Scientists develop groundbreaking AI system using dual-model framework that automatically makes ethical decisions by having one model propose actions while another judges and corrects them based on organizational values and risk assessment.
Scientists at University of Texas at Dallas unveil a revolutionary brain-inspired computer that learns like humans while consuming 90% less energy than current AI systems, potentially bringing powerful machine learning capabilities to mobile devices and dramatically reducing the environmental impact of artificial intelligence.
Georgia Tech researchers develop revolutionary AI-powered artificial muscles using hierarchically structured fibers that learn and adapt in real time like human tissue, with a prosthetic glove demonstration showing the technology can restore natural dexterity and instantly respond to user movements.
Six AI-powered OCR systems including Google Cloud Document AI, Amazon Textract, and Microsoft Azure revolutionize document processing in 2025 by offering advanced features like layout preservation, table detection, and multilingual support beyond traditional text extraction.
Bevel secures $10M Series A funding from General Catalyst as the AI health companion reaches 100,000 daily users with 8x growth, offering $6 monthly software that unifies wearable data across sleep, fitness, and nutrition without requiring proprietary hardware.
Cognition unveils SWE-1.5, a breakthrough AI coding model with hundreds of billions of parameters that blazes at 950 tokens per second—13x faster than Sonnet 4.5—while delivering near state-of-the-art performance through advanced reinforcement learning and partnership with Cerebras infrastructure.
Google dramatically enhances NotebookLM with an 8x larger context window, 6x longer conversation memory, and 50% better response quality, while introducing custom role settings that let users transform the AI into specialized advisors like research consultants or marketing strategists.
Cursor 2.0 launches with breakthrough Composer AI that codes 4x faster than competitors, completing most programming tasks in under 30 seconds while introducing agent-based interface that runs multiple coding processes simultaneously without interference.
Major AI interpretability research approaches including feature visualizations, saliency maps, and sparse autoencoders fail to decode how neural networks actually work after over a decade of investment, prompting Google DeepMind to abandon leading techniques and researchers to shift toward higher-level analysis methods.
Cursor launches Composer, a revolutionary AI coding agent that generates software four times faster than competitors using advanced mixture-of-experts architecture and reinforcement learning trained on real-world engineering challenges.