Original Title: "Focus areas at the intersection of crypto and AI"

Original Author: Kuleen, Head of DePIN at Solana Foundation

Compiled by: Yuliya, PANews

Currently, the intersection of AI and crypto is entering an "Cambrian explosion" experimental stage. This article details the three key development directions of the AI + crypto fusion by the Solana Foundation.

TLDR

1. Building the most vibrant AI-agent-driven economy on Solana

Truth Terminal has already proven the feasibility of AI agents operating on-chain. Experiments in this field are constantly pushing the boundaries of agent on-chain operations, and this area not only has huge potential, but also a very wide design space. This has already become one of the most breakthrough and explosive directions in the crypto and AI fields, and this is just the beginning.

2. Enhancing LLM's capabilities in Solana code development

Large language models have already performed excellently in code writing, and their capabilities will continue to improve in the future. Through these capabilities, the efficiency of Solana developers is expected to increase 2-10 times. In the near future, establishing high-quality benchmarks to evaluate LLMs' understanding and writing of Solana code will help understand the potential impact of LLMs on the Solana ecosystem. High-quality model fine-tuning schemes will be validated in the benchmark tests.

3. Supporting an open and decentralized AI technology stack

The "open and decentralized AI technology stack" contains the following key elements:

• Data acquisition for training

• Training and inference computing capabilities

• Model weight sharing

• Model output verification capabilities

The importance of this open AI technology stack is reflected in:

• Accelerating model development innovation and experimentation

• Providing alternatives for users who do not trust centralized AI

1. Building the most vibrant AI-agent-driven economy

There has been a lot of discussion about Truth Terminal and $GOAT, so there is no need to go into details here. But it is certain that a world full of possibilities has opened up when AI agents start participating in on-chain activities (it is worth noting that agents have not yet taken direct action on-chain).

Although it is currently impossible to accurately predict the future development of agent behavior on-chain, by observing the innovations that have already occurred on Solana, we can glimpse the broad prospects of this design space:

• AI projects like Truth Terminal are developing new digital communities through MEME coins like $GOAT

• Platforms like Holoworld AI, vvaifu.fun, Top Hat AI, and Alethea AI allow users to easily create and deploy intelligent agents and their associated tokens

• AI fund managers trained on the personality traits of famous crypto investors are emerging, and the rapid rise of ai16z on the daos.fun platform has created a new ecosystem of AI funds and agent supporters

• In addition, game platforms like Colony allow players to participate in the game by guiding agent actions, often resulting in unexpected innovative gameplay.

Future Development Direction

In the future, intelligent agents can manage complex projects that require multi-party economic coordination. For example, in the field of scientific research, agents can be responsible for finding therapeutic compounds for specific diseases. Specifically:

• Raise tokens through the Pump Science platform

• Use the raised funds to pay for access fees to paid research materials, and compute the simulation costs on decentralized computing networks like Kuzco, Render Network, and io.net

• Recruit humans to perform experimental verification work (e.g., run experiments to validate/establish simulation results) through platforms like Gib.Work

In addition to complex projects, agents can also perform simple tasks such as building personal websites and creating artistic works (like zerebro), with unlimited application scenarios.

Why is it more meaningful for agents to perform financial activities on-chain than through traditional channels?

Agents can certainly use both traditional financial channels and cryptocurrency systems simultaneously. However, cryptocurrencies have unique advantages in certain areas:

• Micropayment applications - Solana excels in this area, and applications like Drip have already proven this

• Speed advantage - Instant settlement functionality, which helps agents achieve maximum capital efficiency

• Access to capital markets through DeFi - This may be the most powerful reason for agents to participate in the crypto economy. When agents need to engage in financial activities beyond just payments, the advantages of cryptocurrencies become more apparent. Agents can seamlessly mint assets, trade, invest, lend, use leverage, etc. Especially on Solana, with its many top-notch DeFi infrastructures already on the mainnet, it is particularly suitable for supporting these capital market activities.

