๐ง ๐ AMI/AGI Brain & World Ship Design Assistant ๐๐ฌ
#1
by
awacke1
- opened
Welcome to an experimental challenge to use real world science research and scholarly papers to forms basis of specification and design of an AMI and World Ship which explores emerging methods in science, physics, mathematics, data driven frameworks and energy empowerment of frameworks and systems.
Our Journey today starts with a bit of research...
๐ง ๐ AMI/AGI Brain & World Ship Design Assistant ๐๐ฌ
๐๐ AI Research in Video & Gaming Applications Summary
Paper Title | Emoji Summary |
---|---|
"Did You Hear That?" Learning to Play Video Games from Audio Cues | ๐ฎ๐๐โก๏ธ๐ค Learning from audio to enhance game AI. |
A Survey of AI Text-to-Image and AI Text-to-Video Generators | ๐๐ผ๏ธ๐ฅ๐ค Exploring AI's ability to create visuals from text. |
General Video Game AI: Learning from Screen Capture | ๐ฎ๐ฅ๏ธ๐๐ค Screen capture for diverse game learning. |
Machine Learning enabled models for YouTube Ranking Mechanism and Views Prediction | ๐๐ฅ๐๐ค Predicting YouTube content success with AI. |
Large Language Models and Video Games: A Preliminary Scoping Review | ๐ฎ๐๐๐ค Investigating LLMs in game development and research. |
A Comprehensive Review of Computer Vision in Sports | ๐๏ธ๐๏ธโ๐จ๏ธ๐ค Sports analysis through computer vision. |
AI-Generated Content (AIGC) for Various Data Modalities: A Survey | ๐ผ๏ธ๐ฅ๐๐ค Cross-modality content creation with AI. |
From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI | โ๏ธ๐น๏ธ๐๐ค Game AI's impact beyond gaming. |
General Video Game AI: a Multi-Track Framework for Evaluating Agents, Games and Content Generation Algorithms | ๐ฎ๐๐๐ค Multi-track evaluation in game AI. |
Detection of GAN-synthesized street videos | ๐๏ธ๐ฅ๐ต๏ธโโ๏ธ๐ค Spotting AI-generated street videos. |
AI-driven Mobile Apps: an Explorative Study | ๐ฑ๐ค๐ Exploring the AI app landscape. |
A Framework and Dataset for Abstract Art Generation via CalligraphyGAN | ๐๏ธ๐จ๐ค๐ Creating abstract art with AI. |
Learning-Based Video Game Development in MLP@UoM: An Overview | ๐ฎ๐๐ค Learning-focused game development insights. |
Comparative Analysis of Deep-Fake Algorithms | ๐งโ๐ค๐ฅ๐ต๏ธโโ๏ธ๐ค Comparing deep-fake detection methods. |
Generative AI for learning: Investigating the potential of synthetic learning videos | ๐๐ฅ๐ค Synthetic videos for education. |
Extend the FFmpeg Framework to Analyze Media Content | ๐ฅ๐๐ค Enhancing FFmpeg with AI for media analysis. |
A Survey of Embodied AI: From Simulators to Research Tasks | ๐ค๐๐ Exploring embodied AI's simulators and tasks. |
A Survey of Task-Based Machine Learning Content Extraction Services for VIDINT | ๐ฅ๐๐ค Video content extraction with AI. |
AIGCBench: Comprehensive Evaluation of Image-to-Video Content Generated by AI | ๐ผ๏ธ๐ฅ๐๐ค Benchmarking AI-generated video content. |
PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games | ๐ฒ๐ค๐ Reinforcement learning in tabletop games. |