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Meta’s Newest Model: Llama 3.1 - Surprises, Impressions, and Use Cases

· 4 min read
Mat Coolidge
Founder/CEO previously at Cleveland Clinic, FHIR Evangelist, Healthcare Technologist, Patient Advocate

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Meta’s Newest Model: Llama 3.1 - Surprises, Impressions, and Use Cases

This week, Meta released their newest and most advanced open-source model yet, Llama 3.1. This announcement is special for a few reasons. Not only does this advanced model outperform OpenAI’s latest GPT-4o, but Meta has also released it as an “open model”, allowing everyone to build on top of the technology at no cost.

Let's break down some quick impressions, surprises, and interesting use cases.

Surprises:

  1. Model Size and Variants:

    • The size of the model is unprecedented at 405 billion parameters.
    • Meta also released smaller versions of the model, down to 8 billion parameters, which can be run locally on consumer-grade equipment.
  2. Math Benchmark Performance:

    • Surprisingly, the 405 billion parameter model underperformed on math benchmarks, which is unexpected as Llama models are typically strong in this area.
  3. Software Integration:

    • Llama 3.1 excels at integrating with other software, such as web browsers, enhancing its practical applications.
  4. Responsible AI features:

    • On top of being open-source, Meta has implemented several safety measures, including Llama Guard (a multilingual safety model) and Prompt Guard (a prompt injection filter)

Impressions:

  1. Advancement in Open-Source Language Models:

    • Llama 3.1 is considered a significant advancement in open-source language models. The 405 billion parameter version performs exceptionally well on most benchmarks.
  2. Free and Permissive License:

    • The model is free and has a permissive license, allowing for fine-tuning and customization, which is seen as a major advantage over closed-source models.
  3. Performance of Smaller Versions:

    • Some users found the 8 billion parameter version to be less capable than its Llama 3 counterpart for certain tasks. This is an important consideration for those using tools like Ollama for running models locally.

Use Cases:

  1. Multilingual Dialogue:

    • Llama 3.1 is optimized for multilingual dialogue use cases, making it versatile for global and clinical applications.
  2. Research and Development:

    • Meta is making it easier to train new models on Llama 3.1, which could lead to rapid advancements in AI research and development.
    • The model's advanced capabilities make it suitable for reviewing and summarizing medical research, which could aid healthcare professionals in staying up-to-date with the latest findings
  3. Advanced reasoning for complex medical queries

    • Llama 3.1, especially the 405 billion parameter model, has strong reasoning capabilities that can be applied to answer complex medical questions or analyze patient data.
  4. Conversational Patient Intake:

    • Groq has already demonstrated how Llama 3.1 can be used for conversational patient intake, showcasing its potential in healthcare applications.
  5. Developing intelligent healthcare agents

    • Llama 3.1's enhanced tool use and function calling capabilities allow for the creation of complex AI agents that can automate sophisticated healthcare tasks and answer intricate medical queries
  6. Customized healthcare applications

    • Healthcare organizations can fine-tune Llama 3.1 models with their proprietary medical data to create specialized AI systems for specific medical domains or use cases

Conclusion:

The open nature of the model has sparked discussions about potential risks and the need for responsible AI development. Mark Zuckerberg argues that open models are inherently safer, as they can be scrutinized by the community, but others worry about the potential for misuse.

At CareLaunch, we see AI as another tool we can make available to our partners. Rapid advances are happening in the space, and we hope to democratize the availability of these technologies to care providers, both small and large. By integrating advanced models and technologies, we aim to enhance our offerings and support our clients in delivering exceptional care. The potential for creating HIPAA-compliant solutions and improving outreach aligns with our commitment to providing secure and efficient healthcare communication tools.