Thinking Stack Research Image Recognition: How Does It Work and What Are Its Applications? Image recognition has undoubtedly altered the way machines perceive and understand digital images, much like humans do in their natural language processing today's fast-paced technological world. Comp...
Thinking Stack Research AI Hallucination in Generative Models: Risks and Solutions AI Hallucinations occur Recently, from large language model to generative AI capable of producing human-like text, generating images, and solving complex tasks, the rhythm of growth has been accelerat...
Thinking Stack Research Benefits of Using AI in the Enhancement of Image Resolution enhancer From media and healthcare to e-commerce and security, good quality images are a need in today's digital world. Whether it be a photo enhancer, used to enhance personal photos, or the use of clear prod...
Thinking Stack Research Scalability in MLOps: Handling Large-Scale Machine Learning Models Introduction to MLOps and Scalability What is MLOPs ? MLOps, in other words, machine learning operations, is the chief most imperative constituent that deals with deploying machine learning models int...
Thinking Stack Research Revolutionizing Customer Service: The Impact of AI Chat Generators in Business In today's fast-moving digital world, businesses increasingly use artificial intelligence to maximize their operations, offer more improved levels of customer service, and create content. Perhaps the ...
Thinking Stack Research Understanding the Distinctions Between Generative AI and LLMs Artificial intelligence has recently gained huge momentum. Among such, Generative AI and large language models probably hold two of the most critical terminologies a person may need to understand. Whi...
Thinking Stack Research A Survey of Large Language Models and Their Application Introduction to Large Language Models In today's artificial intelligence, large language models are an essential component, especially concerning NLP. These large language models have, in fact, turned...
Thinking Stack Research Generative AI: Applications, Opportunities, & Challenges for GenAI There is significant scope in adopting generative AI to solve complex challenges with new innovations. The GenAI market itself is poised to reach $1.3 Trillion by 2032 according to some estimates, wit...
Thinking Stack Research Optimisation & Validation on Intel Architecture Intelligent Video Summarization Here Generative AI and Large Vision Models to automatically summarize extensive hours of surveillance footage, focusing on significant activities to improve security pr...
Thinking Stack Research Understanding the benefits of RAG in GenAI Retrieval augmented generation or RAG combines pre-trained parametric models and non-parametric memory retrieval, to provide higher quality insights based on entered queries. The AI architecture solut...
Thinking Stack Research What's the Difference between AI and Generative AI? While there are multiple types of AI, based on which applications can be created, all types of AI are functions based. The function of normal AI is to provide some form of output based on an input thr...
Thinking Stack Research Machine Vision vs Computer Vision for Industrial Applications There is a lot of interest around computer vision as a concept in industrial settings, to streamline production and find defects better. Enterprises can benefit from computer vision in multiple ways, ...