Daily & Groq: Real-time AI Enterprise Voice Workflow – Patient Intake Use Case on Llama 3.1 405B

Groq
23 Jul 202405:43

TLDRGroq and Daily partner with Meta to showcase Llama 3.1 405B's voice AI capabilities in healthcare. The demo illustrates a patient intake workflow, highlighting the model's advanced reasoning and conversational abilities. Developers can utilize Daily's real-time network and open-source tools to build complex AI workflows for applications in healthcare and beyond.

Takeaways

  • 🤝 Groq and Daily are partnering with Meta to showcase advanced voice AI capabilities.
  • 🦙 Llama 3.1 45 billion is the latest version of Groq's AI model, designed for high performance on the best hardware.
  • 🗣️ The AI voice agent in the patient intake use case demonstrates real-time interaction with a patient to confirm identity and medical details.
  • 💊 The script includes a conversation where the AI agent assists in confirming medication details and dosages.
  • 🚑 AI applications in healthcare, like the patient intake workflow, provide healthcare providers with more complete and up-to-date patient information.
  • 🔍 Voice AI applications require a capable large language model, fast response times, and developer tools for building complex workflows.
  • 🔧 Gro Cloud's optimized 405 billion implementation ensures human conversational speed for voice responses.
  • 🛠️ Daily's real-time network and open-source AI workflow tooling are used to power agentic audio workflows.
  • 📝 The workflow involves converting speech to text, updating conversation history, and processing responses from the large language model (LLM).
  • 📚 For complex workflows like patient intake, structured data collection is facilitated by function calls within the LLM's responses.
  • 🌐 The core code for the workflow is built on top of an open-source real-time voice inference SDK, emphasizing the flexibility of AI workflows.

Q & A

  • What is the partnership between Groq and Daily about?

    -The partnership between Groq and Daily is aimed at showcasing the latest in voice AI capabilities, specifically using Llama 3.1 45 billion model, to enhance real-time AI enterprise voice workflows in various applications such as healthcare.

  • What is the purpose of using Llama 3.1 45 billion in the healthcare setting?

    -Llama 3.1 45 billion is used in healthcare to provide healthcare providers with more complete and up-to-date information about their patients through advanced AI capabilities, such as patient intake workflows.

  • What are the three requirements for voice AI applications like the patient intake workflow?

    -The three requirements for voice AI applications are a very capable large language model, fast response times, and developer tools that allow for the building of complex workflows.

  • How does the AI voice agent interact with the user in the patient intake workflow?

    -The AI voice agent listens for the user to speak, converts the user's speech to text, adds it to the conversation history, sends that history to an LLM, and then plays back the LLM's response as speech to the user.

  • What is the significance of enabling function calling in the AI model?

    -Enabling function calling allows some of the LLM's responses to be JSON objects describing a function the LLM wants to use, which can represent structured data being collected, such as a list of the user's allergies in a patient's medical record.

  • What is the role of Daily's real-time network in this setup?

    -Daily's real-time network, along with open-source AI workflow tooling, powers agentic audio workflows, enabling developers to build complex and efficient AI applications.

  • What is the core code for the patient intake workflow implemented on?

    -The core code for the patient intake workflow is implemented on top of the open-source real-time voice inference SDK.

  • How does the AI application handle structured data collection in the patient intake process?

    -The AI application handles structured data collection by converting some of the LLM's responses into JSON objects that describe functions, which are then used to collect and save data in the patient's medical record.

  • What are the benefits of using Llama 3.1 45 billion in voice AI applications?

    -Llama 3.1 45 billion offers extremely fast voice response times, open-ended natural language conversational ability, and truly flexible configurable AI workflows, making it ideal for building next-generation applications in areas like healthcare, education, and consumer services.

  • How can interested parties learn more about building with Daily and Groq?

    -Interested parties can visit get.newaai to learn more about building with Daily and Groq and explore the possibilities of using Llama 3.1 45 billion in their applications.

Outlines

00:00

🤖 Voice AI in Healthcare with Llama 3.1

The script introduces a partnership between Grock and Daily with Meta, showcasing the capabilities of the Llama 3.1 AI with 45 billion parameters. It demonstrates a voice AI application in healthcare, where a patient named Chad interacts with an AI to confirm his identity and medical details, including allergies, medications, and symptoms. The AI collects structured data and integrates it into the patient's medical record. The script emphasizes the importance of a capable language model, fast response times, and developer tools for building complex workflows. The demo illustrates the potential of voice AI in improving patient intake processes, providing healthcare providers with more complete and up-to-date patient information.

