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The development of AI faster compared to the computer's growth. Data generated each platform, for example, Facebook, Twitter, WhatsApp is in pets bytes. Facebook generates 4 new petabytes of data per day. Most of the data are mostly instructed data like audio, video, and photos often referred to as big data. Indeed, according to a 2017 report issued by The Boston Consulting Group and MIT Sloan Management Review, “three-quarters of executives believe AI will enable their companies to move into a new business” and “almost 85% believe AI will allow their companies to obtain or sustain a competitive advantage.”
AI Workflow in General
When it comes to the workflow for data scientists, it is really hard to generalize. It is completely deepened on the problem statement of the system. There are different workflows for different AI systems, including supervised learning systems, unsupervised learning systems, and reinforcement learning systems. Regardless, most AI projects typically involve the following steps:
- Collecting data from the source or Connecting to the data source
- Labeling data or Feature identification
- Transforming data according to the algorithm
- The building, Training and testing the model
- Deploying the model
