Specialized AI Models Will Overtake LLMs in Certain Applications
Posted: Sun Feb 09, 2025 8:24 am
We can conceptualize the importance of this development by remembering the importance of the order of operations in solving simple mathematical problems. Executing problems in the correct order (in this case, PEMDAS) makes the difference between the correct answer and something wildly incorrect. This illustration of agentic AI’s importance is simplistic but captures the essence of why it could transform the business world: more reliable answers and, therefore, more reliable AI systems.
In the financial services industry, agentic saudi arabia rcs data AI might automate complex processes like loan underwriting. Here, the AI would decompose tasks into specialized subtasks, collaborate across systems and iteratively refine outputs based on feedback. This could potentially cut review cycles down significantly.
While it’s unlikely that agentic AI will reach the enterprise deployment stage next year, we’ll certainly see many exciting developments as industry frontrunners test these systems’ capabilities.
Until now, large language models (LLMs) have dominated AI discourse. However, smaller, niche-specific models will likely take center stage in 2025. These smaller models excel in precision and efficiency, catering to industries with unique demands like finance, healthcare, and robotics. Their lower data and computational requirements make them ideal for energy-efficient edge computing, enabling real-time applications in autonomous vehicles, retail, and more.
In the financial services industry, agentic saudi arabia rcs data AI might automate complex processes like loan underwriting. Here, the AI would decompose tasks into specialized subtasks, collaborate across systems and iteratively refine outputs based on feedback. This could potentially cut review cycles down significantly.
While it’s unlikely that agentic AI will reach the enterprise deployment stage next year, we’ll certainly see many exciting developments as industry frontrunners test these systems’ capabilities.
Until now, large language models (LLMs) have dominated AI discourse. However, smaller, niche-specific models will likely take center stage in 2025. These smaller models excel in precision and efficiency, catering to industries with unique demands like finance, healthcare, and robotics. Their lower data and computational requirements make them ideal for energy-efficient edge computing, enabling real-time applications in autonomous vehicles, retail, and more.