SuperAnnotate

?? When setting up an LLM for specific tasks, you’ll often face a key decision: Retrieval Augmented Generation (RAG) or fine-tuning? Each approach has its unique strengths. ?? RAG: Provides real-time, up-to-date information by pulling from external databases. Ideal for complex queries and data-heavy industries like legal or healthcare. ??? Fine-Tuning: Customizes LLMs to specific business needs, ensuring precise answers and brand-aligned communication. Ideal for tasks requiring consistency and control, like customer service chatbots. Your choice depends on whether you prioritize adaptability (RAG) or precision (fine-tuning). ?? Read the full article: https://lnkd.in/e4XCg7vr

?? Explore how retrieval-augmented generation (#RAG) remains vital in long-context #LLMs, adapting with techniques like OP-RAG for enhanced precision. ?? Read the full article: https://lnkd.in/etFPq7iq

?? When #AI mimics human communication, it often misses the nuances that make conversations natural. Enter #RLHF - a powerful tool that enables AI to learn from human feedback, aligning its responses with what people actually value. RLHF fine-tunes large language models (#LLMs) to: 1. Improve AI’s understanding of human preferences 2. Create more natural interactions, like customer service bots that truly "get" the user 3. Reduce bias and ensure diverse perspectives in responses Learn more about how RLHF is transforming AI-human interactions in 2024. Link in comments! ??

SuperAnnotate is hosting Fine-tuning Foundation Models on Your Data with SuperAnnotate and AWS. Make sure to attend it on October 10.

It's our pleasure to share that CEO and Co-founder, Vahan Petrosyan will be speaking at this year’s #AIAIBoston. Vahan will talk about the hidden data complexities of building foundational models, and share his insights on navigating them and building more powerful #AI solutions. We’re counting down the days to the event!

Synthetic data is a creative workaround that lets you generate artificial datasets that mimic real-world data. In this article, we'll explore how #syntheticdata is generated specifically for fine-tuning #LLMs and multimodal models. We'll discuss the benefits, challenges, and figure out the best ways to mix synthetic data with real human-generated data to build even better #AI systems. Link in comments!

We are having a great Day 1 at ECCV expo! Our team is loving talking to all of you and sharing all the ways we can help with your projects. If you are attending, make sure to stop by our booth and have a chat. #SuperAnnotate #ComputerVision #ECCV2024

GumGum, a leader in Contextual Intelligence, excels in digital advertising by leveraging #AI to ensure brand safety and precise contextual targeting. A key to their success lies in the partnerships with SuperAnnotate and Databricks, which accelerates their #dataannotation and model #finetuning processes. Discover the challenges they encountered and how these collaborations helped them succeed. Link in comments!

We’re thrilled to share that we’ll be joining the European Conference on Computer Vision (#ECCV2024) expo in Milan from Oct 1-3. ?? Come visit us at Booth 45 to learn more about our latest developments and chat with our team. Can’t wait to see you there!

Fine-tuning LLMs for business-specific data offers: ? Enhanced accuracy ? Customized interactions ? Better data privacy ? Handling rare scenarios effectively Fine-tuning sharpens #LLM capabilities to meet your unique business needs. Want to learn more? We cover everything you need to know about #finetuning large language models in 2024. Link in comments!