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 cryptocurrency technology is entering an experimental phase akin to a "Cambrian explosion." This article by the Solana Foundation elaborates on three key development directions for the AI + crypto fusion.
TLDR.
1. Build 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 continually pushing the boundaries of agent operations on-chain, which not only holds immense potential but also has a vast design space. This has already become one of the most groundbreaking and explosive directions in the fields of crypto and AI, and this is just the beginning.
2. Enhance LLMs' capabilities in Solana code development.
Large language models have already demonstrated excellent performance in code writing and will continue to improve in the future. With these capabilities, the efficiency of Solana developers is expected to increase by 2-10 times. Recently, establishing high-quality benchmarks to evaluate LLMs' understanding and writing capabilities for Solana code will help understand the potential impact of LLMs on the Solana ecosystem. High-quality model fine-tuning programs will be validated in the benchmark tests.
3. Support an open and decentralized AI technology stack.
"Open and Decentralized AI Technology Stack" includes the following key elements:
Training Data Acquisition
Training and Inference Computing Capacity
Model Weights Sharing
Model Output Verification Capability
The importance of this open AI technology stack is reflected in:
Accelerate model development innovation and experimentation.
Provide alternatives for users who distrust centralized AI.
1. Build the most vibrant AI agent-driven economy.
There has been much discussion about Truth Terminal and $GOAT, so there’s no need to elaborate here. But it is certain that when AI agents begin to participate in on-chain activities, a world full of possibilities will unfold (notably, agents have not yet directly acted on-chain).
While 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 vast potential 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 based on the personality characteristics of well-known crypto investors are emerging, with the rapid rise of ai16z on the daos.fun platform, creating a new ecosystem of AI funds and agent supporters.
Additionally, gaming platforms like Colony allow players to participate in games by guiding agent actions, often resulting in unexpected innovative gameplay.
Future Development Directions.
In the future, intelligent agents could manage complex projects that require multi-party economic coordination. For example, in the field of scientific research, agents could be responsible for finding therapeutic compounds for specific diseases. Specifically:
Token fundraising through the Pump Science platform.
Using the raised funds to pay for access to paid research materials and for computational expenses for compound simulations on decentralized compute networks like kuzco, Render Network, io.net, etc.
Recruit human participants for experimental verification tasks through bounty platforms like Gib.Work (e.g., running experiments to verify/establish simulation results).
Beyond complex projects, agents can also perform simple tasks such as building personal websites and creating artworks (like zerebro), with infinite application scenarios.
Why does it make more sense for agents to perform financial activities on-chain rather than using traditional channels?
Agents can fully utilize both traditional financial channels and cryptocurrency systems simultaneously. However, cryptocurrencies have unique advantages in certain areas:
Micro-payment applications — Solana excels in this regard, as demonstrated by applications like Drip.
Speed Advantage — Instant settlement capabilities help agents achieve maximum capital efficiency.
Entering capital markets through DeFi — this might be the strongest rationale for agents participating in the crypto economy. The advantages of cryptocurrencies become even more evident when agents need to carry out financial activities beyond payments. Agents can seamlessly mint assets, trade, invest, lend, use leverage, etc. Especially Solana, which already has numerous top-tier DeFi infrastructures on its mainnet, is particularly suited to support these capital market activities.
From the perspective of technological development laws, path dependency plays a critical role. Whether a product is optimal is not the most important factor; what matters is who can reach critical mass first and become the default choice. As more and more agents earn income through cryptocurrencies, encrypted connections are likely to become a core capability of agents.
The foundation hopes to see.
The Solana Foundation hopes to see agents equipped with crypto wallets conducting bold innovative experiments on-chain. The foundation does not overly limit specific directions here, as the possibilities are indeed too broad — it is believed that the most interesting and valuable agent application scenarios are likely to be unforeseen at present.
However, the foundation is particularly focused on exploring the following directions:
1. Risk Control Mechanism
Although the current models perform excellently, they are still far from perfect.
