GuShiio.com Supporting new architectures such as blockchain and open source AI is crucial. This is not only a technical issue, but also a regulatory and public awareness issue.
Author: a16z
Compiled by: CaptainZ
Welcome to the Web3 special article presented by a16z. This episode focuses on the integration of artificial intelligence (AI) and encryption technology (Crypto). We invited Chris Dixon, founder and managing partner of a16z Crypto, and David George, partner of a16z Growth Fund.
They will discuss in depth topics such as the shortcomings of the Internet economic model, new opportunities for creators, and the far-reaching impact of changes in large platforms.
This issue’s content stems from the cross-border collaboration of the a16z “AI Revolution Dialogue Series” and is even more significant as the paperback edition of Chris Dickson’s best-selling book “Read Write Own” is released. For more information, please refer to the links in the program description.
It should be noted that the content of this program does not constitute tax, business, legal or investment advice. Please visit a16z.com/disclosures for more important information, including our investment list.
The following is a transcript of the interview:
Host: Chris, thank you for joining our program. It’s a pleasure to communicate with you. You are currently mainly focusing on the field of encryption technology. Can you talk about your overall views on the interaction between AI and encryption technology?
Chris Dixon:
Of course, it’s a pleasure to be here. I have always believed that technology waves often appear in pairs or groups, like cloud computing, mobile Internet and Social networks over the past 15 years, reinforcing each other. The mobile Internet has popularized computing devices in the hands of billions of people, Social networks have become killer applications that attract users, and cloud computing provides the infrastructure for all this. These three are indispensable. I remember there were still people arguing about which was more important, and it turned out that they complemented each other and were indispensable.
Now, I think AI, encryption and new hardware (such as robots, autonomous vehicles, virtual reality devices, etc.) are forming the three pillars of a new wave of technology, and they will also promote each other. Encryption technology, which is the focus of my book, provides a new way of architecture for Internet services. It is not only a technology, but also a new paradigm for building networks, with many characteristics that cannot be achieved by traditional methods. I think this will be of great benefit in many areas.
Many people equate encryption technology simply with Bitcoin or memocoin, but in the eyes of me and many smart people in the industry, this is far from the essence. The intersection of AI and encryption technology takes many forms. First of all, a simple combination is the focus of our investment: using this new architecture to build AI systems. For example, a core question in the current AI field is whether AI will be in the hands of a few large companies in the future or will it be controlled by the broader community? This involves the issue of open source. I was surprised to find that over the past decade, the AI field has gone from being completely open (published papers, code sharing) to becoming increasingly closed. Big companies lock in technology on the grounds of “security”, but I think this is more for commercial interests than for real security needs.
Fortunately, there are still some open source models, such as LLaMA, Flux, and Mistral, but the extent to which they are open is still worrying. Model weights are not fully disclosed and data pipes are opaque, so it is doubtful whether these models can be truly replicated. Moreover, these open source projects often rely on the support of a single company and may be closed at any time due to strategic adjustments. As a result, we have invested in some blockchain-based Internet service stacks aimed at providing a decentralized open source infrastructure for AI. For example, the Jensen Project builds the computing layer through crowdsourcing, similar to Airbnb’s model: startups can submit computing tasks to the network, supported by people with idle computing resources, and blockchain is responsible for managing supply-demand matching and economic ledger.
Another example is the Story Protocol, which redefines how intellectual property is registered. You can create an image, a video or a piece of music and record its copyright and terms of use via blockchain. These terms are designed based on existing copyright laws and have international applicability. You can set rules, such as “Adaptations and derivative creations are allowed, provided you pay 10% of my income.” This creates an open market that replaces the traditional business model that requires one-by-one negotiation. Currently, only large companies such as Open AI can reach a billion-dollar deal with Shutterstock, and small creators are often either embezzled or ignored. Story Protocol provides an equal platform for everyone.
At the core of this model is “composability,” a common theme in the blockchain world and a concept specifically discussed in my book. It’s similar to the success of open source software. Countless people contribute small pieces of code and eventually piece together a powerful system. It is this power that Linux has grown from 0% market share in the 1990s to 90% today. The same goes for Story Protocol. You can imagine one person creating a character, another person adding new elements, and then someone mixing and mixing them, ultimately forming a superhero universe. As long as the income flows back as agreed, the creator’s incentive will be guaranteed. This model both embraces new technologies and provides creators with economic models, and is the most exciting part of the combination of AI and encryption technology for me.
Host: The new economic model you mentioned is indeed thought-provoking. David, you have said before that the emergence of ChatGPT may break some kind of contract on the Internet. Can you talk about it in detail?
Chris Dixon:
Yes, there is a chapter in my book called “The New Covenant”, which is about this. The Internet’s success is largely due to its clever incentive mechanism that allows 5 billion people to voluntarily join without the need for central authority to enforce it. Over the past 20 years, the Internet has gradually formed an implicit economic contract, especially between Social networks, search engines and content creators. Take Google as an example. Website owners allow Google to crawl content and display summaries on the premise that Google will give back traffic. Creators make money from traffic, whether it’s advertising, subscriptions or other models. This mutually beneficial relationship is the foundation of the prosperity of the Internet.
But occasionally the contract is broken. For example, Google’s “One Boxing” feature directly displays answers without skipping to the original website, which has affected companies like Stack Overflow, Wikipedia and Yelp. The user experience may be better, but creator traffic has decreased. Now the rise of AI further challenges this contract. Chatbots can directly generate illustrations or recipes without users having to click on the original website. If all AI systems operate in this way, traffic no longer flows back, and the creator’s survival foundation will be broken.
