fix typo

SynaLinks · Jun 12, 2024 · 2b59d2d · 2b59d2d
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@@ -28,7 +28,7 @@ It is the first programmable LLM-based agent that enables you to define its beha
 
 ## Why HybridAGI?
 
-We are not satisfied with the current trajectory of Agent-based systems that lack control and efficiency. Today's approach is to build reactive/MKRL agents that do what they want without any human control, resulting in infinite loops of nonsense because they tend to stay in their data distribution. Multi-agent systems try to solve that, but instead result in more nonsense and prohibitive costs due to the agents chitchatting with each other. Moreover, today's agents require fine-tuning to enhance/correct the behavior of the agent system. In contrast, with HybridAGI, the only thing you need to do is to modify the behavior graph.
+We are not satisfied with the current trajectory of Agent-based systems that lack control and efficiency. Today's approach is to build React/MKRL agents that do what they want without any human control, resulting in infinite loops of nonsense because they tend to stay in their data distribution. Multi-agent systems try to solve that, but instead result in more nonsense and prohibitive costs due to the agents chitchatting with each other. Moreover, today's agents require fine-tuning to enhance/correct the behavior of the agent system. In contrast, with HybridAGI, the only thing you need to do is to modify the behavior graph.
 
 We advocate that fine-tuning should be done only as a last resort when in-context learning fails to give you the expected result. Any person who has already fine-tuned a LLM knows that gathering data is hard, but having the right variability in your dataset is even harder, thus prohibiting most companies from leveraging this technology if they don't have many AI scientists. By rooting cognitive sciences into computer science concepts, without obfuscating them, we empower programmers to build the Agent system of their dreams by controlling the sequence of action and decision.