From the perspective of technological development, path dependence plays a key role. It is not the most optimal product that is most important, but rather who can first reach critical mass and become the default choice. As more and more agents earn returns through cryptocurrencies, crypto connectivity is likely to become a core capability for agents.

What the Foundation hopes to see

The Solana Foundation hopes to see agents equipped with crypto wallets boldly experiment with innovations on-chain. The Foundation does not overly constrain specific directions here, as the possibilities are truly too broad - the most interesting and valuable agent use cases are likely to be those that are currently unforeseeable.

However, the Foundation is particularly focused on exploring the following directions:

1. Risk control mechanisms

• Although current models perform well, they are still far from perfect

• Cannot give agents completely unconstrained freedom of action

2. Promoting non-speculative use cases

• Purchasing tickets through xpticket

• Optimizing stablecoin investment portfolio returns

• Ordering food on DoorDash

3. Development progress requirements

• At least reach the prototype stage on the testnet

• Preferably already running on the mainnet

2. Enhancing LLMs' ability to write Solana code, empowering Solana developers

LLMs have already demonstrated powerful capabilities and are progressing rapidly. Among the application areas of LLMs, the field of code writing may see an especially steep progress curve, as this is a task that can be objectively evaluated. As mentioned below, "programming has a unique advantage: the potential for superhuman data expansion through 'self-play'. Models can write code and run it, or write code, write tests, and then check self-consistency."

Today, although LLMs are still not perfect in writing code, with obvious shortcomings (e.g., poor bug detection), AI-native code editors like Github Copilot and Cursor have already fundamentally changed software development (even changing the way companies recruit talent). Considering the expected rapid rate of progress, these models are likely to completely transform software development. The Foundation hopes to leverage this progress to increase the efficiency of Solana developers by an order of magnitude.

However, there are currently several challenges that hinder LLMs from reaching excellence in understanding Solana:

• Lack of high-quality original training data

• Insufficient number of verified builds

• Lack of high-value interactions on platforms like Stack Overflow

• The rapid development of Solana's infrastructure in the past, meaning that even code written 6 months ago may not be fully suitable for today's needs

• Lack of methods to evaluate the model's understanding of Solana

What the Foundation hopes to see

• Help acquire better Solana data on the internet

The ultimate major achievement will be: a completely AI-generated, high-quality, differentiated Solana validator client.

3. Support an open and decentralized AI technology stack

In the field of AI, the long-term balance of power between open-source and closed-source models remains unclear. There are indeed some arguments supporting the notion that closed-source entities will continue to maintain technological leadership and capture the primary value of base models. The current simplest expectation is to maintain the status quo - tech giants like OpenAI and Anthropic drive frontier development, while open-source models quickly catch up and gain unique advantages through fine-tuning in specific application scenarios.

The Foundation is committed to closely integrating Solana with the open-source AI ecosystem. Specifically, this means supporting access to the following elements:

The importance of this strategy is reflected in:

1. Open-source models accelerate innovation and iteration

The rapid improvement and fine-tuning of open-source models like Llama by the open-source community has demonstrated how the community can effectively complement the work of large AI companies and push the boundaries of AI capabilities (even with a Google researcher pointing out last year that "we don't have a moat around open-source, neither does OpenAI"). The Foundation believes that a thriving open-source AI technology stack is crucial to accelerating progress in this field.

2. Providing choices for users who do not trust centralized AI

AI may be the most powerful tool in the arsenal of authoritarian or totalitarian regimes. State-sanctioned models provide an official "truth" recognized by the authorities, which is an important control mechanism. Highly authoritarian regimes may have superior models because they are willing to disregard citizen privacy to train AI. The use of AI for control is an inevitable trend, and the Foundation hopes to be prepared and fully support the open-source AI technology stack.

There are already multiple projects in the Solana ecosystem supporting the open-source AI technology stack:

The Foundation looks forward to

Hoping to build more products at all levels of the open-source AI technology stack: