I gave OpenAI’s new ChatGPT Images 2.0 ten impossible prompts to test its limits, and the results are stunning

I tested the new ChatGPT Images 2.0 model with 10 real-world prompts to check how the model performs in different scenarios.

ChatGPT Image 2.0 Signals Visual Reasoning To Solve Real-World Tasks

ChatGPT Image 2.0 suggests that AI image generation is evolving into visual reasoning and verifiable AI, with implications ...
IEEE

Adaptive Dual-Axis Style-Based Recalibration Network With Class-Wise Statistics Loss for Imbalanced Medical Image Classification

Abstract: Salient and small lesions (e.g., microaneurysms on fundus) both play significant roles in real-world disease diagnosis under medical image examinations. Although deep neural networks (DNNs) ...
techannouncer

Mastering Python: Practical Code Examples for Every Skill Level

Learning Python can feel like a big task, especially when you’re just starting out. But honestly, the best way to get a handle on it is to just start writing code. We’ve put together some practical ...
IEEE

ITJP: Image and Text Joint Prompts for Few-Shot Whole Slide Image Classification

Multiple instance learning has achieved remarkable results in whole slide image (WSI) classification. However, constrained by patient privacy and the scarcity of cancer data, the insufficient quantity ...
blockchain

Meta Muse Spark Breakthrough: Image-to-Code Demo Shows Asset Extraction and UI Generation

According to AI at Meta on X (via a thread highlighting community projects), creator Pietro Schirano (@skirano) demonstrated Muse Spark converting a UI screenshot into production-ready code while ...
GitHub

text-classification-algorithms

AI-powered Resume Screener using Scikit-learn, featuring text preprocessing, TF-IDF vectorization, and ML models (Logistic Regression, SVM, Random Forest) to classify and rank resumes for automated ...