Introduction

Web3 is a dynamic ecosystem that constantly evolves with the emergence of new technologies. Most recently, the consolidation of cryptocurrency and Artificial Intelligence (AI) gave birth to a new discovery known as Decentralized Finance Artificial Intelligence (DeFAI).

AI has been a tool for optimizing operations on the blockchain, doing this autonomously without manual intervention. AI algorithms help identify patterns, predict market trends, and execute transactions and processes with high speed and precision. This has helped create smart lending protocols, flexible risk assessment models, dynamic gaming ecosystems, and self-optimizing liquidity pools.

At the forefront of this automation process in blockchain is DeepSeek, an open-source multilingual large language model (LLM) that helps deploy smart and efficient AI agents, reducing workflows at a competitively low cost.

What is DeepSeek?

Source: DeepSeek

DeepSeek is an advanced open-source large language model (LLM) built by Hangzhou DeepSeek Artificial Intelligence Basic Technology Research Co., Ltd. It is designed as a multilingual AI model trained in English and Chinese, giving it access to data from both English—and Chinese-speaking communities.

DeepSeek Models

Source: Inferless

On November 2, 2023, DeepSeek released its first model, DeepSeek Coder, designed to help developers generate, complete, and debug various programming languages. Since then, several models have been launched, such as DeepSeek-Prover, DeepSeek-LLM, DeepSeek-MoE, DeepSeek-Math, DeepSeek-VL, DeepSeek-R1, and recently, Janus.

DeepSeek Founder

Source: The Economist

DeepSeek was launched in July 2023 by Liang Wenfeng, a Chinese entrepreneur and a Zhejiang University alumnus renowned for his expertise in solving problems using machine language and artificial intelligence.

Earlier in his career, Liang founded a tech solution, High Flyer, that utilizes AI and mathematics to streamline quantitative investment and trading. High Flyer later became a hedge fund company and a major backer of the LLM, DeepSeek.

DeepSeek’s hiring policy prioritizes technical abilities rather than work experience, so most new hires are either young graduates or developers with less-established AI careers.

Main Features of DeepSeek

DeepSeek models are uniquely designed for efficiency and scalability, matching the pace of other LLMs in the AI ecosystem. Notable features of DeepSeek include:

Open-Source

Source: GitHub - DeepSeek-R1

DeepSeek is keen on open-source contributions, which allow developers to use and customize their models freely. Its open-source mechanism is “open weight,” which provides less freedom for modification than other open-source software.

Cost Efficiency

Source: Business Insider

For owners and developers, DeepSeek’s models’ development and integration costs are significantly lower than those of its competitors, notably Open AI’s Chat GPT.

The DeepSeek-R1 model was reportedly developed for approximately $6 million, compared to the billions spent by other companies to build their AI models. Due to this low development cost, DeepSeek models have one of the most competitive LLM integration costs, making it easy for developers to build solutions using its infrastructure.

User-Friendly Design

Source: DeepSeek

The DeepSeek application offers a chatbot interface similar to ChatGPT. It allows users to engage in natural language conversations and generate content. The application also enables users to solve complex problems for free using its DeepThink (R1) model.

DeepSeek Architecture

DeepSeek adopts a unique infrastructure that has made it distinct from other large language models. This advanced architecture has contributed to the efficiency and effectiveness of the model. Key components include:

Mixture-of-Expert (MoE) System

MoE systems allow necessary neural networks to be activated to execute specific tasks. Despite DeepSeek’s extensive scale and parameter count, it operates with only a few parameters during operation. This selective activation optimizes resource utilization, reducing computational costs while maintaining efficiency.

This system also ensures that tasks are executed with precision since it handles various inputs with accuracy, making DeepSeek a practical tool for developers who want to balance cost-efficiency with high performance.

Multi-Head Latent Attention (MLA)

DeepSeek deploys MLA mechanism that improves its ability to process data by identifying nuanced relationships and handling multiple input aspects simultaneously. This system ensures better task performance by focusing on specific details across diverse inputs.

What are AI Agents?

AI Agents are autonomous software programs powered by large language models (LLMs) to reason, make decisions, execute tasks, and interact with decentralized applications (dApps) on blockchains.

Source: CoinGecko

Once given a task to execute, AI agents deploy LLM to gather data on it, feed it into the model to analyze, extract necessary information, make a decision, and take the required action. They learn in the process of undertaking an action and can repeat it.

For instance, an AI agent can learn from market trends and sentiments in real-time, deploy liquidity based on preset conditions, and execute trades with precision. This interaction between the AI agent and the blockchain network is done autonomously without human intervention.

The Impact of DeepSeek in Crypto and AI Agents

DeepSeek plays a crucial role in consolidating the integration of artificial intelligence within the crypto industry. Its key contributions and impacts include:

Low Costs

Due to its friendly integration cost, DeepSeek has made it easy for developers to create solutions that creatively solve real problems.

Lower costs also contribute to the decentralization of AI-powered blockchain solutions by enabling multiple competing solutions to address the same challenges, providing users with diverse options.

Personalized Virtual Experiences

DeepSeek-powered AI agents can study user preferences and behaviors to provide custom virtual experiences to GameFi and Metaverse users.

In GameFi, these agents analyze users’ needs to power flexible non-player characters (NPCs) with realistic game behaviors. They help create immersive gaming experiences by engaging in dynamic conversations, adapting to player’s actions in real-time, and generating in-game content, such as quests and storylines.