Cannot give agents completely unconstrained freedom of action.
2. Promote non-speculative use cases.
Purchase tickets through xpticket
Optimize Stablecoin Portfolio Yields.
Order food on DoorDash.
3. Development Progress Requirements.
At least reach the prototype stage of the testnet.
Ideally already operational on the mainnet.
2. Enhance LLMs' capability to write Solana code, empowering Solana developers.
LLMs have demonstrated powerful capabilities and are progressing rapidly. Among the application areas of LLMs, coding may see particularly steep advances, as it is an objectively assessable task. As noted below, "programming has unique advantages: the potential for superhuman data scaling through 'self-play.' The model can write code and run it, or write code, create tests, and then check for self-consistency."
Today, while LLMs are still not perfect at writing code and have noticeable deficiencies (such as poor performance in bug discovery), AI-native code editors like Github Copilot and Cursor have fundamentally changed software development (even changing how companies recruit talent). Given the expected rapid rate of progress, these models are likely to revolutionize software development. The foundation hopes to leverage this advancement to significantly enhance the work efficiency of Solana developers.
However, several challenges currently hinder LLMs from achieving excellence in understanding Solana:
Lack of high-quality raw training data.
Insufficient number of verified builds.
Lack of high-value interactions on platforms like Stack Overflow.
Historically, Solana's infrastructure has developed rapidly, meaning that even code written six months ago may not fully meet today’s needs.
Lack of methods to assess models' understanding of Solana.
The foundation hopes to see.
Help obtain better Solana data on the internet.
More teams releasing verified builds.
More people in the ecosystem actively asking good questions and providing high-quality answers on Stack Exchange.
Create high-quality benchmarks for evaluating LLMs' understanding of Solana (RFP to be released soon).
Create LLM fine-tuning models that perform well on the above benchmarks. More importantly, accelerate the work efficiency of Solana developers. Once high-quality benchmarks are established, the foundation may offer rewards for the first model to reach the benchmark threshold score.
The ultimate significant achievement will be: a completely AI-created, high-quality, differentiated Solana validator node client.
3. Support open and decentralized AI technology stack.
In the AI field, the long-term power balance between open-source and closed-source models remains unclear. There are indeed arguments that support closed-source entities will continue to maintain a technological edge and capture the primary value of foundational models. The simplest expectation currently is to maintain the status quo — tech giants like OpenAI and Anthropic pushing the frontier, while open-source models quickly follow 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:
Training Data
Training and Inference Computing Power
Model Weights
Model Output Verification Capability
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 demonstrate how the community can effectively complement the work of large AI companies and push the boundaries of AI capabilities (even a Google researcher pointed out last year that "we have no moat regarding open source, and OpenAI does not either"). The foundation believes that a thriving open-source AI technology stack is crucial for accelerating progress in this field.
2. Provide choices for users who distrust centralized AI.
AI may be the most powerful tool in the arsenal of dictatorial or authoritarian regimes. State-sanctioned models provide officially recognized "truths," serving as an important control vector. Highly authoritarian regimes may possess superior models because they are willing to overlook citizen privacy to train AI. The trend of using AI for control is inevitable, and the foundation hopes to prepare for this by fully supporting the open-source AI technology stack.
Several projects in the Solana ecosystem are already supporting an open AI technology stack:
Data Collection - Grass and Synesis One are advancing data collection.
Decentralized Computing Power - kuzco, Render Network, io.net, Bless Network, Nosana, etc.
Decentralized Training Framework - Nous Research, Prime Intellect.
The foundation looks forward to seeing.
Hope to build more products at all levels of the open-source AI technology stack:
Decentralized Data Collection: e.g., Grass, Datahive, Synesis One
On-chain Identity: Protocols that support wallet verification of human identity and verify AI API responses, allowing users to confirm they are interacting with LLMs.
Decentralized Training: Projects similar to EXO Labs, Nous Research, and Prime Intellect.
IP Infrastructure: Enabling AI to license (and pay for) the content it uses.
