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Greetings from Terminal C at LGA. I'm heading to Minnetonka, Minnesota (which I learned means "Great Water" in the Dakota Sioux language) to do an AI deep-dive workshop this afternoon—which got me thinking. We always talk about Large Language Models (LLMs), but now, we're deploying more and more Small Language Models (SLMs) and Small Action Models (SAMs). So, just because I'm about to get on a plane, here are three definitions that will come in handy for any AI-focused cocktail conversation you may have this weekend.
LLMs are broad, general-purpose models trained on extensive datasets. They excel at language comprehension and generation, making them the backbone of applications like chatbots and customer service automation. Use cases include content creation, automated translation, and summarizing large volumes of text. For example, LLMs are the underlying technologies for tools like ChatGPT.
SLMs are more specialized, secure, and focused on specific tasks. They are derived from LLMs but are enhanced with knowledge graphs and domain-specific data to suit particular applications. A common use case is in the healthcare sector, where SLMs can securely handle patient data and provide tailored responses for medical queries. In enterprise environments, they facilitate internal knowledge management by tapping into company-specific datasets, offering accurate, context-specific insights.
SAMs take things further by acting as dynamic agents. They combine the best of SLMs and LLMs to autonomously execute tasks aligned with business objectives. For instance, a SAM could automate a marketing campaign by analyzing customer interactions, predicting trends, and triggering personalized messages. These models can also optimize supply chain management by making real-time decisions based on evolving data patterns.
That's a quick vocab lesson. While LLMs are big and famous, SLMs and SAMs are quietly shaping the future of AI by delivering more precise, secure, and actionable insights for various specialized applications.
Are you working with SLMs or SAMs? If so, I'd love to hear about your use cases. This is relatively new territory—even for generative AI—so please, share your story. -s
P.S. CES 2025 (Las Vegas, January 7-10, 2025) is just around the corner. We're planning all kinds of good stuff: Executive Briefings and Floor Tours, the Shelly Palmer Innovation Series Breakfast, and four days of exceptional programming. .
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