Unlocking the power of unstructured data with RAG
Unstructured data holds valuable information about codebases, organizational best practices, and customer feedback. Here are some ways you can leverage it with RAG, or retrieval-augmented generation.
LLMs
In-depth articles and tutorials on leveraging LLMs, including natural language processing, code generation, and data analysis, with insights into training, fine-tuning, and deploying LLMs. Curious how to get started? Check out our guide on architecting LLM-powered applications.
Featured
How AI enhances static application security testing (SAST)
Here’s how SAST tools combine generative AI with code scanning to help you deliver features faster and keep vulnerabilities out of code.
Customizing and fine-tuning LLMs: What you need to know
Learn how your organization can customize its LLM-based solution through retrieval augmented generation and fine-tuning.
How we’re experimenting with LLMs to evolve GitHub Copilot
Learn how we’re experimenting with generative AI models to extend GitHub Copilot across the developer lifecycle.
Latest
The architecture of today’s LLM applications
Here’s everything you need to know to build your first LLM app and problem spaces you can start exploring today.
Demystifying LLMs: How they can do things they weren’t trained to do
Explore how LLMs generate text, why they sometimes hallucinate information, and the ethical implications surrounding their incredible capabilities.
A developer’s guide to open source LLMs and generative AI
Open source generative AI projects are a great way to build new AI-powered features and apps.
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