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Evaluating AI Model Security Using Red Teaming Approach: A Comprehensive Study on LLM and MLLM Robustness Against Jailbreak Attacks and Future Improvements
The emergence of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) represents a significant leap forward in AI capabilities. These models have advanced to a point where they can generate text, interpret images, and even understand complex...
Meet AnythingLLM: An Open-Source, All-in-One AI Desktop App for Local LLMs + RAG
In today’s business world, the advent of artificial intelligence (AI) has revolutionized the way organizations communicate, particularly in handling and extracting value from documents. Meet AnythingLLM: an innovative open-sourced full-stack application that...
Researchers at Intel Labs Introduce LLaVA-Gemma: A Compact Vision-Language Model Leveraging the Gemma Large Language Model in Two Variants (Gemma-2B and Gemma-7B)
Recent advancements in large language models (LLMs) and Multimodal Foundation Models (MMFMs) have spurred interest in large multimodal models (LMMs). Models like GPT-4, LLaVA, and their derivatives have shown remarkable performance in vision-language tasks such as...
How to Use Google Colab: A Beginner’s Guide
Google Colab, short for Google Colaboratory, is a free cloud service that supports Python programming and machine learning. It’s a dynamic tool that enables anyone to write and execute Python codes on a browser. This platform is favored for its zero-configuration...
Researchers at Microsoft AI Propose LLM-ABR: A Machine Learning System that Utilizes LLMs to Design Adaptive Bitrate (ABR) Algorithms
Large Language models (LLMs) have demonstrated exceptional capabilities in generating high-quality text and code. Trained on vast collections of text corpus, LLMs can generate code with the help of human instructions. These trained models are proficient in translating...
This Machine Learning Research Introduces Mechanistic Architecture Design (Mad) Pipeline: Encompassing Small-Scale Capability Unit Tests Predictive of Scaling Laws
Creating deep learning architectures requires a lot of resources because it involves a large design space, lengthy prototyping periods, and expensive computations related to at-scale model training and evaluation. Architectural improvements are achieved through an...
