Discover how predictive analytics uses data-driven models like decision trees and neural networks to forecast outcomes and ...

AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology ...

When most people hear “observability,” they think of on-call rotations, alerts and dashboards for SREs. That narrow view is changing. Over the past few years, observability tools and the practices ...

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...

Data is at the heart of today’s advanced AI systems, but it’s costing more and more — making it out of reach for all but the wealthiest tech companies. Last year, James Betker, a researcher at OpenAI, ...

Sophie Bushwick: To train a large artificial intelligence model, you need lots of text and images created by actual humans. As the AI boom continues, it's becoming clearer that some of this data is ...

Researchers have found that introducing human-made data into AI training can help to prevent AI model collapse.