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Showing posts with the label AI Scraping

Google DeepMind Introduces AlphaGenome: AI Revolutionizing Genetic Mutation Forecasting

 In a remarkable leap for biomedical science, Google DeepMind has unveiled AlphaGenome , a powerful new AI system capable of predicting mutations in human DNA with groundbreaking accuracy. This innovation marks a significant advancement in how we understand the genome and paves the way for revolutionary applications in genetic disease research, personalized medicine, and gene therapy development . 🔬 What Is AlphaGenome? AlphaGenome is a deep learning model trained on vast amounts of genomic data to understand how mutations can affect the human body at the molecular level. While previous models could analyze DNA sequences, AlphaGenome anticipates potential mutations — a major step forward in predictive genomics. This means the AI can forecast how a single change in DNA might alter a protein, influence disease risk, or affect treatment response. 🚀 Why This Breakthrough Matters Early Detection of Genetic Disorders AlphaGenome could become a key tool in identifying rare...

Bluesky Faces Growing Debate Over User Data and AI Training Policies

 Bluesky, the decentralized social media platform that emerged as a promising alternative to traditional networks, is currently grappling with a heated discussion within its community regarding user data privacy and the potential use of that data in artificial intelligence (AI) training. As conversations about data privacy grow increasingly important across the tech world, Bluesky’s user base—long invested in the promise of a decentralized and transparent social experience—is raising concerns about how their data might be utilized. The debate centers on whether Bluesky will allow third parties, including AI developers, to access public user data for training machine learning models. Bluesky’s Unique Position in Social Media Bluesky was originally incubated within Twitter but has since branched off as an independent, decentralized network. It promises to hand control back to users through a federated model, where different servers (or “instances”) can operate with their own rules...