Med-PaLM 2: Google’s AI Surpasses the Medical Expertise Benchmark

Google’s Med-PaLM 2 is redefining what artificial intelligence can achieve in the medical field. Surpassing the “passing” score on the United States Medical Licensing Examination (USMLE), this language model has now become an AI expert, setting a new standard in medical knowledge and decision-making.

The AI Doctor Will See You Now

Med-PaLM 2, the successor to Google’s Med-PaLM, has not only improved upon its predecessor’s capabilities but also broadened its expertise across more datasets through enhancements in its foundational large language model (LLM), specialized medical domain fine-tuning, and refined prompting strategies.

Preferred Over Physicians

In a striking testament to its proficiency, a study involving 1,066 consumer medical questions found that Med-PaLM 2’s answers were preferred over those provided by actual physicians across eight of nine evaluation criteria. This preference by a panel of physicians underscores the model’s exceptional understanding and communication of medical knowledge.

The Multimodal Leap: MultiMedBench and Beyond

Google’s vision for Med-PaLM extends to a multimodal dimension with the creation of MultiMedBench. This dataset facilitates the training of a versatile multitask, multimodal version of Med-PaLM, enabling it to interpret medical images, generate and summarize radiology reports, and even perform genomic variant calling—all with a singular set of model weights.

ELIXR: A Lighter Alternative

As an alternative to the heavyweight multimodal models, ELIXR presents a more compute-efficient solution. By grafting language-aligned vision encoders onto a fixed LLM, ELIXR requires less computational power for training while showing promise in visual QA, semantic search, and zero-shot classification tasks.

The Dawn of AI-Enhanced Medical Practice

With Med-PaLM 2 and its multimodal expansions, Google is spearheading a new era where AI is not just an assistant but a potential expert in medical practice. This paradigm shift promises to augment medical decision-making and democratize expert-level medical knowledge, offering a glimpse into a future where healthcare is more accessible and informed by the best available intelligence—artificial or otherwise.

Join us as we delve into the profound implications of Med-PaLM 2 and its kin, where every medical query and image is an opportunity for AI to demonstrate its emergent capabilities and contribute to the ever-evolving field of healthcare.

Scott Felten