Audience

Healthcare providers and clinical professionals looking for a generative AI solution to answer medical questions

About Med-PaLM 2

Healthcare breakthroughs change the world and bring hope to humanity through scientific rigor, human insight, and compassion. We believe AI can contribute to this, with thoughtful collaboration between researchers, healthcare organizations, and the broader ecosystem. Today, we're sharing exciting progress on these initiatives, with the announcement of limited access to Google’s medical large language model, or LLM, called Med-PaLM 2. It will be available in the coming weeks to a select group of Google Cloud customers for limited testing, to explore use cases and share feedback as we investigate safe, responsible, and meaningful ways to use this technology. Med-PaLM 2 harnesses the power of Google’s LLMs, aligned to the medical domain to more accurately and safely answer medical questions. As a result, Med-PaLM 2 was the first LLM to perform at an “expert” test-taker level performance on the MedQA dataset of US Medical Licensing Examination (USMLE)-style questions.

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Company Information

Google Cloud
United States
cloud.google.com/blog/topics/healthcare-life-sciences/sharing-google-med-palm-2-medical-large-language-model

Videos and Screen Captures

Med-PaLM 2 Screenshot 1
Med-PaLM 2 Screenshot 1
Gopher
Gopher
Language, and its role in demonstrating and facilitating comprehension - or intelligence - is a fundamental part of being human. It gives people the ability to communicate thoughts and concepts, express ideas, create memories, and build mutual understanding. These are foundational parts of social intelligence. It’s why our teams at DeepMind study aspects of language processing and communication, both in artificial agents and in humans. As part of a broader portfolio of AI research, we believe the development and study of more powerful language models – systems that predict and generate text – have tremendous potential for building advanced AI systems that can be used safely and efficiently to summarise information, provide expert advice and follow instructions via natural language. Developing beneficial language models requires research into their potential impacts, including the risks they pose.
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PaLM 2
PaLM 2
PaLM 2 is our next generation large language model that builds on Google’s legacy of breakthrough research in machine learning and responsible AI. It excels at advanced reasoning tasks, including code and math, classification and question answering, translation and multilingual proficiency, and natural language generation better than our previous state-of-the-art LLMs, including PaLM. It can accomplish these tasks because of the way it was built – bringing together compute-optimal scaling, an improved dataset mixture, and model architecture improvements. PaLM 2 is grounded in Google’s approach to building and deploying AI responsibly. It was evaluated rigorously for its potential harms and biases, capabilities and downstream uses in research and in-product applications. It’s being used in other state-of-the-art models, like Med-PaLM 2 and Sec-PaLM, and is powering generative AI features and tools at Google, like Bard and the PaLM API.
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Upstage
Upstage
Use the Chat API to create a simple conversational agent with Solar. Function Calling is now supported, the way to connect LLM to external tools. The embedding vectors can be used for tasks such as retrieval and classification. Context-aware English-Korean translation that leverages previous dialogues to ensure unmatched coherence and continuity in your conversations. Verifies whether the answers provided by the LLM are appropriately generated, based on the user's question and search results. Developing a healthcare LLM to automate patient communication, personalize treatment plans, aid in clinical decision support and support medical transcription. Aims to enable business owners and companies to deploy generative AI chatbots on websites and mobile apps easily, providing human-like services in customer support and engagement.
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Crosby Health Apollo
Crosby Health Apollo
Thousands of providers use Apollo by Crosby Health to generate, submit, and track appeals. Reducing the provider burden from clinical denials. Apollo has been trained to understand the clinical context and beats every other medical language model on core metrics. Apollo has been fine-tuned to handle billing tasks with high precision such as auditing, charge capture, and denial management. The fastest clinical language model with the largest context length. Outputs are generated on average at 60 words per second and can intake up to 300 pages. Our AI crafts winning appeal letters for every denial with meticulous arguments for maximum recovery. Eliminate multiple payor portals and fax numbers. One platform that submits and tracks every appeal. Eliminate the provider burden to generate appeals. AI trained to identify medical necessity within documentation. One-click submission to any insurance company.
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Product Details

Platforms Supported
SaaS
Training
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Med-PaLM 2 Product Features