Strong Compute promises to speed up your ML model training – TechCrunch

Training neural networks takes a lot of time, even with the fastest and costliest accelerators on the market. It's maybe no surprise then that a number of startups are looking at how to speed up the process at the software level and remove some of the current bottlenecks in the training process. For Strong Compute, a Sydney, Australia-based startup that was recently accepted into Y Combinator's Winter '22 class, it's all about removing these inefficiencies in the training process. By doing so, the team argues that it can speed up the training process by 100x or more. "PyTorch is beautiful and so is TensorFlow. These toolkits are amazing, but the simplicity they have -- and the ease of implementation they have -- comes at the cost of things being inefficient under the hood," said Strong Compute CEO and founder Ben Sand, who previously co-founded AR company Meta (before Facebook used that name).