#neural-networks

#neural-networks

Dong et al. (2019) and Tay et al. (2022) train on a mixture of denoising tasks with different attention masks (full, causal and prefix attention) to bridge the performance gap with next token pretraining on generative tasks.

The scaling laws in neural networks indicate that larger models and training data consistently enhance performance, leveraging empirical evidence from various studies to back these claims.

If the chilled water isn't actually chilled, the chiller fans are adding to the problem rather than helping solve it, leading to rising temperatures.

In a world where time is the most valuable resource, neural networks have become real super-helpers, especially in tasks like generating ideas and testing hypotheses.