Large language models Archives

AI based chat application for life sciences:
Part II role of ontologies

Explore the vital role of ontologies in enhancing AI-based chat applications for life sciences, with a focus on improving transparency and data meaning.
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AI based chat application for life sciences:
Part I key considerations

Are your teams now posing potentially confidential questions to consumer tools such as Bard and ChatGPT, relying on their responses?
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With new tech comes new operationalization considerations

As technology advances, the landscape of operationalization undergoes a profound shift. Here, we unravel the intricacies that accompany new tech, exploring key operationalization considerations shaping the realms of machine learning and semantic indexing.
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What is Retrieval Augmented Generation and why is the data you feed it so important?

Within the life sciences, evidence-based decision-making is imperative; wrong decisions can have dire consequences. As such, it is vital that systems that support the generation and validation of hypotheses provide direct links, or provenance, to the data that was used to generate them. But how can one implement such a workflow?
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Are ontologies still relevant in the age of LLMs?

Technological advancements exhibit varying degrees of longevity. Some are tried and trusted, enduring longer than others, while other technologies succumb to fleeting hype without attaining substantive fruition. One constant, in this dynamic landscape is the data.
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Microbiome repurposing: Is it a potential therapeutic approach & how can we do it with LLMs?

Discover the past and future of microbiome-based healing. From ancient remedies to modern AI, learn how SciBite's groundbreaking approach blends Large Language Models (LLMs) with advanced tech to unravel the potential of therapeutic microbiomes.
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Large language models (LLMs) and search; it’s a FAIR game

Large language models (LLMs) have limitations when applied to search due to their inability to distinguish between fact and fiction, potential privacy concerns, and provenance issues. LLMs can, however, support search when used in conjunction with FAIR data and could even support the democratisation of data, if used correctly…
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