While the AI industry grows with record-speed, building on a machine learning platform can help to promote best practices and scientific comparability.
Artificial Intelligence has come a long way in recent years. Remember when IBM's Deep Blue beat Gary Kasparov in chess in 1997? Since then, AI has developed from the pioneer days into a massive industry, tackling enormous problems in various fields and developing new techniques and strategies every day.
Like with every new industry in gold rush fever, progress is fast, too fast sometimes to consolidate. New, brilliant approaches to solve a problem are developed at lightning speed, but at the same time best practices need to develop in order to progress further.
Applying Best Practices Systematically
This is where machine learning platforms can help. Working on a platform has many advantages for developers. Platforms offer an abstraction from the underlying hardware infrastructure. Some even offer prebuilt modules for some machine learning tasks.
Another important, but often overlooked feature of machine learning platforms is that they help structurize the development process.
Clusterone, as well as many other platforms use Git to store both code and datasets. This forces developers to apply version control to their project. It also makes it easier for teams to compare the results of different configurations and software versions. Instead of re-uploading code, all it takes is to specify a different Git commit when starting a job.
Increasing Experiment Reproducibility
Using a machine learning platform also helps to promote scientific reproducibility of experiments in the AI community. Code and data can be easily shared between research groups, and built-in versioning makes it easy to trace the progress of a project.
This way, other teams can try to reproduce experiment results using the same infrastructure and hardware, dramatically increasing comparability.
Machine Learning Platforms Help You Adopt Best Practices
With the rise of easy-to-use platforms, machine learning research can become broader and at the same time more consistent. Be part of this exciting development. Clusterone offers everything you need to run your TensorFlow or PyTorch code in minutes. Click here to learn more about our platform.