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Openledger is a data blockchain for AI that provides decentralised trust infrastructure for creating specialized language models. By leveraging datanets to collect and curate data, Openledger enables the development of these models, which are then consumed by AI agents, chatbots, copilots, and various other applications.
In recent years, Large Language Models (LLMs) have transformed how we interact with technology. From chatbots to code assistants, they have presumably made technology simpler and easier to use. Foundational LLMs excel at general tasks, offering broad applicability across various domains. However, when it comes to specialized, industry-specific applications, their performance often falls short. This has lead to the discovery of a small and specialized alternative which excels deeply in a particular niche, These models are called as Specialized Language Models(SLM).
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What is Specialised Language Models?
Specialized Language Models are compact, efficient, and trained to excel in one or more specific areas. They frequently outperform their larger counterparts in speed, performance, and accuracy within their trained domains.
Specialized Model qwen 2.5 outperforms models like Gemini, gpt-4o and o1()
To understand why specialized language models should be preferred over LLMs, Here’s a detailed comparison across various aspects:
Think of LLMs as the operating systems (OS) of AI—a foundational layer offering broad functionality and compatibility across various domains. Just as an OS serves as the baseline for running applications, LLMs provide a versatile foundation for building AI-driven solutions.
In contrast, SLMs function like apps running on this foundation. These are purpose-built systems tailored to meet specific needs.
For example:
• LLMs as the OS include models like ChatGPT, GPT-4, and Claude—general-purpose models capable of handling a wide range of tasks.
• SLMs as the apps could include:
Just as an OS and its apps work together, LLMs and SLMs will coexist in the AI ecosystem. LLMs will act as orchestrators, managing high-level interactions and integrations, while SLMs will delve deep into specific domains to solve problems requiring specialized expertise.
So Now openledger wants to create specialized SLMs and what is stopping it?