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Revolutionizing Databases with Generative AI

GenSQL, a generative AI system for databases, simplifies complex statistical analyses, predicts outcomes, detects anomalies, and generates synthetic data effortlessly. Developed by MIT researchers, GenSQL outperforms other AI-based approaches, providing faster and more accurate results with explainable probabilistic models.

AI Revolution: African Workers at $1/hour

Social media content moderation in outsourced centers in the global south exposes workers to disturbing material and harsh conditions. Meta content moderator Mercy faced a traumatic experience while reviewing a fatal car crash video, highlighting the toll of AI training data processing on human workers.

AI Safeguards Wimbledon Players

The All England Lawn Tennis Club utilizes AI to protect Wimbledon players from online abuse by monitoring social media profiles for threats and offensive language in 35 languages. The Threat Matrix service automatically flags death threats, racism, and sexism, ensuring player safety.

AI: Exploiting Human Labor

Fairwork experts reveal the harsh reality behind AI development in their book, 'Feeding the Machine'. African workers drive AI for just over a dollar an hour, exposing the exploitation in big tech's pursuit of artificial intelligence.

Mastering Medprompt: A Guide to Success

Microsoft introduces Medprompt, a groundbreaking prompting strategy that enhances GPT-4's performance in healthcare without fine-tuning. Can generalist LLMs outperform specialized models in specific domains?

AI: The End of TV as We Know It?

AI could soon be used to write TV shows, even allowing viewers to insert themselves as heroes. However, Justine Bateman warns of creative consequences and viewer confusion when AI interferes with storytelling.

Microsoft's AI Nightmare

Microsoft's new Copilot+ PCs take constant screenshots, offering AI image generation and real-time language translation. The privacy implications of this technology raise concerns about user data security.

Unraveling the Mystery of Machine Learning

Machine Learning models are becoming more prevalent, with 34% of companies already using ML for improved customer retention and revenue growth (IBM, 2022). The need for transparency in ML models, defined by terms like explainability and interpretability, is crucial for trust and accountability in decision-making processes, especially in industries like healthcare and criminal justice.