We witnessed a dramatic rise in the platforms, tools, and applications based on Machine learning. These technologies not only impacted software but also the whole economic activity.
Here are 4 AI trends to watch out for in for the coming months and years:
1. The rise of AI-enabled chips
AI heavily relies on specialized processors that complement the CPU. Even the fastest and most advanced CPU may not improve the speed of training an AI model.
2. Convergence of IoT and AI at the edge
Internet of Things (IoT) , sensors for example will be capable of dealing with video frames, speech synthesis, time-series data and unstructured data generated by devices such as cameras, microphones, and other sensors. IoT is all set to become the biggest driver of artificial intelligence in the enterprise. Edge devices will be equipped with the special AI chips based on FPGAs and ASICs.
3. Interoperability among neural networks becomes key
The lack of interoperability among neural network toolkits is hampering the adoption of AI. To address this challenge, AWS, Facebook and Microsoft have collaborated to build Open Neural Network Exchange (ONNX), which makes it possible to reuse trained neural network models across multiple frameworks.
4. Automated machine learning will gain prominence
When dealing with an AutoML platform, business analysts stay focused on the business problem instead of getting lost in the process and workflow.
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