Google Unveils MedLM Suite, Targeting Healthcare-Specific AI Solutions
Google announced the launch of MedLM, a comprehensive suite of artificial intelligence (AI) models tailored specifically for the healthcare industry.
The suite is designed to assist clinicians and researchers in conducting intricate studies, summarizing doctor-patient interactions, and more.
This strategic move reflects Google's ongoing efforts to capitalize on the burgeoning healthcare AI market, where competition for market share is intensifying, with rivals such as Amazon and Microsoft vying for dominance.
Companies such as HCA Healthcare have been actively testing Google's technology, and experts foresee significant potential impact, emphasizing the need for careful implementation.
The MedLM suite comprises both large and medium-sized AI models, both built on Med-PaLM 2, a robust language model trained on medical data that Google initially introduced in March.
As of Wednesday, the suite is generally available to eligible Google Cloud customers in the U.S.
Google noted that the cost of the AI suite may vary depending on the specific usage of different models, with the medium-sized model being more cost-effective.
Furthermore, Google disclosed plans to integrate healthcare-specific versions of Gemini, the company's latest and most advanced AI model, into MedLM in the future.
Aashima Gupta, Google Cloud’s Global Director of Healthcare Strategy and Solutions, explained the rationale behind the suite, highlighting that different medically tuned AI models excel at specific tasks.
This led Google to introduce a suite of models instead of pursuing a one-size-fits-all approach.
For example, the larger MedLM model is optimized for complex tasks requiring deep knowledge and significant computing power, such as conducting comprehensive studies using data from an entire healthcare organization's patient population.
On the other hand, the medium-sized model is better suited for more agile tasks that can be optimized for specific or real-time functions, such as summarizing interactions between doctors and patients, according to Gupta.
Ashley Capoot / CNBC