Morning Overview on MSNOpinion

Climate models got it wrong, and the missing data explains why

Climate scientists are confronting a hard truth: some of the most widely used models are struggling to keep up with the pace ...
Analytics Insight

Why Large Language Models Can't Always Solve Math Problems

Overview: Large Language Models predict text; they do not truly calculate or verify math.High scores on known Datasets do not ...
NextBigFuture

AI Text Data Training and Other Scaling Problems and Limits

Unnamed OpenAI researchers told The Information that Orion (aka GPT 5), the next OpenAI full-fledged model release, is showing a smaller performance jump than the one seen between GPT-3 and GPT-4 in ...
Forbes

How Better Data Annotation Improves AI Model Performance

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...
ZDNet

Beware of AI 'model collapse': How training on synthetic data pollutes the next generation

To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...
Frontiers

Modeling, Machine Learning, Bioinformatics and Multi-omics Data in Soil Science

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...

Why AI Threat Models In Finance Must Follow The Data, Not The Code

For financial institutions, threat modeling must shift away from diagrams focused purely on code to a life cycle view ...
The Conversation

Tech companies are turning to ‘synthetic data’ to train AI models – but there’s a hidden cost

James Jin Kang does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond ...