marktechpost4d
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 ...
marktechpost4d
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, ...
marktechpost5d
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 ...
marktechpost7d
Starter Guide For Running Large Language Models LLMs
Running large language models (LLMs) presents significant challenges due to their hardware demands, but numerous options exist to make these powerful tools accessible. Today’s landscape offers several ...
marktechpost5d
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 ...
marktechpost5d
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 ...
marktechpost5d
Meet Manus: A New AI Agent from China with Deep Research + Operator + Computer Use + Lovable + Memory
In today’s digital era, the way we work is rapidly evolving, yet many challenges persist. Conventional AI assistants and manual workflows struggle to keep pace with the complexity and volume of modern ...
marktechpost6d
AutoAgent: A Fully-Automated and Highly Self-Developing Framework that Enables Users to Create and Deploy LLM Agents through Natural Language Alone
From business processes to scientific studies, AI agents can process huge datasets, streamline processes, and help in decision-making. Yet, even with all these developments, building and tailoring LLM ...
marktechpost5d
Finer-CAM Revolutionizes AI Visual Explainability: Unlocking Precision in Fine-Grained Image Classification
Researchers at The Ohio State University have introduced Finer-CAM, an innovative method that significantly improves the precision and interpretability of image explanations in fine-grained ...
marktechpost5d
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 ...
marktechpost4d
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 ...
marktechpost7d
A Coding Guide to Sentiment Analysis of Customer Reviews Using IBM’s Open Source AI Model Granite-3B and Hugging Face Transformers
In this tutorial, we will look into how to easily perform sentiment analysis on text data using IBM’s open-source Granite 3B model integrated with Hugging Face Transformers. Sentiment analysis, a ...