Google Announces Bold Progress In AI, Advancing Med-PaLM 2 For Healthcare

Last week, Google hosted its annual I/O developer conference, showcasing the company’s vision for its products and services. Typically, this entails exciting conversations around Google’s mobile platform, Android, or the newest hardware the company is planning to release. However, this year, something else stole the show: Google’s incredible progress in artificial intelligence (AI).

AI has been all the buzz in both Silicon Valley and around the world for the last few months, especially after the release of Chat-GPT and advanced generative AI systems. This has triggered somewhat of a frantic rat-race amongst tech giants: everyone wants a piece of the AI pie, and the race to the top is intense.

For example, Microsoft is investing significant resources into its AI capabilities, relentlessly trying to integrate the technology across a variety of sectors, ranging from manufacturing to healthcare. Amazon is also innovating in this space, offering customers turn-key services to build their own machine learning and AI models.

In a similar fashion, Google has made incredible strides in its own AI journey. Though many may suspect that the buzz around AI is relatively new, the company has actually been setting the foundation for advanced language models and usable AI for many years. This work has culminated in products with incredible potential, including PaLM 2, Google’s latest generation large language model.

As an introduction to PaLM 2, Zoubin Ghahramani, Vice President of Google DeepMind, wrote last week: “today we’re introducing PaLM 2, our next generation language model. PaLM 2 is a state-of-the-art language model with improved multilingual, reasoning and coding capabilities.” He goes on to describe these capabilities further, discussing how PaLM 2 is trained across 100 languages, has a higher capability for common sense reasoning and advanced mathetmatics and logic, and can even generate advanced code.

Notably, Ghahramani also discusses one of the most highly anticipated arenas of impact for AI: healthcare. He delves into Med-PaLM 2, the large language model developed specifically to generate medical insights: “trained by our health research teams with medical knowledge, [Med-PaLM 2] can answer questions and summarize insights from a variety of dense medical texts. It achieves state-of-the-art results in medical competency, and was the first large language model to perform at “expert” level on U.S. Medical Licensing Exam-style [USMLE] questions. We’re now adding multimodal capabilities to synthesize information like x-rays and mammograms to one day improve patient outcomes. Med-PaLM 2 will open up to a small group of Cloud customers for feedback later this summer to identify safe, helpful use cases.”

The full 2023 keynote can be viewed here:

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Google Cloud, especially for Healthcare, has been incredibly successful over the last few years. For example, Google Cloud’s Healthcare Data Engine is an industry-leading platform to optimize interoperability in healthcare, which could resolve some of the sector’s most challenging problems: significant data-fragmentation, lack of cohesive insights, and splintered patient journeys.

Google Cloud’s Global Director of Healthcare Strategy & Solutions, Aashima Gupta, and Global Director of Health Plan Strategy & Solutions, Amy Waldron, explain: “Industry-tailored LLMs like Med-PaLM 2 are part of a burgeoning family of generative AI technologies that have the potential to significantly enhance healthcare experiences. We’re looking forward to working with our customers to understand how Med-PaLM 2 might be used to facilitate rich, informative discussions, answer complex medical questions, and find insights in complicated and unstructured medical texts. They might also explore its utility to help draft short- and long-form responses and summarize documentation and insights from internal data sets and bodies of scientific knowledge.”

The Cloud team was also responsible for launching the Medical Imaging Suite, a comprehensive AI platform to make medical imaging data “accessible, interoperable, and useful.”

Undoubtedly, the development of PaLM 2 will be a gamechanger for healthcare. Whether it be used to conduct advanced analytics of vast amounts of public health or patient data, or simply as a means to better triage and improve physician workflows, the technology has immense potential to create tangible impact.

Especially with regards to synthesis and insight generation, this technology may be immensely useful for organizations that want to scale their tactical approach to improving patient outcomes. For example, for public entities, harnessing this technology may one day make possible the ingestion of terabytes of public health data that is otherwise unstructured to generate usable insights. For private organizations, this technology could prove to be a significant boon in the realms of interoperability, improving patient journeys, and succeeding in true longitudinal care.

Nevertheless, this technology requires guardrails. While there is significant potential for beneficial use, there is also some “fear of the unknown.” That is, in the wrong hands, the powerful technology that drives these advancements in AI can have negative repercussions. This is a prime reason why the developer conference had an entire segment dedicated to the “responsible development” of AI, serving as a reminder of the checks and balances needed in this rapidly growing arena of technology. Nonetheless, if developers and innovators are able to create and harness this technology in a safe and sustainable manner, it may potentially change the face of healthcare delivery for generations to come.