Are Small Language Models the Future of Affordable (and Better) AI?
Today’s question: Want an AI language model that gives more accurate results and saves you money?
When it comes to generative AI and the models that drive them, sometimes less is more. Small language models, trained on much smaller but very specific, high-quality datasets, are far less expensive to train and maintain, and often outperform the kitchen-sink approach of gigantic, multipurpose large language models.?
Here we explain how these mini marvels, geared toward a single task, deliver the power of generative AI for a fraction of the cost.?
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This newsletter was curated by Lisa DiCarlo Lee , Contributing Editor at Salesforce.
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5 个月There is a niche for small language models. Domain expertise is a real thing and leveraging targeted datasets is not just cost effective and efficient but also avoids the risk of hallucination. This also means that humans (yes, I said it), can support the delivery of small language models with their own deep understanding of domain specific use cases.
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5 个月Interesting…Small language models might just be the future of affordable AI, and they’re like the compact cars of the tech world. Imagine driving a sleek, efficient smart car instead of a gas-guzzling monster truck. These petite powerhouses can run on less powerful hardware, saving you a bundle on energy bills—your laptop won’t sound like it’s about to take off anymore. They also need less data for training, so even your grandma’s dusty old computer can get in on the AI action. Plus, they can work on edge devices, giving you speedy responses without relying on the cloud—perfect for when you’re hiding from the Wi-Fi in your basement. These small but mighty models could become the budget-friendly heroes of the AI world, proving that sometimes, size really doesn’t matter!