? For example, if there is an NFT that has transacted in multiple markets of Ethereum, Flow, and Solana, how are all these transactions and owners recorded?Stress testing: In the case of chain congestion or protocol and network level attacks, how will various bridge designs respond?Although bridging unlocks more innovation possibilities for the blockchain ecosystem, if the team takes shortcuts in R&D, it may also bring great risks. The Poly Network cross-chain attack event has shown us the potential economic loss scale of vulnerabilities and attacks, and I estimate that there will be more large-scale attacks in the future. Although for bridge builders, the current network is highly fragmented and competition is fierce. But each team should be highly self-disciplined and prioritize security rather than release speed.

Although the ultimate ideal state is to build a "isomorphic bridge" shared by all things, the reality is that there is probably no single "best" bridge design. Different types of bridges will be suitable for different specific applications (such as asset transfer, contract invocation, token minting, etc.).In addition, the best bridge should be the most secure, connectable, fast, capital efficient, cost-effective, and censorship-resistant. If we want to realize the vision of the "blockchain internet", these attributes need to be maximized by us.

So far, we have not constructed the optimal bridge. There are several interesting research directions for all bridging types:Reducing the cost of block header verification: The cost of block header verification for light clients is very high. If this problem can be solved, it will bring us closer to achieving fully universal and trustless interoperability. An interesting design is to bridge to L2 to reduce these costs. For example, implement the Tendermint light client on zkSync.

Shift from a trust-based model to a mortgage model: Although the capital efficiency of mortgage verifiers is much lower, the security of "social contracts" is not enough to protect billions of dollars in user funds. In addition, the fancy threshold signature mechanism does not reduce trust; this group of signers still belongs to a trusted third party. Without collateral, users actually hand over their assets to an external custodian.Change from a mortgage model to an insurance model: Loss of assets is the last thing users want to encounter. Although verifiers and repeaters of mortgage assets can prevent malicious behavior to a certain extent, the agreement should go further and directly use the confiscated funds to compensate users.

Expanding the liquidity of the liquidity network: The "liquidity network" can be said to be the fastest bridge for asset transfer, and there are some interesting design trade-offs between trust and liquidity. For example, the liquidity network may be able to use the mortgage verifier model to outsource capital supply, where routing may also be a threshold multi-signature with mortgage liquidity.Bridge aggregation: Although the use of bridges may follow the law of exponential for a specific asset, an aggregator like Li Finance can improve the experience of developers and end users.Nowadays, many GameFi projects continue to emerge, and provide a variety of participation methods and play-to-earn and pledge functions. So, how to judge which projects can be held for a long time and can add value? How to find potential NFT agreements?The calculation of agreement income is the focus of value investment.

First of all, let's take a look at what is the agreement income? What is the difference with income?Let me talk about the definition of revenue. Revenue measures the return of all participants, that is, the total cost paid to the contract supplier. For example, the fees paid to liquidity providers in AMM, the transaction fees of decentralized exchanges, and the amount of interest on the lending platform in DeFi. Revenue is obtained by charging a rate to the total flow of the agreement. Simply put, revenue refers to the total fees paid by end users of blockchain or decentralized applications. These revenues will eventually be distributed to token holders, liquidity holders and protocol libraries.

GMV (Gross merchandise volume) refers to the total flow of the agreement, which represents the transaction volume of the blockchain or the transaction volume and borrowing volume of decentralized applications. For decentralized exchanges, GMV is the total transaction volume, and for lending agreements, GMV is the total borrowing volume.The fee rate is the fee charged to GMV, which can be the transaction fee of the blockchain, the transaction fee of Dapp, or the interest rate of the loan.

Income calculation formula:GMV * Take Rate = Revenue

Total transaction volume * rate = project revenue (total fees paid)The total revenue is distributed between the agreement and its Token holders and supplier participants (miners/validators, liquidity providers, lenders, etc.). For early-stage projects, 100% of the revenue is usually distributed directly to supplier participants. In the long run, the revenue sharing model will be more diversified, and the agreement and its owners can also get a share of the total revenue.Agreement revenue represents the cash flow of the agreement. The agreement collects costs from users and is calculated as a percentage of total revenue.The difference between agreement income and income

Revenue is the amount that users pay for the use of the contracted service. These revenues are obtained by the supplier participants who provide the basic service, and the contractual revenue refers to the amount of revenue actually obtained by the Token. This actually represents the bottom value of the agreement, which is the profit margin. In other words, just as early-stage startups and growth companies do not pay dividends to shareholders, not every agreement allocates cash flow to Token.Cost refers to how much of the agreement income is used for grants, wages, and audit fees. That is, the sum of all costs and expenses paid according to the implemented on-chain governance recommendations.

Income: How much funds are distributed to Token holders as dividends, ie = agreement income-cost and difference.To sum up in one sentence, revenue is the amount that users pay to the agreement, which is mainly the income brought by the provider of the underlying service, and the agreement income is the cumulative income brought by Token. Agreement revenue represents profit and is the basis of the agreement.

The agreement income of each project depends on the fee structure of the agreement itself. Different income models complicate the calculation of agreement income. Below is an overview of the agreement revenue calculations for four NFT and DeFi projects.How is agreement income distributed to token holders?

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Perspectives of a 2x entrepreneur turned VC at @UpfrontVC#

Mark Suster

Written by

2x entrepreneur. Sold both companies (last to salesforce.com). Turned VC looking to invest in passionate entrepreneurs 〞 I*m on Twitter at @msuster

Both Sides of the Table

Perspectives of a 2x entrepreneur turned VC at @UpfrontVC, the largest and most active early-stage fund in Southern California. Snapchat: msuster

Mark Suster

Written by

2x entrepreneur. Sold both companies (last to salesforce.com). Turned VC looking to invest in passionate entrepreneurs 〞 I*m on Twitter at @msuster

Both Sides of the Table

Perspectives of a 2x entrepreneur turned VC at @UpfrontVC, the largest and most active early-stage fund in Southern California. Snapchat: msuster