scInterpreter: Training Large Language Models to Interpret scRNA-seq Data for Cell Type Annotation
Unlocking cellular secrets, scInterpreter marries AI with biology, training vast language models to decipher scRNA-seq data, revolutionizing cell type annotation.
Garbage in, garbage out: Zero-shot detection of crime using Large Language Models
Exploring the frontier of AI, we delve into the concept of 'Garbage in, garbage out' in crime detection. Unveiling how Zero-shot learning via Large Language Models could revolutionize our approach, yet reminds us of the criticality of clean, unbiased data.
Agile development can unlock the power of generative AI – here’s how
Unlocking the potential of generative AI through agile development can revolutionize the way we approach innovation. Find out how this dynamic duo is reshaping the future of technology.
TabLLM: Few-shot Classification of Tabular Data with Large Language Models
Unlocking the power of AI for tabular data, TabLLM revolutionizes few-shot classification. This innovative approach leverages large language models to interpret and classify complex datasets with minimal examples, setting a new standard in data analysis.
Cognitive bias in large language models: Cautious optimism meets anti-Panglossian meliorism
In the realm of AI, large language models wade through the murky waters of cognitive bias. Striking a balance, we oscillate between cautious optimism and a determined push for improvement, challenging the notion that our current state is the best of all possible worlds.
