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Private, offline and yours: how to search the literature with local AI systems
Concerns about privacy, reproducibility and cost are prompting scientists to use models on their computers rather than in the cloud.
When he wants to scratch an intellectual itch, Ian Gaudet does what people are increasingly doing on the Internet: he asks a chatbot. But when it comes to his research data, Gaudet, a neuroscientist at Florida Atlantic University in Boca Raton, prefers to stay offline. “I do not want Claude to start telling people my research results,” he explains.
Cloud-based large language models (LLMs), such as those underlying the chatbots Claude (Anthropic), Gemini (Google) and ChatGPT (OpenAI), represent the cutting edge of artificial-intelligence performance. However, these systems might use what is typed into them for training purposes. For researchers such as Gaudet, state-of-the-art performance isn’t worth the risk to data protection, reproducibility or budgets. Instead, they turn to a growing collection of tools, such as Ollama and LM Studio , that enable researchers to download LLMs to their computer and use them offline .
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