marktechpost7d
Top 20 Guardrails to Secure LLM Applications
The rapid adoption of Large Language Models (LLMs) in various industries calls for a robust framework to ensure their secure, ethical, and reliable deployment. Let’s look at 20 essential guardrails ...
marktechpost8d
Salesforce AI Research Introduces CodeTree: A Multi-Agent Framework for Efficient and Scalable Automated Code Generation
Automated code generation is a rapidly evolving field that utilizes large language models (LLMs) to produce executable and logically correct programming solutions. These models, pre-trained on vast ...
marktechpost7d
This AI Paper from UCLA Unveils ‘2-Factor Retrieval’ for Revolutionizing Human-AI Decision-Making in Radiology
Integration of AI into clinical practices is very challenging, especially in radiology. While AI has proven to enhance the accuracy of diagnosis, its “black-box” nature often erodes clinicians’ ...
marktechpost5d
Adaptive Attacks on LLMs: Lessons from the Frontlines of AI Robustness Testing
The field of Artificial Intelligence (AI) is advancing at a rapid rate; specifically, the Large Language Models have become indispensable in modern AI applications. These LLMs have inbuilt safety ...
marktechpost7d
Meta AI Just Open-Sourced Llama 3.3: A New 70B Multilingual Large Language Model (LLM)
Meta AI just released Llama 3.3, an open-source language model designed to offer better performance and quality for text-based applications, like synthetic data generation, at a much lower cost. Llama ...
marktechpost6d
UC Berkeley Researchers Explore the Role of Task Vectors in Vision-Language Models
Vision-and-language models (VLMs) are important tools that use text to handle different computer vision tasks. Tasks like recognizing images, reading text from images (OCR), and detecting objects can ...
marktechpost6d
Retrieval-Augmented Reasoning Enhancement (RARE): A Novel Approach to Factual Reasoning in Medical and Commonsense Domains
Question answering (QA) emerged as a critical task in natural language processing, designed to generate precise answers to complex queries across diverse domains. Within this, medical QA poses unique ...
marktechpost6d
Auto-RAG: An Autonomous Iterative Retrieval Model Centered on the LLM’s Powerful Decision-Making Capabilities
Retrieval Augmented Generation is an efficient solution for knowledge-intensive tasks that improves the quality of outputs and makes it more deterministic with minimal hallucinations. However, RAG ...
marktechpost7d
NVIDIA AI Introduces NVILA: A Family of Open Visual Language Models VLMs Designed to Optimize both Efficiency and Accuracy
Visual language models (VLMs) have come a long way in integrating visual and textual data. Yet, they come with significant challenges. Many of today’s VLMs demand substantial resources for training, ...
marktechpost7d
Advancing Large Multimodal Models: DocHaystack, InfoHaystack, and the Vision-Centric Retrieval-Augmented Generation Framework
LMMs have made significant strides in vision-language understanding but still need help reasoning over large-scale image collections, limiting their real-world applications like visual search and ...
marktechpost7d
CPU-GPU I/O-Aware LLM Inference Reduces Latency in GPUs by Optimizing CPU-GPU Interactions
LLMs are driving major advances in research and development today. A significant shift has been observed in research objectives and methodologies toward an LLM-centric approach. However, they are ...
marktechpost8d
Meet Steel.dev: An Open Source Browser API for AI Agents and Apps
Developing AI applications that interact with the web is challenging due to the need for complex automation scripts. This involves handling browser instances, managing dynamic content, and navigating ...