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Reka AI Open Sourced Reka Flash 3: A 21B General-Purpose Reasoning Model that was Trained from Scratch
In today’s dynamic AI landscape, developers and organizations face several practical challenges. High computational demands, latency issues, and limited access to truly adaptable open-source models ...
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Visual Studio Code Setup Guide
Visual Studio Code (VSCode) is a lightweight but powerful source code editor that runs on your desktop. It comes with built-in support for JavaScript, TypeScript, and Node.js and has a rich ecosystem ...
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Basic Tutorials
The rapid growth of web content presents a challenge for efficiently extracting and summarizing relevant information. In this tutorial, we demonstrate how to leverage Firecrawl for web scraping and ...
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Getting Started with Kaggle Kernels for Machine Learning
Kaggle Kernels (also called Notebooks) represent a revolutionary cloud-based platform for data science and machine learning work. They provide a complete computational environment where you can write, ...
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Google AI Introduces Differentiable Logic Cellular Automata (DiffLogic CA): A Differentiable Logic Approach to Neural Cellular Automata
Researchers and enthusiasts have been fascinated by the challenge of reverse-engineering complex behaviors that emerge from simple rules in cellular automata for decades. Traditionally, this field ...
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A Step by Step Guide to Build a Trend Finder Tool with Python: Web Scraping, NLP (Sentiment Analysis & Topic Modeling), and Word Cloud Visualization
Monitoring and extracting trends from web content has become essential for market research, content creation, or staying ahead in your field. In this tutorial, we provide a practical guide to building ...
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Qilin: A Multimodal Dataset with APP-level User Sessions To Advance Search and Recommendation Systems
Search engines and recommender systems are essential in online content platforms nowadays. Traditional search methodologies focus on textual content, creating a critical gap in handling illustrated ...
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Tufa Labs Introduced LADDER: A Recursive Learning Framework Enabling Large Language Models to Self-Improve without Human Intervention
Large Language Models (LLMs) benefit significantly from reinforcement learning techniques, which enable iterative improvements by learning from rewards. However, training these models efficiently ...
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Inception Unveils Mercury: The First Commercial-Scale Diffusion Large Language Model
The landscape of generative AI and LLMs has experienced a remarkable leap forward with the launch of Mercury by the cutting-edge startup Inception Labs. Introducing the first-ever commercial-scale ...
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Evaluating Brain Alignment in Large Language Models: Insights into Linguistic Competence and Neural Representations
LLMs exhibit striking parallels to neural activity within the human language network, yet the specific linguistic properties that contribute to these brain-like representations remain unclear.
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This AI Paper from MIT and UCL Introduces a Diagrammatic Approach for GPU-Aware Deep Learning Optimization
Deep learning models, having revolutionized areas of computer vision and natural language processing, become less efficient as they increase in complexity and are bound more by memory bandwidth than ...
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This AI Paper Introduces a Parameter-Efficient Fine-Tuning Framework: LoRA, QLoRA, and Test-Time Scaling for Optimized LLM Performance
Large Language Models (LLMs) are essential in fields that require contextual understanding and decision-making. However, their development and deployment come with substantial computational costs, ...