DeepSeek triggers a major reshuffle in the AI Agent sector? Is it time to buy the dip or retreat?
Written by: Azuma, Odaily Planet Daily
AI The Agent sector continued to accelerate its pullback today. Apart from some memes related to the DeepSeek concept, VIRTUAL,AI16Z, AIXBT, ARC and other header Framework/Launchpad/Agent TokenAnd other big and smallTokenBoth recorded double-digit declines.
The decline is certainly related to the overall weakening of the market, but looking at the market discussions, some investors also attribute the collective decline of AI Agents to DeepSXiaobai Navigationeek’s explosion in popularity makes it believed that DeepSeek, as a new generation of more economical LLM, will have an impact on and even reshuffle the current Crypto AI landscape.
I personally do not support this view.
The core point of the above doubts is actually - will the iterative development of LLM subvert the existing agents? Putting aside the controversy over whether DeepSeek's current reasoning quality is better than ChatGPT and Claude, assuming that DeepSeek has more promising iterative potential from the perspective of economic sustainability, will the iterative DeepSeek create a new batch of agents? Will the existing agents become "yesterday's news"?
To answer this question, we need to first understand the relationship between LLM and Agent. We try to answer this question using DeepSeek itself and another "Chinese pride" Kimi (to be honest, Kimi's quality seems to be better in this regard).
DeepSeek:
The relationship between AI Agent (Artificial Intelligence Agent) and AI LMM (Large Language Model) is that LMM can be used as one of the core components of Agent, especially when dealing with natural language understanding and generation tasks. AI Agent is an intelligent system that can perform tasks autonomously and interact with the environment, while LMM provides Agent with powerful language processing capabilities, enabling it to better understand and generate human language, thus playing a role in scenarios such as dialogue, recommendation, and analysis. In short, LMM is an important technical support for AI Agent to achieve intelligent language interaction.
Kimi:
Agents usually rely on LLM to understand and generate natural language. LLM provides powerful language processing capabilities, enabling agents to interact with users in natural language, understand user needs, and generate corresponding responses.
Agents also not only rely on the language processing capabilities of LLM, but also combine multiple capabilities such as decision-making, problem solving, interaction with the external environment, and execution of actions. LLM provides the basis for Agents to understand and generate language, and Agents perform task planning and execution on this basis.
Agents can also combine other tools and APIs to expand their functionality. For example, agents can call search engines, database query tools, file reading and writing tools, etc. to complete more complex tasks. LLM provides language understanding and generation capabilities in this process, enabling AI agents to better interact with these tools.
In summary, the operation of Agent requires the support of LLM, but the quality of its expression and interaction does not entirely depend on LLM. In fact, it is the other capabilities besides LLM that determine the obvious differences between different Agents.
For example, the reason why aixbt can "crush" other similar agents in terms of output is essentially because it does a better job in prompt word design, post-processing mechanism, context management, fine-tuning strategy, randomness control, external tool integration and user feedback mechanism, so it can generate expressions that are closer to the industry - you can call it a first-mover advantage or a moat, this is the current advantage of aixbt.
After understanding this relational logic, let’s now answer the core question in the previous article: “Will the iterative development of LLM subvert the existing Agent?”
The answer is no, because the Agent can easily inherit the capabilities of the new generation of LLM through API integration to achieve evolution, thereby improving the quality of interaction, improving efficiency, and expanding application scenarios...especially considering that DeepSeek itself provides an API format compatible with OpenAI.
In fact, the quick-reacting Agent has already completed the integration of DeepSeek. ai16z founder Shaw said this morning that DAO The AI Agent building framework Eliza developed by the company completed support for DeepSeek two weeks ago.
Under the current trend, we can rationally assume that after Eliza of ai16z, other major frameworks and agents will also complete the integration of DeepSeek as soon as possible. In this way, even if there will be some impacts from new generation DeepSeek Agents in the short term, in the long run, the competition between agents still depends on the external capabilities mentioned above, and at this time, the accumulation of development results brought by the first-mover advantage will once again appear.
Finally, let me post some comments from bigwigs on DeepSeek to recharge the faith of those who stick to the AI Agent sector.
Frank, founder of DeGods, said yesterday: "People's idea about this matter (DeepSeek iterating the old market) is wrong. Current AI projects will benefit from new models like DeepSeek. They only need to replace the OpenAI API call with DeepSeek, and the output will be improved overnight. The new model will not disrupt the Agent, but will accelerate their development."
Daniele, a trader who specializes in AI, said: “If you are selling AI because the DeepSeek model is cheap and open source, Token, then you need to know that DeepSeek is actually very helpful in scaling AI applications to millions of users at low-barrier pricing. This may be the best thing to happen to the industry yet.”
Shaw also published a long article this morning in response to the impact of DeepSeek. The first sentence of the article is as follows: "More powerful models are always good for agents. Over the years, major AI labs have been surpassing each other. Sometimes Google is ahead, sometimes OpenAI, sometimes Claude, and today it's DeepSeek..."
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