David and Goliath: How Web3 Can Compete in AI

The compute and training layers of the AI-industrial-complex are currently dominated by centralized Web2 giants that have unparalleled access to capital, state-of-the-art hardware, and vast datasets. While this will likely remain the case for the most powerful general ML models, mid-tier and bespoke models may increasingly source their compute resources from more affordable and accessible Web3 networks. Similarly, for inference needs that exceed the capabilities of personal edge devices, some consumers may turn to Web3 networks for less censored, more diverse outputs. Rather than attempting to overhaul the entire AI stack, Web3 challengers should focus on these niche use cases, and lean more heavily into their unique value proposition around censorship-resistance, transparency, and social verifiability.

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Eclipse: the Best of Solana, Ethereum, and Celestia

One way to think of the design choices within the layers is the lower down the stack we go, the more we need small machines to be able to verify the truth. By ‘small machines’ we mean a set of requirements that are widely achievable, allowing nearly anyone to verify the truth if they so desire, keeping collusion at bay. So long as these smaller machines are publishing and verifying “the truth,” then bigger machines can run execution at levels higher up the stack, achieving greater performance but not sacrificing decentralization where it matters. Intriguingly, this design means Eclipse’s transaction throughput capacity could surpass that of the Solana L1, allowing it to be home to a diverse ecosystem of its own. 

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Stable Coins, Stable Growth

The core function of blockchain networks is to securely process and maintain timestamped information records. In principle, this can be any kind of data, but the most typical example is information related to financial balances and transactions. The simplest, most common financial transaction is payment and, while most blockchains today serve multiple use cases, processing transfers of nominal units of value – such as when paying for goods, services, or other cryptoassets – remains an essential use case for all major networks. But while successful blockchains are already dominant payment networks in some niche markets, their success for everyday payments at scale is much more strongly tied to government-regulated fiat as opposed to cryptocurrencies.

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Is it time to Move beyond Solidity?

The EVM has been the most popular blockchain operating system since Ethereum launched almost a decade ago. However, few developers love developing with its native programming language, Solidity; some even compare the experience to “chewing glass.” Nevertheless, entrepreneurs choose it because it facilitates access to Ethereum’s users, assets, and liquidity. But if we want to have 10x the number of onchain applications, we must have 100x the number of developers able to build them. To do that, we have to make it much easier for the average programmer to write sophisticated smart contracts while increasing the security and scalability properties of the underlying infrastructure. That’s the central promise behind the Move programming language and the emerging ecosystem of networks that employ it.

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Saga: Open Blockspace for the Multiverse

Saga’s virtual blockchains are called Chainlets, and Chainlets are designed to be dedicated to single applications, though they could host multiple applications if preferred. Each Chainlet is a fully decentralized, proof-of-stake chain with all the properties of a L1, except the requirement for a native staking token. Current throughput of each Chainlet is 6.8 million transactions/day, or ~80 transactions/second (TPS). If an application needs more throughput, additional Chainlets are spun up to accommodate the surge in demand, allowing for elastic scaling that grows infinitely with the application’s performance needs. 

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Onchain Finance is Thriving; What’s Next?

Decentralized public blockchain networks have existed for ~15 years with the associated cryptoassets currently going through their fourth major market cycle. Throughout these years, and especially since the launch of Ethereum in 2015, considerable time and resources have been spent theorizing about and developing applications on top of these networks. While progress has been impressive in the context of financial use cases, other types of applications have struggled, mainly due to the complexity of delivering scalable and seamless user experiences within the constraints imposed by decentralization, as well as fragmentation across different ecosystems and standards. However, recent technological advancements, both within and outside the blockchain industry, have made a broader range of applications not only more feasible, but also more necessary than ever.

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Introducing Gurnoor Singh Narula

At Placeholder, I hope to relate the blockchain revolution to historical technological trends as I explore how the methods of past technological evolutions are mirrored (and can be utilized) within this cycle. More specifically, I’ll be focusing my research interests on exploring the Institutional DeFi stack, the development of on-chain treasuries, and the modular vs. monolithic debate. I’ll also start tackling the intersection of game-theoretic auction design, consensus, and MEV, while researching LVR mitigation and methods that increase LP profitability, especially with the imminent launch of Uniswap v4. On top of all of this interesting work, I’ll keep in touch with my engineering roots as I explore zk-enabled tech (everything from zkVMs to zkApps, and more) as applied research and applications catch up to the theoretical use cases being explored. 

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