a16z's 2024 Outlook List: Modularity, AI, Web3 Gaming...
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a16z's 2024 Outlook List: Modularity, AI, Web3 Gaming...
a16z has listed several exciting trends in the crypto industry for 2024.
Navigating Web3 tides with focused insightsWritten by: a16z
Translated by: 1912212.eth, Foresight News
Based on feedback from partners across American Dynamism, biotech, consumer tech, crypto, enterprise, fintech, gaming, infrastructure, and other fields, we present a comprehensive list of major ideas that technology builders may explore over the coming year. Below are some trends in crypto that partners find exciting for 2024.
Entering a New Era of Decentralization
As we’ve seen time and again, when control of a powerful system or platform rests in the hands of a few—or worse, a single leader—abuses of user freedom become all too easy. This is why decentralization matters: it’s a tool to democratize systems by enabling trust-minimized, composable internet infrastructure; fostering competition and ecosystem diversity; and giving users more choice and greater ownership.
In practice, however, achieving decentralization at scale has been difficult, especially when compared to the efficiency and stability of centralized systems. Meanwhile, most Web3 governance models involve DAOs using simplified but cumbersome governance frameworks based on direct democracy or corporate governance, which don’t align with the socio-political realities of decentralized governance.
Yet thanks to years of experimentation in Web3’s active labs, best practices for decentralization are beginning to emerge. These include decentralized models adapted to applications with richer functionality, as well as DAOs applying Machiavellian principles to design more effective decentralized governance that holds leadership accountable. As these models mature, we should soon see unprecedented levels of decentralized coordination, operational capability, and innovation.
—Miles Jennings, General Counsel & Head of Decentralization (@milesjennings on Farcaster | on Twitter)
Redefining the User Experience for the Future
Although the user experience in crypto has long been criticized since 2016, its fundamentals haven’t changed much. It remains overly complex: self-custodying keys; connecting wallets to dApps; signing transactions across an ever-growing number of network endpoints, and so on. We can’t expect users to learn all this within the first few minutes of using a crypto application.
Now, developers are actively testing and deploying new tools that could reset the front-end UX of crypto in the coming year. One such tool is passkeys, which simplify logging into apps and websites. Unlike traditional passwords requiring manual input, passkeys are auto-generated cryptographic credentials. Other innovations include smart accounts—making accounts themselves programmable and easier to manage; embedded wallets built directly into apps to enable frictionless onboarding; multi-party computation (MPC), allowing third parties to support signing without holding user keys; and advanced RPC (remote procedure call) endpoints that identify user needs and fill gaps automatically. Together, these advances not only help broaden Web3 adoption but can also make user experiences better and more secure than in Web2.
—Eddy Lazzarin, Chief Technology Officer (@eddy on Farcaster | @eddylazzarin on Twitter)
The Rise of Modular Tech Stacks
In the digital world, one force always dominates others: network effects. Network effects are so powerful that there are effectively only two kinds of modularity: modular designs that expand and strengthen network effects, and those that break or weaken them. Outside of rare exceptions, only the former makes sense—especially in open-source contexts.
Monolithic architectures have the advantage of deep integration and optimization across what would otherwise be modular boundaries, improving performance—at least initially. But the greatest strength of open-source, modular tech stacks lies in unlocking permissionless innovation; allowing participants to specialize; and encouraging greater competition. In this world, we need more of this.
—Ali Yahya, Partner (@alive.eth on Farcaster | @alive_eth on Twitter)
The Convergence of AI and Blockchain
Decentralized blockchains serve as a counterbalance to centralized AI. Currently, AI models like ChatGPT can only be trained and operated by a handful of tech giants because the required computing power and training data are prohibitively expensive for smaller players. But with crypto, we can create multilateral, global, permissionless markets where anyone can contribute compute or new datasets to networks in need—and get compensated in return. Leveraging this long tail of resources will lower the cost of AI and make it more accessible.
But as AI transforms how we produce information—and reshapes society, culture, politics, and economics—it also creates a flood of AI-generated content, including deepfakes. Here too, crypto can play a role: opening up black boxes; tracking the provenance of what we see online; and more. We also need ways to build generative AI in a distributed manner and govern it democratically, so no single actor ends up deciding everything for everyone else. Web3 serves as the lab for solving this problem. Decentralized, open-source crypto networks will democratize AI innovation—rather than centralizing it—and ultimately make it safer for consumers.
—Andy Hall, Stanford Professor (@ahall_research); Daren Matsuoka, Data Scientist (@darenmatsuoka on Farcaster | on Twitter); Ali Yahya, Partner (@alive.eth on Farcaster | @alive_eth on Twitter)
From 'Play-to-Earn' to 'Fun-to-Earn'
In play-to-earn games, players can earn real-world money (not just virtual rewards) based on their time and effort spent in-game. This trend ties into broader shifts transforming gaming and its surrounding ecosystem—from the rise of the creator economy to changing relationships between users and platforms. Web3 allows us to break away from the current norm where all revenue from gameplay and transactions flows solely to game companies. Users spend immense time on these platforms and generate significant value—they deserve compensation too.
