By WalkingTree July 28, 2020
As organizations adopt analytic technologies such as ML and AI, they’re discovering more about themselves and their worlds. Adoption of ML, especially, prompts organizations to start asking questions that challenge in different ways what the organization thinks it knows about itself. Let’s take a look at some of the trends framing the state of AI and ML.
Growth in ML and AI is unabated
Engagement with the artificial intelligence topic continues to grow in 2020, 88% in 2018, and 58% in 2019, outpacing share growth in the much larger machine learning topic (14% in 2018, up 5% in 2019).
Unsupervised learning is growing
Interest in unsupervised learning increased significantly, with usage up by 53% in 2018 and by 172% in 2019. What’s driving this growth? Unsupervised learning is noted as a separate topic, with the growth in engagement driven by more sophisticated users and improved tools.
Usage in advanced techniques is up—mostly
Looking at the AI and ML topic detail. There has been an increased usage in neural networks continuing its upward trend—up 52% in 2018; up 17% in 2019—but the related topic of deep learning dropped 10% in 2019.
The rising AI/ML tide lifts all boats
Another topic showing consistent growth is natural language processing (NLP). Its growth rate isn’t spectacular, plus 15% in 2018 and plus 9% in 2019, but NLP now accounts for about 12% of all AI/ML usage.
Python-based tools are ascendant in AI/ML
PyTorch—a wrapper that permits users to call Torch’s ML libraries from Python has a triple-digit growth in usage in just the last few years, surging by almost 400% in 2018 and by 111% in 2019.
Read on to know more about the shift to AI and ML.
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