In Metaverse, AI agents assess users’ preferences to create personalized virtual assets (such as NFTs and avatars). They also help individuals navigate virtual environments and facilitate social interactions.

Advanced AI Capabilities

Traders can use DeepSeek’s advanced emotionally intelligent models, such as DeepSeek-R1, to research and obtain real-time data on their crypto portfolio. Developers of AI agents can integrate these models into their software to enhance their capability.

Increased Accessibility

Due to its open-weight model, crypto platforms, such as centralized exchanges (CEXs), can easily integrate DeepSeek LLMs into their apps to enhance user operations and optimize overall functionality.

Increased Market Volatility

The emergence of DeepSeek has also driven a surge in investment within the AI agent market, as stakeholders and investors recognize AI’s potential to disrupt the Web3 ecosystem. This development has also prompted the evaluation of current AI agent projects and strategies for optimizing the value they provide.

Driving Innovation

DeepSeek has helped drive competition in the LLM space. This has spurred users of their APIs to creatively apply the models to provide solutions that streamline operations on the blockchain.

The open-source nature of DeepSeek has also helped its constant evolution, paving the way for the future launch of more efficient large language models (LLMs).

Benefits and Risks of DeepSeek in Crypto and AI Agents

Integrating DeepSeek into the crypto space presents both opportunities and challenges for developers and users.

Benefits

On-Chain Forensics

Given the vast amount of data recorded on the blockchain, AI can serve as an advanced monitoring tool, detecting unusual movement of funds, tracking high-risk addresses, and analyzing market trends to generate actionable insights.

Enhanced Immersion

With data gathered from individual preferences, AI agents help match users with personalized virtual opportunities based on their skills and interests on GameFi and Metaverse. This includes creative economic models such as customized rewards that enable engaging ecosystems.

Smart Analysis and Streamlined Interactions

DeepSeek can be used to forecast bullish and bearish market trends by studying historical and real-life data. It also helps evaluate news and social media forums to detect market sentiments and manipulations while giving insights on trading.

Unlike human assistants, AI agents don’t get tired, bored, or need sick leaves. They work around the clock and cost very little to manage.

Democratizing Tools

DeepSeek’s open-source model, with its low entry barrier, gives more users access to creating web3 solutions with artificial intelligence. This allows more developers to experiment with the LLMs with a view to promoting research and collaborative development.

Risks

Security Concerns

Source: Cyberscoop

Malicious actors always find ways to infiltrate and manipulate AI agents’ vulnerabilities through targeted attacks. Hacks, scams, and fraudulent activities can be carried out on users of compromised AI agents, potentially leading to significant financial and asset losses.

One of these attacks occurred when Wiz Researcher discovered a publicly accessible ClickHouse database belonging to DeepSeek. This exposed over a million lines of log streams with sensitive information, including chat history, API keys, and backend details. Luckily, the DeepSeek dev team could swiftly respond, retrieve the database, and prevent a disaster.

Algorithm Bias

Since AI agents are designed to operate based on the data they are trained on, they can pose a big threat to inclusivity in GameFi and the Metaverse. For instance, if the training data reflects only a fraction of societal prejudices, gender stereotypes, and racial inequalities, AI agents built on it would inherit these biases and act on them.

In GameFi, this algorithm bias can come in the form of unfair gameplay mechanics that favor players from a certain demographic or biased interactions with NPCs. In Metaverse, they can be presented by discriminatory creation of avatars, restricted social interactions, unequal economic opportunities, and showing users biased content.

Regulatory and Data Privacy Uncertainty

It is quite uncertain how DeepSeek handles sensitive data in relation to internationally recognized regulations such as GDPR, CCPA, HIPAA, and FERPA. Also, the ownership of data processed by its large language models (LLMs) is unclear, raising questions about whether it is retained by DeepSeek, a third party, or the end users.

As a result, DeepSeek has encountered regulatory challenges in several developed countries, with some imposing partial restrictions on its LLMs and others implementing outright bans on their usage.

The Future of AI and Cryptocurrency: What to Expect from Emerging Innovations

Integrating AI into blockchain technology will continue to shape stakeholders’ views of the ecosystem. While blockchain allows for security, transparency, and decentralization, AI enhances data processing capability and automation.

The convergence of AI and crypto is expected to accelerate in the future, giving way to innovations that help enhance risk management tools and security protocols within this industry.

Crypto also seeks AI models that can perform near-perfect predictive analyses of digital asset prices, automate smart contracts audits, optimize blockchain scalability, and smartly address network congestion. Additionally, the crypto industry seeks AI to generate virtual universes and decentralized AI agents, seamlessly integrate AR/VR experiences onto blockchains, and create flexible user experiences.

With the relentless efforts of researchers and the keen interest of venture capitalists, collaboration between these two technologies holds immense promise for creating a more autonomous and resilient decentralized financial ecosystem.

Conclusion

DeepSeek aims to redefine industry standards in AI by prioritizing efficiency and cost-effective deployment. This strategic approach has improved DeepSeek’s accessibility, scalability, and seamless integration into the crypto industry. However, this is just the beginning, as the existing DeepSeek LLM infrastructures continue to evolve, and upcoming launches are poised to significantly impact the market.

AI will become an integral component of blockchain technology in the future, providing automation technologies that optimize transaction processing speeds and access vast data repositories for real-time insights.

It is important to note that although AI agents are usually safe to interact with, users should always refrain from sharing sensitive information like their wallet seed phrases, passwords, social security numbers, and other valuables.