The growth of cryptocurrency agents driven by AI concerns a well -known trajectory, which reflects the initial boom, support and rebirth of projects from the time of ICO. Like the early Blockchain projects, they bloomed at noise, before balanced ecosystems occur, the current wave of projects of AI agents undergo rapid market changes.
The modern HTX Ventures and HTX Research report says that investors are becoming cautious because the competition in the sector intensifies, distracts fluidity and many projects are trying to define clear cases of apply. Despite this, when the sector goes beyond the speculative phase, it is expected that cryptocurrency agents based on AI are evolving sustainable business models based on true utility.
To delve into the evolution of cryptographic agents and the future of blockchain innovation supported by AI, download the full HTX report here.
From the noise meme to reality: the evolution of cryptographic agents
The initial wave of cryptocurrency agents projects in 2024 was powered by mass enthusiasm for AI projects. After the influence of Bitcoin donation in the amount of USD 50,000 from March Andreessen in October 2024 and the success of tokens at the beginning of the year, many AI projects entered space in the first quarter of 2024, and quickly diluted liquidity in the first quarter of 2025. You have a sector agent He followed them.
The market segment is currently entering a more mature phase, and focusing from speculative emotions on generating revenues and product performance. The winners of this developing landscape will be those that can generate stable revenues, cover the costs of launching AI models and provide concrete value to both users and investors.
AI agents applications emphasize the implementation and commercialization of this technology, especially in areas such as automated trade, assets management, market analysis and transition interaction. This approach is in line with the systems of many agents and Defai (Decentralized finances + AI) initiatives such as Hey AnonIN Griffain AND Caingpt.
The last most critical information Advantages of systems of many agents (masses) in portfolio management, especially in cryptocurrency investments. Projects such as Griffain, Neur and Buzz have already shown how artificial intelligence can aid users interact with DEFI protocols and make informed decisions. Unlike one -off AI models, multi -stage systems apply cooperation between specialized agents to enhance the analysis and market of market. These agents operate in teams such as data analysts, risk evaluators and trade implementation units, each trained to handle specific tasks.
Framework masses also introduce the mechanisms of inter -Avaled communication, in which agents in the same team improve forecasts through collective learning, reducing errors in the analysis of market trends. The next DEFAI phase will probably include deeper integration of decentralized management models, in which many agents systems participate in the management of protocols, treasure optimization and enforcement of provisions on compliance with Onchain.
To delve into the evolution of cryptographic agents and the future of blockchain innovation supported by AI, download the full HTX report here.
Deepseek-R1: A break in the training of AI agents
A breakthrough in the technology of AI from Deepseek-R1 appeared, an innovation that questions established AI training methods. Unlike previous models, which were based on supervised tuning (SFT), followed by reinforcement learning (RL), Deepseek-R1 adopts a different approach, completely optimizing the learning of strengthening without the initial supervised phase. This change has led to an extraordinary improvement in the possibility of reasoning and adaptive abilities, paving the way for more sophisticated cryptographic agents powered by AI.
To understand this paradigm change, consider two different approaches to science. In the established SFT and RL model, the student first studies from the workbook, exercises problems with established answers (SFT), and then receives tutoring to improve their understanding (RL). Unlike the Deepseek-R1 model (learning pure reinforcement), the student is thrown directly on the exam and learns through test and errors. This approach allows the student to dynamically improve based on feedback, and not rely on previously defined answers.
Using the pure RL Deepseek-R1 model, AI agents learn through test and errors in real conditions, dynamically adjusting their strategies based on immediate feedback.
This method allows for greater adaptability, which makes it particularly useful in AI multilevel systems in DEFI, in which real -time fluctuations in real time require agents to make autonomous decisions based on data. For example, AI -powered agents can monitor liquidity pools, detect arbitration capabilities and optimize asset asset based on real time. These agents quickly adapt to market fluctuations, ensuring more effective implementation of capital.
Idegen introduced at the end of November 2024 is the first cryptographic agent built on Deepseek R1. This integration of the R1 Deepseek model He emphasizes how cryptography agents can inherit such improved reasoning opportunities, competing with other agreed AI models behind a fraction of costs.
This shift towards AI with many AI agents in AI AI in DEFI emphasizes why AI models closed (such as operai -based systems) become an unbalanced expense. Because work flows often require processing over 10,000 tokens into a transaction, closed AI models impose significant calculation costs, reducing scalability. In contrast, RL models of Open Source, such as Deepseek-R1, allow for a decentralized, profitable AI study adapted to DEFI applications.
The future of AI agents in Web3
The key to longevity in this sector is constant innovation, adaptability and cost efficiency. AI Open Source models, such as Deepseek-R1, reduce entry barriers, enabling blockchain to develop specialized AI solutions. Meanwhile, progress in Defai and many agents will enhance long -term integration between AI and decentralized finances.
Take -out is clear: projects must prove their value outside the noise. Those who develop sustainable economic models and apply the latest AI progress, define the future of bright blockchain ecosystems. The era of ICO cryptocurrency agents is evolving, and another wave of winners will be those that can transform innovations into a long -term life.
To delve into the evolution of cryptographic agents and the future of blockchain innovation supported by AI, download the full HTX report here.
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