These AI systems rely on data under old contracts for training, but new models no longer follow old rules. I worry that in the future, the Internet will become a closed system dominated by three to five major companies, and billions of other websites will die due to loss of traffic. This makes me uneasy. Is the Internet going back to the radio and television model of the 1970s, with only a few channels? What is the benefit of such a world for startups, innovation and creativity? How do long-tail websites survive? How do new things break through?
I’m not saying that encryption is the only solution, but at least we have to admit that the status quo breaks the existing incentives and think about whether that’s a good thing. If not, how should we design new mechanisms? Story Protocol is an attempt to rebuild an incentive system for creators through blockchain.
Host: You mentioned that AI, encryption technology and new hardware are trinity that reinforce each other. Can you talk specifically about how they work together?
Chris Dixon:
Of course. Take the mobile Internet, Social networks and cloud computing as examples. They make each other something. The same is true for today’s AI, encryption technology and new hardware. You can already see some clues, such as the extensive use of AI technology in AR/VR glasses and self-driving cars, and companies such as Tesla are also beginning to show their edge in the field of humanoid robots. These technologies bring AI into the real world and open up new application scenarios.
On the side of encryption technology, I am particularly optimistic about an area called DePIN (decentralized physical infrastructure). Take Project Helium, a community-owned, crowd-sourced telecommunications network that challenges the traditional models of Verizon and AT T. Users install Helium nodes (wireless transmitters) at home to contribute coverage to the network. There are currently hundreds of thousands of nodes across the United States, providing much cheaper services than traditional carriers ($20 per month vs.$70). This is feasible because it uses encryption technology to design incentives that avoid billions of network construction costs for traditional operators.
The most difficult part of network construction is the start-up stage, because in the early days, the network effect was weak, just like a dating website, where 10 users and no one used it, only one million users would be useful. Cryptography solves this problem through token incentives, where early participants are rewarded, driving network expansion. DePIN’s ideas are not limited to telecommunications, but also extend to fields such as climate modeling, map data, and electric vehicle charging. For example, one of the projects we recently invested in is a decentralized energy monitoring network, and others use similar methods to do decentralized science. The early construction of such networks was naturally suitable for encryption technology, and AI could cooperate with it in data collection and processing.
Host: The stage of technological development is also critical. How do you view the evolution of AI?
Chris Dixon:
I like to use a framework to analyze technological development, which is divided into three stages: one is “skeuomomorphic”, which uses new technology to improve existing things; the other is “native”, which creates things that were impossible before; and the third is “second-order effects”, the far-reaching changes triggered by the popularization of technology.
Take the Internet as an example. The 1990s were the first stage. People moved magazines and catalogs online. Amazon sold books more easily than reading magazines, but the essence was still a new form of old things. In the 2000s, Social networks emerged. These were truly native applications with no offline counterparts and a brand new business model. AI is similar. The first stage is the common “old things and new things” now, such as replacing call centers with AI customer service, which is cheap and efficient, may affect tens of millions of jobs, but may also create more new opportunities. This phase may last for 20 years.
The second stage is the “native” stage, which really excites me. For example, after the popularization of photography, art turned to abstraction (such as cubism), and at the same time gave birth to a new art form called film. The same is true for today’s generative AI. Some people think it threatens creativity, but I don’t see it that way. It could be the cornerstone of new art forms, like virtual worlds, new games or movies, and perhaps new interfaces. These innovations require talented creative people to achieve and are often unexpected. Just as movies opened up new horizons back then, AI may also bring similar breakthroughs.
The third stage is the “second-order effect”. After the rise of Social networks, Obama used it to win the election in 2008 to mark a turning point. Subsequently, phenomena such as the Trump movement and populism emerged one after another. These are second-order effects and are still evolving today. The second-order effect of AI may not fully manifest itself until 20-30 years later, and each stage may last for ten years.
Host: What are the limiting factors in the transition from the first stage to the second stage?
Chris Dixon:
The Internet was limited in the early days by physical network construction, such as laying cables. The limitations of AI are different. Technical capabilities are no longer the main bottleneck, but human creativity and policies and regulations. The supply side needs creative talents to develop native applications. In this regard, the current entrepreneurial ecosystem is much more mature than 15 years ago. The number of venture capital institutions has increased from dozens to thousands. The entrepreneurial advice is better, and it is easier for smart people to enter this field. Capital and energy is abundant.
But the demand side is more challenging. Changes in organizational and personal behavior take time. For example, I wanted to use AI to read my book and imitate my voice, but the publishing house and Audible completely banned AI due to trade unions and traditional concepts. It may take a generation for Hollywood to embrace AI-native films, and it may have to be driven by AI startups in emerging countries. The policy level is more complex, and regulated industries such as copyright, medical care, and finance, which account for 70% of the economy, will face fierce controversy. Is AI training data “copied” or “learned”? This may ultimately be resolved by congressional legislation rather than a free market or court ruling.
Host: What is your ideal future for the Internet?
Chris Dixon:
We are at a crossroads. The original vision of the Internet is community ownership, community governance, and benefits flowing to small businesses, innovators and entrepreneurs at the edge of the network. But today, wealth and power are concentrated in the hands of a few large companies, and the five major technology giants account for more than half of the market value. The first sentence in the book is “The structure determines the destiny.” Control and capital flow depend on the way the service is designed.
I worry that we are approaching an irreversible tipping point where the Internet is monopolized by five companies. They have saturated user growth and are now starting to “kick the ladder” and hinder newcomers. This poses a huge threat to “little tech”. If startups have to pay huge “taxes” to giants to compete, they cannot challenge the status quo. We have seen similar cases in the past, such as Zynga, which relies on Facebook, ultimately suffers from platform risks.
Host: Thank you, Chris, it was a pleasure to talk to you.
Chris Dixon:Thanks for the invitation, it was a great chat!
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