Templates

Automatic Talent Matching

Discover how TalentMatch Corp revolutionized their contractor matching process, cutting time from hours to seconds and boosting client satisfaction, all thanks to NUX's AI-powered workflows.
Personalized Student Interventions

Student retention is a persistent challenge that educational institutions face, with repercussions ranging from reduced funding to negative educational outcomes for students. Traditional approaches to tackle this issue often lack the granular insights needed for effective early intervention. The one-size-fits-all solutions commonly employed do not consider the varying degrees of academic performance and engagement levels among students. How can educational institutions adopt a more targeted, d
Personal Interactive Virtual Assistant

This Personal Interactive Virtual Assistant leverages Whisper for text to speech, ChatGPT for answering, and Bark for speech to text, evolving to a multi-modal, personalized assistant that integrates with daily tools, revolutionizing how individuals interact with technology.
Personalized Media Production

This AI-powered creative studio redefines media production by intelligently crafting content that resonates with diverse audiences, making it a groundbreaking solution in the entertainment and advertising industries.
Intelligent Virtual Sales Assistant

Excerpt: This virtual assistant enhances online shopping by integrating chat interaction, product visualization, and intelligent summarization.
Voice-Activated Content Creation

This solution transforms voice commands into visual and audio content, streamlining content creation.

Guides

Daisy-Chaining RAGs from Different Data Sources

Learn how to chain RAG models from multiple data sources for more accurate and complex queries.
Daisy Chaining Machine Learning Models for End-to-End Facial Recognition

In this article, we will explore how an engineer can leverage a series of pre-trained machine-learning models to create a comprehensive facial recognition system. This system will be capable of identifying faces in an image, detecting text within the image, converting that image to text, and finally translating the text. Each component of this process is driven by a different machine-learning model. The use of multiple models in this fashion is often referred to as 'daisy-chaining' models. Out
Real-Time Fraud Detection using SageMaker and LightGBM

Deploying a real-time fraud detection system using SageMaker and PyTorch involves data preprocessing, training a LightGBM model, and deploying it on SageMaker for predictions. This end-to-end guide offers a robust solution to detect fraudulent activities swiftly.
Building a Deepfake Detection System using SageMaker

Build a deepfake detection system using Mesonet and AWS SageMaker. This tutorial covers model deployment, inference pipeline creation, and future steps for fine-tuning.
Set Up and Run OpenAI's CLIP on Amazon SageMaker for Inference

How to deploy and run OpenAI's CLIP model on Amazon SageMaker for efficient real-time and offline inference.

Concepts

Retrieval Augmented Generation (RAG): Enhancing Contextual Responses in AI Models

Retrieval-Augmented Generation (RAG) represents an exciting frontier in artificial intelligence, bridging information retrieval and text generation to answer questions by finding relevant information and synthesizing responses in a coherent and contextually rich way.
What are Vector Embeddings and How are They Used in A.I?

Vector embeddings are a critical component in the world of machine learning and AI. These are mathematical representations of words or documents that enable the computer to interpret, compare, and analyze text, images, videos and audio. The idea is to represent words in a multi-dimensional space, where similar words cluster together. Let's take a deep dive into how vector embeddings work and how they can be utilized. content/vocab/vector-embeddings at master · nux-ai/contentContribute to nux-a

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