Introducing Meta LLaMA 3: A Leap Forward in Large Language Models

Thursday, April 18, 2024

Meta has recently unveiled its latest innovation in the realm of artificial intelligence: the LLaMA 3 large language model. This state-of-the-art model represents a significant advancement in AI technology, offering unprecedented capabilities and accessibility.

What is LLaMA 3?

LLaMA 3 is the third iteration of Meta's large language model series. It is an open-source model that has been fine-tuned with instructions to optimize its performance across a wide array of tasks. The model comes in two sizes: one with 8 billion parameters and another with a colossal 70 billion parameters.

Features and Capabilities

The LLaMA 3 models are designed to excel in language understanding and generation, making them highly effective for applications such as dialogue systems, content creation, and complex problem-solving. Some of the key features include:

-Enhanced Reasoning

LLaMA 3 demonstrates improved reasoning abilities, allowing it to handle multi-step problems with ease.

-Multilingual and Multimodal Future

 Plans are underway to make LLaMA 3 multilingual and multimodal, further expanding its versatility.

Extended Context Windows

 The new models support longer context windows, enabling them to maintain coherence over larger text spans.

The Meta Llama 3 models have been enhanced with a substantial increase in training tokens, reaching 15trillion, which greatly improves their ability to grasp the nuances of language. The context window has been expanded to 8,000 tokens, effectively doubling the previous model's capacity and allowing for the processing of more extensive text excerpts, which aids in making more informed decisions. Additionally, these models employ a novel Tiktoken-based tokenizer that boasts a128,000-token vocabulary, resulting in a more efficient encoding of characters per token. Meta has observed improved performance in both English and multilingual benchmark assessments, confirming the models' strong capabilities in handling multiple languages.

Unmatched Performance Excellence

The introduction of our 8B and 70B parameter LLaMA 3 models marks a significant advancement beyond the capabilities of LLaMA 2, setting a new benchmark for large language models (LLMs) at these scales. Enhanced pretraining and refined post-training techniques have elevated our models to the pinnacle of performance, making them the premier choice in the current landscape for 8B and 70B parameter models. Notable enhancements in our post-training processes have led to a considerable decrease in incorrect rejections, bolstered model alignment, and enriched the variety of responses generated by the models. Furthermore, we've observed a remarkable enhancement in functions such as logical reasoning, code creation, and adherence to instructions, rendering LLaMA 3 more adaptable and responsive to user guidance.

Accessibility and Community Support

In line with Meta's commitment to open innovation, LLaMA 3 is made available to the broader community. It can be accessed on various platforms, including AWS, Databricks, Google Cloud, and Microsoft Azure, among others¹. This move is intended to foster a wave of AI innovation across different sectors.

It's now available on Azure

Trust and Safety

Meta has introduced new trust and safety tools, such as LLaMA Guard 2 and Code Shield, to ensure the responsible use of LLaMA 3. These tools are part of a comprehensive approach to address the ethical considerations associated with deploying large language models¹.

The Impact of LLaMA 3

The release of LLaMA 3 is poised to have a profound impact on the AI landscape. By providing a powerful tool that is openly accessible, Meta is enabling developers and researchers to push the boundaries of what's possible with AI. The model's capabilities in understanding and generating human-like text will unlock new possibilities in various fields, from education to customer service.

As we look to the future, LLaMA 3 stands as a testament to Meta's dedication to advancing AI technology while maintaining a focus on ethical and responsible development. It's an exciting time for AI, and LLaMA 3 is at the forefront of this technological revolution.

More details 

(1) Introducing Meta Llama 3: The most capable openly available LLM to date.

(2) Meta Llama 3.

#Meta #llama #Azure #MVPBuzz #generativeai #GenAI #LLM #Opensource 

Power BI With Copilot

Sunday, April 14, 2024

Get Started with Copilot for Power BI and Create Reports Faster

Ready to unlock the power of AI in your data analysis? Copilot, a new feature in Power BI Desktop, is here to help you create reports faster and easier. With Copilot's assistance, you can generate report summaries, suggest report content, and even create entire report pages based on your high-level instructions.

What You'll Need to Use Copilot:

  • Access: You'll need write access to a workspace assigned to a paid Power BI capacity (P1 or higher) or a paid Fabric capacity (F64 or higher) with Copilot enabled by your administrator.
  • Power BI Desktop: Ensure you're using the latest version of Power BI Desktop.

Getting Started with Copilot:

  1. Enable Copilot (Admin): Your administrator needs to enable Copilot in Microsoft Fabric and activate the tenant switch.
  2. Open the Copilot Pane: Click the Copilot icon in the ribbon to open the Copilot pane.
  3. Welcome and Workspace Selection: The first time you use Copilot, a dialog will appear prompting you to choose a compatible workspace. Select any workspace assigned to the required capacity.
  4. Start Your Interaction: Once you've selected a workspace, you'll see a welcome card. Click "Get started" to begin using Copilot.

How Copilot Can Help You:

  • Summarize Your Data Model: Gain a clearer understanding of your data with Copilot's summaries of your Power BI semantic model. This can help you identify key insights and streamline your report building process.

  • Suggest Report Content: Stuck on what to include in your report? Copilot can analyze your data and propose relevant topics for you to explore. From the Copilot pane, select "Suggest content for a report" to get started.
  • Create Report Pages: Save time crafting reports from scratch. Provide Copilot with a high-level prompt related to your data, and Copilot will generate a customizable report page with relevant tables, fields, measures, and charts. Here are some examples of prompts you can use:
    • Analyze performance across different shifts based on metrics like good count, reject count, and alarm count.
    • Evaluate production line efficiency and overall equipment effectiveness.
    • Compare costs, materials, and their impact on production for each product

Important Considerations:

  • The Copilot button will always be visible in the ribbon, but functionality requires signing in, admin enabled tenant settings, and workspace access as mentioned earlier.
  • The workspace you select for Copilot usage doesn't have to be the same one where you publish your report.
  • Copilot is currently in preview, and its responses are generated using AI, so always double-check your work for accuracy.
  • There are limitations for creating report pages with certain connection modes like live connect to SSAS and AAS, and real-time streaming in Power BI.

Stay Updated:

Keep an eye out for the latest Copilot enhancements by following the monthly Power BI feature summary blogs.

Embrace AI-powered report creation with Copilot and transform your data analysis workflow!

RAG live Demo with Azure and openAi

Saturday, April 6, 2024