AI in 2023: The Application Layer Has Arrived: Demystifying Sharding and its Technical Properties

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Aug 18, 2023

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AI in 2023: The Application Layer Has Arrived: Demystifying Sharding and its Technical Properties

Artificial intelligence (AI) has become an integral part of our lives, and its applications continue to expand rapidly. When we talk about the use cases of AI, they can be broadly categorized into two buckets: creativity and productivity. The advancements in AI have led to the development of Copilot, a tool that generates a significant portion of code in projects. It is predicted that within five years, Copilot will be responsible for 80% of code generation. However, despite these advancements, we are still in the early stages of AI applications, and it is challenging to determine the killer apps that will emerge.

As AI becomes more prevalent, companies must find ways to build competitive moats to stay ahead of the competition. True tech differentiation is rare, and companies will need to leverage network effects or iterative loops of user engagement and product refinement to maintain a competitive edge. It is anticipated that many of the most successful AI startups will be SaaS companies. However, these AI SaaS companies will face the challenge of standing out in a crowded enterprise SaaS market. They will need to offer best-in-class products to cut through the noise and capture the attention of potential customers.

While there are concerns about the capabilities of large language models and the implications they may have, it is essential to find ways to adapt to these tools rather than banning them. The younger generation, who will grow up in a world teeming with AI, needs to understand how to navigate this new landscape effectively. It is crucial to embrace the positive and humanistic aspects of AI, as it amplifies both creativity and productivity. Just as cars did not replace walking but became an engine for transportation, AI serves as an engine for the imagination.

In the world of blockchain technology, scalability has always been a challenge. The scalability trilemma states that a blockchain can have two out of three properties: scalability, decentralization, and security. Sharding, a technique that splits the work of verification among randomly selected groups of validators called committees, has emerged as a solution to this problem. Sharding is the future of Ethereum scalability and will play a crucial role in enabling the platform to handle thousands of transactions per second at an affordable cost.

Traditional blockchains rely on every participant running a full node, which limits scalability. High-TPS chains offer scalability but sacrifice decentralization. On the other hand, multi-chain ecosystems allow for decentralization and scalability but lack security. Sharding through random sampling addresses these issues by distributing the verification workload randomly among validators. This prevents attackers from concentrating their power on one shard, ensuring the security of the entire chain.

However, there are still some challenges to overcome in sharded systems. Sharded chains relying solely on committees are vulnerable to adaptive adversaries and have weaker accountability. Data availability sampling is only secure if there is a sufficient number of online clients, increasing the risk of failures under extreme networking conditions. Sharded blockchains also rely on sharded peer-to-peer networks, which are easier to attack due to fewer nodes.

Some propose an alternative to sharding, which involves a chain structured like a centralized high-TPS chain but incorporates data availability sampling and sharding for verification. While this approach may address some challenges, it introduces new vulnerabilities. Centralized infrastructure is more susceptible to censorship from external actors, and there is a higher risk of the entire chain being controlled by a few companies' cloud services.

In conclusion, AI has made significant strides in various applications, and we are only scratching the surface of its potential. Companies must find innovative ways to stay ahead of the competition and leverage the power of AI. Sharding offers a promising solution to the scalability challenges faced by blockchain technology, but it comes with its own set of challenges. As we continue to explore the possibilities of AI and blockchain, it is crucial to prioritize security, decentralization, and scalability while finding ways to mitigate potential risks.

Actionable Advice:

  • 1. Embrace AI as a tool for creativity and productivity. Explore the various AI-powered tools available in the market and leverage them to enhance your work.
  • 2. Stay updated with the latest developments in AI and blockchain. It is essential to understand the potential of these technologies and how they can impact your industry.
  • 3. Foster a culture of innovation within your organization. Encourage employees to explore new ideas and technologies, and provide them with the resources and support they need to bring those ideas to life.

In the future, AI and blockchain will continue to shape the way we live and work. By understanding their applications and potential, we can navigate this rapidly evolving landscape and harness the power of these technologies to drive innovation and growth.

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