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The Hidden Variable in AI Success: Why Data Quality Trumps Model Size

The conversation about artificial intelligence typically orbits around model architecture, parameter counts, and ...

How synthetic data trains AI to solve real problems

The second approach uses generative AI to produce data. Modern generative models are trained on vast amounts of data and can ...

Phi-4 proves that a 'data-first' SFT methodology is the new differentiator

The Phi-4 model was trained on just 1.4 million carefully chosen prompt-response pairs. Instead of brute force, the Microsoft ...
dbta

Using Data Models to Improve Development

One of the biggest challenges facing organizations today is making sure that the right information gets to the right people. It requires attention, diligence, and planning to ensure that data is used ...
TechCrunch

Making AI models ‘forget’ undesirable data hurts their performance

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 ...
VentureBeat

How MIT is training AI language models in an era of quality data scarcity

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Improving the robustness of machine learning (ML) models for natural ...
Forbes

IBM Federated Learning Research - Extracting Machine Learning Models From Multiple Data Pools

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.
Retail TouchPoints

Using Prebuilt Data Models? You Should Be

In 1978, LEGO introduced a brand new line of construction sets branded LEGO Space. The sets in the series included parts and features built for science fiction adventure and were among the first to ...