But games don’t need to become workplaces (at least not for most players). What we really need are games that are both fun and allow players to capture more of the value they create. Thus, “play-to-earn” is increasingly evolving into “fun-to-earn,” drawing an important distinction between gaming and work. As play-to-earn games move beyond their initial growth phase, the dynamics governing their in-game economies will continue to evolve. Ultimately, though, this won’t be a separate trend—it will simply become part of gaming itself.
—Arianna Simpson, @AriannaSimpson
When AI Becomes the Game Designer, Crypto Provides the Guarantees
As someone who spends a lot of time thinking about the future of Web3 gaming, it’s clear to me that AI agents in games must come with guarantees: they must be based on specific models, and those models must not be tampered with during execution. Otherwise, the integrity of the game collapses.
When legends, terrains, narratives, and logic are all procedurally generated—in other words, when AI becomes the game designer—we’ll want to know the designer is credibly neutral. We’ll want confidence that this world is built on solid foundations. What crypto provides above all is exactly these guarantees—including the ability to understand, diagnose, and penalize when AI goes wrong. In this sense, AI alignment is actually an incentive design problem, just like managing any human agent—and that’s precisely what crypto excels at.
—Carra Wu, Partner (@carra on Farcaster, @carrawu on Twitter)
Formal Verification Becomes Less Formal
While formal methods are popular in verifying hardware systems, they’re less common in software development. For most developers not working on hard or safety-critical systems, these methods are too complex and can add significant cost and delay. However, smart contract developers face different demands: they build systems handling billions of dollars; vulnerabilities can have catastrophic consequences; and fixes often can’t be deployed immediately. Therefore, in software—and especially smart contract development—there’s a pressing need for more accessible formal verification methods.
Over the past year, a wave of new tools—including our own—has emerged, offering vastly improved developer experiences compared to traditional formal systems. These tools take advantage of the fact that smart contracts are architecturally simpler than conventional software—featuring atomic and deterministic execution, no concurrency or exceptions, small memory footprints, and limited loops. Their performance is also rapidly improving, leveraging recent breakthroughs in SMT solvers (which use sophisticated algorithms to detect or confirm errors in software and hardware logic). As developers and security experts widely adopt tools inspired by formal methods, we can expect the next generation of smart contract protocols to be far more robust and less vulnerable to costly hacks.
—Karma (Daniel Reynaud), Research Engineering Partner (@karma on Farcaster, @0xkarmacoma on Twitter)
NFTs Become Ubiquitous Brand Assets
More and more well-known brands are launching digital assets as NFTs to mainstream consumers. For example, Starbucks introduced a gamified loyalty program where participants collect digital collectibles while exploring the company’s coffee offerings (not to mention AR pumpkin spice mazes!). Meanwhile, Nike and Reddit have developed digital NFT collectibles explicitly marketed to broad audiences. But brands can do far more: they can use NFTs to represent and reinforce customer identity and community ties; connect physical goods with their digital counterparts; and even co-create new products and experiences with their most loyal fans.
Last year, we saw a trend toward mass collecting low-cost NFTs tied to consumer goods—often managed via custodial wallets and/or Layer 2 blockchains, keeping transaction costs minimal. As we enter 2024, the conditions are ripe for NFTs to become universally adopted digital brand assets, applicable across a wide range of companies and communities, as Steve Kaczynski and I explain in our forthcoming book.
—Scott Duke Kominers, Research Partner (@skominers on Farcaster | on Twitter)
SNARKs Go Mainstream
Historically, technologists have had a few strategies for verifying computational workloads:
1) Re-executing the computation on a trusted machine;
2) Executing the computation on specialized machines designed for the task (i.e., TEEs - Trusted Execution Environments); or
3) Running the computation on reliably neutral infrastructure, such as blockchains. Each approach comes with trade-offs in cost or scalability. But now, SNARKs (Succinct Non-interactive Arguments of Knowledge) are becoming more practical. SNARKs allow an untrusted "prover" to generate a cryptographically verifiable receipt for a computation—one that cannot be forged. In the past, generating such receipts cost ~10^9 times more than the original computation; recent advances are bringing this down to around 10^6.
Thus, SNARKs become viable whenever the initial computation provider can bear a 10^6 overhead and the end user cannot re-execute or store the original data. The resulting use cases are numerous: edge devices in IoT can verify firmware updates; media editing software can embed authenticity and transformation metadata—so meme remixes can credit their sources; LLM inferences can include provenance data; we can have self-validating tax forms, tamper-proof bank audits, and many other consumer-beneficial applications.
—Sam Ragsdale, Investment Engineer (@samrags on Farcaster, @samrags_ on Twitter)
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