One key milestone of tech market maturation is when leading alternatives narrow to a two-way horse race. That now describes the market for AI modeling frameworks, which are the environments within which data scientists build and train statistically driven computational graphs.
The AI modeling horse race narrows to TensorFlow vs. PyTorch
The clear leaders in AI modeling framework are now the Google-developed TensorFlow and the Facebook-developed PyTorch, and they’re pulling away from the rest of the market in usage, share, and momentum.
Though TensorFlow still has the predominant market share among working data scientists, PyTorch has come along fast among key user segments. According to this recent study, PyTorch has become the overwhelming favorite of data scientists in academic and other research positions; whereas TensorFlow continues to have strong adoption by enterprise AI, deep learning, and machine learning developers. PyTorch has built its following on such strengths as seamless integration with the Python ecosystem, a better designed API, and better performance for some ad-hoc analyses.