05:01

🚀 Advancing Voice AI Applications with Llama 3.1

This paragraph discusses the next frontier of AI product development with voice AI experiences. It highlights the features of the Llama 3.1 model, such as fast voice response times, open-ended natural language conversational ability, and flexible, configurable AI workflows. The script invites viewers to visit get.new.aai to explore the possibilities of building next-generation applications in various fields, including healthcare, education, and consumer services, with the support of Grock and Daily. The closing note expresses excitement for the innovations that can be created using these advanced tools.

Mindmap

Keywords

💡AI Enterprise Voice Workflow

AI Enterprise Voice Workflow refers to the integration of artificial intelligence into business processes to automate and enhance voice-based interactions. In the context of the video, this workflow is applied in a healthcare setting for patient intake, demonstrating how AI can streamline the process of gathering patient information and medical history, thereby improving efficiency and patient experience.

💡Llama 3.1 45 billion

Llama 3.1 45 billion appears to be a reference to a specific version of a large language model with 45 billion parameters. This model is highlighted for its advanced reasoning abilities and its role in enabling open-ended conversation and agentic action sequences in the voice AI application demonstrated in the video.

💡Meta

Meta, in this context, likely refers to the company formerly known as Facebook, which is known for its ventures into various technology sectors, including AI. The video suggests that Groq and Daily are partnering with Meta to showcase the capabilities of their AI voice technology.

💡Gro Cloud

Gro Cloud is mentioned as the platform that optimizes the implementation of the Llama 3.1 45 billion model, delivering voice responses at human conversational speed. This indicates the use of cloud computing to enhance the performance of the AI voice application.

💡Patient Intake

Patient Intake is a process where healthcare providers gather information about a patient's medical history, current medications, allergies, and symptoms. In the video, the AI voice agent facilitates this process, asking relevant questions and recording the patient's responses, which is crucial for the doctor's visit.

💡Voice AI Applications

Voice AI Applications are software solutions that use artificial intelligence to process and respond to voice commands or queries. The video showcases such an application in healthcare, emphasizing how it can provide healthcare providers with more complete and up-to-date patient information while offering patients new ways to access information and care.

💡Function Calling

Function Calling in the context of the video refers to the ability of the AI model to execute specific functions or actions based on the conversation's needs. This is crucial for collecting structured data, such as listing a patient's allergies, which are then saved in the patient's medical record.

💡Structured Data

Structured Data is information that is organized in a specific way, making it easily searchable and analyzable. In the video, the AI model collects structured data such as allergies and medications, which is essential for maintaining accurate patient records and facilitating healthcare delivery.

💡Real-time Network

The Real-time Network mentioned in the video is a tool that allows for the processing and transmission of data instantly, which is critical for voice AI applications to provide immediate responses and interactions, enhancing the user experience.

💡SDK

SDK stands for Software Development Kit, which is a set of tools, libraries, and documentation that developers can use to create applications for a certain software platform. The video refers to an open-source real-time voice inference SDK, which is used to implement the voice AI workflow demonstrated.

💡Natural Language Conversational Ability

Natural Language Conversational Ability is the capacity of an AI system to understand and respond to human language in a way that is natural and intuitive. The video emphasizes this ability as a key feature of the Llama 3.1 45 billion model, allowing for more human-like interactions in the voice AI application.

Highlights

Grock and Daily are partnering with Meta to showcase the latest in voice AI capability.

Llama 3.1 45 billion is running on the best hardware in the world.

The AI-powered voice system can confirm patient identity and collect medical information.

Patients can interact with the AI to list prescription medications and dosages.

The AI can handle interruptions and requests for clarification during the intake process.

Patients can report allergies and existing medical conditions to the AI.

The AI can collect structured data through function calls in its responses.

Voice AI applications in healthcare provide more complete and up-to-date patient information.

AI applications like patient intake require a capable large language model, fast response times, and developer tools.

Llama 3.1 45 billion has advanced reasoning abilities for open-ended conversation.

Gro Cloud's optimized implementation delivers voice responses at human conversational speed.

Daily's real-time network and open-source AI workflow tooling power agentic audio workflows.

The AI voice agent listens for user input, converts speech to text, and adds it to the conversation history.

The AI's response is turned into speech and played back to the user.

Patient intake workflows require configuring the model for function calling.

Function calls in the AI's responses represent structured data collection.

Llama 3.1 45 billion unlocks possibilities for next-generation applications in healthcare, education, and consumer services.

Llama 3.1 powered voice provides advanced building blocks for voice AI applications.

Developers can build with Daily and Gro by visiting get.new.ai.

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