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The rise of generative AI (genAI) has shifted focus from Large Language Models (LLMs) to Small Language Models (SLMs) due to emerging challenges. As tech giants like Microsoft, Google, and Apple explore SLMs, they aim to create open-source models to enhance application ecosystems. DIGITIMES Research highlights that SLMs, defined as models with fewer than 10 billion parameters, offer advantages such as better efficiency and lower costs.
Despite their benefits, SLMs face challenges like reduced accuracy compared to LLMs and a lack of standard evaluation methods. The potential applications for SLMs are vast, particularly in specialized fields like coding and niche languages. As the industry evolves, finding the optimal parameter count for effective SLMs remains a key focus.
• SLMs are emerging as a significant trend in generative AI.
• Tech giants are launching open-source SLMs to capitalize on new opportunities.
The article discusses how generative AI has become a focal point for tech companies since the introduction of ChatGPT.
The article emphasizes their advantages over larger models, particularly in deployment and cost.
The article highlights the challenges faced by LLMs, including data limitations and high resource demands.
The company is actively exploring SLMs to enhance its AI capabilities and application ecosystems.
The company is developing SLMs, such as Google's Gemini, to improve efficiency and accessibility.
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