VentureBeat and other experts have argued that open-source large language models (LLMs) may have a more powerful impact on generative AI in the enterprise. More powerful, that is, than closed models, ...

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 ...

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 ...

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 ...

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

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 ...

AI promises a smarter, faster, more efficient future, but beneath that optimism lies a quiet problem that’s getting worse: the data itself. We talk a lot about algorithms, but not enough about the ...