Kareem Amin

Synthetically-generated data plays an increasingly larger role in training large language models. However, while synthetic data has been found to be useful, studies have also shown that without proper curation it can cause LLM performance to plateau, or even "collapse", after many training iterations. In this paper, we formalize this question and develop a theoretical framework to investigate how much curation is needed in order to ensure that LLM performance continually improves.

Clay, a Canadian-founded go-to-market AI startup based in New York City, has closed a $115-million USD (approximately $159 million CAD) Series D round that values the company at $7.1 billion USD. The financing was led by Wellington and included participation from Andreessen Horowitz, CapitalG, Meritech, Sequoia and others.

As the digital landscape unfurls its myriad complexities, the dawn of Automated Machine Learning (AutoML) emerges as a beacon of innovation. This is not merely a technological advancement; it’s the inception of a transformative era, a symphony of manual prowess harmonizing with the rhythm of automation. 🌅 Within the hallowed halls of academia, a conversation during my PhD studies with a sagacious professor offered a profound insight.