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Today:

• OpenAI Considers Humanoid Robot Development

• Qwen’s QVQ Challenges Top Models

• NYT Developed Its Own Chatbot

• AI Revolutionizes Soccer Game Analysis

OpenAI Considers Humanoid Robot Development

OpenAI considered developing a humanoid robot. The AI company has invested in robotics firms like Figure and 1X but abandoned its own robotics division in 2021. 

With recent advancements in AI and hardware, OpenAI may revisit this competitive field, though reentry would require significant effort to catch up. The report highlights OpenAI's ongoing interest in combining AI systems with robotics innovations.

Qwen’s QVQ Challenges Top Models

Alibaba's AI research team, Qwen, has unveiled QVQ-72B-Preview, an open-source model specializing in visual reasoning. It analyzes images step-by-step, excelling in math and physics benchmarks alongside top AI models like OpenAI's o1. 

While powerful, it faces challenges like language switching and logical loops. Qwen envisions this as a step toward a unified "omni" AI for tackling complex problems. The model is available for free via Hugging Face.

NYT Developed Its Own Chatbot

In 2023, The New York Times began developing an internal ChatGPT-like tool, advising its team to avoid other AI language models (LLMs). This surfaced in Microsoft's AI copyright case, where it requested details on reporters' chatbot use. 

It remains unclear if this tool aligns with products the Times has since introduced. The revelation highlights the media's exploration of proprietary AI solutions amidst broader industry debates.

AI Revolutionizes Soccer Game Analysis

Researchers from Shanghai Jiao Tong University and Alibaba developed MatchVision, an AI system that analyzes soccer games, identifies 24 events like goals and fouls, and generates commentary. 

Built using "SoccerReplay-1988," the largest soccer dataset, it spans 3,300+ hours of footage. MatchVision achieves 84% accuracy, outperforming prior systems. This technology could enhance highlights and assist referees. The dataset and model will soon be available on GitHub.

🧠RESEARCH

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding

3DGraphLLM enhances 3D scene understanding by integrating semantic graphs with large language models. It captures object relationships, improving performance in 3D vision-language tasks. Tested on multiple datasets, it outperforms methods relying solely on object coordinates.

DepthLab: From Partial to Complete

DepthLab addresses missing depth data with a robust inpainting model using image diffusion priors. It excels in filling gaps while preserving scale consistency. Tested on tasks like 3D scene inpainting and LiDAR depth completion, it outperforms existing methods in accuracy and visuals.

Fourier Position Embedding: Enhancing Attention's Periodic Extension for Length Generalization

Fourier Position Embedding (FoPE) enhances attention in language models by addressing limitations in RoPE-based mechanisms. FoPE leverages Fourier Series to improve periodicity and length generalization, ensuring stable performance across extended contexts. It outperforms RoPE and ALiBi in maintaining accuracy and robustness.

🛠️TOP TOOLS

Midjourney Prompt Generator - Designed to create detailed and effective prompts for the Midjourney AI image generation platform. 

BasedLabs AI - AI-powered tools for image and video generation

Mokker AI - AI-powered solution for instant, professional product photography, allowing users to generate high-quality images from a single product photo.

ChatGPT Sidebar - AI assistant for various tasks across web pages.

GhostCut - AI-powered video editing tool that offers advanced features such as automatic text removal, video translation, and dubbing in multiple languages.

📲SOCIAL MEDIA

🗞️MORE NEWS

• AI is transforming blood test analysis by detecting diseases like ovarian cancer and pneumonia earlier and more accurately. Using pattern recognition and vast data sets, it reduces diagnostic time and costs, improving patient outcomes.

• Tech giants Nvidia, OpenAI, and others are intensifying competition in AI by expanding into rival domains. Companies aim to dominate AI hardware, software, and services while reducing reliance on key suppliers to cut costs and innovate.

• Dogs trained to detect cancer scents, paired with AI, achieved 94% accuracy in identifying four cancer types from breath samples. This innovative approach shows promise for early detection, improving survival rates through advanced screening technology.