Superalignment Fast Grants
We’re launching $10M in grants to support technical research towards the alignment and safety of superhuman AI systems, including weak-to-strong generalization, interpretability, scalable oversight, and more.
We’re launching $10M in grants to support technical research towards the alignment and safety of superhuman AI systems, including weak-to-strong generalization, interpretability, scalable oversight, and more.
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The evolution of language models is a critical component in the dynamic field of natural language processing. These models, essential for emulating human-like text comprehension and generation, are instrumental in various applications, from translation to conversational interfaces. The core challenge tackled in this area is refining model efficiency, particularly in managing lengthy data sequences. Traditional…
Manifold learning, rooted in the manifold assumption, reveals low-dimensional structures within input data, positing that the data exists on a low-dimensional manifold within a high-dimensional ambient space. Deep Manifold Learning (DML), facilitated by deep neural networks, extends to graph data applications. For instance, MGAE leverages auto-encoders in the graph domain to embed node features and…
Large-scale multilingual language models are the foundation of many cross-lingual and non-English Natural Language Processing (NLP) applications. These models are trained on massive volumes of text in multiple languages. However, the drawback to their widespread use is that because numerous languages are modeled in a single model, there is competition for the limited capacity of…
While generating realistic tabular data, one of the difficulties faced by the researchers is maintaining privacy, especially in sensitive domains like finance and healthcare. As the amount of data and the importance of data analysis is increasing in all fields and privacy concerns are leading to hesitancy in deploying AI models, the importance of maintaining…